The Cairo Book

By the Cairo Community and its contributors. Special thanks to StarkWare through OnlyDust, and Voyager for supporting the creation of this book.

This version of the text assumes you’re using Cairo version 2.9.2 and Starknet Foundry version 0.35.1. See the Installation section of Chapter 1 to install or update Cairo and Starknet Foundry.

While reading this book, if you want to experiment with Cairo code and see how it compiles into Sierra (Intermediate Representation) and CASM (Cairo Assembly), you can use the cairovm.codes playground.

This book is open source. Find a typo or want to contribute? Check out the book's GitHub repository.

Prólogo

Zero-knowledge proofs have emerged as a transformative technology in the blockchain space, offering solutions for both privacy and scalability challenges. Among these, STARKs (Scalable Transparent ARguments of Knowledge) stand out as a particularly powerful innovation. Unlike traditional proof systems, STARKs rely solely on collision-resistant hash functions, making them post-quantum secure and eliminating the need for trusted setups.

However, writing general-purpose programs that can generate cryptographic proofs has historically been a significant challenge. Developers needed deep expertise in cryptography and complex mathematical concepts to create verifiable computations, making it impractical for mainstream adoption.

This is where Cairo comes in. As a general-purpose programming language designed specifically for creating provable programs, Cairo abstracts away the underlying cryptographic complexities while maintaining the full power of STARKs. Strongly inspired by Rust, Cairo has been built to help you create provable programs without requiring specific knowledge of its underlying architecture, allowing you to focus on the program logic itself.

Los desarrolladores de blockchain que desean implementar contratos en Starknet utilizarán el lenguaje de programación Cairo para codificar sus contratos inteligentes. Esto permite al sistema operativo Starknet generar trazas de ejecución para transacciones que deben ser demostradas por un probador, que luego se verifica en Ethereum L1 antes de actualizar la raíz del estado de Starknet.

However, Cairo is not only for blockchain developers. As a general purpose programming language, it can be used for any computation that would benefit from being proved on one computer and verified on other machines. Powered by a Rust VM, and a next-generation prover, the execution and proof generation of Cairo programs is blazingly fast - making Cairo the best tool for building provable applications.

Este libro está diseñado para desarrolladores con una comprensión básica de los conceptos de programación. Es un texto amigable y accesible destinado a ayudarte a mejorar tus conocimientos de Cairo, pero también a ayudarte a desarrollar tus habilidades de programación en general. ¡Así que sumérgete y prepárate para aprender todo lo que hay que saber sobre Cairo!

Acknowledgements

This book would not have been possible without the help of the Cairo community. We would like to thank every contributor for their contributions to this book!

We would like to thank the Rust community for the Rust Book, which has been a great source of inspiration for this book. Many examples and explanations have been adapted from the Rust Book to fit the Cairo programming language, as the two languages share many similarities.

Introducción

¿Qué es Cairo?

Cairo is a programming language designed to leverage the power of mathematical proofs for computational integrity. Just as C.S. Lewis defined integrity as "doing the right thing, even when no one is watching," Cairo enables programs to prove they've done the right computation, even when executed on untrusted machines.

The language is built on STARK technology, a modern evolution of PCP (Probabilistically Checkable Proofs) that transforms computational claims into constraint systems. While Cairo's ultimate purpose is to generate these mathematical proofs that can be verified efficiently and with absolute certainty.

What Can You Do with It?

Cairo enables a paradigm shift in how we think about trusted computation. Its primary application today is Starknet, a Layer 2 scaling solution for Ethereum that addresses one of blockchain's fundamental challenges: scalability without sacrificing security.

In the traditional blockchain model, every participant must verify every computation. Starknet changes this by using Cairo's proof system: computations are executed off-chain by a prover who generates a STARK proof, which is then verified by an Ethereum smart contract. This verification requires significantly less computational power than re-executing the computations, enabling massive scalability while maintaining security.

However, Cairo's potential extends beyond blockchain. Any scenario where computational integrity needs to be verified efficiently can benefit from Cairo's verifiable computation capabilities.

Who Is This Book For?

This book caters to three main audiences, each with their own learning path:

1. General-Purpose Developers: If you're interested in Cairo for its verifiable computation capabilities outside of blockchain, you'll want to focus on chapters 1-12. These chapters cover the core language features and programming concepts without diving deep into smart contract specifics.

2. New Smart Contract Developers: If you're new to both Cairo and smart contracts, we recommend reading the book front to back. This will give you a solid foundation in both the language fundamentals and smart contract development principles.

3. Experienced Smart Contract Developers: If you're already familiar with smart contract development in other languages, or Rust, you might want to follow this focused path:

   • Chapters 1-3 for Cairo basics
   • Chapter 8 for Cairo's trait and generics system
   • Skip to Chapter 15 for smart contract development
   • Reference other chapters as needed

Regardless of your background, this book assumes basic programming knowledge such as variables, functions, and common data structures. While prior experience with Rust can be helpful (as Cairo shares many similarities), it's not required.

Referencias

• Arquitectura del CPU de Cairo: https://eprint.iacr.org/2021/1063
• Cairo, Sierra y Casm: https://medium.com/nethermind-eth/under-the-hood-of-cairo-1-0-exploring-sierra-7f32808421f5
• Estado no determinista: https://twitter.com/PapiniShahar/status/1638203716535713798

Primeros pasos

Let’s start your Cairo journey! There’s a lot to learn, but every journey starts somewhere. In this chapter, we’ll discuss:

• Installing Scarb, which is Cairo's build toolchain and package manager, on Linux, macOS, and Windows.
• Installing Starknet Foundry, which is the default test runnner when creating a Cairo project.
• Writing a program that prints Hello, world!.
• Using basic Scarb commands to create a project and execute a program.

Getting Help

If you have any questions about Starknet or Cairo, you can ask them in the Starknet Discord server. The community is friendly and always willing to help.

Interacting with the Starknet AI Agent

Starknet proposes its own AI agent designed to assist with Cairo and Starknet-related questions. This AI agent is trained on the Cairo book and the Starknet documentation, using Retrieval-Augmented Generation (RAG) to efficiently retrieve information and provide accurate assistance.

You can find the Starknet Agent on the Starknet Agent website.

Instalación

Cairo puede instalarse simplemente descargando Scarb. Scarb incluye el compilador Cairo y el servidor de lenguaje Cairo en un paquete fácil de instalar para que puedas empezar a escribir código Cairo inmediatamente.

Scarb es el gestor de paquetes de Cairo y está fuertemente inspirado en Cargo, el sistema de construcción y gestor de paquetes de Rust.

Scarb se encarga de muchas tareas por ti, como construir tu código (ya sea en Cairo puro o contratos Starknet), descargar las librerias necesarias para tu código, construir esas librerias y proporcionar soporte LSP (Language Server Protocol) para la extensión de Cairo 1 en VSCode.

A medida que escribas programas Cairo más complejos, es posible que añadas dependencias, y si comienzas un proyecto utilizando Scarb, gestionar elcódigo externo y las dependencias será mucho más fácil de hacer.

Starknet Foundry is a toolchain for Cairo programs and Starknet smart contract development. It supports many features, including writing and running tests with advanced features, deploying contracts, interacting with the Starknet network, and more.

Let's start by installing Scarb and Starknet Foundry.

Instalando Scarb

Requisitos

Scarb requiere un ejecutable Git disponible en la variable de entorno PATH.

Instalación

To install Scarb, please refer to the installation instructions. We strongly recommend that you install Scarb via asdf, a CLI tool that can manage multiple language runtime versions on a per-project basis. This will ensure that the version of Scarb you use to work on a project always matches the one defined in the project settings, avoiding problems related to version mismatches.

Please refer to the asdf documentation to install all prerequisites.

Once you have asdf installed locally, you can download Scarb plugin with the following command:

asdf plugin add scarb

This will allow you to download specific versions:

asdf install scarb 2.9.2

and set a global version:

asdf global scarb 2.9.2

Otherwise, you can simply run the following command in your terminal, and follow the onscreen instructions. This will install the latest stable release of Scarb.

curl --proto '=https' --tlsv1.2 -sSf https://docs.swmansion.com/scarb/install.sh | sh

$ scarb --version
scarb 2.9.2 (5070ff374 2024-12-11)
cairo: 2.9.2 (https://crates.io/crates/cairo-lang-compiler/2.9.2)
sierra: 1.6.0

Installing Starknet Foundry

To install Starknet Foundry, please refer to the installation instructions. We also recommend that you install it via asdf.

Once installed, you can run the following command to see the version:

$ snforge --version
snforge 0.35.1

We'll describe Starknet Foundry in more detail in Chapter 10 for Cairo programs testing and in Chapter 18 when discussing Starknet smart contract testing and security in the second part of the book.

Installing the VSCode Extension

Cairo tiene una extensión VSCode que proporciona resaltado de sintaxis, cairo1). Una vez instalada, ve a la configuración de la extensión, y asegúrate de marcar las opciones Enable Language Server y Enable Scarb options."

¡Hola, mundo!

Ahora que has instalado Cairo, es hora de escribir tu primer programa Cairo. Es tradicional cuando se aprende un nuevo lenguaje se escriba un pequeño programa que imprima el texto Hello, world! en la pantalla, ¡así que haremos lo mismo aquí!

Note: This book assumes basic familiarity with the command line. Cairo makes no specific demands about your editing or tooling or where your code lives, so if you prefer to use an integrated development environment (IDE) instead of the command line, feel free to use your favorite IDE. The Cairo team has developed a VSCode extension for the Cairo language that you can use to get the features from the language server and code highlighting. See Appendix F for more details.

Creando un Directorio de Proyecto

Empezarás creando un directorio para almacenar tu código de Cairo. A Cairo no le importa a Cairo dónde vive tu código, pero para los ejercicios y proyectos de este libro, sugerimos hacer un directorio cairo_projects en tu directorio home y mantener todos tus proyectos allí.

Open a terminal and enter the following commands to make a cairo_projects directory.

Para Linux, macOS y PowerShell en Windows, introduce esto:

mkdir ~/cairo_projects
cd ~/cairo_projects

Para Windows CMD, introduzca esto:

> mkdir "%USERPROFILE%\cairo_projects"
> cd /d "%USERPROFILE%\cairo_projects"

Nota: De ahora en adelante, para cada ejemplo mostrado en el libro, asumimos que estarás trabajando desde un directorio de proyecto Scarb. Si no estás utilizando Scarb, e intentas ejecutar los ejemplos desde un directorio diferente, puede que tengas que ajustar los comandos en consecuencia o crear un proyecto Scarb.

Crear un Proyecto con Scarb

Vamos a crear un nuevo proyecto usando Scarb.

Navigate to your cairo_projects directory (or wherever you decided to store your code). Then run the following:

scarb new hello_world

Scarb will ask you about the dependencies you want to add. You will be given two options :

? Which test runner do you want to set up? ›
❯ Starknet Foundry (default)
  Cairo Test

In general, we'll prefer using the first one ❯ Starknet Foundry (default).

This creates a new directory and project called hello_world. We’ve named our project hello_world, and Scarb creates its files in a directory of the same name.

Go into the hello_world directory with the command cd hello_world. You’ll see that Scarb has generated three files and two directory for us: a Scarb.toml file, a src directory with a lib.cairo file inside and a tests directory containing a test_contract.cairo file. For now, we can remove this tests directory.

También ha inicializado un nuevo repositorio Git junto con un archivo .gitignore

Note: Git is a common version control system. You can stop using version control system by using the --no-vcs flag. Run scarb new --help to see the available options.

Open Scarb.toml in your text editor of choice. It should look similar to the code in Listing 1-1.

Filename: Scarb.toml

[package]
name = "test"
version = "0.1.0"
edition = "2024_07"

# See more keys and their definitions at https://docs.swmansion.com/scarb/docs/reference/manifest.html

[dependencies]
starknet = "2.9.2"

[dev-dependencies]
snforge_std = "0.35.1"
assert_macros = "2.9.2"

[[target.starknet-contract]]
sierra = true

[scripts]
test = "snforge test"

# ...

Listing 1-1: Contents of Scarb.toml generated by scarb new

Este archivo se encuentra en formato TOML (Tom’s Obvious, Minimal Language), que es el formato de configuración de Scarb.

La primera línea, [package], es un encabezado de sección que indica que las siguientes sentencias están configurando un paquete. A medida que agreguemos más información a este archivo, agregaremos otras secciones.

The next three lines set the configuration information Scarb needs to compile your program: the name of the package and the version of Scarb to use, and the edition of the prelude to use. The prelude is the collection of the most commonly used items that are automatically imported into every Cairo program. You can learn more about the prelude in Appendix D.

The [dependencies] section, is the start of a section for you to list any of your project’s dependencies. In Cairo, packages of code are referred to as crates. We won’t need any other crates for this project.

The [dev-dependencies] section is about dependencies that are required for development, but are not needed for the actual production build of the project. snforge_std and assert_macros are two examples of such dependencies. If you want to test your project without using Starknet Foundry, you can use cairo_test.

The [[target.starknet-contract]] section allows to build Starknet smart contracts. We can remove it for now.

The [script] section allows to define custom scripts. By default, there is one script for running tests using snforge with the scarb test command. We can also remove it for now.

Starknet Foundry also have more options, check out Starknet Foundry documentation for more information.

By default, using Starknet Foundry adds the starknet dependency and the [[target.starknet-contract]] section, so that you can build contracts for Starknet out of the box. We will start with only Cairo programs, so you can edit your Scarb.toml file to the following:

Filename: Scarb.toml

[package]
name = "hello_world"
version = "0.1.0"
edition = "2024_07"

[dependencies]

Listing 1-2: Contents of modified Scarb.toml

The other file created by Scarb is src/lib.cairo, let's delete all the content and put in the following content, we will explain the reason later.

mod hello_world;

Then create a new file called src/hello_world.cairo and put the following code in it:

Filename: src/hello_world.cairo

fn main() {
    println!("Hello, World!");
}

We have just created a file called lib.cairo, which contains a module declaration referencing another module named hello_world, as well as the file hello_world.cairo, containing the implementation details of the hello_world module.

Scarb requires your source files to be located within the src directory.

The top-level project directory is reserved for README files, license information, configuration files, and any other non-code-related content. Scarb ensures a designated location for all project components, maintaining a structured organization.

If you started a project that doesn’t use Scarb, you can convert it to a project that does use Scarb. Move the project code into the src directory and create an appropriate Scarb.toml file. You can also use scarb init command to generate the src folder and the Scarb.toml it contains.

├── Scarb.toml
├── src
│   ├── lib.cairo
│   └── hello_world.cairo

A sample Scarb project structure

Crear un proyecto con Scarb

From your hello_world directory, build your project by entering the following command:

$ scarb build 
   Compiling hello_world v0.1.0 (listings/ch01-getting-started/no_listing_01_hello_world/Scarb.toml)
    Finished `dev` profile target(s) in 8 seconds

This command creates a hello_world.sierra.json file in target/dev, let's ignore the sierra file for now.

If you have installed Cairo correctly, you should be able to run the main function of your program with the scarb cairo-run command and see the following output:

$ scarb cairo-run 
   Compiling hello_world v0.1.0 (listings/ch01-getting-started/no_listing_01_hello_world/Scarb.toml)
    Finished `dev` profile target(s) in 15 seconds
     Running hello_world
Hello, World!
Run completed successfully, returning []

Regardless of your operating system, the string Hello, world! should be printed to the terminal.

If Hello, world! did print, congratulations! You’ve officially written a Cairo program. That makes you a Cairo programmer — welcome!

Anatomía de un Programa Cairo

Revisemos este programa “Hello, world!” en detalle. Aquí está la primera pieza del rompecabezas:

fn main() {

}

Estas líneas definen una función llamada main. La función main es especial: siempre es el primer código que se ejecuta en cada programa ejecutable de Cairo. Aquí, la primera línea declara una función llamada main que no tiene parámetros y devuelve nada. Si hubiera parámetros, irían dentro de los paréntesis ().

El cuerpo de la función está envuelto en {}. Cairo requiere llaves alrededor de todos los cuerpos de funciones. Es una buena práctica colocar la llave de apertura en la misma línea que la declaración de la función, añadiendo un espacio en medio.

Note: If you want to stick to a standard style across Cairo projects, you can use the automatic formatter tool available with scarb fmt to format your code in a particular style (more on scarb fmt in Appendix F). The Cairo team has included this tool with the standard Cairo distribution, as cairo-run is, so it should already be installed on your computer!

El cuerpo de la función main contiene el siguiente código:

    println!("Hello, World!");

Esta línea hace todo el trabajo en este pequeño programa: imprime texto en la pantalla. Hay cuatro detalles importantes a tener en cuenta aquí.

Primero, el estilo de Cairo es identar con cuatro espacios, no con una tabulación.

Second, println! calls a Cairo macro. If it had called a function instead, it would be entered as println (without the !). We’ll discuss Cairo macros in more detail in the "Macros" chapter. For now, you just need to know that using a ! means that you’re calling a macro instead of a normal function and that macros don’t always follow the same rules as functions.

En tercer lugar, ves la short string 'Hello, world!'. Pasamos este short string como argumento a print(), y la cadena corta se imprime en la pantalla.

Cuarto, terminamos la línea con un punto y coma (;), que indica que esta expresión ha terminado y la siguiente está lista para comenzar. La mayoría de las líneas de código de Cairo terminan con punto y coma.

Resumen

Recapitulemos lo que hemos aprendido hasta ahora sobre Scarb:

• We can install one or multiple Scarb versions, either the latest stable or a specific one, using asdf.
• Podemos crear un proyecto utilizando scarb new.
• Podemos construir un proyecto usando scarb build para generar el código compilado de Sierra.
• We can execute a Cairo program using the scarb cairo-run command.

Una ventaja adicional de usar Scarb es que los comandos son los mismos sin importar el sistema operativo en el que estemos trabajando. Así que, en este punto, ya no proporcionaremos instrucciones específicas para Linux y macOS frente a Windows.

You’re already off to a great start on your Cairo journey! This is a great time to build a more substantial program to get used to reading and writing Cairo code.

Conceptos comunes de programación

Este capítulo cubre conceptos que aparecen en casi todos los lenguajes de programación y cómo funcionan en Cairo. Muchos lenguajes de programación tienen mucho en común en su núcleo. Ninguno de los conceptos presentados en este capítulo son exclusivos de Cairo, pero los discutiremos en el contexto de Cairo y explicaremos las convenciones sobre el uso de estos conceptos.

Específicamente, aprenderás sobre variables, tipos básicos, funciones, comentarios y flujo de control. Estos fundamentos estarán en cada programa de Cairo, y aprenderlos desde el principio te dará un núcleo fuerte desde el que empezar.

Variables y mutabilidad

Cairo usa un modelo de memoria inmutable, lo que significa que una vez que se escribe en una celda de memoria, no se puede sobrescribir, sino solo leer. Para reflejar este modelo de memoria inmutable, las variables en Cairo son inmutables por defecto. Sin embargo, el lenguaje abstrae este modelo y te da la opción de hacer tus variables mutables. Exploremos cómo y por qué Cairo impone la inmutabilidad, y cómo puedes hacer tus variables mutables.

Cuando una variable es inmutable, una vez que un valor está ligado a un nombre, no puedes cambiar ese valor. Para ilustrar esto, genera un nuevo proyecto llamado variables en tu directorio cairo_projects usando scarb new variables.

A continuación, en tu nuevo directorio variables, abra src/lib.cairo y sustituya su código por el siguiente, que todavía no compilará:

Filename: src/lib.cairo

fn main() {
    let x = 5;
    println!("The value of x is: {}", x);
    x = 6;
    println!("The value of x is: {}", x);
}

Save and run the program using scarb cairo-run. You should receive an error message regarding an immutability error, as shown in this output:

$ scarb cairo-run 
   Compiling no_listing_01_variables_are_immutable v0.1.0 (listings/ch02-common-programming-concepts/no_listing_01_variables_are_immutable/Scarb.toml)
error: Cannot assign to an immutable variable.
 --> listings/ch02-common-programming-concepts/no_listing_01_variables_are_immutable/src/lib.cairo:6:5
    x = 6;
    ^***^

error: could not compile `no_listing_01_variables_are_immutable` due to previous error
error: `scarb metadata` exited with error

This example shows how the compiler helps you find errors in your programs. Compiler errors can be frustrating, but they only mean your program isn’t safely doing what you want it to do yet; they do not mean that you’re not a good programmer! Experienced Caironautes still get compiler errors.

Recibiste el mensaje de error Cannot assign to an immutable variable. porque intentaste asignar un segundo valor a la variable inmutable x.

Es importante que obtengamos errores en tiempo de compilación cuando intentamos cambiar un valor designado como inmutable porque esta situación específica puede conducir a errores. Si una parte de nuestro código opera bajo la suposición de que un valor nunca cambiará y otra parte de nuestro código cambia ese valor, es posible que la primera parte del código no haga lo que fue diseñada para hacer. La causa de este tipo de error puede ser difícil de rastrear después de los hechos, especialmente cuando la segunda parte del código cambia el valor sólo a veces.

Cairo, a diferencia de la mayoría de los otros lenguajes, tiene memoria inmutable. Esto hace que una clase completa de errores sea imposible, porque los valores nunca cambiarán inesperadamente. Esto facilita el razonamiento sobre el código.

Pero la mutabilidad puede ser muy útil, y puede hacer que el código sea más cómodo de escribir. Aunque las variables son inmutables por defecto, puedes hacerlas mutables añadiendo mut delante del nombre de la variable. Añadir mut también transmite intención a los futuros lectores del código indicando que otras partes del código cambiarán el valor de esta variable.

However, you might be wondering at this point what exactly happens when a variable is declared as mut, as we previously mentioned that Cairo's memory is immutable. The answer is that the value is immutable, but the variable isn't. The value associated to the variable can be changed. Assigning to a mutable variable in Cairo is essentially equivalent to redeclaring it to refer to another value in another memory cell, but the compiler handles that for you, and the keyword mut makes it explicit. Upon examining the low-level Cairo Assembly code, it becomes clear that variable mutation is implemented as syntactic sugar, which translates mutation operations into a series of steps equivalent to variable shadowing. The only difference is that at the Cairo level, the variable is not redeclared so its type cannot change.

Por ejemplo, cambiemos src/lib.cairo por lo siguiente:

fn main() {
    let mut x = 5;
    println!("The value of x is: {}", x);
    x = 6;
    println!("The value of x is: {}", x);
}

Cuando ejecutamos el programa ahora, obtenemos esto:

$ scarb cairo-run 
   Compiling no_listing_02_adding_mut v0.1.0 (listings/ch02-common-programming-concepts/no_listing_02_adding_mut/Scarb.toml)
    Finished `dev` profile target(s) in 4 seconds
     Running no_listing_02_adding_mut
The value of x is: 5
The value of x is: 6
Run completed successfully, returning []

Se nos permite cambiar el valor ligado a x de 5 a 6 cuando se usa mut. En última instancia, la decisión de utilizar la mutabilidad o no es suya y depende de lo que usted piensa que es más claro en esa situación particular.

Constantes

Al igual que las variables inmutables, las constants son valores que están vinculados a un nombre y no se les permite cambiar, pero hay algunas diferencias entre las constantes y las variables.

First, you aren’t allowed to use mut with constants. Constants aren’t just immutable by default—they’re always immutable. You declare constants using the const keyword instead of the let keyword, and the type of the value must be annotated. We’ll cover types and type annotations in the next section, “Data Types”, so don’t worry about the details right now. Just know that you must always annotate the type.

Constant variables can be declared with any usual data type, including structs, enums and fixed-size arrays.

Las constantes solo se pueden declarar en el ámbito global, lo que las hace útiles para valores que muchas partes del código necesitan conocer.

The last difference is that constants may natively be set only to a constant expression, not the result of a value that could only be computed at runtime.

Here’s an example of constants declaration:

struct AnyStruct {
    a: u256,
    b: u32,
}

enum AnyEnum {
    A: felt252,
    B: (usize, u256),
}

const ONE_HOUR_IN_SECONDS: u32 = 3600;
const STRUCT_INSTANCE: AnyStruct = AnyStruct { a: 0, b: 1 };
const ENUM_INSTANCE: AnyEnum = AnyEnum::A('any enum');
const BOOL_FIXED_SIZE_ARRAY: [bool; 2] = [true, false];

Nonetheless, it is possible to use the consteval_int! macro to create a const variable that is the result of some computation:

    const ONE_HOUR_IN_SECONDS: u32 = consteval_int!(60 * 60);

We will dive into more detail about macros in the dedicated section.

La convención de nomenclatura de Cairo para las constantes es utilizar mayúsculas con guiones bajos entre palabras.

Las constantes son válidas durante todo el tiempo que se ejecuta un programa, dentro del ámbito en el que fueron declaradas. Esta propiedad hace que las constantes sean útiles para los valores en el dominio de su aplicación que varias partes del programa podrían necesitar conocer, como el número máximo de puntos que cualquier jugador de un juego puede ganar o la velocidad de la luz.

Nombrar los valores codificados en el programa como constantes y usarlas en todo el código es útil para transmitir el significado de ese valor a los futuros mantenedores del código. También ayuda a tener solo un lugar en tu código que necesitarías cambiar si el valor codificado necesitara ser actualizado en el futuro.

Shadowing

El shadowing (sombreado) de variables se refiere a la declaración de una nueva variable con el mismo nombre que una variable anterior. Los Caironautas dicen que la primera variable está sombreada por la segunda, lo que significa que la segunda variable es la que el compilador verá cuando uses el nombre de la variable. En efecto, la segunda variable eclipsa a la primera, tomando cualquier uso del nombre de la variable para sí misma hasta que ella misma sea sombreada o termine el ámbito. Podemos sombrear una variable usando el mismo nombre de la variable y repitiendo el uso de la palabra clave let de la siguiente manera:

fn main() {
    let x = 5;
    let x = x + 1;
    {
        let x = x * 2;
        println!("Inner scope x value is: {}", x);
    }
    println!("Outer scope x value is: {}", x);
}

Este programa primero asigna un valor de 5 a x. Luego crea una nueva variable x repitiendo let x =, tomando el valor original y sumando 1, por lo que el valor de x es ahora 6. Luego, dentro de un ámbito interno creado con llaves, la tercera instrucción let también sombrea x y crea una nueva variable, multiplicando el valor anterior por 2 para darle a x un valor de 12. Cuando ese ámbito termina, la sombra interna termina y x vuelve a ser 6. Al ejecutar este programa, se mostrará lo siguiente:

$ scarb cairo-run 
   Compiling no_listing_03_shadowing v0.1.0 (listings/ch02-common-programming-concepts/no_listing_03_shadowing/Scarb.toml)
    Finished `dev` profile target(s) in 4 seconds
     Running no_listing_03_shadowing
Inner scope x value is: 12
Outer scope x value is: 6
Run completed successfully, returning []

El shadowing es diferente a marcar una variable como mut, porque obtendremos un error en tiempo de compilación si intentamos reasignar a esta variable sin usar la palabra clave let. Al usar let, podemos realizar algunas transformaciones en un valor pero hacer que la variable sea inmutable después de que se hayan completado esas transformaciones.

Otra distinción entre mut y el shadowing es que al usar nuevamente la palabra clave let, estamos creando efectivamente una nueva variable, lo que nos permite cambiar el tipo del valor mientras reutilizamos el mismo nombre. Como se mencionó anteriormente, el shadowing de variables y las variables mutables son equivalentes a un nivel más bajo. La única diferencia es que al hacer shadowing de una variable, el compilador no mostrará un error si cambias su tipo. Por ejemplo, supongamos que nuestro programa realiza una conversión de tipo entre los tipos u64 y felt252.

fn main() {
    let x: u64 = 2;
    println!("The value of x is {} of type u64", x);
    let x: felt252 = x.into(); // converts x to a felt, type annotation is required.
    println!("The value of x is {} of type felt252", x);
}

El primer variable x tiene un tipo u64, mientras que la segunda variable x tiene un tipo felt252. Por lo tanto, el shadowing nos ahorra tener que inventar diferentes nombres, como x_u64 y x_felt252; en su lugar, podemos reutilizar el nombre más simple x. Sin embargo, si intentamos usar mut para esto, como se muestra aquí, obtendremos un error en tiempo de compilación:

fn main() {
    let mut x: u64 = 2;
    println!("The value of x is: {}", x);
    x = 5_u8;
    println!("The value of x is: {}", x);
}

El error indica que se esperaba un u64 (el tipo original), pero se obtuvo un tipo diferente:

$ scarb cairo-run 
   Compiling no_listing_05_mut_cant_change_type v0.1.0 (listings/ch02-common-programming-concepts/no_listing_05_mut_cant_change_type/Scarb.toml)
error: Unexpected argument type. Expected: "core::integer::u64", found: "core::integer::u8".
 --> listings/ch02-common-programming-concepts/no_listing_05_mut_cant_change_type/src/lib.cairo:6:9
    x = 5_u8;
        ^**^

error: could not compile `no_listing_05_mut_cant_change_type` due to previous error
error: `scarb metadata` exited with error

Ahora que hemos explorado cómo funcionan las variables, veamos otros tipos de datos que pueden tener.

Tipos de datos

Cada valor en Cairo tiene un cierto tipo de dato, lo que le dice a Cairo qué tipo de datos se están especificando para que sepa cómo trabajar con esos datos. Esta sección cubre dos subconjuntos de tipos de datos: escalares y compuestos.

Ten en cuenta que Cairo es un lenguaje de tipado estático, lo que significa que debe conocer los tipos de todas las variables en tiempo de compilación. El compilador suele inferir el tipo deseado en función del valor y su uso. En casos en que pueden ser posibles varios tipos, podemos utilizar un método de conversión donde especificamos el tipo de salida deseado.

fn main() {
    let x: felt252 = 3;
    let y: u32 = x.try_into().unwrap();
}

Verás diferentes anotaciones de tipo para otros tipos de datos.

Tipos Escalares

Un tipo scalar representa un único valor. Cairo tiene tres tipos escalares primarios:felts, integers(Enteros) y booleans. Puede que reconozca de otros lenguajes de programación. Veamos cómo funcionan en Cairo.

Tipo Felt

In Cairo, if you don't specify the type of a variable or argument, its type defaults to a field element, represented by the keyword felt252. In the context of Cairo, when we say “a field element” we mean an integer in the range \( 0 \leq x < P \), where \( P \) is a very large prime number currently equal to \( {2^{251}} + 17 \cdot {2^{192}} + 1 \). When adding, subtracting, or multiplying, if the result falls outside the specified range of the prime number, an overflow (or underflow) occurs, and an appropriate multiple of \( P \) is added or subtracted to bring the result back within the range (i.e., the result is computed \( \mod P \) ).

The most important difference between integers and field elements is division: Division of field elements (and therefore division in Cairo) is unlike regular CPUs division, where integer division \( \frac{x}{y} \) is defined as \( \left\lfloor \frac{x}{y} \right\rfloor \) where the integer part of the quotient is returned (so you get \( \frac{7}{3} = 2 \)) and it may or may not satisfy the equation \( \frac{x}{y} \cdot y == x \), depending on the divisibility of x by y.

In Cairo, the result of \( \frac{x}{y} \) is defined to always satisfy the equation \( \frac{x}{y} \cdot y == x \). If y divides x as integers, you will get the expected result in Cairo (for example \( \frac{6}{2} \) will indeed result in 3). But when y does not divide x, you may get a surprising result: for example, since \( 2 \cdot \frac{P + 1}{2} = P + 1 \equiv 1 \mod P \), the value of \( \frac{1}{2} \) in Cairo is \( \frac{P + 1}{2} \) (and not 0 or 0.5), as it satisfies the above equation.

Tipos Integer

The felt252 type is a fundamental type that serves as the basis for creating all types in the core library. However, it is highly recommended for programmers to use the integer types instead of the felt252 type whenever possible, as the integer types come with added security features that provide extra protection against potential vulnerabilities in the code, such as overflow and underflow checks. By using these integer types, programmers can ensure that their programs are more secure and less susceptible to attacks or other security threats. An integer is a number without a fractional component. This type declaration indicates the number of bits the programmer can use to store the integer. Table 3-1 shows the built-in integer types in Cairo. We can use any of these variants to declare the type of an integer value.

Cada variante tiene un tamaño explícito. Tenga en cuenta que por ahora, el tipo usize es sólo un alias para u32; sin embargo, podría ser útil cuando en el futuro Cairo pueda ser compilado a MLIR.Como las variables son sin signo, no pueden contener un número negativo. Este código hará que el programa genere un error:

fn sub_u8s(x: u8, y: u8) -> u8 {
    x - y
}

fn main() {
    sub_u8s(1, 3);
}

All integer types previously mentioned fit into a felt252, except for u256 which needs 4 more bits to be stored. Under the hood, u256 is basically a struct with 2 fields: u256 {low: u128, high: u128}.

Cairo also provides support for signed integers, starting with the prefix i. These integers can represent both positive and negative values, with sizes ranging from i8 to i128. Each signed variant can store numbers from \( -({2^{n - 1}}) \) to \( {2^{n - 1}} - 1 \) inclusive, where n is the number of bits that variant uses. So an i8 can store numbers from \( -({2^7}) \) to \( {2^7} - 1 \), which equals -128 to 127.

You can write integer literals in any of the forms shown in Table 3-2. Note that number literals that can be multiple numeric types allow a type suffix, such as 57_u8, to designate the type. It is also possible to use a visual separator _ for number literals, in order to improve code readability.

Entonces, ¿cómo saber qué tipo de entero utilizar? Intenta estimar el valor máximo que puede tener tu int y elige el tamaño adecuado."La principal situación en la que usarías usize es al indexar algún tipo de colección.

Operaciones Numéricas

Cairo soporta las operaciones matemáticas básicas que esperarías para todos los tipos de integer: suma, resta, multiplicación y resto (u256 no soporta división y resto todavía). Entero trunca hacia cero al entero más cercano. El siguiente código muestra cómo utilizar cada operación numérica en una sentencia let:

fn main() {
    // addition
    let sum = 5_u128 + 10_u128;

    // subtraction
    let difference = 95_u128 - 4_u128;

    // multiplication
    let product = 4_u128 * 30_u128;

    // division
    let quotient = 56_u128 / 32_u128; //result is 1
    let quotient = 64_u128 / 32_u128; //result is 2

    // remainder
    let remainder = 43_u128 % 5_u128; // result is 3
}

Cada expresión de estas sentencias utiliza un operador matemático y se evalúa a un único valor, que se asigna a una variable.

Appendix B contains a list of all operators that Cairo provides.

Tipo Boolean

As in most other programming languages, a Boolean type in Cairo has two possible values: true and false. Booleans are one felt252 in size. The Boolean type in Cairo is specified using bool. For example:

fn main() {
    let t = true;

    let f: bool = false; // with explicit type annotation
}

When declaring a bool variable, it is mandatory to use either true or false literals as value. Hence, it is not allowed to use integer literals (i.e. 0 instead of false) for bool declarations.

The main way to use Boolean values is through conditionals, such as an if expression. We’ll cover how if expressions work in Cairo in the "Control Flow" section.

String Types

Cairo doesn't have a native type for strings but provides two ways to handle them: short strings using simple quotes and ByteArray using double quotes.

Short strings

A short string is an ASCII string where each character is encoded on one byte (see the ASCII table). For example:

• 'a' is equivalent to 0x61
• 'b' is equivalent to 0x62
• 'c' is equivalent to 0x63
• 0x616263 is equivalent to 'abc'.

Cairo uses the felt252 for short strings. As the felt252 is on 251 bits, a short string is limited to 31 characters (31 * 8 = 248 bits, which is the maximum multiple of 8 that fits in 251 bits).

You can choose to represent your short string with an hexadecimal value like 0x616263 or by directly writing the string using simple quotes like 'abc', which is more convenient.

Here are some examples of declaring short strings in Cairo:

fn main() {
    let my_first_char = 'C';
    let my_first_char_in_hex = 0x43;

    let my_first_string = 'Hello world';
    let my_first_string_in_hex = 0x48656C6C6F20776F726C64;

    let long_string: ByteArray = "this is a string which has more than 31 characters";
}

Byte Array Strings

Cairo's Core Library provides a ByteArray type for handling strings and byte sequences longer than short strings. This type is particularly useful for longer strings or when you need to perform operations on the string data.

The ByteArray in Cairo is implemented as a combination of two parts:

1. An array of bytes31 words, where each word contains 31 bytes of data.
2. A pending felt252 word that acts as a buffer for bytes that haven't yet filled a complete bytes31 word.

This design enables efficient handling of byte sequences while aligning with Cairo's memory model and basic types. Developers interact with ByteArray through its provided methods and operators, abstracting away the internal implementation details.

Unlike short strings, ByteArray strings can contain more than 31 characters and are written using double quotes:

fn main() {
    let my_first_char = 'C';
    let my_first_char_in_hex = 0x43;

    let my_first_string = 'Hello world';
    let my_first_string_in_hex = 0x48656C6C6F20776F726C64;

    let long_string: ByteArray = "this is a string which has more than 31 characters";
}

Compound Types

El Tipo Tupla

Una tuple es una forma general de agrupar un número de valores con una variedad de tipos en un tipo compuesto. Las tuplas tienen una longitud fija: una vez declaradas, no pueden aumentar ni disminuir de tamaño.

Se crea una tupla escribiendo una lista de valores separados por comas entre paréntesis. Cada posición de la tupla tiene un tipo, y los tipos de los distintos valores de la tupla no tienen por qué ser iguales. Hemos añadido anotaciones opcionales de tipo en este ejemplo:

fn main() {
    let tup: (u32, u64, bool) = (10, 20, true);
}

La variable tup se vincula a toda la tupla porque una tupla se considera un único elemento compuesto. Para obtener los valores individuales de una tupla, podemos utilizar la concordancia de patrones para desestructurar un valor de tupla, así:

fn main() {
    let tup = (500, 6, true);

    let (x, y, z) = tup;

    if y == 6 {
        println!("y is 6!");
    }
}

This program first creates a tuple and binds it to the variable tup. It then uses a pattern with let to take tup and turn it into three separate variables, x, y, and z. This is called destructuring because it breaks the single tuple into three parts. Finally, the program prints y is 6! as the value of y is 6.

We can also declare the tuple with value and types, and destructure it at the same time. For example:

fn main() {
    let (x, y): (felt252, felt252) = (2, 3);
}

The Unit Type ()

Un tipo unidad es un tipo que sólo tiene un valor ().Se representa mediante una tupla sin elementos. Su tamaño es siempre cero y se garantiza que no existirá en el código compilado.

You might be wondering why you would even need a unit type? In Cairo, everything is an expression, and an expression that returns nothing actually returns () implicitly.

The Fixed Size Array Type

Another way to have a collection of multiple values is with a fixed size array. Unlike a tuple, every element of a fixed size array must have the same type.

We write the values in a fixed-size array as a comma-separated list inside square brackets. The array’s type is written using square brackets with the type of each element, a semicolon, and then the number of elements in the array, like so:

fn main() {
    let arr1: [u64; 5] = [1, 2, 3, 4, 5];
}

In the type annotation [u64; 5], u64 specifies the type of each element, while 5 after the semicolon defines the array's length. This syntax ensures that the array always contains exactly 5 elements of type u64.

Fixed size arrays are useful when you want to hardcode a potentially long sequence of data directly in your program. This type of array must not be confused with the Array<T> type, which is a similar collection type provided by the core library that is allowed to grow in size. If you're unsure whether to use a fixed size array or the Array<T> type, chances are that you are looking for the Array<T> type.

Because their size is known at compile-time, fixed-size arrays don't require runtime memory management, which makes them more efficient than dynamically-sized arrays. Overall, they're more useful when you know the number of elements will not need to change. For example, they can be used to efficiently store lookup tables that won't change during runtime. If you were using the names of the month in a program, you would probably use a fixed size array rather than an Array<T> because you know it will always contain 12 elements:

    let months = [
        'January', 'February', 'March', 'April', 'May', 'June', 'July', 'August', 'September',
        'October', 'November', 'December',
    ];

You can also initialize an array to contain the same value for each element by specifying the initial value, followed by a semicolon, and then the length of the array in square brackets, as shown here:

    let a = [3; 5];

The array named a will contain 5 elements that will all be set to the value 3 initially. This is the same as writing let a = [3, 3, 3, 3, 3]; but in a more concise way.

Accessing Fixed Size Arrays Elements

As a fixed-size array is a data structure known at compile time, it's content is represented as a sequence of values in the program bytecode. Accessing an element of that array will simply read that value from the program bytecode efficiently.

We have two different ways of accessing fixed size array elements:

• Deconstructing the array into multiple variables, as we did with tuples.

fn main() {
    let my_arr = [1, 2, 3, 4, 5];

    // Accessing elements of a fixed-size array by deconstruction
    let [a, b, c, _, _] = my_arr;
    println!("c: {}", c); // c: 3    
}

• Converting the array to a Span, that supports indexing. This operation is free and doesn't incur any runtime cost.

fn main() {
    let my_arr = [1, 2, 3, 4, 5];

    // Accessing elements of a fixed-size array by index
    let my_span = my_arr.span();
    println!("my_span[2]: {}", my_span[2]); // my_span[2]: 3
}

Note that if we plan to repeatedly access the array, then it makes sense to call .span() only once and keep it available throughout the accesses.

Conversión de Tipos

Cairo addresses conversion between types by using the try_into and into methods provided by the TryInto and Into traits from the core library. There are numerous implementations of these traits within the standard library for conversion between types, and they can be implemented for custom types as well.

Into

The Into trait allows for a type to define how to convert itself into another type. It can be used for type conversion when success is guaranteed, such as when the source type is smaller than the destination type.

To perform the conversion, call var.into() on the source value to convert it to another type. The new variable's type must be explicitly defined, as demonstrated in the example below.

fn main() {
    let my_u8: u8 = 10;
    let my_u16: u16 = my_u8.into();
    let my_u32: u32 = my_u16.into();
    let my_u64: u64 = my_u32.into();
    let my_u128: u128 = my_u64.into();

    let my_felt252 = 10;
    // As a felt252 is smaller than a u256, we can use the into() method
    let my_u256: u256 = my_felt252.into();
    let my_other_felt252: felt252 = my_u8.into();
    let my_third_felt252: felt252 = my_u16.into();
}

TryInto

Similar to Into, TryInto is a generic trait for converting between types. Unlike Into, the TryInto trait is used for fallible conversions, and as such, returns Option<T>. An example of a fallible conversion is when the target type might not fit the source value.

Also similar to Into is the process to perform the conversion; just call var.try_into() on the source value to convert it to another type. The new variable's type also must be explicitly defined, as demonstrated in the example below.

fn main() {
    let my_u256: u256 = 10;

    // Since a u256 might not fit in a felt252, we need to unwrap the Option<T> type
    let my_felt252: felt252 = my_u256.try_into().unwrap();
    let my_u128: u128 = my_felt252.try_into().unwrap();
    let my_u64: u64 = my_u128.try_into().unwrap();
    let my_u32: u32 = my_u64.try_into().unwrap();
    let my_u16: u16 = my_u32.try_into().unwrap();
    let my_u8: u8 = my_u16.try_into().unwrap();

    let my_large_u16: u16 = 2048;
    let my_large_u8: u8 = my_large_u16.try_into().unwrap(); // panics with 'Option::unwrap failed.'
}

Funciones

Las funciones son frecuentes en el código de Cairo. Ya has visto una de las funciones más importantes del lenguaje: la función main, que es el punto de entrada de muchos programas. También has visto la palabra clave fn, que te permite declarar nuevas funciones.

El código de Cairo utiliza el estilo snake case como convención para los nombres de funciones y variables, en el cual todas las letras están en minúscula y los guiones bajos separan las palabras. Aquí hay un programa que contiene un ejemplo de definición de función:

fn another_function() {
    println!("Another function.");
}

fn main() {
    println!("Hello, world!");
    another_function();
}

Definimos una función en Cairo introduciendo fn seguido de un nombre de función y un conjunto de paréntesis. Las llaves indican al compilador dónde empieza y termina el cuerpo de la función.

Podemos llamar a cualquier función que hayamos definido introduciendo su nombre seguido de paréntesis. Dado que otra_funcion está definida en el programa, puede ser llamada desde dentro de la función main. Tenga en cuenta que hemos definido otra_funcion antes de la función main en el código fuente; también podríamos haberla definido después también. A Cairo no le importa dónde definas tus funciones, sólo que estén definidas en algún lugar en un ámbito que pueda ser visto por quien las llame.

Empecemos un nuevo proyecto con Scarb llamado functions para explorar las funciones más a fondo. Coloque el ejemplo another_function en src/lib.cairo y ejecútelo. Usted Debería ver la siguiente salida:

$ scarb cairo-run 
   Compiling no_listing_15_functions v0.1.0 (listings/ch02-common-programming-concepts/no_listing_15_functions/Scarb.toml)
    Finished `dev` profile target(s) in 4 seconds
     Running no_listing_15_functions
Hello, world!
Another function.
Run completed successfully, returning []

The lines execute in the order in which they appear in the main function. First the Hello, world! message prints, and then another_function is called and its message is printed.

Parámetros

Podemos definir funciones para que tengan parameters, que son variables especiales que forman parte de la firma de una función. Cuando una función tiene parámetros, puedes proporcionarle valores concretos para esos parámetros. Técnicamente, los valores valores concretos se llaman arguments, pero en la conversación informal, la gente tiende a usar las palabras parameters y arguments indistintamente para las variables en la definición de una función o los valores concretos que se pasan cuando se llama a una función.

En esta versión de another_function añadimos un parámetro:

fn main() {
    another_function(5);
}

fn another_function(x: felt252) {
    println!("The value of x is: {}", x);
}

Intente ejecutar este programa; debería obtener la siguiente salida:

$ scarb cairo-run 
   Compiling no_listing_16_single_param v0.1.0 (listings/ch02-common-programming-concepts/no_listing_16_single_param/Scarb.toml)
    Finished `dev` profile target(s) in 4 seconds
     Running no_listing_16_single_param
The value of x is: 5
Run completed successfully, returning []

La declaración de another_function tiene un parámetro llamado x. El tipo de x se especifica cómo felt252. Cuando pasamos 5 a another_function, la macro println! coloca 5 donde estaba el par de llaves que contenían a x en el formato string.

En las firmas de función, must declarar el tipo de cada parámetro. Esta es una decisión deliberada en el diseño de Cairo: requerir anotaciones de tipo en las significa que el compilador casi nunca necesita usarlas en otra parte del código el código para averiguar a qué tipo se refiere. El compilador también puede dar mensajes de error más útiles si sabe qué tipos espera la función.

Cuando defina múltiples parámetros, separe las declaraciones de parámetros con comas, así:

fn main() {
    print_labeled_measurement(5, "h");
}

fn print_labeled_measurement(value: u128, unit_label: ByteArray) {
    println!("The measurement is: {value}{unit_label}");
}

Este ejemplo crea una función llamada print_labeled_measurement con dos parámetros. El primer parámetro se llama value y es un u128. El segundo se llama unit_label y es de tipo ByteArray, el tipo interno de Cairo para representar literales de string. La función luego imprime texto que contiene tanto el valor como la etiqueta de unidad unit_label.

Let’s try running this code. Replace the program currently in your functions project’s src/lib.cairo file with the preceding example and run it using scarb cairo-run:

$ scarb cairo-run 
   Compiling no_listing_17_multiple_params v0.1.0 (listings/ch02-common-programming-concepts/no_listing_17_multiple_params/Scarb.toml)
    Finished `dev` profile target(s) in 5 seconds
     Running no_listing_17_multiple_params
The measurement is: 5h
Run completed successfully, returning []

Dado que llamamos a la función con 5 como el valor para valor y "h" como el valor para unit_label, la salida del programa contiene esos valores.

Named Parameters

En Cairo, los parámetros con nombre permiten especificar los nombres de los argumentos cuando se llama a una función. Esto hace que las llamadas a funciones sean más legibles y autodescriptivas. Si quieres usar parámetros con nombre, necesitas especificar el nombre del parámetro y el valor que quieres pasarle. La sintaxis es parameter_name: value. Si pasas una variable que tiene el mismo nombre que el parámetro, puedes escribir simplemente :parameter_name en lugar de parameter_name: variable_name.

Aquí un ejemplo:

fn foo(x: u8, y: u8) {}

fn main() {
    let first_arg = 3;
    let second_arg = 4;
    foo(x: first_arg, y: second_arg);
    let x = 1;
    let y = 2;
    foo(:x, :y)
}

Declaraciones y Expresiones

Los cuerpos de las funciones están compuestos por una serie de sentencias que terminan opcionalmente en una expresión. Hasta ahora, las funciones que hemos cubierto no han incluido una expresión final, pero ya has visto una expresión como parte de una sentencia. Como Cairo es un lenguaje basado en expresiones, esta es una distinción importante que debemos entender. Otros lenguajes no tienen las mismas distinciones, así que veamos qué son las sentencias y expresiones y cómo sus diferencias afectan los cuerpos de las funciones.

• Declaraciones son instrucciones que realizan alguna acción y no devuelven un valor.
• Expresiones se evalúan a un valor resultante. Veamos algunos ejemplos.

De hecho, ya hemos utilizado declaraciones y expresiones. Crear una variable y asignarle un valor con la palabra clave let es una declaración. En el Listado 2-1, let y = 6; es una declaración.

fn main() {
    let y = 6;
}

Listing 2-1: A main function declaration containing one statement

Las definiciones de funciones también son sentencias; todo el ejemplo anterior es una sentencia en sí misma.

Las declaraciones no devuelven valores. Por lo tanto, no se puede asignar una sentencia let a otra variable, como intenta hacer el siguiente código; se producirá un error:

fn main() {
    let x = (let y = 6);
}

Cuando ejecutes este programa, el error que obtendrás se verá así:

$ scarb cairo-run 
   Compiling no_listing_18_statements_dont_return_values v0.1.0 (listings/ch02-common-programming-concepts/no_listing_20_statements_dont_return_values/Scarb.toml)
error: Missing token TerminalRParen.
 --> listings/ch02-common-programming-concepts/no_listing_20_statements_dont_return_values/src/lib.cairo:3:14
    let x = (let y = 6);
             ^

error: Missing token TerminalSemicolon.
 --> listings/ch02-common-programming-concepts/no_listing_20_statements_dont_return_values/src/lib.cairo:3:14
    let x = (let y = 6);
             ^

error: Missing token TerminalSemicolon.
 --> listings/ch02-common-programming-concepts/no_listing_20_statements_dont_return_values/src/lib.cairo:3:23
    let x = (let y = 6);
                      ^

error: Skipped tokens. Expected: statement.
 --> listings/ch02-common-programming-concepts/no_listing_20_statements_dont_return_values/src/lib.cairo:3:23
    let x = (let y = 6);
                      ^^

warn[E0001]: Unused variable. Consider ignoring by prefixing with `_`.
 --> listings/ch02-common-programming-concepts/no_listing_20_statements_dont_return_values/src/lib.cairo:3:9
    let x = (let y = 6);
        ^

warn[E0001]: Unused variable. Consider ignoring by prefixing with `_`.
 --> listings/ch02-common-programming-concepts/no_listing_20_statements_dont_return_values/src/lib.cairo:3:18
    let x = (let y = 6);
                 ^

error: could not compile `no_listing_18_statements_dont_return_values` due to previous error
error: `scarb metadata` exited with error

La declaración let y = 6 no devuelve un valor, por lo que no hay nada a lo que x pueda enlazar. Esto es diferente de lo que sucede en otros lenguajes, como C y Ruby, donde la asignación devuelve el valor de la asignación. En esos lenguajes, puedes escribir x = y = 6 y tanto x como y tendrán el valor 6; esto no es así en Cairo.

Expressions evaluate to a value and make up most of the rest of the code that you’ll write in Cairo. Consider a math operation, such as 5 + 6, which is an expression that evaluates to the value 11. Expressions can be part of statements: in Listing 2-1, the 6 in the statement let y = 6; is an expression that evaluates to the value 6.

Calling a function is an expression since it always evaluates to a value: the function's explicit return value, if specified, or the 'unit' type () otherwise.

A new scope block created with curly brackets is an expression, for example:

fn main() {
    let y = {
        let x = 3;
        x + 1
    };

    println!("The value of y is: {}", y);
}

Esta expresión:

    let y = {
        let x = 3;
        x + 1
    };

Este bloque de código, en este caso, se evalúa como 4. Ese valor se asigna a y como parte de la declaración let. Ten en cuenta que la línea x + 1 no tiene un punto y coma al final, lo que es diferente a la mayoría de las líneas que has visto hasta ahora. Las expresiones no incluyen un punto y coma al final. Si agregas un punto y coma al final de una expresión, la conviertes en una declaración, y en ese caso no se devolverá ningún valor. Tenlo en cuenta mientras exploras los valores de retorno de las funciones y las expresiones a continuación.

Funciones con Valores de Retorno

Las funciones pueden devolver valores al código que las llama. No nombramos los valores de retorno, pero debemos declarar su tipo después de una flecha (->). En Cairo, el valor de retorno de la función es sinónimo del valor de la última expresión en el bloque del cuerpo de una función. Puede salir temprano de una función usando la palabra clave return y especificando un valor, pero la mayoría de las funciones devuelven la última expresión implícitamente. Aquí hay un ejemplo de una función que devuelve un valor:

fn five() -> u32 {
    5
}

fn main() {
    let x = five();
    println!("The value of x is: {}", x);
}

No hay llamadas a funciones ni declaraciones let en la función five, solo el número 5 por sí mismo. Esa es una función perfectamente válida en Cairo. Observa que se especifica el tipo de retorno de la función como -> u32. Intenta ejecutar este código; la salida debería verse así:

$ scarb cairo-run 
   Compiling no_listing_20_function_return_values v0.1.0 (listings/ch02-common-programming-concepts/no_listing_22_function_return_values/Scarb.toml)
    Finished `dev` profile target(s) in 4 seconds
     Running no_listing_20_function_return_values
The value of x is: 5
Run completed successfully, returning []

El 5 en five es el valor de retorno de la función, por eso el tipo de retorno es u32. Vamos a examinar esto con más detalle. Hay dos partes importantes: en primer lugar, la línea let x = five(); muestra que estamos usando el valor de retorno de una función para inicializar una variable. Debido a que la función five devuelve un 5, esa línea es lo mismo que:

let x = 5;

Segundo, la función five no tiene parámetros y define el tipo del valor de retorno, pero el cuerpo de la función es un solitario 5 sin punto y coma porque es una expresión cuyo valor queremos devolver. Veamos otro ejemplo:

fn main() {
    let x = plus_one(5);

    println!("The value of x is: {}", x);
}

fn plus_one(x: u32) -> u32 {
    x + 1
}

Al ejecutar este código se imprimirá x = 6. Pero si agregamos un punto y coma al final de la línea que contiene x + 1, cambiándola de una expresión a una declaración, obtendremos un error:

fn main() {
    let x = plus_one(5);

    println!("The value of x is: {}", x);
}

fn plus_one(x: u32) -> u32 {
    x + 1;
}

$ scarb cairo-run 
   Compiling no_listing_22_function_return_invalid v0.1.0 (listings/ch02-common-programming-concepts/no_listing_24_function_return_invalid/Scarb.toml)
error: Unexpected return type. Expected: "core::integer::u32", found: "()".
 --> listings/ch02-common-programming-concepts/no_listing_24_function_return_invalid/src/lib.cairo:9:28
fn plus_one(x: u32) -> u32 {
                           ^

error: could not compile `no_listing_22_function_return_invalid` due to previous error
error: `scarb metadata` exited with error

El mensaje principal de error, Unexpected return type, revela el problema principal con este código. La definición de la función plus_one indica que devolverá un u32, pero las sentencias no se evalúan a un valor, lo cual se expresa por (), el tipo unit. Por lo tanto, no se devuelve nada, lo que contradice la definición de la función y resulta en un error.

Comentarios

All programmers strive to make their code easy to understand, but sometimes extra explanation is warranted. In these cases, programmers leave comments in their source code that the compiler will ignore but people reading the source code may find useful.

Here’s a simple comment:

// hello, world

In Cairo, the idiomatic comment style starts a comment with two slashes, and the comment continues until the end of the line. For comments that extend beyond a single line, you’ll need to include // on each line, like this:

// So we’re doing something complicated here, long enough that we need
// multiple lines of comments to do it! Whew! Hopefully, this comment will
// explain what’s going on.

Comments can also be placed at the end of lines containing code:

fn main() -> felt252 {
    1 + 4 // return the sum of 1 and 4
}

But you’ll more often see them used in this format, with the comment on a separate line above the code it’s annotating:

fn main() -> felt252 {
    // this function performs a simple addition
    1 + 4
}

Item-level Documentation

Item-level documentation comments refer to specific items such as functions, implementations, traits, etc. They are prefixed with three slashes (///). These comments provide a detailed description of the item, examples of usage, and any conditions that might cause a panic. In case of functions, the comments may also include separate sections for parameter and return value descriptions.

/// Returns the sum of `arg1` and `arg2`.
/// `arg1` cannot be zero.
///
/// # Panics
///
/// This function will panic if `arg1` is `0`.
///
/// # Examples
///
/// ```
/// let a: felt252 = 2;
/// let b: felt252 = 3;
/// let c: felt252 = add(a, b);
/// assert(c == a + b, "Should equal a + b");
/// ```
fn add(arg1: felt252, arg2: felt252) -> felt252 {
    assert(arg1 != 0, 'Cannot be zero');
    arg1 + arg2
}

Module Documentation

Module documentation comments provide an overview of the entire module, including its purpose and examples of use. These comments are meant to be placed above the module they're describing and are prefixed with //!. This type of documentation gives a broad understanding of what the module does and how it can be used.

//! # my_module and implementation
//!
//! This is an example description of my_module and some of its features.
//!
//! # Examples
//!
//! ```
//! mod my_other_module {
//!   use path::to::my_module;
//!
//!   fn foo() {
//!     my_module.bar();
//!   }
//! }
//! ```
mod my_module { // rest of implementation...
}

Flujo de control

La capacidad de ejecutar cierto código dependiendo de si una condición es verdadera y de ejecutar código repetidamente mientras una condición es verdadera son bloques de construcción básicos en la mayoría de los lenguajes de programación. Las construcciones más comunes que le permiten controlar el flujo de ejecución del código en Cairo son las expresiones if y los bucles.

Expresiones if

Una expresión if le permite ramificar su código según condiciones. Proporciona una condición y luego establece: "Si se cumple esta condición, ejecute este bloque de código. Si no se cumple la condición, no ejecute este bloque de código".

Create a new project called branches in your cairo_projects directory to explore the if expression. In the src/lib.cairo file, input the following:

fn main() {
    let number = 3;

    if number == 5 {
        println!("condition was true and number = {}", number);
    } else {
        println!("condition was false and number = {}", number);
    }
}

Todos las expresiones if comienzan con la palabra clave if, seguido de una condición. En este caso, la condición verifica si la variable number tiene un valor igual a 5. Colocamos el bloque de código a ejecutar si la condición es true inmediatamente después de la condición dentro de llaves.

Opcionalmente, también podemos incluir una expresión else, que elegimos hacer aquí, para dar al programa un bloque de código alternativo para ejecutar si la condición se evalúa como false. Si no proporciona una expresión else y la condición es false, el programa simplemente omitirá el bloque if y pasará al siguiente fragmento de código.

Intente ejecutar este código; debería ver la siguiente salida:

$ scarb cairo-run 
   Compiling no_listing_24_if v0.1.0 (listings/ch02-common-programming-concepts/no_listing_27_if/Scarb.toml)
    Finished `dev` profile target(s) in 4 seconds
     Running no_listing_24_if
condition was false and number = 3
Run completed successfully, returning []

Intentaré cambiar el valor de number por uno que haga que la condición sea true para ver qué sucede:

    let number = 5;

$ scarb cairo-run
condition was true and number = 5
Run completed successfully, returning []

It’s also worth noting that the condition in this code must be a bool. If the condition isn’t a bool, we’ll get an error. For example, try running the following code:

fn main() {
    let number = 3;

    if number {
        println!("number was three");
    }
}

The if condition evaluates to a value of 3 this time, and Cairo throws an error:

$ scarb build 
   Compiling no_listing_28_bis_if_not_bool v0.1.0 (listings/ch02-common-programming-concepts/no_listing_28_bis_if_not_bool/Scarb.toml)
error: Mismatched types. The type `core::bool` cannot be created from a numeric literal.
 --> listings/ch02-common-programming-concepts/no_listing_28_bis_if_not_bool/src/lib.cairo:4:18
    let number = 3;
                 ^

error: could not compile `no_listing_28_bis_if_not_bool` due to previous error

The error indicates that Cairo inferred the type of number to be a bool based on its later use as a condition of the if statement. It tries to create a bool from the value 3, but Cairo doesn't support instantiating a bool from a numeric literal anyway - you can only use true or false to create a bool. Unlike languages such as Ruby and JavaScript, Cairo will not automatically try to convert non-Boolean types to a Boolean. If we want the if code block to run only when a number is not equal to 0, for example, we can change the if expression to the following:

fn main() {
    let number = 3;

    if number != 0 {
        println!("number was something other than zero");
    }
}

Running this code will print number was something other than zero.

Manejando de múltiples condiciones con else if

You can use multiple conditions by combining if and else in an else if expression. For example:

fn main() {
    let number = 3;

    if number == 12 {
        println!("number is 12");
    } else if number == 3 {
        println!("number is 3");
    } else if number - 2 == 1 {
        println!("number minus 2 is 1");
    } else {
        println!("number not found");
    }
}

Este programa tiene cuatro posibles caminos que puede seguir. Después de ejecutarlo, debería ver la siguiente salida:

$ scarb cairo-run 
   Compiling no_listing_25_else_if v0.1.0 (listings/ch02-common-programming-concepts/no_listing_30_else_if/Scarb.toml)
    Finished `dev` profile target(s) in 4 seconds
     Running no_listing_25_else_if
number is 3
Run completed successfully, returning []

When this program executes, it checks each if expression in turn and executes the first body for which the condition evaluates to true. Note that even though number - 2 == 1 is true, we don’t see the output number minus 2 is 1 nor do we see the number not found text from the else block. That’s because Cairo only executes the block for the first true condition, and once it finds one, it doesn’t even check the rest. Using too many else if expressions can clutter your code, so if you have more than one, you might want to refactor your code. Chapter 6 describes a powerful Cairo branching construct called match for these cases.

Using if in a let Statement

Because if is an expression, we can use it on the right side of a let statement to assign the outcome to a variable.

fn main() {
    let condition = true;
    let number = if condition {
        5
    } else {
        6
    };

    if number == 5 {
        println!("condition was true and number is {}", number);
    }
}

$ scarb cairo-run 
   Compiling no_listing_26_if_let v0.1.0 (listings/ch02-common-programming-concepts/no_listing_31_if_let/Scarb.toml)
    Finished `dev` profile target(s) in 4 seconds
     Running no_listing_26_if_let
condition was true and number is 5
Run completed successfully, returning []

The number variable will be bound to a value based on the outcome of the if expression, which will be 5 here.

Repetición con bucles

It’s often useful to execute a block of code more than once. For this task, Cairo provides a simple loop syntax, which will run through the code inside the loop body to the end and then start immediately back at the beginning. To experiment with loops, let’s create a new project called loops.

Cairo has three kinds of loops: loop, while, and for. Let’s try each one.

Repetición de Código con loop

La palabra clave loop le dice a Cairo que ejecute un bloque de código una y otra vez para siempre o hasta que le digas explícitamente que pare.

Como ejemplo, cambie el archivo src/lib.cairo en tu directorio loops para quede de la siguiente manera:

fn main() {
    loop {
        println!("again!");
    }
}

When we run this program, we’ll see again! printed over and over continuously until either the program runs out of gas or we stop the program manually. Most terminals support the keyboard shortcut ctrl-c to interrupt a program that is stuck in a continual loop. Give it a try:

$ scarb cairo-run --available-gas=20000000
   Compiling loops v0.1.0 (file:///projects/loops)
    Finished release target(s) in 0 seconds
     Running loops
again!
again!
again!
^Cagain!

The symbol ^C represents where you pressed ctrl-c. You may or may not see the word again! printed after the ^C, depending on where the code was in the loop when it received the interrupt signal.

Note: Cairo prevents us from running program with infinite loops by including a gas meter. The gas meter is a mechanism that limits the amount of computation that can be done in a program. By setting a value to the --available-gas flag, we can set the maximum amount of gas available to the program. Gas is a unit of measurement that expresses the computation cost of an instruction. When the gas meter runs out, the program will stop. In the previous case, we set the gas limit high enough for the program to run for quite some time.

It is particularly important in the context of smart contracts deployed on Starknet, as it prevents from running infinite loops on the network. If you're writing a program that needs to run a loop, you will need to execute it with the --available-gas flag set to a value that is large enough to run the program.

Now, try running the same program again, but this time with the --available-gas flag set to 200000 instead of 2000000000000. You will see the program only prints again! 3 times before it stops, as it ran out of gas to keep executing the loop.

Fortunately, Cairo also provides a way to break out of a loop using code. You can place the break keyword within the loop to tell the program when to stop executing the loop.

fn main() {
    let mut i: usize = 0;
    loop {
        if i > 10 {
            break;
        }
        println!("i = {}", i);
        i += 1;
    }
}

The continue keyword tells the program to go to the next iteration of the loop and to skip the rest of the code in this iteration. Let's add a continue statement to our loop to skip the println! statement when i is equal to 5.

fn main() {
    let mut i: usize = 0;
    loop {
        if i > 10 {
            break;
        }
        if i == 5 {
            i += 1;
            continue;
        }
        println!("i = {}", i);
        i += 1;
    }
}

Al ejecutar este programa, no se imprimirá el valor de i cuando sea igual a 5.

Retorno de Valores de Loops

Uno de los usos de un loop es volver a intentar una operación que sabes que podría fallar, como verificar si una operación ha tenido éxito. También es posible que necesites pasar el resultado de esa operación fuera del bucle para el resto de tu código. Para hacer esto, puedes agregar el valor que deseas devolver después de la expresión break que utilizas para detener el bucle; ese valor se devolverá fuera del bucle para que puedas utilizarlo, como se muestra aquí:

fn main() {
    let mut counter = 0;

    let result = loop {
        if counter == 10 {
            break counter * 2;
        }
        counter += 1;
    };

    println!("The result is {}", result);
}

Antes del bucle, declaramos una variable llamada counter y la inicializamos en 0. Luego declaramos una variable llamada result para mantener el valor devuelto por el bucle. En cada iteración del bucle, comprobamos si counter es igual a 10, y añadimos 1 a la variable counter. Cuando se cumple la condición, utilizamos la palabra clave break con el valor counter * 2. Después del bucle, usamos un punto y coma para terminar la sentencia que asigna el valor a result. Finalmente el valor en result, que en este caso es 20.

Conditional Loops with while

A program will often need to evaluate a condition within a loop. While the condition is true, the loop runs. When the condition ceases to be true, the program calls break, stopping the loop. It’s possible to implement behavior like this using a combination of loop, if, else, and break; you could try that now in a program, if you’d like. However, this pattern is so common that Cairo has a built-in language construct for it, called a while loop.

In Listing 2-2, we use while to loop the program three times, counting down each time after printing the value of number, and then, after the loop, print a message and exit.

fn main() {
    let mut number = 3;

    while number != 0 {
        println!("{number}!");
        number -= 1;
    };

    println!("LIFTOFF!!!");
}

Listing 2-2: Using a while loop to run code while a condition holds true.

This construct eliminates a lot of nesting that would be necessary if you used loop, if, else, and break, and it’s clearer. While a condition evaluates to true, the code runs; otherwise, it exits the loop.

Looping Through a Collection with for

You can also use the while construct to loop over the elements of a collection, such as an array. For example, the loop in Listing 2-3 prints each element in the array a.

fn main() {
    let a = [10, 20, 30, 40, 50].span();
    let mut index = 0;

    while index < 5 {
        println!("the value is: {}", a[index]);
        index += 1;
    }
}

Listing 2-3: Looping through each element of a collection using a while loop

Here, the code counts up through the elements in the array. It starts at index 0, and then loops until it reaches the final index in the array (that is, when index < 5 is no longer true). Running this code will print every element in the array:

$ scarb cairo-run 
   Compiling no_listing_45_iter_loop_while v0.1.0 (listings/ch02-common-programming-concepts/no_listing_45_iter_loop_while/Scarb.toml)
    Finished `dev` profile target(s) in 4 seconds
     Running no_listing_45_iter_loop_while
the value is: 10
the value is: 20
the value is: 30
the value is: 40
the value is: 50
Run completed successfully, returning []

All five array values appear in the terminal, as expected. Even though index will reach a value of 5 at some point, the loop stops executing before trying to fetch a sixth value from the array.

However, this approach is error prone; we could cause the program to panic if the index value or test condition is incorrect. For example, if you changed the definition of the a array to have four elements but forgot to update the condition to while index < 4, the code would panic. It’s also slow, because the compiler adds runtime code to perform the conditional check of whether the index is within the bounds of the array on every iteration through the loop.

As a more concise alternative, you can use a for loop and execute some code for each item in a collection. A for loop looks like the code in Listing 2-4.

fn main() {
    let a = [10, 20, 30, 40, 50].span();

    for element in a {
        println!("the value is: {element}");
    }
}

Listing 2-4: Looping through each element of a collection using a for loop

When we run this code, we’ll see the same output as in Listing 2-3. More importantly, we’ve now increased the safety of the code and eliminated the chance of bugs that might result from going beyond the end of the array or not going far enough and missing some items.

Using the for loop, you wouldn’t need to remember to change any other code if you changed the number of values in the array, as you would with the method used in Listing 2-3.

The safety and conciseness of for loops make them the most commonly used loop construct in Cairo. Even in situations in which you want to run some code a certain number of times, as in the countdown example that used a while loop in Listing 2-2. Another way to run code a certain number of times would be to use a Range, provided by the core library, which generates all numbers in sequence starting from one number and ending before another number.

Here’s how you can use a Range to count from 1 to 3:

fn main() {
    for number in 1..4_u8 {
        println!("{number}!");
    };
    println!("Go!!!");
}

This code is a bit nicer, isn’t it?

Equivalence Between Loops and Recursive Functions

Loops and recursive functions are two common ways to repeat a block of code multiple times. The loop keyword is used to create an infinite loop that can be broken by using the break keyword.

fn main() -> felt252 {
    let mut x: felt252 = 0;
    loop {
        if x == 2 {
            break;
        } else {
            x += 1;
        }
    };
    x
}

Loops can be transformed into recursive functions by calling the function within itself. Here is an example of a recursive function that mimics the behavior of the loop example above.

fn main() -> felt252 {
    recursive_function(0)
}

fn recursive_function(mut x: felt252) -> felt252 {
    if x == 2 {
        x
    } else {
        recursive_function(x + 1)
    }
}

In both cases, the code block will run indefinitely until the condition x == 2 is met, at which point the value of x will be displayed.

In Cairo, loops and recursions are not only conceptually equivalent: they are also compiled down to similar low-level representations. To understand this, we can compile both examples to Sierra, and analyze the Sierra Code generated by the Cairo compiler for both examples. Add the following in your Scarb.toml file:

[lib]
sierra-text = true

Then, run scarb build to compile both examples. You will find the Sierra code generated by for both examples is extremely similar, as the loop is compiled to a recursive function in the Sierra statements.

Note: For our example, our findings came from understanding the statements section in Sierra that shows the execution traces of the two programs. If you are curious to learn more about Sierra, check out Exploring Sierra.

Resumen

¡Lo has conseguido! Este fue un capítulo considerable: aprendiste sobre variables, tipos de datos, funciones, comentarios, expresiones if y bucles. Para practicar con los conceptos discutidos en este capítulo, intenta construir programas para hacer lo siguiente:

• Generar el n-th número de Fibonacci.
• Calcular el factorial de un número n.

Ahora, revisaremos los tipos de colección comunes en Cairo en el próximo capítulo.

Colecciones Comunes

Cairo ofrece un conjunto de tipos de colecciones comunes que pueden utilizarse para almacenar y manipular datos. Estas colecciones están diseñadas para ser eficientes, flexibles y fáciles de usar. Esta sección presenta los tipos principales de colecciones disponibles en Cairo: Arrays y Diccionarios.

Arrays

Un array es una colección de elementos del mismo tipo. Puedes crear y utilizar métodos de array mediante el uso del rasgo ArrayTrait de la libreria principal.

An important thing to note is that arrays have limited modification options. Arrays are, in fact, queues whose values can't be modified. This has to do with the fact that once a memory slot is written to, it cannot be overwritten, but only read from it. You can only append items to the end of an array and remove items from the front.

Crear un Array

Creating an array is done with the ArrayTrait::new() call. Here's an example of creating an array and appending 3 elements to it:

fn main() {
    let mut a = ArrayTrait::new();
    a.append(0);
    a.append(1);
    a.append(2);
}

Cuando sea necesario, puedes pasar el tipo esperado de elementos dentro del array al instanciarlo de esta manera, o definir explícitamente el tipo del mismo.

let mut arr = ArrayTrait::<u128>::new();

let mut arr:Array<u128> = ArrayTrait::new();

Actualizar un Array

Añadir Elementos

Para añadir un elemento al final de un array, puedes utilizar el método append():

fn main() {
    let mut a = ArrayTrait::new();
    a.append(0);
    a.append(1);
    a.append(2);
}

Eliminar Elementos

You can only remove elements from the front of an array by using the pop_front() method. This method returns an Option that can be unwrapped, containing the removed element, or Option::None if the array is empty.

fn main() {
    let mut a = ArrayTrait::new();
    a.append(10);
    a.append(1);
    a.append(2);

    let first_value = a.pop_front().unwrap();
    println!("The first value is {}", first_value);
}

The above code will print The first value is 10 as we remove the first element that was added.

En Cairo, la memoria es inmutable, lo que significa que no es posible modificar los elementos de un array una vez que han sido añadidos. Sólo se pueden añadir elementos al final de un array y eliminar elementos de la parte frontal de un array. Estas operaciones no requieren mutación de memoria, ya que implican actualizar punteros en lugar de modificar directamente las celdas de memoria.

Lectura de Elementos en un Array

Para acceder a los elementos de un array, puedes utilizar los métodos get() o at() que devuelven diferentes tipos. Utilizar arr.at(index) es equivalente a utilizar el operador de subíndice arr[index].

get() Method

The get function returns an Option<Box<@T>>, which means it returns an option to a Box type (Cairo's smart-pointer type) containing a snapshot to the element at the specified index if that element exists in the array. If the element doesn't exist, get returns None. This method is useful when you expect to access indices that may not be within the array's bounds and want to handle such cases gracefully without panics. Snapshots will be explained in more detail in the "References and Snapshots" chapter.

He aquí un ejemplo con el método get():

fn main() -> u128 {
    let mut arr = ArrayTrait::<u128>::new();
    arr.append(100);
    let index_to_access =
        1; // Change this value to see different results, what would happen if the index doesn't exist?
    match arr.get(index_to_access) {
        Option::Some(x) => {
            *x
                .unbox() // Don't worry about * for now, if you are curious see Chapter 4.2 #desnap operator
            // It basically means "transform what get(idx) returned into a real value"
        },
        Option::None => { panic!("out of bounds") },
    }
}

at() Method

The at function, and its equivalent the subscripting operator, on the other hand, directly return a snapshot to the element at the specified index using the unbox() operator to extract the value stored in a box. If the index is out of bounds, a panic error occurs. You should only use at when you want the program to panic if the provided index is out of the array's bounds, which can prevent unexpected behavior.

fn main() {
    let mut a = ArrayTrait::new();
    a.append(0);
    a.append(1);

    // using the `at()` method
    let first = *a.at(0);
    assert!(first == 0);
    // using the subscripting operator
    let second = *a[1];
    assert!(second == 1);
}

En este ejemplo, la variable llamada first obtendrá el valor 0 porque es el valor del índice 0 del array. La variable llamada second obtendrá el valor 1 del índice 1 del array.

En resumen, usa at cuando quieras que el programa entre en pánico ante intentos de acceso fuera de los límites, y usa get cuando prefieras manejar estos casos con gracia sin entrar en pánico.

Size-related Methods

To determine the number of elements in an array, use the len() method. The return value is of type usize.

Si quieres comprobar si un array está vacío o no, puedes utilizar el método is_empty(), que devuelve true si el array está vacío y false en caso contrario.

array! Macro

A veces, necesitamos crear arrays con valores que ya se conocen en tiempo de compilación. La forma básica de hacerlo es redundante. Primero declararías el array y luego añadirías cada valor uno por uno. array! es una forma más sencilla de realizar esta tarea al combinar los dos pasos. En tiempo de compilación, el compilador expandirá la macro para generar el código que añade los elementos de forma secuencial

Sin array!:

    let mut arr = ArrayTrait::new();
    arr.append(1);
    arr.append(2);
    arr.append(3);
    arr.append(4);
    arr.append(5);

Con array!:

    let arr = array![1, 2, 3, 4, 5];

Storing Multiple Types with Enums

If you want to store elements of different types in an array, you can use an Enum to define a custom data type that can hold multiple types. Enums will be explained in more detail in the "Enums and Pattern Matching" chapter.

#[derive(Copy, Drop)]
enum Data {
    Integer: u128,
    Felt: felt252,
    Tuple: (u32, u32),
}

fn main() {
    let mut messages: Array<Data> = array![];
    messages.append(Data::Integer(100));
    messages.append(Data::Felt('hello world'));
    messages.append(Data::Tuple((10, 30)));
}

Span

Span is a struct that represents a snapshot of an Array. It is designed to provide safe and controlled access to the elements of an array without modifying the original array. Span is particularly useful for ensuring data integrity and avoiding borrowing issues when passing arrays between functions or when performing read-only operations, as introduced in "References and Snapshots".

All methods provided by Array can also be used with Span, except for the append() method.

Turning an Array into Span

Para crear un Span de un Array, llama al método span():

fn main() {
    let mut array: Array<u8> = ArrayTrait::new();
    array.span();
}

Diccionarios

Cairo proporciona en su libreria principal un tipo de datos similar a un diccionario. El tipo de datos Felt252Dict representa una colección de pares key-value donde cada key es única y está asociada con un value correspondiente. Este tipo de estructura de datos se conoce de manera diferente en varios lenguajes de programación, como mapas, tablas hash, arrays asociativos y muchos otros.

El tipo Felt252Dict es útil cuando deseas organizar tus datos de una manera específica para la cual el uso de un Array e indexación no es suficiente. Los diccionarios en Cairo también permiten al programador simular fácilmente la existencia de memoria mutable cuando no la hay.

Uso Basico de Diccionarios

It is normal in other languages when creating a new dictionary to define the data types of both key and value. In Cairo, the key type is restricted to felt252, leaving only the possibility to specify the value data type, represented by T in Felt252Dict<T>.

La funcionalidad principal de un Felt252Dict se implementa en el rasgo Felt252DictTrait, que incluye todas las operaciones básicas. Entre ellas podemos encontrar:

1. insert(felt252, T) -> () para escribir valores en una instancia de diccionario.
2. get(felt252) -> T para leer sus valores.

Estas funciones nos permiten manipular diccionarios como en cualquier otro lenguaje. En el siguiente ejemplo, creamos un diccionario para representar una relación entre individuos y sus saldos:

use core::dict::Felt252Dict;

fn main() {
    let mut balances: Felt252Dict<u64> = Default::default();

    balances.insert('Alex', 100);
    balances.insert('Maria', 200);

    let alex_balance = balances.get('Alex');
    assert!(alex_balance == 100, "Balance is not 100");

    let maria_balance = balances.get('Maria');
    assert!(maria_balance == 200, "Balance is not 200");
}

Podemos crear una nueva instancia de Felt252Dict<u64> utilizando el método default del rasgo Default y añadir dos individuos, cada uno con su propio saldo, utilizando el método insert. Por último, comprobamos el saldo de nuestros usuarios con el método get. Estos métodos están definidos en el trait Felt252DictTrait de la librería principal.

Throughout the book we have talked about how Cairo's memory is immutable, meaning you can only write to a memory cell once but the Felt252Dict<T> type represents a way to overcome this obstacle. We will explain how this is implemented later on in "Dictionaries Underneath".

Basándonos en nuestro ejemplo anterior, vamos a mostrar un ejemplo de código en el que cambia el saldo del mismo usuario:

use core::dict::Felt252Dict;

fn main() {
    let mut balances: Felt252Dict<u64> = Default::default();

    // Insert Alex with 100 balance
    balances.insert('Alex', 100);
    // Check that Alex has indeed 100 associated with him
    let alex_balance = balances.get('Alex');
    assert!(alex_balance == 100, "Alex balance is not 100");

    // Insert Alex again, this time with 200 balance
    balances.insert('Alex', 200);
    // Check the new balance is correct
    let alex_balance_2 = balances.get('Alex');
    assert!(alex_balance_2 == 200, "Alex balance is not 200");
}

Notice how in this example we added the 'Alex' individual twice, each time using a different balance and each time that we checked for its balance it had the last value inserted! Felt252Dict<T> effectively allows us to "rewrite" the stored value for any given key.

Antes de seguir adelante y explicar cómo se implementan los diccionarios vale la pena mencionar que una vez que instanciar un Felt252Dict<T>, detrás de las escenas de todas las claves tienen sus valores asociados inicializado como cero. Esto significa que si, por ejemplo, intentas obtener el saldo de un usuario inexistente obtendrás 0 en lugar de un error o un valor indefinido. Esto también significa que no hay forma de borrar datos de un diccionario. Algo a tener en cuenta a la hora de incorporar esta estructura a tu código.

Hasta este punto, hemos visto todas las características básicas de Felt252Dict<T> y cómo imita el mismo comportamiento que las estructuras de datos correspondientes en cualquier otro lenguaje, es decir, externamente, por supuesto. Cairo es en su núcleo un lenguaje de programación Turing-completo no determinista, muy diferente de cualquier otro lenguaje popular existente, lo que como consecuencia significa que ¡los diccionarios se implementan también de forma muy diferente!

En las siguientes secciones, vamos a dar algunas ideas sobre Felt252Dict<T> mecanismos internos y los compromisos que se tomaron para que funcionen. Después de eso, vamos a echar un vistazo a cómo utilizar los diccionarios con otras estructuras de datos, así como utilizar el método entry como otra forma de interactuar con ellos.

Diccionarios por Debajo

Una de las restricciones del diseño no determinista de Cairo es que su sistema de memoria es inmutable, así que para simular la mutabilidad, el lenguaje implementa Felt252Dict<T> como una lista de entradas. Cada una de las entradas representa un momento en el que se accedió al diccionario para leer/actualizar/escribir. Una entrada tiene tres campos:

1. A key field that identifies the key for this key-value pair of the dictionary.
2. Un campo previous_value que indica qué valor anterior tenía key.
3. Un campo new_value que indica el nuevo valor que se tiene en key.

Si intentamos implementar Felt252Dict<T> usando estructuras de alto nivel lo definiríamos internamente como Array<Entry<T>> donde cada Entry<T> tiene información sobre qué par key-value representa y los valores anteriores y nuevos que contiene. La definición de Entry<T> sería:

struct Entry<T> {
    key: felt252,
    previous_value: T,
    new_value: T,
}

For each time we interact with a Felt252Dict<T>, a new Entry<T> will be registered:

• Un get registraría una entrada en la que no hay cambio de estado, los valores anteriores y nuevos se almacenan con el mismo valor.
• Un insert registraría una nueva Entry<T> donde el new_value sería el elemento que se inserta, y el previous_value el último elemento insertado antes de este. En caso de que sea la primera entrada para una determinada clave, entonces el valor anterior será cero.

El uso de esta lista de entradas muestra cómo no hay ninguna reescritura, sólo la creación de nuevas celdas de memoria por interacción Felt252Dict<T>. Vamos a mostrar un ejemplo de esto usando el diccionario balances de la sección anterior e insertando los usuarios Alex y Maria:

use core::dict::Felt252Dict;

struct Entry<T> {
    key: felt252,
    previous_value: T,
    new_value: T,
}

fn main() {
    let mut balances: Felt252Dict<u64> = Default::default();
    balances.insert('Alex', 100_u64);
    balances.insert('Maria', 50_u64);
    balances.insert('Alex', 200_u64);
    balances.get('Maria');
}

Estas instrucciones producirían la siguiente lista de entradas:

Observe que como 'Alex' se insertó dos veces, aparece dos veces y los valores previous y current se establecen correctamente. También la lectura de 'Maria' registró una entrada sin cambios de los valores anteriores a los actuales.

Este enfoque para implementar Felt252Dict<T> significa que para cada operación de lectura/escritura, hay un escaneo de toda la lista de entradas en busca de la última entrada con la misma clave. Una vez encontrada la entrada, se extrae su nuevo_valor y se utiliza en la nueva entrada que se añade como valor_anterior. Esto significa que interactuar con Felt252Dict<T> tiene una complejidad temporal en el peor de los casos de O(n) donde n es el número de entradas de la lista.

Si te pones a pensar en formas alternativas de implementar Felt252Dict<T> seguramente las encontrarás, probablemente incluso eliminando completamente la necesidad de un campo previous_value, sin embargo, como Cairo no es un lenguaje normal esto no funcionará. Uno de los propósitos de Cairo es, con el sistema de pruebas STARK, generar pruebas de integridad computacional. Esto significa que necesitas verificar que la ejecución del programa es correcta y dentro de los límites de las restricciones de Cairo. Una de esas comprobaciones de límites consiste en "comprimir diccionarios" y eso requiere información tanto de los valores anteriores como de los nuevos para cada entrada.

Comprimir Diccionarios

To verify that the proof generated by a Cairo program execution that used a Felt252Dict<T> is correct, we need to check that there wasn't any illegal tampering with the dictionary. This is done through a method called squash_dict that reviews each entry of the entry list and checks that access to the dictionary remains coherent throughout the execution.

El proceso de comprimir es el siguiente: dadas todas las entradas con cierta clave k, tomadas en el mismo orden en que fueron insertadas, verificar que la i-ésima entrada new_value es igual a la i-th + 1 entrada previous_value.

Por ejemplo, dada la siguiente lista de entradas:

Después de comprimir, la lista de entradas se reduciría a:

En caso de un cambio en alguno de los valores de la primera tabla, la compresión habría fallado durante la ejecución.

Destrucción de Diccionarios

If you run the examples from "Basic Use of Dictionaries" section, you'd notice that there was never a call to squash dictionary, but the program compiled successfully nonetheless. What happened behind the scene was that squash was called automatically via the Felt252Dict<T> implementation of the Destruct<T> trait. This call occurred just before the balance dictionary went out of scope.

The Destruct<T> trait represents another way of removing instances out of scope apart from Drop<T>. The main difference between these two is that Drop<T> is treated as a no-op operation, meaning it does not generate new CASM while Destruct<T> does not have this restriction. The only type which actively uses the Destruct<T> trait is Felt252Dict<T>, for every other type Destruct<T> and Drop<T> are synonyms. You can read more about these traits in Drop and Destruct section of Appendix C.

Later in "Dictionaries as Struct Members" section, we will have a hands-on example where we implement the Destruct<T> trait for a custom type.

Más Diccionarios

Hasta este punto, hemos dado una visión general de la funcionalidad de Felt252Dict<T> de cómo y por qué se implementa de una determinada manera. Si no lo has entendido todo, no te preocupes porque en esta sección tendremos algunos ejemplos más utilizando diccionarios.

We will start by explaining the entry method which is part of a dictionary basic functionality included in Felt252DictTrait<T> which we didn't mention at the beginning. Soon after, we will see examples of how to use Felt252Dict<T> with other complex types such as Array<T>.

Entrada y Finalización

In the "Dictionaries Underneath" section, we explained how Felt252Dict<T> internally worked. It was a list of entries for each time the dictionary was accessed in any manner. It would first find the last entry given a certain key and then update it accordingly to whatever operation it was executing. The Cairo language gives us the tools to replicate this ourselves through the entry and finalize methods.

El método entry viene como parte de Felt252DictTrait<T> con el propósito de crear una nueva entrada dada una determinada clave. Una vez llamado, este método toma posesión del diccionario y devuelve la entrada a actualizar. La característica del método es la siguiente:

fn entry(self: Felt252Dict<T>, key: felt252) -> (Felt252DictEntry<T>, T) nopanic

The first input parameter takes ownership of the dictionary while the second one is used to create the appropriate entry. It returns a tuple containing a Felt252DictEntry<T>, which is the type used by Cairo to represent dictionary entries, and a T representing the value held previously. The nopanic notation simply indicates that the function is guaranteed to never panic.

Lo siguiente que hay que hacer es actualizar la entrada con el nuevo valor. Para esto, utilizamos el método finalize que inserta la entrada y devuelve la propiedad del diccionario:

fn finalize(self: Felt252DictEntry<T>, new_value: T) -> Felt252Dict<T>

This method receives the entry and the new value as parameters, and returns the updated dictionary.

Veamos un ejemplo utilizando entry y finalize. Imaginemos que queremos implementar nuestra propia versión del método get de un diccionario. Deberíamos hacer lo siguiente:

1. Create the new entry to add using the entry method.
2. Insertar nuevamente la entrada donde el new_value sea igual al previous_value.
3. Devolver el valor.

Implementar nuestra propia función get se vería así:

use core::dict::{Felt252Dict, Felt252DictEntryTrait};

fn custom_get<T, +Felt252DictValue<T>, +Drop<T>, +Copy<T>>(
    ref dict: Felt252Dict<T>, key: felt252,
) -> T {
    // Get the new entry and the previous value held at `key`
    let (entry, prev_value) = dict.entry(key);

    // Store the value to return
    let return_value = prev_value;

    // Update the entry with `prev_value` and get back ownership of the dictionary
    dict = entry.finalize(prev_value);

    // Return the read value
    return_value
}

The ref keyword means that the ownership of the variable will be given back at the end of the function. This concept will be explained in more detail in the "References and Snapshots" section.

Implementar el método insert seguiría un flujo de trabajo similar, excepto por la inserción de un nuevo valor al finalizar. Si lo implementáramos, tendría el siguiente aspecto:

use core::dict::{Felt252Dict, Felt252DictEntryTrait};

fn custom_insert<T, +Felt252DictValue<T>, +Destruct<T>, +Drop<T>>(
    ref dict: Felt252Dict<T>, key: felt252, value: T,
) {
    // Get the last entry associated with `key`
    // Notice that if `key` does not exist, `_prev_value` will
    // be the default value of T.
    let (entry, _prev_value) = dict.entry(key);

    // Insert `entry` back in the dictionary with the updated value,
    // and receive ownership of the dictionary
    dict = entry.finalize(value);
}

Como nota final, estos dos métodos se implementan de manera similar a cómo insert y get se implementan para Felt252Dict<T>. Este código muestra algunos ejemplos de uso:

use core::dict::{Felt252Dict, Felt252DictEntryTrait};

fn custom_get<T, +Felt252DictValue<T>, +Drop<T>, +Copy<T>>(
    ref dict: Felt252Dict<T>, key: felt252,
) -> T {
    // Get the new entry and the previous value held at `key`
    let (entry, prev_value) = dict.entry(key);

    // Store the value to return
    let return_value = prev_value;

    // Update the entry with `prev_value` and get back ownership of the dictionary
    dict = entry.finalize(prev_value);

    // Return the read value
    return_value
}

fn custom_insert<T, +Felt252DictValue<T>, +Destruct<T>, +Drop<T>>(
    ref dict: Felt252Dict<T>, key: felt252, value: T,
) {
    // Get the last entry associated with `key`
    // Notice that if `key` does not exist, `_prev_value` will
    // be the default value of T.
    let (entry, _prev_value) = dict.entry(key);

    // Insert `entry` back in the dictionary with the updated value,
    // and receive ownership of the dictionary
    dict = entry.finalize(value);
}

fn main() {
    let mut dict: Felt252Dict<u64> = Default::default();

    custom_insert(ref dict, '0', 100);

    let val = custom_get(ref dict, '0');

    assert!(val == 100, "Expecting 100");
}

Dictionaries of Types not Supported Natively

One restriction of Felt252Dict<T> that we haven't talked about is the trait Felt252DictValue<T>. This trait defines the zero_default method which is the one that gets called when a value does not exist in the dictionary. This is implemented by some common data types, such as most unsigned integers, bool and felt252 - but it is not implemented for more complex types such as arrays, structs (including u256), and other types from the core library. This means that making a dictionary of types not natively supported is not a straightforward task, because you would need to write a couple of trait implementations in order to make the data type a valid dictionary value type. To compensate this, you can wrap your type inside a Nullable<T>.

Nullable<T> is a smart pointer type that can either point to a value or be null in the absence of value. It is usually used in Object Oriented Programming Languages when a reference doesn't point anywhere. The difference with Option is that the wrapped value is stored inside a Box<T> data type. The Box<T> type is a smart pointer that allows us to use a dedicated boxed_segment memory segment for our data, and access this segment using a pointer that can only be manipulated in one place at a time. See Smart Pointers Chapter for more information.

Vamos a mostrarlo con un ejemplo. Intentaremos almacenar un Span<felt252> dentro de un diccionario. Para ello utilizaremos Nullable<T> y Box<T>. Además, estamos almacenando un Span<T> y no un Array<T> porque este último no implementa el rasgo Copy<T> que es necesario para leer de un diccionario.

use core::dict::Felt252Dict;
use core::nullable::{NullableTrait, match_nullable, FromNullableResult};

fn main() {
    // Create the dictionary
    let mut d: Felt252Dict<Nullable<Span<felt252>>> = Default::default();

    // Create the array to insert
    let a = array![8, 9, 10];

    // Insert it as a `Span`
    d.insert(0, NullableTrait::new(a.span()));

//...

En este fragmento de código, lo primero que hicimos fue crear un nuevo diccionario d. Queremos que contenga un Nullable<Span>. Después, creamos un array y lo llenamos de valores.

The last step is inserting the array as a span inside the dictionary. Notice that we do this using the new function of the NullableTrait.

Una vez que el elemento está dentro del diccionario, y queremos obtenerlo, seguimos los mismos pasos pero en orden inverso. El siguiente código muestra cómo conseguirlo:

//...

    // Get value back
    let val = d.get(0);

    // Search the value and assert it is not null
    let span = match match_nullable(val) {
        FromNullableResult::Null => panic!("No value found"),
        FromNullableResult::NotNull(val) => val.unbox(),
    };

    // Verify we are having the right values
    assert!(*span.at(0) == 8, "Expecting 8");
    assert!(*span.at(1) == 9, "Expecting 9");
    assert!(*span.at(2) == 10, "Expecting 10");
}

Aquí tenemos:

1. Lee el valor utilizando get.
2. Verificado que no es nulo usando la función match_nullable.
3. Desenvolvió el valor dentro de la caja y afirmó que era correcto.

El script completo tendría este aspecto:

use core::dict::Felt252Dict;
use core::nullable::{NullableTrait, match_nullable, FromNullableResult};

fn main() {
    // Create the dictionary
    let mut d: Felt252Dict<Nullable<Span<felt252>>> = Default::default();

    // Create the array to insert
    let a = array![8, 9, 10];

    // Insert it as a `Span`
    d.insert(0, NullableTrait::new(a.span()));

    // Get value back
    let val = d.get(0);

    // Search the value and assert it is not null
    let span = match match_nullable(val) {
        FromNullableResult::Null => panic!("No value found"),
        FromNullableResult::NotNull(val) => val.unbox(),
    };

    // Verify we are having the right values
    assert!(*span.at(0) == 8, "Expecting 8");
    assert!(*span.at(1) == 9, "Expecting 9");
    assert!(*span.at(2) == 10, "Expecting 10");
}

Using Arrays inside Dictionaries

In the previous section, we explored how to store and retrieve complex types inside a dictionary using Nullable<T> and Box<T>. Now, let's take a look at how to store an array inside a dictionary and dynamically modify its contents.

Storing arrays in dictionaries in Cairo is slightly different from storing other types. This is because arrays are more complex data structures that require special handling to avoid issues with memory copying and references.

First, let's look at how to create a dictionary and insert an array into it. This process is pretty straightforward and follows a similar pattern to inserting other types of data:

use core::dict::Felt252Dict;

fn main() {
    let arr = array![20, 19, 26];
    let mut dict: Felt252Dict<Nullable<Array<u8>>> = Default::default();
    dict.insert(0, NullableTrait::new(arr));
    println!("Array inserted successfully.");
}

However, attempting to read an array from the dictionary using the get method will result in a compiler error. This is because get tries to copy the array in memory, which is not possible for arrays (as we've already mentioned in the previous section, Array<T> does not implement the Copy<T> trait):

use core::nullable::{match_nullable, FromNullableResult};
use core::dict::Felt252Dict;

fn main() {
    let arr = array![20, 19, 26];
    let mut dict: Felt252Dict<Nullable<Array<u8>>> = Default::default();
    dict.insert(0, NullableTrait::new(arr));
    println!("Array: {:?}", get_array_entry(ref dict, 0));
}

fn get_array_entry(ref dict: Felt252Dict<Nullable<Array<u8>>>, index: felt252) -> Span<u8> {
    let val = dict.get(0); // This will cause a compiler error
    let arr = match match_nullable(val) {
        FromNullableResult::Null => panic!("No value!"),
        FromNullableResult::NotNull(val) => val.unbox(),
    };
    arr.span()
}

$ scarb cairo-run 
   Compiling no_listing_15_dict_of_array_attempt_get v0.1.0 (listings/ch03-common-collections/no_listing_15_dict_of_array_attempt_get/Scarb.toml)
error: Trait has no implementation in context: core::traits::Copy::<core::nullable::Nullable::<core::array::Array::<core::integer::u8>>>.
 --> listings/ch03-common-collections/no_listing_15_dict_of_array_attempt_get/src/lib.cairo:13:20
    let val = dict.get(0); // This will cause a compiler error
                   ^*^

error: could not compile `no_listing_15_dict_of_array_attempt_get` due to previous error
error: `scarb metadata` exited with error

To correctly read an array from the dictionary, we need to use dictionary entries. This allows us to get a reference to the array value without copying it:

fn get_array_entry(ref dict: Felt252Dict<Nullable<Array<u8>>>, index: felt252) -> Span<u8> {
    let (entry, _arr) = dict.entry(index);
    let mut arr = _arr.deref_or(array![]);
    let span = arr.span();
    dict = entry.finalize(NullableTrait::new(arr));
    span
}

Note: We must convert the array to a Span before finalizing the entry, because calling NullableTrait::new(arr) moves the array, thus making it impossible to return it from the function.

To modify the stored array, such as appending a new value, we can use a similar approach. The following append_value function demonstrates this:

fn append_value(ref dict: Felt252Dict<Nullable<Array<u8>>>, index: felt252, value: u8) {
    let (entry, arr) = dict.entry(index);
    let mut unboxed_val = arr.deref_or(array![]);
    unboxed_val.append(value);
    dict = entry.finalize(NullableTrait::new(unboxed_val));
}

In the append_value function, we access the dictionary entry, dereference the array, append the new value, and finalize the entry with the updated array.

Note: Removing an item from a stored array can be implemented in a similar manner.

Below is the complete example demonstrating the creation, insertion, reading, and modification of an array in a dictionary:

use core::nullable::NullableTrait;
use core::dict::{Felt252Dict, Felt252DictEntryTrait};

fn append_value(ref dict: Felt252Dict<Nullable<Array<u8>>>, index: felt252, value: u8) {
    let (entry, arr) = dict.entry(index);
    let mut unboxed_val = arr.deref_or(array![]);
    unboxed_val.append(value);
    dict = entry.finalize(NullableTrait::new(unboxed_val));
}

fn get_array_entry(ref dict: Felt252Dict<Nullable<Array<u8>>>, index: felt252) -> Span<u8> {
    let (entry, _arr) = dict.entry(index);
    let mut arr = _arr.deref_or(array![]);
    let span = arr.span();
    dict = entry.finalize(NullableTrait::new(arr));
    span
}

fn main() {
    let arr = array![20, 19, 26];
    let mut dict: Felt252Dict<Nullable<Array<u8>>> = Default::default();
    dict.insert(0, NullableTrait::new(arr));
    println!("Before insertion: {:?}", get_array_entry(ref dict, 0));

    append_value(ref dict, 0, 30);

    println!("After insertion: {:?}", get_array_entry(ref dict, 0));
}

Understanding Cairo's Ownership system

Cairo is a language built around a linear type system that allows us to statically ensure that in every Cairo program, a value is used exactly once. This linear type system helps prevent runtime errors by ensuring that operations that could cause such errors, such as writing twice to a memory cell, are detected at compile time. This is achieved by implementing an ownership system and forbidding copying and dropping values by default. In this chapter, we’ll talk about Cairo's ownership system as well as references and snapshots.

Ownership Using a Linear Type System

Cairo uses a linear type system. In such a type system, any value (a basic type, a struct, an enum) must be used and must only be used once. 'Used' here means that the value is either destroyed or moved.

Destruction can happen in several ways:

• a variable goes out of scope.
• a struct is destructured.
• explicit destruction using destruct().

Moving a value simply means passing that value to another function.

This results in somewhat similar constraints to the Rust ownership model, but there are some differences. In particular, the Rust ownership model exists (in part) to avoid data races and concurrent mutable access to a memory value. This is obviously impossible in Cairo since the memory is immutable. Instead, Cairo leverages its linear type system for two main purposes:

• Ensuring that all code is provable and thus verifiable.
• Abstracting away the immutable memory of the Cairo VM.

Ownership

In Cairo, ownership applies to variables and not to values. A value can safely be referred to by many different variables (even if they are mutable variables), as the value itself is always immutable. Variables however can be mutable, so the compiler must ensure that constant variables aren't accidentally modified by the programmer. This makes it possible to talk about ownership of a variable: the owner is the code that can read (and write if mutable) the variable.

This means that variables (not values) follow similar rules to Rust values:

• Each variable in Cairo has an owner.
• There can only be one owner at a time.
• When the owner goes out of scope, the variable is destroyed.

Now that we’re past basic Cairo syntax, we won’t include all the fn main() { code in examples, so if you’re following along, make sure to put the following examples inside a main function manually. As a result, our examples will be a bit more concise, letting us focus on the actual details rather than boilerplate code.

Variable Scope

As a first example of the linear type system, we’ll look at the scope of some variables. A scope is the range within a program for which an item is valid. Take the following variable:

let s = 'hello';

The variable s refers to a short string. The variable is valid from the point at which it’s declared until the end of the current scope. Listing 4-1 shows a program with comments annotating where the variable s would be valid.

//TAG: ignore_fmt
fn main() {
    { // s is not valid here, it’s not yet declared
        let s = 'hello'; // s is valid from this point forward
        // do stuff with s
    } // this scope is now over, and s is no longer valid
}

Listing 4-1: A variable and the scope in which it is valid

En otras palabras, hay dos puntos importantes en el tiempo aquí:

• When s comes into scope, it is valid.
• It remains valid until it goes out of scope.

At this point, the relationship between scopes and when variables are valid is similar to that in other programming languages. Now we’ll build on top of this understanding by using the Array type we introduced in the previous "Arrays" section.

Moving values

As said earlier, moving a value simply means passing that value to another function. When that happens, the variable referring to that value in the original scope is destroyed and can no longer be used, and a new variable is created to hold the same value.

Arrays are an example of a complex type that is moved when passing it to another function. Here is a short reminder of what an array looks like:

fn main() {
    let mut arr: Array<u128> = array![];
    arr.append(1);
    arr.append(2);
}

How does the type system ensure that the Cairo program never tries to write to the same memory cell twice? Consider the following code, where we try to remove the front of the array twice:

fn foo(mut arr: Array<u128>) {
    arr.pop_front();
}

fn main() {
    let arr: Array<u128> = array![];
    foo(arr);
    foo(arr);
}

In this case, we try to pass the same value (the array in the arr variable) to both function calls. This means our code tries to remove the first element twice, which would try to write to the same memory cell twice - which is forbidden by the Cairo VM, leading to a runtime error. Thankfully, this code does not actually compile. Once we have passed the array to the foo function, the variable arr is no longer usable. We get this compile-time error, telling us that we would need Array to implement the Copy Trait:

$ scarb cairo-run 
   Compiling no_listing_02_pass_array_by_value v0.1.0 (listings/ch04-understanding-ownership/no_listing_02_pass_array_by_value/Scarb.toml)
warn: Unhandled `#[must_use]` type `core::option::Option::<core::integer::u128>`
 --> listings/ch04-understanding-ownership/no_listing_02_pass_array_by_value/src/lib.cairo:3:5
    arr.pop_front();
    ^*************^

error: Variable was previously moved.
 --> listings/ch04-understanding-ownership/no_listing_02_pass_array_by_value/src/lib.cairo:9:9
    foo(arr);
        ^*^
note: variable was previously used here:
  --> listings/ch04-understanding-ownership/no_listing_02_pass_array_by_value/src/lib.cairo:8:9
    foo(arr);
        ^*^
note: Trait has no implementation in context: core::traits::Copy::<core::array::Array::<core::integer::u128>>.

error: could not compile `no_listing_02_pass_array_by_value` due to previous error
error: `scarb metadata` exited with error

The Copy Trait

The Copy trait allows simple types to be duplicated by copying felts, without allocating new memory segments. This contrasts with Cairo's default "move" semantics, which transfer ownership of values to ensure memory safety and prevent issues like multiple writes to the same memory cell. Copy is implemented for types where duplication is safe and efficient, bypassing the need for move semantics. Types like Array and Felt252Dict cannot implement Copy, as manipulating them in different scopes is forbidden by the type system.

All basic types previously described in "Data Types" implement by default the Copy trait.

While Arrays and Dictionaries can't be copied, custom types that don't contain either of them can be. You can implement the Copy trait on your type by adding the #[derive(Copy)] annotation to your type definition. However, Cairo won't allow a type to be annotated with Copy if the type itself or any of its components doesn't implement the Copy trait.

#[derive(Copy, Drop)]
struct Point {
    x: u128,
    y: u128,
}

fn main() {
    let p1 = Point { x: 5, y: 10 };
    foo(p1);
    foo(p1);
}

fn foo(p: Point) { // do something with p
}

In this example, we can pass p1 twice to the foo function because the Point type implements the Copy trait. This means that when we pass p1 to foo, we are actually passing a copy of p1, so p1 remains valid. In ownership terms, this means that the ownership of p1 remains with the main function. If you remove the Copy trait derivation from the Point type, you will get a compile-time error when trying to compile the code.

Don't worry about the Struct keyword. We will introduce this in Chapter 5.

Destroying Values - Example with FeltDict

The other way linear types can be used is by being destroyed. Destruction must ensure that the 'resource' is now correctly released. In Rust, for example, this could be closing the access to a file, or locking a mutex. In Cairo, one type that has such behaviour is Felt252Dict. For provability, dicts must be 'squashed' when they are destructed. This would be very easy to forget, so it is enforced by the type system and the compiler.

No-op Destruction: the Drop Trait

You may have noticed that the Point type in the previous example also implements the Drop trait. For example, the following code will not compile, because the struct A is not moved or destroyed before it goes out of scope:

struct A {}

fn main() {
    A {}; // error: Variable not dropped.
}

However, types that implement the Drop trait are automatically destroyed when going out of scope. This destruction does nothing, it is a no-op - simply a hint to the compiler that this type can safely be destroyed once it's no longer useful. We call this "dropping" a value.

At the moment, the Drop implementation can be derived for all types, allowing them to be dropped when going out of scope, except for dictionaries (Felt252Dict) and types containing dictionaries. For example, the following code compiles:

#[derive(Drop)]
struct A {}

fn main() {
    A {}; // Now there is no error.
}

Destruction with a Side-effect: the Destruct Trait

When a value is destroyed, the compiler first tries to call the drop method on that type. If it doesn't exist, then the compiler tries to call destruct instead. This method is provided by the Destruct trait.

As said earlier, dictionaries in Cairo are types that must be "squashed" when destructed, so that the sequence of access can be proven. This is easy for developers to forget, so instead dictionaries implement the Destruct trait to ensure that all dictionaries are squashed when going out of scope. As such, the following example will not compile:

use core::dict::Felt252Dict;

struct A {
    dict: Felt252Dict<u128>,
}

fn main() {
    A { dict: Default::default() };
}

Si intenta ejecutar este código, obtendrá un error de tiempo de compilación:

$ scarb cairo-run 
   Compiling no_listing_06_no_destruct_compile_fails v0.1.0 (listings/ch04-understanding-ownership/no_listing_06_no_destruct_compile_fails/Scarb.toml)
error: Variable not dropped.
 --> listings/ch04-understanding-ownership/no_listing_06_no_destruct_compile_fails/src/lib.cairo:9:5
    A { dict: Default::default() };
    ^****************************^
note: Trait has no implementation in context: core::traits::Drop::<no_listing_06_no_destruct_compile_fails::A>.
note: Trait has no implementation in context: core::traits::Destruct::<no_listing_06_no_destruct_compile_fails::A>.

error: could not compile `no_listing_06_no_destruct_compile_fails` due to previous error
error: `scarb metadata` exited with error

When A goes out of scope, it can't be dropped as it implements neither the Drop (as it contains a dictionary and can't derive(Drop)) nor the Destruct trait. To fix this, we can derive the Destruct trait implementation for the A type:

use core::dict::Felt252Dict;

#[derive(Destruct)]
struct A {
    dict: Felt252Dict<u128>,
}

fn main() {
    A { dict: Default::default() }; // No error here
}

Ahora, cuando A salga del ámbito, su diccionario será automáticamente squashed, y el programa compilará.

Copy Array Data with clone

If we do want to deeply copy the data of an Array, we can use a common method called clone. We’ll discuss method syntax in a dedicated section in Chapter 5, but because methods are a common feature in many programming languages, you’ve probably seen them before.

Aquí hay un ejemplo del método clone en acción.

fn main() {
    let arr1: Array<u128> = array![];
    let arr2 = arr1.clone();
}

When you see a call to clone, you know that some arbitrary code is being executed and that code may be expensive. It’s a visual indicator that something different is going on. In this case, the value arr1 refers to is being copied, resulting in new memory cells being used, and a new variable arr2 is created, referring to the new copied value.

Return Values and Scope

Returning values is equivalent to moving them. Listing 4-2 shows an example of a function that returns some value, with similar annotations as those in Listing 4-1.

Filename: src/lib.cairo

#[derive(Drop)]
struct A {}

fn main() {
    let a1 = gives_ownership();           // gives_ownership moves its return
                                          // value into a1

    let a2 = A {};                        // a2 comes into scope

    let a3 = takes_and_gives_back(a2);    // a2 is moved into
                                          // takes_and_gives_back, which also
                                          // moves its return value into a3

} // Here, a3 goes out of scope and is dropped. a2 was moved, so nothing
  // happens. a1 goes out of scope and is dropped.

fn gives_ownership() -> A {               // gives_ownership will move its
                                          // return value into the function
                                          // that calls it

    let some_a = A {};                    // some_a comes into scope

    some_a                                // some_a is returned and
                                          // moves ownership to the calling
                                          // function
}

// This function takes an instance some_a of A and returns it
fn takes_and_gives_back(some_a: A) -> A { // some_a comes into scope

    some_a                                // some_a is returned and 
                                          // moves ownership to the calling
                                          // function
}

Listing 4-2: Moving return values

While this works, moving into and out of every function is a bit tedious. What if we want to let a function use a value but not move the value? It’s quite annoying that anything we pass in also needs to be passed back if we want to use it again, in addition to any data resulting from the body of the function that we might want to return as well.

Cairo does let us return multiple values using a tuple, as shown in Listing 4-3.

Filename: src/lib.cairo

fn main() {
    let arr1: Array<u128> = array![];

    let (arr2, len) = calculate_length(arr1);
}

fn calculate_length(arr: Array<u128>) -> (Array<u128>, usize) {
    let length = arr.len(); // len() returns the length of an array

    (arr, length)
}

Listing 4-3: Returning many values

But this is too much ceremony and a lot of work for a concept that should be common. Luckily for us, Cairo has two features for passing a value without destroying or moving it, called references and snapshots.

Referencias y Snapshots

The issue with the tuple code in previous Listing 4-3 is that we have to return the Array to the calling function so we can still use the Array after the call to calculate_length, because the Array was moved into calculate_length.

Snapshots

In the previous chapter, we talked about how Cairo's ownership system prevents us from using a variable after we've moved it, protecting us from potentially writing twice to the same memory cell. However, it's not very convenient. Let's see how we can retain ownership of the variable in the calling function using snapshots.

In Cairo, a snapshot is an immutable view of a value at a certain point in time. Recall that memory is immutable, so modifying a value actually creates a new memory cell. The old memory cell still exists, and snapshots are variables that refer to that "old" value. In this sense, snapshots are a view "into the past".

Here is how you would define and use a calculate_length function that takes a snapshot of an array as a parameter instead of taking ownership of the underlying value. In this example, the calculate_length function returns the length of the array passed as a parameter. As we're passing it as a snapshot, which is an immutable view of the array, we can be sure that the calculate_length function will not mutate the array, and ownership of the array is kept in the main function.

Filename: src/lib.cairo

fn main() {
    let mut arr1: Array<u128> = array![];
    let first_snapshot = @arr1; // Take a snapshot of `arr1` at this point in time
    arr1.append(1); // Mutate `arr1` by appending a value
    let first_length = calculate_length(
        first_snapshot,
    ); // Calculate the length of the array when the snapshot was taken
    let second_length = calculate_length(@arr1); // Calculate the current length of the array
    println!("The length of the array when the snapshot was taken is {}", first_length);
    println!("The current length of the array is {}", second_length);
}

fn calculate_length(arr: @Array<u128>) -> usize {
    arr.len()
}

Note: it is only possible to call the len() method on an array snapshot because it is defined as such in the ArrayTrait trait. If you try to call a method that is not defined for snapshots on a snapshot, you will get a compilation error. However, you can call methods expecting a snapshot on non-snapshot types.

La salida de este programa es:

$ scarb cairo-run 
   Compiling no_listing_09_snapshots v0.1.0 (listings/ch04-understanding-ownership/no_listing_09_snapshots/Scarb.toml)
    Finished `dev` profile target(s) in 3 seconds
     Running no_listing_09_snapshots
The length of the array when the snapshot was taken is 0
The current length of the array is 1
Run completed successfully, returning []

First, notice that all the tuple code in the variable declaration and the function return value is gone. Second, note that we pass @arr1 into calculate_length and, in its definition, we take @Array<u128> rather than Array<u128>.

Veamos más de cerca la llamada a la función aquí:

let second_length = calculate_length(@arr1); // Calculate the current length of the array

The @arr1 syntax lets us create a snapshot of the value in arr1. Because a snapshot is an immutable view of a value at a specific point in time, the usual rules of the linear type system are not enforced. In particular, snapshot variables always implement the Drop trait, never the Destruct trait, even dictionary snapshots.

De manera similar, la firma de la función utiliza @ para indicar que el tipo del parámetro arr es una instantánea. Añadamos algunas anotaciones explicativas:

fn calculate_length(
    array_snapshot: @Array<u128> // array_snapshot is a snapshot of an Array
) -> usize {
    array_snapshot.len()
} // Here, array_snapshot goes out of scope and is dropped.
// However, because it is only a view of what the original array `arr` contains, the original `arr` can still be used.

El alcance en el que la variable array_snapshot es válida es el mismo que el alcance de cualquier parámetro de función, pero el valor subyacente del snapshot no se eliminará cuando array_snapshot deje de usarse. Cuando las funciones tienen snapshots como parámetros en lugar de los valores reales, no necesitamos devolver los valores para devolver la propiedad del valor original, porque nunca la tuvimos.

Desnap Operator

To convert a snapshot back into a regular variable, you can use the desnap operator *, which serves as the opposite of the @ operator.

Only Copy types can be desnapped. However, in the general case, because the value is not modified, the new variable created by the desnap operator reuses the old value, and so desnapping is a completely free operation, just like Copy.

In the following example, we want to calculate the area of a rectangle, but we don't want to take ownership of the rectangle in the calculate_area function, because we might want to use the rectangle again after the function call. Since our function doesn't mutate the rectangle instance, we can pass the snapshot of the rectangle to the function, and then transform the snapshots back into values using the desnap operator *.

#[derive(Drop)]
struct Rectangle {
    height: u64,
    width: u64,
}

fn main() {
    let rec = Rectangle { height: 3, width: 10 };
    let area = calculate_area(@rec);
    println!("Area: {}", area);
}

fn calculate_area(rec: @Rectangle) -> u64 {
    // As rec is a snapshot to a Rectangle, its fields are also snapshots of the fields types.
    // We need to transform the snapshots back into values using the desnap operator `*`.
    // This is only possible if the type is copyable, which is the case for u64.
    // Here, `*` is used for both multiplying the height and width and for desnapping the snapshots.
    *rec.height * *rec.width
}

But, what happens if we try to modify something we’re passing as a snapshot? Try the code in Listing 4-4. Spoiler alert: it doesn’t work!

Filename: src/lib.cairo

#[derive(Copy, Drop)]
struct Rectangle {
    height: u64,
    width: u64,
}

fn main() {
    let rec = Rectangle { height: 3, width: 10 };
    flip(@rec);
}

fn flip(rec: @Rectangle) {
    let temp = rec.height;
    rec.height = rec.width;
    rec.width = temp;
}

Listing 4-4: Attempting to modify a snapshot value

Aquí está el error:

$ scarb cairo-run 
   Compiling listing_04_04 v0.1.0 (listings/ch04-understanding-ownership/listing_04_attempt_modifying_snapshot/Scarb.toml)
error: Invalid left-hand side of assignment.
 --> listings/ch04-understanding-ownership/listing_04_attempt_modifying_snapshot/src/lib.cairo:15:5
    rec.height = rec.width;
    ^********^

error: Invalid left-hand side of assignment.
 --> listings/ch04-understanding-ownership/listing_04_attempt_modifying_snapshot/src/lib.cairo:16:5
    rec.width = temp;
    ^*******^

error: could not compile `listing_04_04` due to previous error
error: `scarb metadata` exited with error

El compilador nos impide modificar los valores asociados a las instantáneas.

Mutable References

We can achieve the behavior we want in Listing 4-4 by using a mutable reference instead of a snapshot. Mutable references are actually mutable values passed to a function that are implicitly returned at the end of the function, returning ownership to the calling context. By doing so, they allow you to mutate the value passed while keeping ownership of it by returning it automatically at the end of the execution. In Cairo, a parameter can be passed as mutable reference using the ref modifier.

Note: In Cairo, a parameter can only be passed as mutable reference using the ref modifier if the variable is declared as mutable with mut.

In Listing 4-5, we use a mutable reference to modify the value of the height and width fields of the Rectangle instance in the flip function.

#[derive(Drop)]
struct Rectangle {
    height: u64,
    width: u64,
}

fn main() {
    let mut rec = Rectangle { height: 3, width: 10 };
    flip(ref rec);
    println!("height: {}, width: {}", rec.height, rec.width);
}

fn flip(ref rec: Rectangle) {
    let temp = rec.height;
    rec.height = rec.width;
    rec.width = temp;
}

Listing 4-5: Use of a mutable reference to modify a value

Primero, cambiamos rec a mut. Luego, pasamos una referencia mutable de rec a flip con ref rec y actualizamos la firma de la función para aceptar una referencia mutable con ref rec: Rectangle. Esto deja muy claro que la función flip modificará el valor de la instancia de Rectangle pasada como parámetro.

La salida del programa es:

$ scarb cairo-run 
   Compiling listing_04_05 v0.1.0 (listings/ch04-understanding-ownership/listing_05_mutable_reference/Scarb.toml)
    Finished `dev` profile target(s) in 3 seconds
     Running listing_04_05
height: 10, width: 3
Run completed successfully, returning []

Como era de esperar, los campos height y width de la variable rec se han intercambiado.

Small Recap

Let’s recap what we’ve discussed about the linear type system, ownership, snapshots, and references:

• At any given time, a variable can only have one owner.
• You can pass a variable by-value, by-snapshot, or by-reference to a function.
• If you pass-by-value, ownership of the variable is transferred to the function.
• If you want to keep ownership of the variable and know that your function won’t mutate it, you can pass it as a snapshot with @.
• If you want to keep ownership of the variable and know that your function will mutate it, you can pass it as a mutable reference with ref.

Uso de estructuras para estructurar datos relacionados

Un struct, o estructura, es un tipo de datos personalizado que te permite empaquetar y nombrar múltiples valores relacionados que conforman un grupo significativo. Si estás familiarizado con un lenguaje orientado a objetos, un struct es como los atributos de datos de un objeto. En este capítulo, compararemos y contrastaremos las tuplas con los structs para construir sobre lo que ya sabes y demostrar cuándo los structs son una mejor manera de agrupar datos.

We’ll demonstrate how to define and instantiate structs. We’ll discuss how to define associated functions, especially the kind of associated functions called methods, to specify behavior associated with a struct type. Structs and enums (discussed in the next chapter) are the building blocks for creating new types in your program’s domain to take full advantage of Cairo's compile-time type checking.

Definición e instanciación de estructuras

Structs are similar to tuples, discussed in the Data Types section, in that both hold multiple related values. Like tuples, the pieces of a struct can be different types. Unlike with tuples, in a struct you’ll name each piece of data so it’s clear what the values mean. Adding these names means that structs are more flexible than tuples: you don’t have to rely on the order of the data to specify or access the values of an instance.

To define a struct, we enter the keyword struct and name the entire struct. A struct’s name should describe the significance of the pieces of data being grouped together. Then, inside curly brackets, we define the names and types of the pieces of data, which we call fields. For example, Listing 5-1 shows a struct that stores information about a user account.

Filename: src/lib.cairo

#[derive(Drop)]
struct User {
    active: bool,
    username: ByteArray,
    email: ByteArray,
    sign_in_count: u64,
}

Listing 5-1: A User struct definition

To use a struct after we’ve defined it, we create an instance of that struct by specifying concrete values for each of the fields. We create an instance by stating the name of the struct and then add curly brackets containing key: value pairs, where the keys are the names of the fields and the values are the data we want to store in those fields. We don’t have to specify the fields in the same order in which we declared them in the struct. In other words, the struct definition is like a general template for the type, and instances fill in that template with particular data to create values of the type.

For example, we can declare two particular users as shown in Listing 5-2.

Filename: src/lib.cairo

#[derive(Drop)]
struct User {
    active: bool,
    username: ByteArray,
    email: ByteArray,
    sign_in_count: u64,
}

fn main() {
    let user1 = User {
        active: true, username: "someusername123", email: "someone@example.com", sign_in_count: 1,
    };
    let user2 = User {
        sign_in_count: 1, username: "someusername123", active: true, email: "someone@example.com",
    };
}

Listing 5-2: Creating two instances of the User struct

To get a specific value from a struct, we use dot notation. For example, to access user1's email address, we use user1.email. If the instance is mutable, we can change a value by using the dot notation and assigning into a particular field. Listing 5-3 shows how to change the value in the email field of a mutable User instance.

Filename: src/lib.cairo

#[derive(Drop)]
struct User {
    active: bool,
    username: ByteArray,
    email: ByteArray,
    sign_in_count: u64,
}
fn main() {
    let mut user1 = User {
        active: true, username: "someusername123", email: "someone@example.com", sign_in_count: 1,
    };
    user1.email = "anotheremail@example.com";
}

fn build_user(email: ByteArray, username: ByteArray) -> User {
    User { active: true, username: username, email: email, sign_in_count: 1 }
}

fn build_user_short(email: ByteArray, username: ByteArray) -> User {
    User { active: true, username, email, sign_in_count: 1 }
}

Listing 5-3: Changing the value in the email field of a User instance

Tenga en cuenta que toda la instancia debe ser mutable; Cairo no nos permite marcar solo ciertos campos como mutables.

Como con cualquier expresión, podemos construir una nueva instancia de la estructura como la última expresión en el cuerpo de la función para devolver implícitamente esa nueva instancia.

Listing 5-4 shows a build_user function that returns a User instance with the given email and username. The active field gets the value of true, and the sign_in_count gets a value of 1.

Filename: src/lib.cairo

#[derive(Drop)]
struct User {
    active: bool,
    username: ByteArray,
    email: ByteArray,
    sign_in_count: u64,
}
fn main() {
    let mut user1 = User {
        active: true, username: "someusername123", email: "someone@example.com", sign_in_count: 1,
    };
    user1.email = "anotheremail@example.com";
}

fn build_user(email: ByteArray, username: ByteArray) -> User {
    User { active: true, username: username, email: email, sign_in_count: 1 }
}

fn build_user_short(email: ByteArray, username: ByteArray) -> User {
    User { active: true, username, email, sign_in_count: 1 }
}

Listing 5-4: A build_user function that takes an email and username and returns a User instance.

Tiene sentido nombrar los parámetros de la función con el mismo nombre que los campos de la estructura, porque tener que repetir los nombres y variables de los campos emaily username es un poco tedioso. Si la estructura tuviera más campos, repetir cada nombre sería aún más molesto. ¡Afortunadamente, hay una forma abreviada!

Using the Field Init Shorthand

Because the parameter names and the struct field names are exactly the same in Listing 5-4, we can use the field init shorthand syntax to rewrite build_user so it behaves exactly the same but doesn’t have the repetition of username and email, as shown in Listing 5-5.

Filename: src/lib.cairo

#[derive(Drop)]
struct User {
    active: bool,
    username: ByteArray,
    email: ByteArray,
    sign_in_count: u64,
}
fn main() {
    let mut user1 = User {
        active: true, username: "someusername123", email: "someone@example.com", sign_in_count: 1,
    };
    user1.email = "anotheremail@example.com";
}

fn build_user(email: ByteArray, username: ByteArray) -> User {
    User { active: true, username: username, email: email, sign_in_count: 1 }
}

fn build_user_short(email: ByteArray, username: ByteArray) -> User {
    User { active: true, username, email, sign_in_count: 1 }
}

Listing 5-5: A build_user function that uses field init shorthand because the username and email parameters have the same name as struct fields.

Aquí, estamos creando una nueva instancia de la estructura User, que tiene un campo llamado email. Queremos establecer el valor del campo email con el valor del parámetro email de la función build_user. Debido a que el campo email y el parámetro email tienen el mismo nombre, solo necesitamos escribir email en lugar de email: email.

Creating Instances from Other Instances with Struct Update Syntax

It’s often useful to create a new instance of a struct that includes most of the values from another instance, but changes some. You can do this using struct update syntax.

First, in Listing 5-6 we show how to create a new User instance in user2 regularly, without the update syntax. We set a new value for email but otherwise use the same values from user1 that we created in Listing 5-2.

Filename: src/lib.cairo

#[derive(Drop)]
struct User {
    active: bool,
    username: ByteArray,
    email: ByteArray,
    sign_in_count: u64,
}

fn main() {
    // --snip--

    let user1 = User {
        email: "someone@example.com", username: "someusername123", active: true, sign_in_count: 1,
    };

    let user2 = User {
        active: user1.active,
        username: user1.username,
        email: "another@example.com",
        sign_in_count: user1.sign_in_count,
    };
}

Listing 5-6: Creating a new User instance using all but one of the values from user1

Using struct update syntax, we can achieve the same effect with less code, as shown in Listing 5-7. The syntax .. specifies that the remaining fields not explicitly set should have the same value as the fields in the given instance.

Filename: src/lib.cairo

use core::byte_array;
#[derive(Drop)]
struct User {
    active: bool,
    username: ByteArray,
    email: ByteArray,
    sign_in_count: u64,
}

fn main() {
    // --snip--

    let user1 = User {
        email: "someone@example.com", username: "someusername123", active: true, sign_in_count: 1,
    };

    let user2 = User { email: "another@example.com", ..user1 };
}

Listing 5-7: Using struct update syntax to set a new email value for a User instance but to use the rest of the values from user1

The code in Listing 5-7 also creates an instance of user2 that has a different value for email but has the same values for the username, active, and sign_in_count fields as user1. The ..user1 part must come last to specify that any remaining fields should get their values from the corresponding fields in user1, but we can choose to specify values for as many fields as we want in any order, regardless of the order of the fields in the struct’s definition.

Note that the struct update syntax uses = like an assignment; this is because it moves the data, just as we saw in the "Moving Values" section. In this example, we can no longer use user1 as a whole after creating user2 because the ByteArray in the username field of user1 was moved into user2. If we had given user2 new ByteArray values for both email and username, and thus only used the active and sign_in_count values from user1, then user1 would still be valid after creating user2. Both active and sign_in_count are types that implement the Copy trait, so the behavior we discussed in the "Copy Trait" section would apply.

Un programa de ejemplo usando estructuras

Para entender cuándo podríamos usar estructuras, escribamos un programa que calcule el área de un rectángulo. Comenzaremos usando variables individuales y luego reescribiremos el programa hasta que estemos usando estructuras en su lugar.

Let’s make a new project with Scarb called rectangles that will take the width and height of a rectangle specified in pixels and calculate the area of the rectangle. Listing 5-8 shows a short program with one way of doing exactly that in our project’s src/lib.cairo.

Filename: src/lib.cairo

fn main() {
    let width = 30;
    let height = 10;
    let area = area(width, height);
    println!("Area is {}", area);
}

fn area(width: u64, height: u64) -> u64 {
    width * height
}

Listing 5-8: Calculating the area of a rectangle specified by separate width and height variables.

Now run the program with scarb cairo-run:

$ scarb cairo-run 
   Compiling listing_04_06_no_struct v0.1.0 (listings/ch05-using-structs-to-structure-related-data/listing_03_no_struct/Scarb.toml)
    Finished `dev` profile target(s) in 3 seconds
     Running listing_04_06_no_struct
Area is 300
Run completed successfully, returning []

Este código logra calcular el área del rectángulo llamando a la función area con cada dimensión, pero podemos hacer más para que este código sea claro y legible.

El problema con este código es evidente en la declaración de la función area:

fn area(width: u64, height: u64) -> u64 {

The area function is supposed to calculate the area of one rectangle, but the function we wrote has two parameters, and it’s not clear anywhere in our program that the parameters are related. It would be more readable and more manageable to group width and height together. We’ve already discussed one way we might do that in the Tuple Section of Chapter 2.

Refactoring with Tuples

Listing 5-9 shows another version of our program that uses tuples.

Filename: src/lib.cairo

fn main() {
    let rectangle = (30, 10);
    let area = area(rectangle);
    println!("Area is {}", area);
}

fn area(dimension: (u64, u64)) -> u64 {
    let (x, y) = dimension;
    x * y
}

Listing 5-9: Specifying the width and height of the rectangle with a tuple.

En cierto modo, este programa es mejor. Las tuplas nos permiten agregar un poco de estructura y ahora estamos pasando solo un argumento. Pero en otro sentido, esta versión es menos clara: las tuplas no nombran sus elementos, por lo que tenemos que indexar las partes de la tupla, lo que hace que nuestro cálculo sea menos obvio.

Mezclar el ancho y la altura no importaría para el cálculo del área, pero si queremos calcular la diferencia, ¡sería importante! Tendríamos que tener en cuenta que width es el índice de tupla 0 y height es el índice de tupla 1. Esto sería aún más difícil de entender y tener en cuenta para otra persona si usara nuestro código. Debido a que no hemos transmitido el significado de nuestros datos en nuestro código, ahora es más fácil introducir errores.

Refactoring with Structs: Adding More Meaning

Usamos estructuras para agregar significado al etiquetar los datos. Podemos transformar la tupla que estamos usando en una estructura con un nombre para el todo y nombres para las partes.

Filename: src/lib.cairo

struct Rectangle {
    width: u64,
    height: u64,
}

fn main() {
    let rectangle = Rectangle { width: 30, height: 10 };
    let area = area(rectangle);
    println!("Area is {}", area);
}

fn area(rectangle: Rectangle) -> u64 {
    rectangle.width * rectangle.height
}

Listing 5-10: Defining a Rectangle struct.

Aquí hemos definido una estructura y la hemos llamado Rectangle. Dentro de las llaves, definimos los campos como width y height, los cuales tienen el tipo u64. Luego, en main, creamos una instancia particular de Rectangle que tiene un ancho de 30 y una altura de 10. Nuestra función area ahora está definida con un parámetro, al que hemos llamado rectangle que es de tipo de la estructura Rectangle. Luego podemos acceder a los campos de la instancia con notación de punto, y dar nombres descriptivos a los valores en lugar de usar los valores de índice de tupla de 0 y 1.

Conversions of Custom Types

We've already described how to perform type conversion on in-built types, see Data Types > Type Conversion. In this section, we will see how to define conversions for custom types.

Note: conversion can be defined for compound types, e.g. tuples, too.

Into

Defining a conversion for a custom type using the Into trait will typically require specification of the type to convert into, as the compiler is unable to determine this most of the time. However this is a small trade-off considering we get the functionality for free.

// Compiler automatically imports the core library, so you can omit this import
use core::traits::Into;

#[derive(Drop, PartialEq)]
struct Rectangle {
    width: u64,
    height: u64,
}

#[derive(Drop)]
struct Square {
    side_length: u64,
}

impl SquareIntoRectangle of Into<Square, Rectangle> {
    fn into(self: Square) -> Rectangle {
        Rectangle { width: self.side_length, height: self.side_length }
    }
}

fn main() {
    let square = Square { side_length: 5 };
    // Compiler will complain if you remove the type annotation
    let result: Rectangle = square.into();
    let expected = Rectangle { width: 5, height: 5 };
    assert!(
        result == expected,
        "A square is always convertible to a rectangle with the same width and height!",
    );
}

TryInto

Defining a conversion for TryInto is similar to defining it for Into.

// Compiler automatically imports the core library, so you can omit this import
use core::traits::TryInto;

#[derive(Drop)]
struct Rectangle {
    width: u64,
    height: u64,
}

#[derive(Drop, PartialEq)]
struct Square {
    side_length: u64,
}

impl RectangleIntoSquare of TryInto<Rectangle, Square> {
    fn try_into(self: Rectangle) -> Option<Square> {
        if self.height == self.width {
            Option::Some(Square { side_length: self.height })
        } else {
            Option::None
        }
    }
}

fn main() {
    let rectangle = Rectangle { width: 8, height: 8 };
    let result: Square = rectangle.try_into().unwrap();
    let expected = Square { side_length: 8 };
    assert!(
        result == expected,
        "Rectangle with equal width and height should be convertible to a square.",
    );

    let rectangle = Rectangle { width: 5, height: 8 };
    let result: Option<Square> = rectangle.try_into();
    assert!(
        result.is_none(),
        "Rectangle with different width and height should not be convertible to a square.",
    );
}

Sintaxis de métodos

Methods are similar to functions: we declare them with the fn keyword and a name, they can have parameters and a return value, and they contain some code that’s run when the method is called from somewhere else. Unlike functions, methods are defined within the context of a struct (or an enum which we cover in Chapter 6), and their first parameter is always self, which represents the instance of the type the method is being called on.

Defining Methods

Let’s change the area function that has a Rectangle instance as a parameter and instead make an area method defined on the Rectangle struct, as shown in Listing 5-11

#[derive(Copy, Drop)]
struct Rectangle {
    width: u64,
    height: u64,
}

trait RectangleTrait {
    fn area(self: @Rectangle) -> u64;
}

impl RectangleImpl of RectangleTrait {
    fn area(self: @Rectangle) -> u64 {
        (*self.width) * (*self.height)
    }
}

fn main() {
    let rect1 = Rectangle { width: 30, height: 50 };
    println!("Area is {}", rect1.area());
}

Listing 5-11: Defining an area method on the Rectangle struct.

To define the function within the context of Rectangle, we start an impl (implementation) block for a trait RectangleTrait that defines the methods that can be called on a Rectangle instance. As impl blocks can only be defined for traits and not types, we need to define this trait first - but it's not meant to be used for anything else.

Everything within this impl block will be associated with the Rectangle type. Then we move the area function within the impl curly brackets and change the first (and in this case, only) parameter to be self in the signature and everywhere within the body. In main, where we called the area function and passed rect1 as an argument, we can instead use method syntax to call the area method on our Rectangle instance. The method syntax goes after an instance: we add a dot followed by the method name, parentheses, and any arguments.

In the signature for area, we use self: @Rectangle instead of rectangle: @Rectangle. Methods must have a parameter named self, for their first parameter, and the type of self indicates the type that method can be called on. Methods can take ownership of self, but self can also be passed by snapshot or by reference, just like any other parameter.

There is no direct link between a type and a trait. Only the type of the self parameter of a method defines the type from which this method can be called. That means, it is technically possible to define methods on multiple types in a same trait (mixing Rectangle and Circle methods, for example). But this is not a recommended practice as it can lead to confusion.

The main reason for using methods instead of functions, in addition to providing method syntax, is for organization. We’ve put all the things we can do with an instance of a type in one impl block rather than making future users of our code search for capabilities of Rectangle in various places in the library we provide.

The generate_trait Attribute

If you are familiar with Rust, you may find Cairo's approach confusing because methods cannot be defined directly on types. Instead, you must define a trait and an implementation of this trait associated with the type for which the method is intended. However, defining a trait and then implementing it to define methods on a specific type is verbose, and unnecessary: the trait itself will not be reused.

So, to avoid defining useless traits, Cairo provides the #[generate_trait] attribute to add above a trait implementation, which tells the compiler to generate the corresponding trait definition for you, and let's you focus on the implementation only. Both approaches are equivalent, but it's considered a best practice to not explicitly define traits in this case.

The previous example can also be written as follows:

#[derive(Copy, Drop)]
struct Rectangle {
    width: u64,
    height: u64,
}

#[generate_trait]
impl RectangleImpl of RectangleTrait {
    fn area(self: @Rectangle) -> u64 {
        (*self.width) * (*self.height)
    }
}

fn main() {
    let rect1 = Rectangle { width: 30, height: 50 };
    println!("Area is {}", rect1.area());
}

Let's use this #[generate_trait] in the following chapters to make our code cleaner.

Snapshots and References

As the area method does not modify the calling instance, self is declared as a snapshot of a Rectangle instance with the @ snapshot operator. But, of course, we can also define some methods receiving a mutable reference of this instance, to be able to modify it.

Let's write a new method scale which resizes a rectangle of a factor given as parameter:

#[generate_trait]
impl RectangleImpl of RectangleTrait {
    fn area(self: @Rectangle) -> u64 {
        (*self.width) * (*self.height)
    }
    fn scale(ref self: Rectangle, factor: u64) {
        self.width *= factor;
        self.height *= factor;
    }
}

fn main() {
    let mut rect2 = Rectangle { width: 10, height: 20 };
    rect2.scale(2);
    println!("The new size is (width: {}, height: {})", rect2.width, rect2.height);
}

It is also possible to define a method which takes ownership of the instance by using just self as the first parameter but it is rare. This technique is usually used when the method transforms self into something else and you want to prevent the caller from using the original instance after the transformation.

Look at the Understanding Ownership chapter for more details about these important notions.

Methods with Several Parameters

Let’s practice using methods by implementing another method on the Rectangle struct. This time we want to write the method can_hold which accepts another instance of Rectangle and returns true if this rectangle can fit completely within self; otherwise, it should return false.

#[generate_trait]
impl RectangleImpl of RectangleTrait {
    fn area(self: @Rectangle) -> u64 {
        *self.width * *self.height
    }

    fn scale(ref self: Rectangle, factor: u64) {
        self.width *= factor;
        self.height *= factor;
    }

    fn can_hold(self: @Rectangle, other: @Rectangle) -> bool {
        *self.width > *other.width && *self.height > *other.height
    }
}

fn main() {
    let rect1 = Rectangle { width: 30, height: 50 };
    let rect2 = Rectangle { width: 10, height: 40 };
    let rect3 = Rectangle { width: 60, height: 45 };

    println!("Can rect1 hold rect2? {}", rect1.can_hold(@rect2));
    println!("Can rect1 hold rect3? {}", rect1.can_hold(@rect3));
}

Here, we expect that rect1 can hold rect2 but not rect3.

Associated functions

We call associated functions all functions that are defined inside an impl block that are associated to a specific type. While this is not enforced by the compiler, it is a good practice to keep associated functions related to the same type in the same impl block - for example, all functions related to Rectangle will be grouped in the same impl block for RectangleTrait.

Methods are a special kind of associated function, but we can also define associated functions that don’t have self as their first parameter (and thus are not methods) because they don’t need an instance of the type to work with, but are still associated with that type.

Associated functions that aren’t methods are often used for constructors that will return a new instance of the type. These are often called new, but new isn’t a special name and isn’t built into the language. For example, we could choose to provide an associated function named square that would have one dimension parameter and use that as both width and height, thus making it easier to create a square Rectangle rather than having to specify the same value twice:

Let's create the function new which creates a Rectangle from a width and a height, square which creates a square Rectangle from a size and avg which computes the average of two Rectangle instances:

#[generate_trait]
impl RectangleImpl of RectangleTrait {
    fn area(self: @Rectangle) -> u64 {
        (*self.width) * (*self.height)
    }

    fn new(width: u64, height: u64) -> Rectangle {
        Rectangle { width, height }
    }

    fn square(size: u64) -> Rectangle {
        Rectangle { width: size, height: size }
    }

    fn avg(lhs: @Rectangle, rhs: @Rectangle) -> Rectangle {
        Rectangle {
            width: ((*lhs.width) + (*rhs.width)) / 2, height: ((*lhs.height) + (*rhs.height)) / 2,
        }
    }
}

fn main() {
    let rect1 = RectangleTrait::new(30, 50);
    let rect2 = RectangleTrait::square(10);

    println!(
        "The average Rectangle of {:?} and {:?} is {:?}",
        @rect1,
        @rect2,
        RectangleTrait::avg(@rect1, @rect2),
    );
}

To call the square associated function, we use the :: syntax with the struct name; let sq = RectangleTrait::square(3); is an example. This function is namespaced by the trait: the :: syntax is used for both associated functions and namespaces created by modules. We’ll discuss modules in Chapter 7.

Note that the avg function could also be written as a method with self as the first rectangle. In this case, instead of using the method with RectangleTrait::avg(@rect1, @rect2), it would be called with rect1.avg(rect2).

Multiple Traits and impl Blocks

Each struct is allowed to have multiple trait and impl blocks. For example, the following code is equivalent to the code shown in the Methods with several parameters section, which has each method in its own trait and impl blocks.

#[generate_trait]
impl RectangleCalcImpl of RectangleCalc {
    fn area(self: @Rectangle) -> u64 {
        (*self.width) * (*self.height)
    }
}

#[generate_trait]
impl RectangleCmpImpl of RectangleCmp {
    fn can_hold(self: @Rectangle, other: @Rectangle) -> bool {
        *self.width > *other.width && *self.height > *other.height
    }
}

There’s no strong reason to separate these methods into multiple trait and impl blocks here, but this is valid syntax.

Enums y Concordancia de Patrones

In this chapter, we’ll look at enumerations, also referred to as enums. Enums allow you to define a type by enumerating its possible variants. First, we’ll define and use an enum to show how an enum can encode meaning along with data. Next, we’ll explore a particularly useful enum, called Option, which expresses that a value can be either something or nothing. Finally, we’ll look at how pattern matching in the match expression makes it easy to run different code for different values of an enum.

Enums

Los Enums, abreviatura de "enumeraciones", son una forma de definir un tipo de datos personalizado que consiste en un conjunto fijo de valores nombrados, llamados variantes. Los enums son útiles para representar una colección de valores relacionados donde cada valor es distinto y tiene un significado específico.

Enum Variants and Values

Aquí hay un ejemplo sencillo de un enum:

#[derive(Drop)]
enum Direction {
    North,
    East,
    South,
    West,
}

In this example, we've defined an enum called Direction with four variants: North, East, South, and West. The naming convention is to use PascalCase for enum variants. Each variant represents a distinct value of the Direction type. In this particular example, variants don't have any associated value. One variant can be instantiated using this syntax:

#[derive(Drop)]
enum Direction {
    North,
    East,
    South,
    West,
}

fn main() {
    let direction = Direction::North;
}

Now let's imagine that our variants have associated values, that store the exact degree of the direction. We can define a new Direction enum:

#[derive(Drop)]
enum Direction {
    North: u128,
    East: u128,
    South: u128,
    West: u128,
}

fn main() {
    let direction = Direction::North(10);
}

and instantiate it as follows:

#[derive(Drop)]
enum Direction {
    North: u128,
    East: u128,
    South: u128,
    West: u128,
}

fn main() {
    let direction = Direction::North(10);
}

In this code, each variant is associated with a u128 value, representing the direction in degrees. In the next example, we will see that it is also possible to associate different data types with each variant.

It's easy to write code that acts differently depending on the variant of an enum instance, in this example to run specific code according to a direction. You can learn more about it in the Match Control Flow Construct section.

Enums Combined with Custom Types

Enums can also be used to store more interesting custom data associated with each variant. For example:

#[derive(Drop)]
enum Message {
    Quit,
    Echo: felt252,
    Move: (u128, u128),
}

In this example, the Message enum has three variants: Quit, Echo, and Move, all with different types:

• Quit doesn't have any associated value.
• Echo is a single felt252.
• Move is a tuple of two u128 values.

You could even use a Struct or another enum you defined inside one of your enum variants.

Trait Implementations for Enums

En Cairo, puedes definir traits e implementarlos para tus enums personalizados. Esto te permite definir métodos y comportamientos asociados con el enum. Aquí hay un ejemplo de cómo definir un trait e implementarlo para el enum Message anterior:

trait Processing {
    fn process(self: Message);
}

impl ProcessingImpl of Processing {
    fn process(self: Message) {
        match self {
            Message::Quit => { println!("quitting") },
            Message::Echo(value) => { println!("echoing {}", value) },
            Message::Move((x, y)) => { println!("moving from {} to {}", x, y) },
        }
    }
}

In this example, we implemented the Processing trait for Message. Here is how it could be used to process a Quit message:

#[derive(Drop)]
enum Message {
    Quit,
    Echo: felt252,
    Move: (u128, u128),
}

trait Processing {
    fn process(self: Message);
}

impl ProcessingImpl of Processing {
    fn process(self: Message) {
        match self {
            Message::Quit => { println!("quitting") },
            Message::Echo(value) => { println!("echoing {}", value) },
            Message::Move((x, y)) => { println!("moving from {} to {}", x, y) },
        }
    }
}
fn main() {
    let msg: Message = Message::Quit;
    msg.process(); // prints "quitting"
}

The Option Enum and Its Advantages

The Option enum is a standard Cairo enum that represents the concept of an optional value. It has two variants: Some: T and None. Some: T indicates that there's a value of type T, while None represents the absence of a value.

enum Option<T> {
    Some: T,
    None,
}

El enum Option es útil porque te permite representar explícitamente la posibilidad de que un valor esté ausente, lo que hace que tu código sea más expresivo y fácil de entender. Usar Option también puede ayudar a prevenir errores causados por el uso de valores null no inicializados o inesperados.

To give you an example, here is a function which returns the index of the first element of an array with a given value, or None if the element is not present.

Estamos demostrando dos enfoques para la función anterior:

• Recursive approach with find_value_recursive.
• Iterative approach with find_value_iterative.

fn find_value_recursive(mut arr: Span<felt252>, value: felt252, index: usize) -> Option<usize> {
    match arr.pop_front() {
        Option::Some(index_value) => { if (*index_value == value) {
            return Option::Some(index);
        } },
        Option::None => { return Option::None; },
    };

    find_value_recursive(arr, value, index + 1)
}

fn find_value_iterative(mut arr: Span<felt252>, value: felt252) -> Option<usize> {
    let mut result = Option::None;
    let mut index = 0;

    while let Option::Some(array_value) = arr.pop_front() {
        if (*array_value == value) {
            result = Option::Some(index);
            break;
        };

        index += 1;
    };

    result
}

Enums can be useful in many situations, especially when using the match flow construct that we just used. We will describe it in the next section.

Other enums are used very often, such as the Result enum, allowing to handle errors gracefully. We will explain the Result enum in detail in the "Error Handling" chapter.

La construcción del flujo de control de coincidencias

Cairo has an extremely powerful control flow construct called match that allows you to compare a value against a series of patterns and then execute code based on which pattern matches. Patterns can be made up of literal values, variable names, wildcards, and many other things. The power of match comes from the expressiveness of the patterns and the fact that the compiler confirms that all possible cases are handled.

Think of a match expression as being like a coin-sorting machine: coins slide down a track with variously sized holes along it, and each coin falls through the first hole it encounters that it fits into. In the same way, values go through each pattern in a match, and at the first pattern the value “fits”, the value falls into the associated code block to be used during execution.

Speaking of coins, let’s use them as an example using match! We can write a function that takes an unknown US coin and, in a similar way as the counting machine, determines which coin it is and returns its value in cents, as shown in Listing 6-1.

enum Coin {
    Penny,
    Nickel,
    Dime,
    Quarter,
}

fn value_in_cents(coin: Coin) -> felt252 {
    match coin {
        Coin::Penny => 1,
        Coin::Nickel => 5,
        Coin::Dime => 10,
        Coin::Quarter => 25,
    }
}

Listing 6-1: An enum and a match expression that has the variants of the enum as its patterns

Let’s break down the match expression in the value_in_cents function. First, we list the match keyword followed by an expression, which in this case is the value coin. This seems very similar to a conditional expression used with the if statement, but there’s a big difference: with if, the condition needs to evaluate to a boolean value, but here it can be any type. The type of coin in this example is the Coin enum that we defined on the first line.

Next are the match arms. An arm has two parts: a pattern and some code. The first arm here has a pattern that is the value Coin::Penny and then the => operator that separates the pattern and the code to run. The code in this case is just the value 1. Each arm is separated from the next with a comma.

When the match expression executes, it compares the resultant value against the pattern of each arm, in the order they are given. If a pattern matches the value, the code associated with that pattern is executed. If that pattern doesn’t match the value, execution continues to the next arm, much as in a coin-sorting machine. We can have as many arms as we need: in the above example, our match has four arms.

El código asociado con cada brazo es una expresión, y el valor resultante de la expresión en el brazo coincidente es el valor que se devuelve para toda la expresión match.

We don’t typically use curly brackets if the match arm code is short, as it is in our example where each arm just returns a value. If you want to run multiple lines of code in a match arm, you must use curly brackets, with a comma following the arm. For example, the following code prints “Lucky penny!” every time the method is called with a Coin::Penny, but still returns the last value of the block, 1:

fn value_in_cents(coin: Coin) -> felt252 {
    match coin {
        Coin::Penny => {
            println!("Lucky penny!");
            1
        },
        Coin::Nickel => 5,
        Coin::Dime => 10,
        Coin::Quarter => 25,
    }
}

Patterns That Bind to Values

Another useful feature of match arms is that they can bind to the parts of the values that match the pattern. This is how we can extract values out of enum variants.

As an example, let’s change one of our enum variants to hold data inside it. From 1999 through 2008, the United States minted quarters with different designs for each of the 50 states on one side. No other coins got state designs, so only quarters have this extra value. We can add this information to our enum by changing the Quarter variant to include a UsState value stored inside it, which we’ve done in Listing 6-2.

#[derive(Drop, Debug)] // Debug so we can inspect the state in a minute
enum UsState {
    Alabama,
    Alaska,
}

#[derive(Drop)]
enum Coin {
    Penny,
    Nickel,
    Dime,
    Quarter: UsState,
}

Listing 6-2: A Coin enum in which the Quarter variant also holds a UsState value

Imaginemos que un amigo está tratando de recolectar todas las 50 monedas de cuarto de estado. Mientras clasificamos nuestro cambio suelto por tipo de moneda, también llamaremos el nombre del estado asociado con cada cuarto para que si es uno que nuestro amigo no tiene, puedan agregarlo a su colección.

In the match expression for this code, we add a variable called state to the pattern that matches values of the variant Coin::Quarter. When a Coin::Quarter matches, the state variable will bind to the value of that quarter’s state. Then we can use state in the code for that arm, like so:

fn value_in_cents(coin: Coin) -> felt252 {
    match coin {
        Coin::Penny => 1,
        Coin::Nickel => 5,
        Coin::Dime => 10,
        Coin::Quarter(state) => {
            println!("State quarter from {:?}!", state);
            25
        },
    }
}

Because state is an UsState enum which implements the Debug trait, we can print state value with println! macro.

Note: {:?} is a special formatting syntax that allows to print a debug form of the parameter passed to the println! macro. You can find more information about it in Appendix C.

If we were to call value_in_cents(Coin::Quarter(UsState::Alaska)), coin would be Coin::Quarter(UsState::Alaska). When we compare that value with each of the match arms, none of them match until we reach Coin::Quarter(state). At that point, the binding for state will be the value UsState::Alaska. We can then use that binding in println! macro, thus getting the inner state value out of the Coin enum variant for Quarter.

Matching with Option<T>

In the previous section, we wanted to get the inner T value out of the Some case when using Option<T>; we can also handle Option<T> using match, as we did with the Coin enum! Instead of comparing coins, we’ll compare the variants of Option<T>, but the way the match expression works remains the same.

Let’s say we want to write a function that takes an Option<u8> and, if there’s a value inside, adds 1 to that value. If there is no value inside, the function should return the None value and not attempt to perform any operations.

This function is very easy to write, thanks to match, and will look like Listing 6-3.

fn plus_one(x: Option<u8>) -> Option<u8> {
    match x {
        Option::Some(val) => Option::Some(val + 1),
        Option::None => Option::None,
    }
}

fn main() {
    let five: Option<u8> = Option::Some(5);
    let six: Option<u8> = plus_one(five);
    let none = plus_one(Option::None);
}

Listing 6-3: A function that uses a match expression on an Option<u8>

Let’s examine the first execution of plus_one in more detail. When we call plus_one(five), the variable x in the body of plus_one will have the value Some(5). We then compare that against each match arm:

        Option::Some(val) => Option::Some(val + 1),

Does Option::Some(5) value match the pattern Option::Some(val)? It does! We have the same variant. The val binds to the value contained in Option::Some, so val takes the value 5. The code in the match arm is then executed, so we add 1 to the value of val and create a new Option::Some value with our total 6 inside. Because the first arm matched, no other arms are compared.

Now let’s consider the second call of plus_one in our main function, where x is Option::None. We enter the match and compare to the first arm:

        Option::Some(val) => Option::Some(val + 1),

El valor Option::Some(5_u8) no coincide con el patrón Option::None, así que continuamos con el siguiente brazo:

        Option::None => Option::None,

It matches! There’s no value to add to, so the matching construct ends and returns the Option::None value on the right side of =>.

Combinar match y enumeraciones es útil en muchas situaciones. Verás este patrón mucho en el código de Cairo: match contra una enumeración, enlaza una variable con los datos internos y luego ejecuta código basado en ella. Es un poco complicado al principio, pero una vez que te acostumbras, desearás tenerlo en todos los lenguajes. Es consistentemente favorito de los usuarios.

Matches Are Exhaustive

There’s one other aspect of match we need to discuss: the arms’ patterns must cover all possibilities. Consider this version of our plus_one function, which has a bug and won’t compile:

fn plus_one(x: Option<u8>) -> Option<u8> {
    match x {
        Option::Some(val) => Option::Some(val + 1),
    }
}

We didn’t handle the None case, so this code will cause a bug. Luckily, it’s a bug Cairo knows how to catch. If we try to compile this code, we’ll get this error:

$ scarb cairo-run 
   Compiling no_listing_08_missing_match_arm v0.1.0 (listings/ch06-enums-and-pattern-matching/no_listing_09_missing_match_arm/Scarb.toml)
error: Missing match arm: `None` not covered.
 --> listings/ch06-enums-and-pattern-matching/no_listing_09_missing_match_arm/src/lib.cairo:5:5
    match x {
    ^*******^

error: could not compile `no_listing_08_missing_match_arm` due to previous error
error: `scarb metadata` exited with error

Cairo knows that we didn’t cover every possible case, and even knows which pattern we forgot! Matches in Cairo are exhaustive: we must exhaust every last possibility in order for the code to be valid. Especially in the case of Option<T>, when Cairo prevents us from forgetting to explicitly handle the None case, it protects us from assuming that we have a value when we might have null, thus making the billion-dollar mistake discussed earlier impossible.

Catch-all with the _ Placeholder

Using enums, we can also take special actions for a few particular values, but for all other values take one default action. _ is a special pattern that matches any value and does not bind to that value. You can use it by simply adding a new arm with _ as the pattern for the last arm of the match expression.

Imagine we have a vending machine that only accepts Dime coins. We want to have a function that processes inserted coins and returns true only if the coin is accepted.

Here's a vending_machine_accept function that implements this logic:

fn vending_machine_accept(coin: Coin) -> bool {
    match coin {
        Coin::Dime => true,
        _ => false,
    }
}

This example also meets the exhaustiveness requirement because we’re explicitly ignoring all other values in the last arm; we haven’t forgotten anything.

There's no catch-all pattern in Cairo that allows you to use the value of the pattern.

Multiple Patterns with the | Operator

In match expressions, you can match multiple patterns using the | syntax, which is the pattern or operator.

For example, in the following code we modified the vending_machine_accept function to accept both Dime and Quarter coins in a single arm:

fn vending_machine_accept(coin: Coin) -> bool {
    match coin {
        Coin::Dime | Coin::Quarter => true,
        _ => false,
    }
}

Matching Tuples

It is possible to match tuples. Let's introduce a new DayType enum:

#[derive(Drop)]
enum DayType {
    Week,
    Weekend,
    Holiday,
}

Now, let's suppose that our vending machine accepts any coin on weekdays, but only accepts quarters and dimes on weekends and holidays. We can modify the vending_machine_accept function to accept a tuple of a Coin and a Weekday and return true only if the given coin is accepted on the specified day:

fn vending_machine_accept(c: (DayType, Coin)) -> bool {
    match c {
        (DayType::Week, _) => true,
        (_, Coin::Dime) | (_, Coin::Quarter) => true,
        (_, _) => false,
    }
}

Writing (_, _) for the last arm of a tuple matching pattern might feel superfluous. Hence, we can use the _ => syntax if we want, for example, that our vending machine only accepts quarters on weekdays:

fn vending_week_machine(c: (DayType, Coin)) -> bool {
    match c {
        (DayType::Week, Coin::Quarter) => true,
        _ => false,
    }
}

Matching felt252 and Integer Variables

You can also match felt252 and integer variables. This is useful when you want to match against a range of values. However, there are some restrictions:

• Only integers that fit into a single felt252 are supported (i.e. u256 is not supported).
• The first arm must be 0.
• Each arm must cover a sequential segment, contiguously with other arms.

Imagine we’re implementing a game where you roll a six-sided die to get a number between 0 and 5. If you have 0, 1 or 2 you win. If you have 3, you can roll again. For all other values you lose.

Here's a match that implements that logic:

fn roll(value: u8) {
    match value {
        0 | 1 | 2 => println!("you won!"),
        3 => println!("you can roll again!"),
        _ => println!("you lost..."),
    }
}

These restrictions are planned to be relaxed in future versions of Cairo.

Concise Control Flow with if let and while let

if let

The if let syntax lets you combine if and let into a less verbose way to handle values that match one pattern while ignoring the rest. Consider the program in Listing 6-4 that matches on an Option::Some<u8> value in the config_max variable but only wants to execute code if the value is Option::Some variant.

fn main() {
    let config_max = Option::Some(5);
    match config_max {
        Option::Some(max) => println!("The maximum is configured to be {}", max),
        _ => (),
    }
}

Listing 6-4: A match that only cares about executing code when the value is Option::Some

If the value is Option::Some, we print out the value in the Option::Some variant by binding the value to the variable max in the pattern. We don’t want to do anything with the None value. To satisfy the match expression, we have to add _ => () after processing just one variant, which is annoying boilerplate code to add.

Instead, we could write this in a shorter way using if let. The following code behaves the same as the match in Listing 6-4:

fn main() {
    let number = Option::Some(5);
    if let Option::Some(max) = number {
        println!("The maximum is configured to be {}", max);
    }
}

The syntax if let takes a pattern and an expression separated by an equal sign. It works the same way as a match, where the expression is given to the match and the pattern is its first arm. In this case, the pattern is Option::Some(max), and max binds to the value inside Option::Some. We can then use max in the body of the if let block in the same way we used max in the corresponding match arm. The code in the if let block isn’t run if the value doesn’t match the pattern.

Using if let means less typing, less indentation, and less boilerplate code. However, you lose the exhaustive checking that match enforces. Choosing between match and if let depends on what you’re doing in your particular situation and whether gaining conciseness is an appropriate trade-off for losing exhaustive checking.

In other words, you can think of if let as syntactic sugar for a match that runs code when the value matches one pattern and then ignores all other values.

We can include an else with an if let. The block of code that goes with else is the same as the block of code that would go with the _ case in the match expression. Recall the Coin enum definition in Listing 6-2, where the Quarter variant also held a UsState value. If we wanted to count all non-quarter coins we see while also announcing the state of the quarters, we could do that with a match expression, like this:

#[derive(Drop)]
enum Coin {
    Penny,
    Nickel,
    Dime,
    Quarter,
}

fn main() {
    let coin = Coin::Quarter;
    let mut count = 0;
    match coin {
        Coin::Quarter => println!("You got a quarter!"),
        _ => count += 1,
    }
}

Or we could use an if let and else expression, like this:

#[derive(Drop)]
enum Coin {
    Penny,
    Nickel,
    Dime,
    Quarter,
}

fn main() {
    let coin = Coin::Quarter;
    let mut count = 0;
    if let Coin::Quarter = coin {
        println!("You got a quarter!");
    } else {
        count += 1;
    }
    println!("{}", count);
}

If you have a situation in which your program has logic that is too verbose to express using match, remember that if let is in your Cairo toolbox as well.

while let

The while let syntax is similar to the if let syntax, but it allows you to loop over a collection of values and execute a block of code for each value that matches a specified pattern. In the case below, the pattern is Option::Some(x), which matches any Some variant of the Option enum.

fn main() {
    let mut arr = array![1, 2, 3, 4, 5, 6, 7, 8, 9];
    let mut sum = 0;
    while let Option::Some(value) = arr.pop_front() {
        sum += value;
    };
    println!("{}", sum);
}

Using while let provides a more concise and idiomatic way of writing this loop compared to a traditional while loop with explicit pattern matching or handling of the Option type. However, as with if let, you lose the exhaustive checking that a match expression provides, so you need to be careful to handle any remaining cases outside the while let loop if necessary.

Gestionando Proyectos Cairo con Paquetes, Crates y Módulos

As you write large programs, organizing your code will become increasingly important. By grouping related functionality and separating code with distinct features, you’ll clarify where to find code that implements a particular feature and where to go to change how a feature works.

The programs we’ve written so far have been in one module in one file. As a project grows, you should organize code by splitting it into multiple modules and then multiple files. As a package grows, you can extract parts into separate crates that become external dependencies. This chapter covers all these techniques.

We’ll also discuss encapsulating implementation details, which lets you reuse code at a higher level: once you’ve implemented an operation, other code can call your code without having to know how the implementation works.

A related concept is scope: the nested context in which code is written has a set of names that are defined as “in scope”. When reading, writing, and compiling code, programmers and compilers need to know whether a particular name at a particular spot refers to a variable, function, struct, enum, module, constant, or other item and what that item means. You can create scopes and change which names are in or out of scope. You can’t have two items with the same name in the same scope.

Cairo has a number of features that allow you to manage your code’s organization. These features, sometimes collectively referred to as the module system, include:

• Packages: A Scarb feature that lets you build, test, and share crates.
• Crates: A tree of modules that corresponds to a single compilation unit. It has a root directory, and a root module defined at the lib.cairo file under this directory.
• Modules and use: Let you control the organization and scope of items.
• Paths: A way of naming an item, such as a struct, function, or module.

In this chapter, we’ll cover all these features, discuss how they interact, and explain how to use them to manage scope. By the end, you should have a solid understanding of the module system and be able to work with scopes like a pro!

Paquetes y Crates

What is a Crate?

A crate is a subset of a package that is used in the actual Cairo compilation. This includes:

• The package source code, identified by the package name and the crate root, which is the main entry point of the package.
• A subset of the package metadata that identifies crate-level settings of the Cairo compiler, for example, the edition field in the Scarb.toml file.

Crates can contain modules, and the modules may be defined in other files that get compiled with the crate, as will be discussed in the subsequent sections.

What is the Crate Root?

The crate root is the lib.cairo source file that the Cairo compiler starts from and makes up the root module of your crate. We’ll explain modules in depth in the "Defining Modules to Control Scope" chapter.

What is a Package?

A Cairo package is a directory (or equivalent) containing:

• A Scarb.toml manifest file with a [package] section.
• Associated source code.

This definition implies that a package might contain other packages, with a corresponding Scarb.toml file for each package.

Creating a Package with Scarb

You can create a new Cairo package using the Scarb command-line tool. To create a new package, run the following command:

scarb new my_package

This command will generate a new package directory named my_package with the following structure:

my_package/
├── Scarb.toml
└── src
    └── lib.cairo

• src/ is the main directory where all the Cairo source files for the package will be stored.
• lib.cairo is the default root module of the crate, which is also the main entry point of the package.
• Scarb.toml is the package manifest file, which contains metadata and configuration options for the package, such as dependencies, package name, version, and authors. You can find documentation about it on the Scarb reference.

[package]
name = "my_package"
version = "0.1.0"
edition = "2024_07"

[dependencies]
# foo = { path = "vendor/foo" }

As you develop your package, you may want to organize your code into multiple Cairo source files. You can do this by creating additional .cairo files within the src directory or its subdirectories.

Definición de módulos para controlar el alcance

In this section, we’ll talk about modules and other parts of the module system, namely paths that allow you to name items and the use keyword that brings a path into scope.

First, we’re going to start with a list of rules for easy reference when you’re organizing your code in the future. Then we’ll explain each of the rules in detail.

Modules Cheat Sheet

Here we provide a quick reference on how modules, paths and the use keyword work in the compiler, and how most developers organize their code. We’ll be going through examples of each of these rules throughout this chapter, but this is a great place to refer to as a reminder of how modules work. You can create a new Scarb project with scarb new backyard to follow along.

• Start from the crate root: When compiling a crate, the compiler first looks in the crate root file (src/lib.cairo) for code to compile.

• Declaring modules: In the crate root file, you can declare new modules; say, you declare a “garden” module with mod garden;. The compiler will look for the module’s code in these places:

  • Inline, within curly brackets that replace the semicolon following mod garden.

      // crate root file (src/lib.cairo)
      mod garden {
          // code defining the garden module goes here
      }
    

  • In the file src/garden.cairo.

• Declaring submodules: In any file other than the crate root, you can declare submodules. For example, you might declare mod vegetables; in src/garden.cairo. The compiler will look for the submodule’s code within the directory named for the parent module in these places:

  • Inline, directly following mod vegetables, within curly brackets instead of the semicolon.

    // src/garden.cairo file
    mod vegetables {
        // code defining the vegetables submodule goes here
    }
    

  • In the file src/garden/vegetables.cairo.

• Paths to code in modules: Once a module is part of your crate, you can refer to code in that module from anywhere else in that same crate, using the path to the code. For example, an Asparagus type in the vegetables submodule would be found at crate::garden::vegetables::Asparagus.

• Private vs public: Code within a module is private from its parent modules by default. This means that it may only be accessed by the current module and its descendants. To make a module public, declare it with pub mod instead of mod. To make items within a public module public as well, use pub before their declarations. Cairo also provides the pub(crate) keyword, allowing an item or module to be only visible within the crate in which the definition is included.

• The use keyword: Within a scope, the use keyword creates shortcuts to items to reduce repetition of long paths. In any scope that can refer to crate::garden::vegetables::Asparagus, you can create a shortcut with use crate::garden::vegetables::Asparagus; and from then on you only need to write Asparagus to make use of that type in the scope.

Here we create a crate named backyard that illustrates these rules. The crate’s directory, also named backyard, contains these files and directories:

backyard/
├── Scarb.toml
└── src
    ├── garden
    │   └── vegetables.cairo
    ├── garden.cairo
    └── lib.cairo

El archivo raíz de la caja en este caso es src/lib.cairo, y contiene:

Filename: src/lib.cairo

pub mod garden;
use crate::garden::vegetables::Asparagus;

fn main() {
    let plant = Asparagus {};
    println!("I'm growing {:?}!", plant);
}

The pub mod garden; line imports the garden module. Using pub to make garden publicly accessible, or pub(crate) if you really want to make garden only available for your crate, is optional to run our program here, as the main function resides in the same module as pub mod garden; declaration. Nevertheless, not declaring garden as pub will make it not accessible from any other package. This line tells the compiler to include the code it finds in src/garden.cairo, which is:

Filename: src/garden.cairo

pub mod vegetables;

Here, pub mod vegetables; means the code in src/garden/vegetables.cairo is included too. That code is:

#[derive(Drop, Debug)]
pub struct Asparagus {}

The line use crate::garden::vegetables::Asparagus; lets us bring the Asparagus type into scope, so we can use it in the main function.

¡Ahora vamos a entrar en los detalles de estas reglas y demostrarlas en acción!

Grouping Related Code in Modules

Modules let us organize code within a crate for readability and easy reuse. Modules also allow us to control the privacy of items, because code within a module is private by default. Private items are internal implementation details not available for outside use. We can choose to make modules and the items within them public, which exposes them to allow external code to use and depend on them.

As an example, let’s write a library crate that provides the functionality of a restaurant. We’ll define the signatures of functions but leave their bodies empty to concentrate on the organization of the code, rather than the implementation of a restaurant.

In the restaurant industry, some parts of a restaurant are referred to as front of house and others as back of house. Front of house is where customers are; this encompasses where the hosts seat customers, servers take orders and payment, and bartenders make drinks. Back of house is where the chefs and cooks work in the kitchen, dishwashers clean up, and managers do administrative work.

To structure our crate in this way, we can organize its functions into nested modules. Create a new package named restaurant by running scarb new restaurant; then enter the code in Listing 7-1 into src/lib.cairo to define some modules and function signatures. Here’s the front of house section:

Filename: src/lib.cairo

mod front_of_house {
    mod hosting {
        fn add_to_waitlist() {}

        fn seat_at_table() {}
    }

    mod serving {
        fn take_order() {}

        fn serve_order() {}

        fn take_payment() {}
    }
}

Listing 7-1: A front_of_house module containing other modules that then contain functions

We define a module with the mod keyword followed by the name of the module (in this case, front_of_house). The body of the module then goes inside curly brackets. Inside modules, we can place other modules, as in this case with the modules hosting and serving. Modules can also hold definitions for other items, such as structs, enums, constants, traits, and functions.

By using modules, we can group related definitions together and name why they’re related. Programmers using this code can navigate the code based on the groups rather than having to read through all the definitions, making it easier to find the definitions relevant to them. Programmers adding new functionality to this code would know where to place the code to keep the program organized.

Earlier, we mentioned that src/lib.cairo is called the crate root. The reason for this name is that the content of this file forms a module named after the crate name at the root of the crate’s module structure, known as the module tree.

Listing 7-2 shows the module tree for the structure in Listing 7-1.

restaurant
 └── front_of_house
     ├── hosting
     │   ├── add_to_waitlist
     │   └── seat_at_table
     └── serving
         ├── take_order
         ├── serve_order
         └── take_payment

Listing 7-2: The module tree for the code in Listing 7-1

This tree shows how some of the modules nest inside one another; for example, hosting nests inside front_of_house. The tree also shows that some modules are siblings to each other, meaning they’re defined in the same module; hosting and serving are siblings defined within front_of_house. If module A is contained inside module B, we say that module A is the child of module B and that module B is the parent of module A. Notice that the entire module tree is rooted under the explicit name of the crate restaurant.

The module tree might remind you of the filesystem’s directory tree on your computer; this is a very apt comparison! Just like directories in a filesystem, you use modules to organize your code. And just like files in a directory, we need a way to find our modules.

Rutas para referirse a un elemento en el Arbol de Módulos

Para indicarle a Cairo dónde encontrar un elemento en el árbol de módulos, usamos un camino de la misma forma que usamos una ruta al navegar por un sistema de archivos. Para llamar a una función, necesitamos conocer su camino.

Un camino puede tomar dos formas:

• An absolute path is the full path starting from a crate root. The absolute path begins with the crate name.
• A relative path starts from the current module.

Both absolute and relative paths are followed by one or more identifiers separated by double colons (::).

To illustrate this notion let's take back our example Listing 7-1 for the restaurant we used in the last chapter. We have a crate named restaurant in which we have a module named front_of_house that contains a module named hosting. The hosting module contains a function named add_to_waitlist. We want to call the add_to_waitlist function from the eat_at_restaurant function. We need to tell Cairo the path to the add_to_waitlist function so it can find it.

Filename: src/lib.cairo

mod front_of_house {
    mod hosting {
        fn add_to_waitlist() {}

        fn seat_at_table() {}
    }

    mod serving {
        fn take_order() {}

        fn serve_order() {}

        fn take_payment() {}
    }
}


pub fn eat_at_restaurant() {
    // Absolute path
    crate::front_of_house::hosting::add_to_waitlist();

    // Relative path
    front_of_house::hosting::add_to_waitlist();
}

Listing 7-3: Calling the add_to_waitlist function using absolute and relative paths

The eat_at_restaurant function is part of our library's public API, so we mark it with the pub keyword. We’ll go into more detail about pub in the "Exposing Paths with the pub Keyword" section.

The first time we call the add_to_waitlist function in eat_at_restaurant, we use an absolute path. The add_to_waitlist function is defined in the same crate as eat_at_restaurant. In Cairo, absolute paths start from the crate root, which you need to refer to by using the crate name. You can imagine a filesystem with the same structure: we’d specify the path /front_of_house/hosting/add_to_waitlist to run the add_to_waitlist program; using the crate name to start from the crate root is like using a slash (/) to start from the filesystem root in your shell.

The second time we call add_to_waitlist, we use a relative path. The path starts with front_of_house, the name of the module defined at the same level of the module tree as eat_at_restaurant. Here the filesystem equivalent would be using the path ./front_of_house/hosting/add_to_waitlist. Starting with a module name means that the path is relative to the current module.

Let’s try to compile Listing 7-3 and find out why it won’t compile yet! We get the following error:

$ scarb cairo-run 
   Compiling listing_07_02 v0.1.0 (listings/ch07-managing-cairo-projects-with-packages-crates-and-modules/listing_02_paths/Scarb.toml)
error: Item `listing_07_02::front_of_house::hosting` is not visible in this context.
 --> listings/ch07-managing-cairo-projects-with-packages-crates-and-modules/listing_02_paths/src/lib.cairo:22:28
    crate::front_of_house::hosting::add_to_waitlist();
                           ^*****^

error: Item `listing_07_02::front_of_house::hosting::add_to_waitlist` is not visible in this context.
 --> listings/ch07-managing-cairo-projects-with-packages-crates-and-modules/listing_02_paths/src/lib.cairo:22:37
    crate::front_of_house::hosting::add_to_waitlist();
                                    ^*************^

error: Item `listing_07_02::front_of_house::hosting` is not visible in this context.
 --> listings/ch07-managing-cairo-projects-with-packages-crates-and-modules/listing_02_paths/src/lib.cairo:25:21
    front_of_house::hosting::add_to_waitlist();
                    ^*****^

error: Item `listing_07_02::front_of_house::hosting::add_to_waitlist` is not visible in this context.
 --> listings/ch07-managing-cairo-projects-with-packages-crates-and-modules/listing_02_paths/src/lib.cairo:25:30
    front_of_house::hosting::add_to_waitlist();
                             ^*************^

error: could not compile `listing_07_02` due to previous error
error: `scarb metadata` exited with error

The error messages say that module hosting and the add_to_waitlist function are not visible. In other words, we have the correct paths for the hosting module and the add_to_waitlist function, but Cairo won’t let us use them because it doesn’t have access to them. In Cairo, all items (functions, methods, structs, enums, modules, and constants) are private to parent modules by default. If you want to make an item like a function or struct private, you put it in a module.

Items in a parent module can’t use the private items inside child modules, but items in child modules can use the items in their ancestor modules. This is because child modules wrap and hide their implementation details, but the child modules can see the context in which they’re defined. To continue with our metaphor, think of the privacy rules as being like the back office of a restaurant: what goes on in there is private to restaurant customers, but office managers can see and do everything in the restaurant they operate.

Cairo chose to have the module system function this way so that hiding inner implementation details is the default. That way, you know which parts of the inner code you can change without breaking outer code. However, Cairo does give you the option to expose inner parts of child modules’ code to outer ancestor modules by using the pub keyword to make an item public.

Exposing Paths with the pub Keyword

Let’s return to the previous error that told us the hosting module and the add_to_waitlist function are not visible. We want the eat_at_restaurant function in the parent module to have access to the add_to_waitlist function in the child module, so we mark the hosting module with the pub keyword, as shown in Listing 7-4.

Filename: src/lib.cairo

mod front_of_house {
    pub mod hosting {
        fn add_to_waitlist() {}
    }
}

pub fn eat_at_restaurant() {
    // Absolute path
    crate::front_of_house::hosting::add_to_waitlist();

    // Relative path
    front_of_house::hosting::add_to_waitlist();
}

Listing 7-4: Declaring the hosting module as pub to use it from eat_at_restaurant

Unfortunately, the code in Listing 7-4 still results in an error.

What happened? Adding the pub keyword in front of mod hosting; makes the module public. With this change, if we can access front_of_house, we can access hosting. But the contents of hosting are still private; making the module public doesn’t make its contents public. The pub keyword on a module only lets code in its ancestor modules refer to it, not access its inner code. Because modules are containers, there’s not much we can do by only making the module public; we need to go further and choose to make one or more of the items within the module public as well.

Let’s also make the add_to_waitlist function public by adding the pub keyword before its definition, as in Listing 7-5.

Filename: src/lib.cairo

mod front_of_house {
    pub mod hosting {
        pub fn add_to_waitlist() {}
    }
}

pub fn eat_at_restaurant() {
    // Absolute path
    crate::front_of_house::hosting::add_to_waitlist(); // ✅ Compiles

    // Relative path
    front_of_house::hosting::add_to_waitlist(); // ✅ Compiles
}

Listing 7-5: Declaring the hosting module as pub to use it from eat_at_restaurant

Now the code will compile! To see why adding the pub keyword lets us use these paths in add_to_waitlist with respect to the privacy rules, let’s look at the absolute and the relative paths.

In the absolute path, we start with the crate root, the root of our crate’s module tree. The front_of_house module is defined in the crate root. While front_of_house isn’t public, because the eat_at_restaurant function is defined in the same module as front_of_house (that is, front_of_house and eat_at_restaurant are siblings), we can refer to front_of_house from eat_at_restaurant. Next is the hosting module marked with pub. We can access the parent module of hosting, so we can access hosting itself. Finally, the add_to_waitlist function is marked with pub and we can access its parent module, so this function call works!

In the relative path, the logic is the same as the absolute path except for the first step: rather than starting from the crate root, the path starts from front_of_house. The front_of_house module is defined within the same module as eat_at_restaurant, so the relative path starting from the module in which eat_at_restaurant is defined works. Then, because hosting and add_to_waitlist are marked with pub, the rest of the path works, and this function call is valid!

Starting Relative Paths with super

We can construct relative paths that begin in the parent module, rather than the current module or the crate root, by using super at the start of the path. This is like starting a filesystem path with the .. syntax. Using super allows us to reference an item that we know is in the parent module, which can make rearranging the module tree easier when the module is closely related to the parent, but the parent might be moved elsewhere in the module tree someday.

Consider the code in Listing 7-6 that models the situation in which a chef fixes an incorrect order and personally brings it out to the customer. The function fix_incorrect_order defined in the back_of_house module calls the function deliver_order defined in the parent module by specifying the path to deliver_order starting with super:

Filename: src/lib.cairo

fn deliver_order() {}

mod back_of_house {
    fn fix_incorrect_order() {
        cook_order();
        super::deliver_order();
    }

    fn cook_order() {}
}

Listing 7-6: Calling a function using a relative path starting with super

Here you can see directly that you access a parent's module easily using super, which wasn't the case previously. Note that the back_of_house is kept private, as external users are not supposed to interact with the back of house directly.

Making Structs and Enums Public

We can also use pub to designate structs and enums as public, but there are a few extra details to consider when using pub with structs and enums.

• If we use pub before a struct definition, we make the struct public, but the struct’s fields will still be private. We can make each field public or not on a case-by-case basis.
• In contrast, if we make an enum public, all of its variants are then public. We only need the pub before the enum keyword.

There’s one more situation involving pub that we haven’t covered, and that is our last module system feature: the use keyword. We’ll cover use by itself first, and then we’ll show how to combine pub and use.

Bringing Paths into Scope with the use Keyword

Tener que escribir las rutas para llamar a las funciones puede resultar incómodo y repetitivo. Afortunadamente, hay una manera de simplificar este proceso: podemos crear un acceso directo a una ruta con la palabra clave use una vez, y luego utilizar el nombre más corto en todas partes en el ámbito.

In Listing 7-7, we bring the crate::front_of_house::hosting module into the scope of the eat_at_restaurant function so we only have to specify hosting::add_to_waitlist to call the add_to_waitlist function in eat_at_restaurant.

Filename: src/lib.cairo

// section "Defining Modules to Control Scope"

mod front_of_house {
    pub mod hosting {
        pub fn add_to_waitlist() {}
    }
}

use crate::front_of_house::hosting;

pub fn eat_at_restaurant() {
    hosting::add_to_waitlist(); // ✅ Shorter path
}

Listing 7-7: Bringing a module into scope with use

Adding use and a path in a scope is similar to creating a symbolic link in the filesystem. By adding use crate::front_of_house::hosting; in the crate root, hosting is now a valid name in that scope, just as though the hosting module had been defined in the crate root.

Note that use only creates the shortcut for the particular scope in which the use occurs. Listing 7-8 moves the eat_at_restaurant function into a new child module named customer, which is then a different scope than the use statement, so the function body won’t compile:

Filename: src/lib.cairo

mod front_of_house {
    pub mod hosting {
        pub fn add_to_waitlist() {}
    }
}

use crate::front_of_house::hosting;

mod customer {
    pub fn eat_at_restaurant() {
        hosting::add_to_waitlist();
    }
}

Listing 7-8: A use statement only applies in the scope it’s in.

The compiler error shows that the shortcut no longer applies within the customer module:

$ scarb build 
   Compiling listing_07_05 v0.1.0 (listings/ch07-managing-cairo-projects-with-packages-crates-and-modules/listing_07_use_and_scope/Scarb.toml)
warn: Unused import: `listing_07_05::hosting`
 --> listings/ch07-managing-cairo-projects-with-packages-crates-and-modules/listing_07_use_and_scope/src/lib.cairo:10:28
use crate::front_of_house::hosting;
                           ^*****^

error: Identifier not found.
 --> listings/ch07-managing-cairo-projects-with-packages-crates-and-modules/listing_07_use_and_scope/src/lib.cairo:14:9
        hosting::add_to_waitlist();
        ^*****^

error: could not compile `listing_07_05` due to previous error

Creating Idiomatic use Paths

In Listing 7-7, you might have wondered why we specified use crate::front_of_house::hosting and then called hosting::add_to_waitlist in eat_at_restaurant rather than specifying the use path all the way out to the add_to_waitlist function to achieve the same result, as in Listing 7-9.

Filename: src/lib.cairo

mod front_of_house {
    pub mod hosting {
        pub fn add_to_waitlist() {}
    }
}

use crate::front_of_house::hosting::add_to_waitlist;

pub fn eat_at_restaurant() {
    add_to_waitlist();
}

Listing 7-9: Bringing the add_to_waitlist function into scope with use, which is unidiomatic

Although both Listing 7-7 and 7-9 accomplish the same task, Listing 7-7 is the idiomatic way to bring a function into scope with use. Bringing the function’s parent module into scope with use means we have to specify the parent module when calling the function. Specifying the parent module when calling the function makes it clear that the function isn’t locally defined while still minimizing repetition of the full path. The code in Listing 7-9 is unclear as to where add_to_waitlist is defined.

On the other hand, when bringing in structs, enums, traits, and other items with use, it’s idiomatic to specify the full path. Listing 7-10 shows the idiomatic way to bring the core library’s BitSize trait into the scope, allowing to call bits method to retrieve the size in bits of a type.

use core::num::traits::BitSize;

fn main() {
    let u8_size: usize = BitSize::<u8>::bits();
    println!("A u8 variable has {} bits", u8_size)
}

Listing 7-10: Bringing BitSize trait into scope in an idiomatic way

There’s no strong reason behind this idiom: it’s just the convention that has emerged in the Rust community, and folks have gotten used to reading and writing Rust code this way. As Cairo shares many idioms with Rust, we follow this convention as well.

The exception to this idiom is if we’re bringing two items with the same name into scope with use statements, because Cairo doesn’t allow that.

Providing New Names with the as Keyword

There’s another solution to the problem of bringing two types of the same name into the same scope with use: after the path, we can specify as and a new local name, or alias, for the type. Listing 7-11 shows how you can rename an import with as:

Filename: src/lib.cairo

use core::array::ArrayTrait as Arr;

fn main() {
    let mut arr = Arr::new(); // ArrayTrait was renamed to Arr
    arr.append(1);
}

Listing 7-11: Renaming a trait when it’s brought into scope with the as keyword

En este caso, hemos introducido ArrayTrait en el ámbito con el alias Arr. Ahora podemos acceder a los métodos del rasgo con el identificador Arr.

Importing Multiple Items from the Same Module

When you want to import multiple items (like functions, structs or enums) from the same module in Cairo, you can use curly braces {} to list all of the items that you want to import. This helps to keep your code clean and easy to read by avoiding a long list of individual use statements.

La sintaxis general para importar varios elementos del mismo módulo es:

use module::{item1, item2, item3};

He aquí un ejemplo en el que importamos tres estructuras del mismo módulo:

// Assuming we have a module called `shapes` with the structures `Square`, `Circle`, and `Triangle`.
mod shapes {
    #[derive(Drop)]
    pub struct Square {
        pub side: u32,
    }

    #[derive(Drop)]
    pub struct Circle {
        pub radius: u32,
    }

    #[derive(Drop)]
    pub struct Triangle {
        pub base: u32,
        pub height: u32,
    }
}

// We can import the structures `Square`, `Circle`, and `Triangle` from the `shapes` module like
// this:
use shapes::{Square, Circle, Triangle};

// Now we can directly use `Square`, `Circle`, and `Triangle` in our code.
fn main() {
    let sq = Square { side: 5 };
    let cr = Circle { radius: 3 };
    let tr = Triangle { base: 5, height: 2 };
    // ...
}

Listing 7-12: Importing multiple items from the same module

Re-exporting Names in Module Files

When we bring a name into scope with the use keyword, the name available in the new scope can be imported as if it had been defined in that code’s scope. This technique is called re-exporting because we’re bringing an item into scope, but also making that item available for others to bring into their scope, with the pub keyword.

Por ejemplo, reexportemos la función add_to_waitlist del ejemplo del restaurante:

Filename: src/lib.cairo

mod front_of_house {
    pub mod hosting {
        pub fn add_to_waitlist() {}
    }
}

pub use crate::front_of_house::hosting;

fn eat_at_restaurant() {
    hosting::add_to_waitlist();
}

Listing 7-13: Making a name available for any code to use from a new scope with pub use

Before this change, external code would have to call the add_to_waitlist function by using the path restaurant::front_of_house::hosting::add_to_waitlist(). Now that this pub use has re-exported the hosting module from the root module, external code can now use the path restaurant::hosting::add_to_waitlist() instead.

Re-exporting is useful when the internal structure of your code is different from how programmers calling your code would think about the domain. For example, in this restaurant metaphor, the people running the restaurant think about “front of house” and “back of house.” But customers visiting a restaurant probably won’t think about the parts of the restaurant in those terms. With pub use, we can write our code with one structure but expose a different structure. Doing so makes our library well organized for programmers working on the library and programmers calling the library.

Using External Packages in Cairo with Scarb

You might need to use external packages to leverage the functionality provided by the community. Scarb allows you to use dependencies by cloning packages from their Git repositories. To use an external package in your project with Scarb, simply declare the Git repository URL of the dependency you want to add in a dedicated [dependencies] section in your Scarb.toml configuration file. Note that the URL might correspond to the main branch, or any specific commit, branch or tag. For this, you will have to pass an extra rev, branch, or tag field, respectively. For example, the following code imports the main branch of alexandria_math crate from alexandria package:

[dependencies]
alexandria_math = { git = "https://github.com/keep-starknet-strange/alexandria.git" }

while the following code imports a specific branch (which is deprecated and should not be used):

[dependencies]
alexandria_math = { git = "https://github.com/keep-starknet-strange/alexandria.git", branch = "cairo-v2.3.0-rc0" }

If you want to import multiple packages in your project, you need to create only one [dependencies] section and list all the desired packages beneath it. You can also specify development dependencies by declaring a [dev-dependencies] section.

After that, simply run scarb build to fetch all external dependencies and compile your package with all the dependencies included.

Note that it is also possible to add dependencies with the scarb add command, which will automatically edit the Scarb.toml file for you. For development dependencies, just use the scarb add --dev command.

To remove a dependency, simply remove the corresponding line from your Scarb.toml file, or use the scarb rm command.

The Glob Operator

If we want to bring all public items defined in a path into scope, we can specify that path followed by the * glob operator:

#![allow(unused)]
fn main() {
use core::num::traits::*;
}

This use statement brings all public items defined in core::num::traits into the current scope. Be careful when using the glob operator! Glob can make it harder to tell what names are in scope and where a name used in your program was defined.

The glob operator is often used when testing to bring everything under test into the tests module; we’ll talk about that in the “How to Write Tests” section in Chapter 10.

Separación de Módulos en Distintos Ficheros

So far, all the examples in this chapter defined multiple modules in one file. When modules get large, you might want to move their definitions to a separate file to make the code easier to navigate.

For example, let’s start from the code in Listing 7-7 that had multiple restaurant modules. We’ll extract modules into files instead of having all the modules defined in the crate root file. In this case, the crate root file is src/lib.cairo.

First, we’ll extract the front_of_house module to its own file. Remove the code inside the curly brackets for the front_of_house module, leaving only the mod front_of_house; declaration, so that src/lib.cairo contains the code shown in Listing 7-14. Note that this won’t compile until we create the src/front_of_house.cairo file.

Filename: src/lib.cairo

mod front_of_house;

use crate::front_of_house::hosting;

fn eat_at_restaurant() {
    hosting::add_to_waitlist();
}

Listing 7-14: Declaring the front_of_house module whose body will be in src/front_of_house.cairo

Next, place the code that was in the curly brackets into a new file named src/front_of_house.cairo, as shown in Listing 7-15. The compiler knows to look in this file because it came across the module declaration in the crate root with the name front_of_house.

Filename: src/front_of_house.cairo

pub mod hosting {
    pub fn add_to_waitlist() {}
}

Listing 7-15: Definitions inside the front_of_house module in src/front_of_house.cairo

Note that you only need to load a file using a mod declaration once in your module tree. Once the compiler knows the file is part of the project (and knows where in the module tree the code resides because of where you’ve put the mod statement), other files in your project should refer to the loaded file’s code using a path to where it was declared, as covered in the "Paths for Referring to an Item in the Module Tree" chapter. In other words, mod is not an “include” operation that you may have seen in other programming languages.

Next, we’ll extract the hosting module to its own file. The process is a bit different because hosting is a child module of front_of_house, not of the root module. We’ll place the file for hosting in a new directory that will be named for its ancestors in the module tree, in this case src/front_of_house/.

To start moving hosting, we change src/front_of_house.cairo to contain only the declaration of the hosting module:

Filename: src/front_of_house.cairo

pub mod hosting;

Then we create a src/front_of_house directory and a file hosting.cairo to contain the definitions made in the hosting module:

Filename: src/front_of_house/hosting.cairo

pub fn add_to_waitlist() {}

If we instead put hosting.cairo in the src directory, the compiler would expect the hosting.cairo code to be in a hosting module declared in the crate root, and not declared as a child of the front_of_house module. The compiler’s rules for which files to check for which modules’ code means the directories and files more closely match the module tree.

We’ve moved each module’s code to a separate file, and the module tree remains the same. The function calls in eat_at_restaurant will work without any modification, even though the definitions live in different files. This technique lets you move modules to new files as they grow in size.

Note that the use crate::front_of_house::hosting; statement in src/lib.cairo also hasn’t changed, nor does use have any impact on what files are compiled as part of the crate. The mod keyword declares modules, and Cairo looks in a file with the same name as the module for the code that goes into that module.

Resumen

Cairo lets you split a package into multiple crates and a crate into modules so you can refer to items defined in one module from another module. You can do this by specifying absolute or relative paths. These paths can be brought into scope with a use statement so you can use a shorter path for multiple uses of the item in that scope. Module code is private by default.

Generic Types and Traits

Every programming language has tools for effectively handling the duplication of concepts. In Cairo, one such tool is generics: abstract stand-ins for concrete types or other properties. We can express the behavior of generics or how they relate to other generics without knowing what will be in their place when compiling and running the code.

Functions can take parameters of some generic type, instead of a concrete type like u32 or bool, in the same way a function takes parameters with unknown values to run the same code on multiple concrete values. In fact, we’ve already used generics in Chapter 6 with Option<T>.

In this chapter, you’ll explore how to define your own types, functions, and traits with generics.

Generics allow us to replace specific types with a placeholder that represents multiple types to remove code duplication. Upon compilation, the compiler creates a new definition for each concrete type that replaces a generic type, reducing development time for the programmer, but code duplication at compile level still exists. This may be of importance if you are writing Starknet contracts and using a generic for multiple types which will cause contract size to increment.

Luego aprenderás cómo usar traits para definir comportamientos de manera genérica. Puedes combinar traits con tipos genéricos para restringir un tipo genérico para que acepte solo aquellos tipos que tienen un comportamiento particular, en lugar de cualquier tipo.

Removing Duplication by Extracting a Function

Generics allow us to replace specific types with a placeholder that represents multiple types to remove code duplication. Before diving into generics syntax, let’s first look at how to remove duplication in a way that doesn’t involve generic types by extracting a function that replaces specific values with a placeholder that represents multiple values. Then we’ll apply the same technique to extract a generic function! By learning how to identify duplicated code that can be extracted into a function, you'll start to recognize instances where generics can be used to reduce duplication.

We begin with a short program that finds the largest number in an array of u8:

fn main() {
    let mut number_list: Array<u8> = array![34, 50, 25, 100, 65];

    let mut largest = number_list.pop_front().unwrap();

    while let Option::Some(number) = number_list.pop_front() {
        if number > largest {
            largest = number;
        }
    };

    println!("The largest number is {}", largest);
}

We store an array of u8 in the variable number_list and extract the first number in the array in a variable named largest. We then iterate through all the numbers in the array, and if the current number is greater than the number stored in largest, we update the value of largest. However, if the current number is less than or equal to the largest number seen so far, the variable doesn’t change, and the code moves on to the next number in the list. After considering all the numbers in the array, largest should contain the largest number, which in this case is 100.

We've now been tasked with finding the largest number in two different arrays of numbers. To do so, we can choose to duplicate the previous code and use the same logic at two different places in the program, as follows:

fn main() {
    let mut number_list: Array<u8> = array![34, 50, 25, 100, 65];

    let mut largest = number_list.pop_front().unwrap();

    while let Option::Some(number) = number_list.pop_front() {
        if number > largest {
            largest = number;
        }
    };

    println!("The largest number is {}", largest);

    let mut number_list: Array<u8> = array![102, 34, 255, 89, 54, 2, 43, 8];

    let mut largest = number_list.pop_front().unwrap();

    while let Option::Some(number) = number_list.pop_front() {
        if number > largest {
            largest = number;
        }
    };

    println!("The largest number is {}", largest);
}

Although this code works, duplicating code is tedious and error-prone. We also have to remember to update the code in multiple places when we want to change it.

To eliminate this duplication, we’ll create an abstraction by defining a function that operates on any array of u8 passed in a parameter. This solution makes our code clearer and lets us express the concept of finding the largest number in an array abstractly.

To do that, we extract the code that finds the largest number into a function named largest. Then we call the function to find the largest number in the two arrays. We could also use the function on any other array of u8 values we might have in the future.

fn largest(ref number_list: Array<u8>) -> u8 {
    let mut largest = number_list.pop_front().unwrap();

    while let Option::Some(number) = number_list.pop_front() {
        if number > largest {
            largest = number;
        }
    };

    largest
}

fn main() {
    let mut number_list = array![34, 50, 25, 100, 65];

    let result = largest(ref number_list);
    println!("The largest number is {}", result);

    let mut number_list = array![102, 34, 255, 89, 54, 2, 43, 8];

    let result = largest(ref number_list);
    println!("The largest number is {}", result);
}

The largest function has a parameter called number_list, passed by reference, which represents any concrete array of u8 values we might pass into the function. As a result, when we call the function, the code runs on the specific values that we pass in.

In summary, here are the steps we took to change the code:

• Identify duplicate code.
• Extract the duplicate code into the body of the function and specify the inputs and return values of that code in the function signature.
• Update the two instances of duplicated code to call the function instead.

Next, we’ll use these same steps with generics to reduce code duplication. In the same way that the function body can operate on an abstract Array<T> instead of specific u8 values, generics allow code to operate on abstract types.

Tipos de Datos Genéricos

We use generics to create definitions for item declarations, such as structs and functions, which we can then use with many different concrete data types. In Cairo, we can use generics when defining functions, structs, enums, traits, implementations and methods. In this chapter, we are going to take a look at how to effectively use generic types with all of them.

Generics allow us to write reusable code that works with many types, thus avoiding code duplication, while enhancing code maintainability.

Funciones Genéricas

Making a function generic means it can operate on different types, avoiding the need for multiple, type-specific implementations. This leads to significant code reduction and increases the flexibility of the code.

Cuando definimos una función que utiliza genéricos, colocamos los genéricos en la firma de la función, donde normalmente especificaríamos los tipos de datos del parámetro y del valor de retorno. Por ejemplo, imaginemos que queremos crear una función que, dados dos Array de elementos, devuelva el mayor de ellos. Si necesitamos realizar esta operación para listas de distintos tipos, tendríamos que redefinir la función cada vez. Por suerte podemos implementar la función una vez usando genéricos y pasar a otras tareas.

// Specify generic type T between the angulars
fn largest_list<T>(l1: Array<T>, l2: Array<T>) -> Array<T> {
    if l1.len() > l2.len() {
        l1
    } else {
        l2
    }
}

fn main() {
    let mut l1 = array![1, 2];
    let mut l2 = array![3, 4, 5];

    // There is no need to specify the concrete type of T because
    // it is inferred by the compiler
    let l3 = largest_list(l1, l2);
}

The largest_list function compares two lists of the same type and returns the one with more elements and drops the other. If you compile the previous code, you will notice that it will fail with an error saying that there are no traits defined for dropping an array of a generic type. This happens because the compiler has no way to guarantee that an Array<T> is droppable when executing the main function. In order to drop an array of T, the compiler must first know how to drop T. This can be fixed by specifying in the function signature of largest_list that T must implement the Drop trait. The correct function definition of largest_list is as follows:

fn largest_list<T, impl TDrop: Drop<T>>(l1: Array<T>, l2: Array<T>) -> Array<T> {
    if l1.len() > l2.len() {
        l1
    } else {
        l2
    }
}

The new largest_list function includes in its definition the requirement that whatever generic type is placed there, it must be droppable. This is what we call trait bounds. The main function remains unchanged, the compiler is smart enough to deduce which concrete type is being used and if it implements the Drop trait.

Constraints for Generic Types

When defining generic types, it is useful to have information about them. Knowing which traits a generic type implements allows us to use it more effectively in a function's logic at the cost of constraining the generic types that can be used with the function. We saw an example of this previously by adding the TDrop implementation as part of the generic arguments of largest_list. While TDrop was added to satisfy the compiler's requirements, we can also add constraints to benefit our function logic.

Imagine that we want, given a list of elements of some generic type T, to find the smallest element among them. Initially, we know that for an element of type T to be comparable, it must implement the PartialOrd trait. The resulting function would be:

// Given a list of T get the smallest one
// The PartialOrd trait implements comparison operations for T
fn smallest_element<T, impl TPartialOrd: PartialOrd<T>>(list: @Array<T>) -> T {
    // This represents the smallest element through the iteration
    // Notice that we use the desnap (*) operator
    let mut smallest = *list[0];

    // The index we will use to move through the list
    let mut index = 1;

    // Iterate through the whole list storing the smallest
    while index < list.len() {
        if *list[index] < smallest {
            smallest = *list[index];
        }
        index = index + 1;
    };

    smallest
}

fn main() {
    let list: Array<u8> = array![5, 3, 10];

    // We need to specify that we are passing a snapshot of `list` as an argument
    let s = smallest_element(@list);
    assert!(s == 3);
}

The smallest_element function uses a generic type T that implements the PartialOrd trait, takes a snapshot of an Array<T> as a parameter and returns a copy of the smallest element. Because the parameter is of type @Array<T>, we no longer need to drop it at the end of the execution and so we are not required to implement the Drop trait for T as well. Why does it not compile then?

When indexing on list, the value results in a snap of the indexed element, and unless PartialOrd is implemented for @T we need to desnap the element using *. The * operation requires a copy from @T to T, which means that T needs to implement the Copy trait. After copying an element of type @T to T, there are now variables with type T that need to be dropped, requiring T to implement the Drop trait as well. We must then add both Drop and Copy traits implementation for the function to be correct. After updating the smallest_element function the resulting code would be:

fn smallest_element<T, impl TPartialOrd: PartialOrd<T>, impl TCopy: Copy<T>, impl TDrop: Drop<T>>(
    list: @Array<T>,
) -> T {
    let mut smallest = *list[0];
    let mut index = 1;

    while index < list.len() {
        if *list[index] < smallest {
            smallest = *list[index];
        }
        index = index + 1;
    };

    smallest
}

Anonymous Generic Implementation Parameter (+ Operator)

Until now, we have always specified a name for each implementation of the required generic trait: TPartialOrd for PartialOrd<T>, TDrop for Drop<T>, and TCopy for Copy<T>.

However, most of the time, we don't use the implementation in the function body; we only use it as a constraint. In these cases, we can use the + operator to specify that the generic type must implement a trait without naming the implementation. This is referred to as an anonymous generic implementation parameter.

For example, +PartialOrd<T> is equivalent to impl TPartialOrd: PartialOrd<T>.

We can rewrite the smallest_element function signature as follows:

fn smallest_element<T, +PartialOrd<T>, +Copy<T>, +Drop<T>>(list: @Array<T>) -> T {
    let mut smallest = *list[0];
    let mut index = 1;
    loop {
        if index >= list.len() {
            break smallest;
        }
        if *list[index] < smallest {
            smallest = *list[index];
        }
        index = index + 1;
    }
}

Structs

We can also define structs to use a generic type parameter for one or more fields using the <> syntax, similar to function definitions. First, we declare the name of the type parameter inside the angle brackets just after the name of the struct. Then we use the generic type in the struct definition where we would otherwise specify concrete data types. The next code example shows the definition Wallet<T> which has a balance field of type T.

#[derive(Drop)]
struct Wallet<T> {
    balance: T,
}

fn main() {
    let w = Wallet { balance: 3 };
}

El código anterior deriva el trait Drop para el tipo Wallet automáticamente. Es equivalente a escribir el siguiente código:

struct Wallet<T> {
    balance: T,
}

impl WalletDrop<T, +Drop<T>> of Drop<Wallet<T>>;

fn main() {
    let w = Wallet { balance: 3 };
}

Evitamos el uso de la macro derive para la implementación de Drop de Wallet y en su lugar definimos nuestra propia implementación de WalletDrop. Nótese que debemos definir, al igual que en las funciones, un tipo genérico adicional para WalletDrop diciendo que T también implementa el trait Drop. Básicamente estamos diciendo que la estructura Wallet<T> es dropeable siempre y cuando T también lo sea.

Finalmente, si queremos añadir un campo a Wallet que represente su dirección y queremos que ese campo sea diferente de T pero genérico también, podemos simplemente añadir otro tipo genérico entre el <>:

#[derive(Drop)]
struct Wallet<T, U> {
    balance: T,
    address: U,
}

fn main() {
    let w = Wallet { balance: 3, address: 14 };
}

We add to the Wallet struct definition a new generic type U and then assign this type to the new field member address. Notice that the derive attribute for the Drop trait works for U as well.

Enums

Como hicimos con las estructuras, podemos definir enumeraciones para contener tipos de datos genéricos en sus variantes. Por ejemplo, la enumeración Option<T> proporcionada por la biblioteca central de Cairo:

enum Option<T> {
    Some: T,
    None,
}

El enum Option<T> es genérico sobre un tipo T y tiene dos variantes: Some, que contiene un valor de tipo T, y None, que no contiene ningún valor. Al utilizar el enum Option<T>, es posible expresar el concepto abstracto de un valor opcional y debido a que el valor tiene un tipo genérico T, podemos utilizar esta abstracción con cualquier tipo.

Enums can use multiple generic types as well, like the definition of the Result<T, E> enum that the core library provides:

enum Result<T, E> {
    Ok: T,
    Err: E,
}

El enum Result<T, E> tiene dos tipos genéricos, T y E, y dos variantes: Ok que tiene el valor de tipo T y Err que tiene el valor de tipo E. Esta definición hace que sea conveniente usar el enum Result en cualquier lugar donde tengamos una operación que pueda tener éxito (devolviendo un valor de tipo T) o fallar (devolviendo un valor de tipo E).

Generic Methods

We can implement methods on structs and enums, and use the generic types in their definitions, too. Using our previous definition of Wallet<T> struct, we define a balance method for it:

#[derive(Copy, Drop)]
struct Wallet<T> {
    balance: T,
}

trait WalletTrait<T> {
    fn balance(self: @Wallet<T>) -> T;
}

impl WalletImpl<T, +Copy<T>> of WalletTrait<T> {
    fn balance(self: @Wallet<T>) -> T {
        return *self.balance;
    }
}

fn main() {
    let w = Wallet { balance: 50 };
    assert!(w.balance() == 50);
}

We first define WalletTrait<T> trait using a generic type T which defines a method that returns the value of the field balance from Wallet. Then we give an implementation for the trait in WalletImpl<T>. Note that you need to include a generic type in both definitions of the trait and the implementation.

We can also specify constraints on generic types when defining methods on the type. We could, for example, implement methods only for Wallet<u128> instances rather than Wallet<T>. In the code example, we define an implementation for wallets which have a concrete type of u128 for the balance field.

#[derive(Copy, Drop)]
struct Wallet<T> {
    balance: T,
}

/// Generic trait for wallets
trait WalletTrait<T> {
    fn balance(self: @Wallet<T>) -> T;
}

impl WalletImpl<T, +Copy<T>> of WalletTrait<T> {
    fn balance(self: @Wallet<T>) -> T {
        return *self.balance;
    }
}

/// Trait for wallets of type u128
trait WalletReceiveTrait {
    fn receive(ref self: Wallet<u128>, value: u128);
}

impl WalletReceiveImpl of WalletReceiveTrait {
    fn receive(ref self: Wallet<u128>, value: u128) {
        self.balance += value;
    }
}

fn main() {
    let mut w = Wallet { balance: 50 };
    assert!(w.balance() == 50);

    w.receive(100);
    assert!(w.balance() == 150);
}

The new method receive increments the size of balance of any instance of a Wallet<u128>. Notice that we changed the main function making w a mutable variable in order for it to be able to update its balance. If we were to change the initialization of w by changing the type of balance the previous code wouldn't compile.

Cairo allows us to define generic methods inside generic traits as well. Using the past implementation from Wallet<U, V> we are going to define a trait that picks two wallets of different generic types and creates a new one with a generic type of each. First, let's rewrite the struct definition:

struct Wallet<T, U> {
    balance: T,
    address: U,
}

Next, we are going to naively define the mixup trait and implementation:

// This does not compile!
trait WalletMixTrait<T1, U1> {
    fn mixup<T2, U2>(self: Wallet<T1, U1>, other: Wallet<T2, U2>) -> Wallet<T1, U2>;
}

impl WalletMixImpl<T1, U1> of WalletMixTrait<T1, U1> {
    fn mixup<T2, U2>(self: Wallet<T1, U1>, other: Wallet<T2, U2>) -> Wallet<T1, U2> {
        Wallet { balance: self.balance, address: other.address }
    }
}

We are creating a trait WalletMixTrait<T1, U1> with the mixup<T2, U2> method which given an instance of Wallet<T1, U1> and Wallet<T2, U2> creates a new Wallet<T1, U2>. As mixup signature specifies, both self and other are getting dropped at the end of the function, which is why this code does not compile. If you have been following from the start until now you would know that we must add a requirement for all the generic types specifying that they will implement the Drop trait for the compiler to know how to drop instances of Wallet<T, U>. The updated implementation is as follows:

trait WalletMixTrait<T1, U1> {
    fn mixup<T2, +Drop<T2>, U2, +Drop<U2>>(
        self: Wallet<T1, U1>, other: Wallet<T2, U2>,
    ) -> Wallet<T1, U2>;
}

impl WalletMixImpl<T1, +Drop<T1>, U1, +Drop<U1>> of WalletMixTrait<T1, U1> {
    fn mixup<T2, +Drop<T2>, U2, +Drop<U2>>(
        self: Wallet<T1, U1>, other: Wallet<T2, U2>,
    ) -> Wallet<T1, U2> {
        Wallet { balance: self.balance, address: other.address }
    }
}

Sí, agregamos los requisitos para que T1 y U1 sean droppables en la declaración de WalletMixImpl. Luego hacemos lo mismo para T2 y U2, esta vez como parte de la firma de mixup. Ahora podemos probar la función mixup:

fn main() {
    let w1: Wallet<bool, u128> = Wallet { balance: true, address: 10 };
    let w2: Wallet<felt252, u8> = Wallet { balance: 32, address: 100 };

    let w3 = w1.mixup(w2);

    assert!(w3.balance);
    assert!(w3.address == 100);
}

Primero creamos dos instancias: una de Wallet<bool, u128> y la otra de Wallet<felt252, u8>. Luego, llamamos a mixup y creamos una nueva instancia de Wallet<bool, u8>.

Traits en Cairo

A trait defines a set of methods that can be implemented by a type. These methods can be called on instances of the type when this trait is implemented. A trait combined with a generic type defines functionality a particular type has and can share with other types. We can use traits to define shared behavior in an abstract way. We can use trait bounds to specify that a generic type can be any type that has certain behavior.

Note: Traits are similar to a feature often called interfaces in other languages, although with some differences.

While traits can be written to not accept generic types, they are most useful when used with generic types. We already covered generics in the previous chapter, and we will use them in this chapter to demonstrate how traits can be used to define shared behavior for generic types.

Defining a Trait

A type’s behavior consists of the methods we can call on that type. Different types share the same behavior if we can call the same methods on all of those types. Trait definitions are a way to group method signatures together to define a set of behaviors necessary to accomplish some purpose.

For example, let’s say we have a struct NewsArticle that holds a news story in a particular location. We can define a trait Summary that describes the behavior of something that can summarize the NewsArticle type.

#[derive(Drop, Clone)]
struct NewsArticle {
    headline: ByteArray,
    location: ByteArray,
    author: ByteArray,
    content: ByteArray,
}

pub trait Summary {
    fn summarize(self: @NewsArticle) -> ByteArray;
}

impl NewsArticleSummary of Summary {
    fn summarize(self: @NewsArticle) -> ByteArray {
        format!("{:?} by {:?} ({:?})", self.headline, self.author, self.location)
    }
}

Listing 8-1: A Summary trait that consists of the behavior provided by a summarize method

In Listing 8-1, we declare a trait using the trait keyword and then the trait’s name, which is Summary in this case. We’ve also declared the trait as pub so that crates depending on this crate can make use of this trait too, as we’ll see in a few examples.

Inside the curly brackets, we declare the method signatures that describe the behaviors of the types that implement this trait, which in this case is fn summarize(self: @NewsArticle) -> ByteArray;. After the method signature, instead of providing an implementation within curly brackets, we use a semicolon.

Note: the ByteArray type is the type used to represent strings in Cairo.

As the trait is not generic, the self parameter is not generic either and is of type @NewsArticle. This means that the summarize method can only be called on instances of NewsArticle.

Now, consider that we want to make a media aggregator library crate named aggregator that can display summaries of data that might be stored in a NewsArticle or Tweet instance. To do this, we need a summary from each type, and we’ll request that summary by calling a summarize method on an instance of that type. By defining the Summary trait on generic type T, we can implement the summarize method on any type we want to be able to summarize.

mod aggregator {
    pub trait Summary<T> {
        fn summarize(self: @T) -> ByteArray;
    }

    #[derive(Drop)]
    pub struct NewsArticle {
        pub headline: ByteArray,
        pub location: ByteArray,
        pub author: ByteArray,
        pub content: ByteArray,
    }

    impl NewsArticleSummary of Summary<NewsArticle> {
        fn summarize(self: @NewsArticle) -> ByteArray {
            format!("{} by {} ({})", self.headline, self.author, self.location)
        }
    }

    #[derive(Drop)]
    pub struct Tweet {
        pub username: ByteArray,
        pub content: ByteArray,
        pub reply: bool,
        pub retweet: bool,
    }

    impl TweetSummary of Summary<Tweet> {
        fn summarize(self: @Tweet) -> ByteArray {
            format!("{}: {}", self.username, self.content)
        }
    }
}

use aggregator::{Summary, NewsArticle, Tweet};

fn main() {
    let news = NewsArticle {
        headline: "Cairo has become the most popular language for developers",
        location: "Worldwide",
        author: "Cairo Digger",
        content: "Cairo is a new programming language for zero-knowledge proofs",
    };

    let tweet = Tweet {
        username: "EliBenSasson",
        content: "Crypto is full of short-term maximizing projects. \n @Starknet and @StarkWareLtd are about long-term vision maximization.",
        reply: false,
        retweet: false,
    }; // Tweet instantiation

    println!("New article available! {}", news.summarize());
    println!("New tweet! {}", tweet.summarize());
}

Listing 8-2: A Summary trait that consists of the behavior provided by a summarize method for a generic type

Each type implementing this trait must provide its own custom behavior for the body of the method. The compiler will enforce that any type that implements the Summary trait will have the method summarize defined with this signature exactly.

A trait can have multiple methods in its body: the method signatures are listed one per line and each line ends in a semicolon.

Implementing a Trait on a Type

Now that we’ve defined the desired signatures of the Summary trait’s methods, we can implement it on the types in our media aggregator. The following code shows an implementation of the Summary trait on the NewsArticle struct that uses the headline, the author, and the location to create the return value of summarize. For the Tweet struct, we define summarize as the username followed by the entire text of the tweet, assuming that tweet content is already limited to 280 characters.

mod aggregator {
    pub trait Summary<T> {
        fn summarize(self: @T) -> ByteArray;
    }

    #[derive(Drop)]
    pub struct NewsArticle {
        pub headline: ByteArray,
        pub location: ByteArray,
        pub author: ByteArray,
        pub content: ByteArray,
    }

    impl NewsArticleSummary of Summary<NewsArticle> {
        fn summarize(self: @NewsArticle) -> ByteArray {
            format!("{} by {} ({})", self.headline, self.author, self.location)
        }
    }

    #[derive(Drop)]
    pub struct Tweet {
        pub username: ByteArray,
        pub content: ByteArray,
        pub reply: bool,
        pub retweet: bool,
    }

    impl TweetSummary of Summary<Tweet> {
        fn summarize(self: @Tweet) -> ByteArray {
            format!("{}: {}", self.username, self.content)
        }
    }
}

use aggregator::{Summary, NewsArticle, Tweet};

fn main() {
    let news = NewsArticle {
        headline: "Cairo has become the most popular language for developers",
        location: "Worldwide",
        author: "Cairo Digger",
        content: "Cairo is a new programming language for zero-knowledge proofs",
    };

    let tweet = Tweet {
        username: "EliBenSasson",
        content: "Crypto is full of short-term maximizing projects. \n @Starknet and @StarkWareLtd are about long-term vision maximization.",
        reply: false,
        retweet: false,
    }; // Tweet instantiation

    println!("New article available! {}", news.summarize());
    println!("New tweet! {}", tweet.summarize());
}

Listing 8-3: Implementation of the Summary trait on NewsArticle and Tweet

Implementing a trait on a type is similar to implementing regular methods. The difference is that after impl, we put a name for the implementation, then use the of keyword, and then specify the name of the trait we are writing the implementation for. If the implementation is for a generic type, we place the generic type name in the angle brackets after the trait name.

Note that for the trait method to be accessible, there must be an implementation of that trait visible from the scope where the method is called. If the trait is pub and the implementation is not, and the implementation is not visible in the scope where the trait method is called, this will cause a compilation error.

Within the impl block, we put the method signatures that the trait definition has defined. Instead of adding a semicolon after each signature, we use curly brackets and fill in the method body with the specific behavior that we want the methods of the trait to have for the particular type.

Now that the library has implemented the Summary trait on NewsArticle and Tweet, users of the crate can call the trait methods on instances of NewsArticle and Tweet in the same way we call regular methods. The only difference is that the user must bring the trait into scope as well as the types. Here’s an example of how a crate could use our aggregator crate:

mod aggregator {
    pub trait Summary<T> {
        fn summarize(self: @T) -> ByteArray;
    }

    #[derive(Drop)]
    pub struct NewsArticle {
        pub headline: ByteArray,
        pub location: ByteArray,
        pub author: ByteArray,
        pub content: ByteArray,
    }

    impl NewsArticleSummary of Summary<NewsArticle> {
        fn summarize(self: @NewsArticle) -> ByteArray {
            format!("{} by {} ({})", self.headline, self.author, self.location)
        }
    }

    #[derive(Drop)]
    pub struct Tweet {
        pub username: ByteArray,
        pub content: ByteArray,
        pub reply: bool,
        pub retweet: bool,
    }

    impl TweetSummary of Summary<Tweet> {
        fn summarize(self: @Tweet) -> ByteArray {
            format!("{}: {}", self.username, self.content)
        }
    }
}

use aggregator::{Summary, NewsArticle, Tweet};

fn main() {
    let news = NewsArticle {
        headline: "Cairo has become the most popular language for developers",
        location: "Worldwide",
        author: "Cairo Digger",
        content: "Cairo is a new programming language for zero-knowledge proofs",
    };

    let tweet = Tweet {
        username: "EliBenSasson",
        content: "Crypto is full of short-term maximizing projects. \n @Starknet and @StarkWareLtd are about long-term vision maximization.",
        reply: false,
        retweet: false,
    }; // Tweet instantiation

    println!("New article available! {}", news.summarize());
    println!("New tweet! {}", tweet.summarize());
}

This code prints the following:

$ scarb cairo-run 
   Compiling no_listing_15_traits v0.1.0 (listings/ch08-generic-types-and-traits/no_listing_15_traits/Scarb.toml)
    Finished `dev` profile target(s) in 3 seconds
     Running no_listing_15_traits
New article available! Cairo has become the most popular language for developers by Cairo Digger (Worldwide)
New tweet! EliBenSasson: Crypto is full of short-term maximizing projects. 
 @Starknet and @StarkWareLtd are about long-term vision maximization.
Run completed successfully, returning []

Other crates that depend on the aggregator crate can also bring the Summary trait into scope to implement Summary on their own types.

Default Implementations

Sometimes it’s useful to have default behavior for some or all of the methods in a trait instead of requiring implementations for all methods on every type. Then, as we implement the trait on a particular type, we can keep or override each method’s default behavior.

In Listing 8-5 we specify a default string for the summarize method of the Summary trait instead of only defining the method signature, as we did in Listing 8-2.

Filename: src/lib.cairo

mod aggregator {
    pub trait Summary<T> {
        fn summarize(self: @T) -> ByteArray {
            "(Read more...)"
        }
    }

    #[derive(Drop)]
    pub struct NewsArticle {
        pub headline: ByteArray,
        pub location: ByteArray,
        pub author: ByteArray,
        pub content: ByteArray,
    }

    impl NewsArticleSummary of Summary<NewsArticle> {}

    #[derive(Drop)]
    pub struct Tweet {
        pub username: ByteArray,
        pub content: ByteArray,
        pub reply: bool,
        pub retweet: bool,
    }

    impl TweetSummary of Summary<Tweet> {
        fn summarize(self: @Tweet) -> ByteArray {
            format!("{}: {}", self.username, self.content)
        }
    }
}

use aggregator::{Summary, NewsArticle};

fn main() {
    let news = NewsArticle {
        headline: "Cairo has become the most popular language for developers",
        location: "Worldwide",
        author: "Cairo Digger",
        content: "Cairo is a new programming language for zero-knowledge proofs",
    };

    println!("New article available! {}", news.summarize());
}

Listing 8-5: Defining a Summary trait with a default implementation of the summarize method

To use a default implementation to summarize instances of NewsArticle, we specify an empty impl block with impl NewsArticleSummary of Summary<NewsArticle> {}.

Even though we’re no longer defining the summarize method on NewsArticle directly, we’ve provided a default implementation and specified that NewsArticle implements the Summary trait. As a result, we can still call the summarize method on an instance of NewsArticle, like this:

mod aggregator {
    pub trait Summary<T> {
        fn summarize(self: @T) -> ByteArray {
            "(Read more...)"
        }
    }

    #[derive(Drop)]
    pub struct NewsArticle {
        pub headline: ByteArray,
        pub location: ByteArray,
        pub author: ByteArray,
        pub content: ByteArray,
    }

    impl NewsArticleSummary of Summary<NewsArticle> {}

    #[derive(Drop)]
    pub struct Tweet {
        pub username: ByteArray,
        pub content: ByteArray,
        pub reply: bool,
        pub retweet: bool,
    }

    impl TweetSummary of Summary<Tweet> {
        fn summarize(self: @Tweet) -> ByteArray {
            format!("{}: {}", self.username, self.content)
        }
    }
}

use aggregator::{Summary, NewsArticle};

fn main() {
    let news = NewsArticle {
        headline: "Cairo has become the most popular language for developers",
        location: "Worldwide",
        author: "Cairo Digger",
        content: "Cairo is a new programming language for zero-knowledge proofs",
    };

    println!("New article available! {}", news.summarize());
}

This code prints New article available! (Read more...).

Creating a default implementation doesn’t require us to change anything about the previous implementation of Summary on Tweet. The reason is that the syntax for overriding a default implementation is the same as the syntax for implementing a trait method that doesn’t have a default implementation.

Default implementations can call other methods in the same trait, even if those other methods don’t have a default implementation. In this way, a trait can provide a lot of useful functionality and only require implementors to specify a small part of it. For example, we could define the Summary trait to have a summarize_author method whose implementation is required, and then define a summarize method that has a default implementation that calls the summarize_author method:

mod aggregator {
    pub trait Summary<T> {
        fn summarize(
            self: @T,
        ) -> ByteArray {
            format!("(Read more from {}...)", Self::summarize_author(self))
        }
        fn summarize_author(self: @T) -> ByteArray;
    }

    #[derive(Drop)]
    pub struct Tweet {
        pub username: ByteArray,
        pub content: ByteArray,
        pub reply: bool,
        pub retweet: bool,
    }

    impl TweetSummary of Summary<Tweet> {
        fn summarize_author(self: @Tweet) -> ByteArray {
            format!("@{}", self.username)
        }
    }
}

use aggregator::{Summary, Tweet};

fn main() {
    let tweet = Tweet {
        username: "EliBenSasson",
        content: "Crypto is full of short-term maximizing projects. \n @Starknet and @StarkWareLtd are about long-term vision maximization.",
        reply: false,
        retweet: false,
    };

    println!("1 new tweet: {}", tweet.summarize());
}

To use this version of Summary, we only need to define summarize_author when we implement the trait on a type:

mod aggregator {
    pub trait Summary<T> {
        fn summarize(
            self: @T,
        ) -> ByteArray {
            format!("(Read more from {}...)", Self::summarize_author(self))
        }
        fn summarize_author(self: @T) -> ByteArray;
    }

    #[derive(Drop)]
    pub struct Tweet {
        pub username: ByteArray,
        pub content: ByteArray,
        pub reply: bool,
        pub retweet: bool,
    }

    impl TweetSummary of Summary<Tweet> {
        fn summarize_author(self: @Tweet) -> ByteArray {
            format!("@{}", self.username)
        }
    }
}

use aggregator::{Summary, Tweet};

fn main() {
    let tweet = Tweet {
        username: "EliBenSasson",
        content: "Crypto is full of short-term maximizing projects. \n @Starknet and @StarkWareLtd are about long-term vision maximization.",
        reply: false,
        retweet: false,
    };

    println!("1 new tweet: {}", tweet.summarize());
}

After we define summarize_author, we can call summarize on instances of the Tweet struct, and the default implementation of summarize will call the definition of summarize_author that we’ve provided. Because we’ve implemented summarize_author, the Summary trait has given us the behavior of the summarize method without requiring us to write any more code.

mod aggregator {
    pub trait Summary<T> {
        fn summarize(
            self: @T,
        ) -> ByteArray {
            format!("(Read more from {}...)", Self::summarize_author(self))
        }
        fn summarize_author(self: @T) -> ByteArray;
    }

    #[derive(Drop)]
    pub struct Tweet {
        pub username: ByteArray,
        pub content: ByteArray,
        pub reply: bool,
        pub retweet: bool,
    }

    impl TweetSummary of Summary<Tweet> {
        fn summarize_author(self: @Tweet) -> ByteArray {
            format!("@{}", self.username)
        }
    }
}

use aggregator::{Summary, Tweet};

fn main() {
    let tweet = Tweet {
        username: "EliBenSasson",
        content: "Crypto is full of short-term maximizing projects. \n @Starknet and @StarkWareLtd are about long-term vision maximization.",
        reply: false,
        retweet: false,
    };

    println!("1 new tweet: {}", tweet.summarize());
}

This code prints 1 new tweet: (Read more from @EliBenSasson...).

Note that it isn’t possible to call the default implementation from an overriding implementation of that same method.

Managing and Using External Trait

To use traits methods, you need to make sure the correct traits/implementation(s) are imported. In some cases you might need to import not only the trait but also the implementation if they are declared in separate modules. If CircleGeometry implementation was in a separate module/file named circle, then to define boundary method on Circle struct, we'd need to import ShapeGeometry trait in the circle module.

If the code were to be organized into modules like in Listing 8-6 where the implementation of a trait is defined in a different module than the trait itself, explicitly importing the relevant trait or implementation would be required.

// Here T is an alias type which will be provided during implementation
pub trait ShapeGeometry<T> {
    fn boundary(self: T) -> u64;
    fn area(self: T) -> u64;
}

mod rectangle {
    // Importing ShapeGeometry is required to implement this trait for Rectangle
    use super::ShapeGeometry;

    #[derive(Copy, Drop)]
    pub struct Rectangle {
        pub height: u64,
        pub width: u64,
    }

    // Implementation RectangleGeometry passes in <Rectangle>
    // to implement the trait for that type
    impl RectangleGeometry of ShapeGeometry<Rectangle> {
        fn boundary(self: Rectangle) -> u64 {
            2 * (self.height + self.width)
        }
        fn area(self: Rectangle) -> u64 {
            self.height * self.width
        }
    }
}

mod circle {
    // Importing ShapeGeometry is required to implement this trait for Circle
    use super::ShapeGeometry;

    #[derive(Copy, Drop)]
    pub struct Circle {
        pub radius: u64,
    }

    // Implementation CircleGeometry passes in <Circle>
    // to implement the imported trait for that type
    impl CircleGeometry of ShapeGeometry<Circle> {
        fn boundary(self: Circle) -> u64 {
            (2 * 314 * self.radius) / 100
        }
        fn area(self: Circle) -> u64 {
            (314 * self.radius * self.radius) / 100
        }
    }
}

use rectangle::Rectangle;
use circle::Circle;

fn main() {
    let rect = Rectangle { height: 5, width: 7 };
    println!("Rectangle area: {}", ShapeGeometry::area(rect)); //35
    println!("Rectangle boundary: {}", ShapeGeometry::boundary(rect)); //24

    let circ = Circle { radius: 5 };
    println!("Circle area: {}", ShapeGeometry::area(circ)); //78
    println!("Circle boundary: {}", ShapeGeometry::boundary(circ)); //31
}

Listing 8-6: Implementing an external trait

Note that in Listing 8-6, CircleGeometry and RectangleGeometry implementations don't need to be declared as pub. Indeed, ShapeGeometry trait, which is public, is used to print the result in the main function. The compiler will find the appropriate implementation for the ShapeGeometry public trait, regardless of the implementation visibility.

Impl Aliases

Implementations can be aliased when imported. This is most useful when you want to instantiate generic implementations with concrete types. For example, let's say we define a trait Two that is used to return the value 2 for a type T. We can write a trivial generic implementation of Two for all types that implement the One trait, simply by adding twice the value of one and returning it. However, in our public API, we may only want to expose the Two implementation for the u8 and u128 types.

trait Two<T> {
    fn two() -> T;
}

mod one_based {
    pub impl TwoImpl<
        T, +Copy<T>, +Drop<T>, +Add<T>, impl One: core::num::traits::One<T>,
    > of super::Two<T> {
        fn two() -> T {
            One::one() + One::one()
        }
    }
}

pub impl U8Two = one_based::TwoImpl<u8>;
pub impl U128Two = one_based::TwoImpl<u128>;

Listing 8-7: Using impl aliases to instantiate generic impls with concrete types

We can define the generic implementation in a private module, use an impl alias to instantiate the generic implementation for these two concrete types, and make these two implementations public, while keeping the generic implementation private and unexposed. This way, we can avoid code duplication using the generic implementation, while keeping the public API clean and simple.

Negative Impls

Note: This is still an experimental feature and can only be used if experimental-features = ["negative_impls"] is enabled in your Scarb.toml file, under the [package] section.

Negative implementations, also known as negative traits or negative bounds, are a mechanism that allows you to express that a type does not implement a certain trait when defining the implementation of a trait over a generic type. Negative impls enable you to write implementations that are applicable only when another implementation does not exist in the current scope.

For example, let's say we have a trait Producer and a trait Consumer, and we want to define a generic behavior where all types implement the Consumer trait by default. However, we want to ensure that no type can be both a Consumer and a Producer. We can use negative impls to express this restriction.

In Listing 8-8, we define a ProducerType that implements the Producer trait, and two other types, AnotherType and AThirdType, which do not implement the Producer trait. We then use negative impls to create a default implementation of the Consumer trait for all types that do not implement the Producer trait.

#[derive(Drop)]
struct ProducerType {}

#[derive(Drop, Debug)]
struct AnotherType {}

#[derive(Drop, Debug)]
struct AThirdType {}

trait Producer<T> {
    fn produce(self: T) -> u32;
}

trait Consumer<T> {
    fn consume(self: T, input: u32);
}

impl ProducerImpl of Producer<ProducerType> {
    fn produce(self: ProducerType) -> u32 {
        42
    }
}

impl TConsumerImpl<T, +core::fmt::Debug<T>, +Drop<T>, -Producer<T>> of Consumer<T> {
    fn consume(self: T, input: u32) {
        println!("{:?} consumed value: {}", self, input);
    }
}

fn main() {
    let producer = ProducerType {};
    let another_type = AnotherType {};
    let third_type = AThirdType {};
    let production = producer.produce();

    // producer.consume(production); Invalid: ProducerType does not implement Consumer
    another_type.consume(production);
    third_type.consume(production);
}

Listing 8-8: Using negative impls to enforce that a type cannot implement both Producer and Consumer traits simultaneously

In the main function, we create instances of ProducerType, AnotherType, and AThirdType. We then call the produce method on the producer instance and pass the result to the consume method on the another_type and third_type instances. Finally, we try to call the consume method on the producer instance, which results in a compile-time error because ProducerType does not implement the Consumer trait.

Error handling

In this chapter, we will explore various error handling techniques provided by Cairo, which not only allow you to address potential issues in your code, but also make it easier to create programs that are adaptable and maintainable. By examining different approaches to managing errors, such as pattern matching with the Result enum, using the ? operator for more ergonomic error propagation, and employing the unwrap or expect methods for handling recoverable errors, you'll gain a deeper understanding of Cairo's error handling features. These concepts are crucial for building robust applications that can effectively handle unexpected situations, ensuring your code is ready for production.

Unrecoverable Errors with panic

In Cairo, unexpected issues may arise during program execution, resulting in runtime errors. While the panic function from the core library doesn't provide a resolution for these errors, it does acknowledge their occurrence and terminates the program. There are two primary ways that a panic can be triggered in Cairo: inadvertently, through actions causing the code to panic (e.g., accessing an array beyond its bounds), or deliberately, by invoking the panic function.

When a panic occurs, it leads to an abrupt termination of the program. The panic function takes an array as an argument, which can be used to provide an error message and performs an unwind process where all variables are dropped and dictionaries squashed to ensure the soundness of the program to safely terminate the execution.

Here is how we can call panic from inside a program and return the error code 2:

Filename: src/lib.cairo

fn main() {
    let mut data = array![2];

    if true {
        panic(data);
    }
    println!("This line isn't reached");
}

La ejecución del programa producirá el siguiente resultado:

$ scarb cairo-run 
   Compiling no_listing_01_panic v0.1.0 (listings/ch09-error-handling/no_listing_01_panic/Scarb.toml)
    Finished `dev` profile target(s) in 4 seconds
     Running no_listing_01_panic
Run panicked with [2, ].

As you can notice in the output, the call to println! macro is never reached, as the program terminates after encountering the panic statement.

An alternative and more idiomatic approach to panic in Cairo would be to use the panic_with_felt252 function. This function serves as an abstraction of the array-defining process and is often preferred due to its clearer and more concise expression of intent. By using panic_with_felt252, developers can panic in a one-liner by providing a felt252 error message as an argument, making the code more readable and maintainable.

Veamos un ejemplo:

use core::panic_with_felt252;

fn main() {
    panic_with_felt252(2);
}

Executing this program will yield the same error message as before. In that case, if there is no need for an array and multiple values to be returned within the error, panic_with_felt252 is a more succinct alternative.

panic! Macro

panic! macro can be really helpful. The previous example returning the error code 2 shows how convenient panic! macro is. There is no need to create an array and pass it as an argument like with the panic function.

fn main() {
    if true {
        panic!("2");
    }
    println!("This line isn't reached");
}

Unlike the panic_with_felt252 function, using panic! allows the input, which is ultimately the panic error, to be a literal longer than 31 bytes. This is because panic! takes a string as a parameter. For example, the following line of code will successfully compile:

panic!("the error for panic! macro is not limited to 31 characters anymore");

nopanic Notation

Puede utilizar la anotación nopanic para indicar que una función nunca entrará en pánico. Sólo las funciones nopanic pueden ser llamadas en una función anotada como nopanic.

Aquí un ejemplo:

fn function_never_panic() -> felt252 nopanic {
    42
}

This function will always return 42 and is guaranteed to never panic. Conversely, the following function is not guaranteed to never panic:

fn function_never_panic() nopanic {
    assert(1 == 1, 'what');
}

If you try to compile this function that includes code that may panic, you will get the following error:

$ scarb cairo-run 
   Compiling no_listing_04_nopanic_wrong v0.1.0 (listings/ch09-error-handling/no_listing_05_nopanic_wrong/Scarb.toml)
error: Function is declared as nopanic but calls a function that may panic.
 --> listings/ch09-error-handling/no_listing_05_nopanic_wrong/src/lib.cairo:4:12
    assert(1 == 1, 'what');
           ^****^

error: Function is declared as nopanic but calls a function that may panic.
 --> listings/ch09-error-handling/no_listing_05_nopanic_wrong/src/lib.cairo:4:5
    assert(1 == 1, 'what');
    ^********************^

error: could not compile `no_listing_04_nopanic_wrong` due to previous error
error: `scarb metadata` exited with error

Note that there are two functions that may panic here, assert and equality with ==. We usually don't use assert function in practice and use assert! macro instead. We will discuss assert! macro in more detail in the Testing Cairo Programs chapter.

panic_with Attribute

You can use the panic_with attribute to mark a function that returns an Option or Result. This attribute takes two arguments, which are the data that is passed as the panic reason as well as the name for a wrapping function. It will create a wrapper for your annotated function which will panic if the function returns None or Err, with the given data as the panic error.

Ejemplo:

#[panic_with('value is 0', wrap_not_zero)]
fn wrap_if_not_zero(value: u128) -> Option<u128> {
    if value == 0 {
        Option::None
    } else {
        Option::Some(value)
    }
}

fn main() {
    wrap_if_not_zero(0); // this returns None
    wrap_not_zero(0); // this panics with 'value is 0'
}

Recoverable Errors with Result

La mayoría de los errores no son lo suficientemente graves como para que el programa se detenga por completo. A veces, cuando una función falla, es por una razón que usted puede interpretar fácilmente y a la que puede responder. Por ejemplo, si intenta sumar dos enteros grandes y la operación se desborda porque la suma excede el valor máximo representable, es posible que desee devolver un error o un resultado envuelto en lugar de causar un comportamiento indefinido o terminar el proceso.

The Result Enum

Recall from Generic data types section in Chapter 8 that the Result enum is defined as having two variants, Ok and Err, as follows:

enum Result<T, E> {
    Ok: T,
    Err: E,
}

El enum Result<T, E> tiene dos tipos genéricos, T y E, y dos variantes: Ok que tiene el valor de tipo T y Err que tiene el valor de tipo E. Esta definición hace que sea conveniente usar el enum Result en cualquier lugar donde tengamos una operación que pueda tener éxito (devolviendo un valor de tipo T) o fallar (devolviendo un valor de tipo E).

The ResultTrait

El rasgo ResultTrait proporciona métodos para trabajar con el enum Result<T, E>, como desenvolver valores, comprobar si el Result es Ok o Err, y entrar en pánico con un mensaje personalizado. La implementación de ResultTraitImpl define la lógica de estos métodos.

trait ResultTrait<T, E> {
    fn expect<+Drop<E>>(self: Result<T, E>, err: felt252) -> T;

    fn unwrap<+Drop<E>>(self: Result<T, E>) -> T;

    fn expect_err<+Drop<T>>(self: Result<T, E>, err: felt252) -> E;

    fn unwrap_err<+Drop<T>>(self: Result<T, E>) -> E;

    fn is_ok(self: @Result<T, E>) -> bool;

    fn is_err(self: @Result<T, E>) -> bool;
}

Los métodos expect y unwrap se parecen en que ambos intentan extraer el valor de tipo T de un Resultado<T, E> cuando está en la variante Ok. Si el Resultado es Ok(x), ambos métodos devuelven el valor x. Sin embargo, la diferencia clave entre los dos métodos radica en su comportamiento cuando el Result está en la variante Err. El método expect te permite proporcionar un mensaje de error personalizado (como un valor felt252) que se utilizará cuando se produzca el pánico, dándote más control y contexto sobre el pánico. Por otro lado, el método unwrap entra en pánico con un mensaje de error por defecto, proporcionando menos información sobre la causa del pánico.

The expect_err and unwrap_err methods have the exact opposite behavior. If the Result is Err(x), both methods return the value x. However, the key difference between the two methods is in case of Result::Ok(). The expect_err method allows you to provide a custom error message (as a felt252 value) that will be used when panicking, giving you more control and context over the panic. On the other hand, the unwrap_err method panics with a default error message, providing less information about the cause of the panic.

A careful reader may have noticed the <+Drop<T>> and <+Drop<E>> in the first four methods signatures. This syntax represents generic type constraints in the Cairo language, as seen in the previous chapter. These constraints indicate that the associated functions require an implementation of the Drop trait for the generic types T and E, respectively.

Por último, los métodos is_ok y is_err son funciones de utilidad proporcionadas por el rasgo ResultTrait para comprobar la variante de un valor del enum Result.

• is_ok toma una instantánea de un valor Result<T, E> y devuelve true si el Result es la variante Ok, lo que significa que la operación se ha realizado correctamente. Si el Resultado es la variante Err, devuelve false.
• is_err takes a snapshot of a Result<T, E> value and returns true if the Result is the Err variant, meaning the operation encountered an error. If the Result is the Ok variant, it returns false.

These methods are helpful when you want to check the success or failure of an operation without consuming the Result value, allowing you to perform additional operations or make decisions based on the variant without unwrapping it.

Puede encontrar la implementación del ResultTrait aquí.

It is always easier to understand with examples. Have a look at this function signature:

fn u128_overflowing_add(a: u128, b: u128) -> Result<u128, u128>;

It takes two u128 integers, a and b, and returns a Result<u128, u128> where the Ok variant holds the sum if the addition does not overflow, and the Err variant holds the overflowed value if the addition does overflow.

Ahora, podemos utilizar esta función en otros lugares. Por ejemplo:

fn u128_checked_add(a: u128, b: u128) -> Option<u128> {
    match u128_overflowing_add(a, b) {
        Result::Ok(r) => Option::Some(r),
        Result::Err(r) => Option::None,
    }
}

Here, it accepts two u128 integers, a and b, and returns an Option<u128>. It uses the Result returned by u128_overflowing_add to determine the success or failure of the addition operation. The match expression checks the Result from u128_overflowing_add. If the result is Ok(r), it returns Option::Some(r) containing the sum. If the result is Err(r), it returns Option::None to indicate that the operation has failed due to overflow. The function does not panic in case of an overflow.

Let's take another example:

fn parse_u8(s: felt252) -> Result<u8, felt252> {
    match s.try_into() {
        Option::Some(value) => Result::Ok(value),
        Option::None => Result::Err('Invalid integer'),
    }
}

In this example, the parse_u8 function takes a felt252 and tries to convert it into a u8 integer using the try_into method. If successful, it returns Result::Ok(value), otherwise it returns Result::Err('Invalid integer').

Nuestros dos casos de prueba son:

fn parse_u8(s: felt252) -> Result<u8, felt252> {
    match s.try_into() {
        Option::Some(value) => Result::Ok(value),
        Option::None => Result::Err('Invalid integer'),
    }
}

#[cfg(test)]
mod tests {
    use super::*;

    #[test]
    fn test_felt252_to_u8() {
        let number: felt252 = 5;
        // should not panic
        let res = parse_u8(number).unwrap();
    }

    #[test]
    #[should_panic]
    fn test_felt252_to_u8_panic() {
        let number: felt252 = 256;
        // should panic
        let res = parse_u8(number).unwrap();
    }
}

Don't worry about the #[cfg(test)] attribute for now. We'll explain in more detail its meaning in the next Testing Cairo Programs chapter.

#[test] attribute means the function is a test function, and #[should_panic] attribute means this test will pass if the test execution panics.

The first one tests a valid conversion from felt252 to u8, expecting the unwrap method not to panic. The second test function attempts to convert a value that is out of the u8 range, expecting the unwrap method to panic with the error message Invalid integer.

The ? Operator

El último operador del que hablaremos es el operador ?. El operador ? se utiliza para un manejo de errores más idiomático y conciso. Cuando usas el operador ? en un tipo Result u Option, hará lo siguiente:

• If the value is Result::Ok(x) or Option::Some(x), it will return the inner value x directly.
• If the value is Result::Err(e) or Option::None, it will propagate the error or None by immediately returning from the function.

El operador ? es útil cuando se desea manejar los errores implícitamente y dejar que la función de llamada se ocupe de ellos.

Aquí un ejemplo:

fn do_something_with_parse_u8(input: felt252) -> Result<u8, felt252> {
    let input_to_u8: u8 = parse_u8(input)?;
    // DO SOMETHING
    let res = input_to_u8 - 1;
    Result::Ok(res)
}

We can see that do_something_with_parse_u8 function takes a felt252 value as input and calls parse_u8 function. The ? operator is used to propagate the error, if any, or unwrap the successful value.

Y con un pequeño caso de prueba:

fn parse_u8(s: felt252) -> Result<u8, felt252> {
    match s.try_into() {
        Option::Some(value) => Result::Ok(value),
        Option::None => Result::Err('Invalid integer'),
    }
}

fn do_something_with_parse_u8(input: felt252) -> Result<u8, felt252> {
    let input_to_u8: u8 = parse_u8(input)?;
    // DO SOMETHING
    let res = input_to_u8 - 1;
    Result::Ok(res)
}

#[cfg(test)]
mod tests {
    use super::*;
    #[test]
    fn test_function_2() {
        let number: felt252 = 258;
        match do_something_with_parse_u8(number) {
            Result::Ok(value) => println!("Result: {}", value),
            Result::Err(e) => println!("Error: {}", e),
        }
    }
}

The console will print the error Invalid Integer.

Resumen

We saw that recoverable errors can be handled in Cairo using the Result enum, which has two variants: Ok and Err. The Result<T, E> enum is generic, with types T and E representing the successful and error values, respectively. The ResultTrait provides methods for working with Result<T, E>, such as unwrapping values, checking if the result is Ok or Err, and panicking with custom messages.

Para gestionar errores recuperables, una función puede devolver un tipo Result y utilizar la concordancia de patrones para gestionar el éxito o el fracaso de una operación. El operador ? puede utilizarse para gestionar errores implícitamente, propagando el error o desenvolviendo el valor correcto. Esto permite una gestión de errores más concisa y clara, en la que el autor de la llamada es responsable de gestionar los errores generados por la función llamada.

Test de Programas en Cairo

Correctness in our programs is the extent to which our code does what we intend it to do. Cairo is designed with a high degree of concern about the correctness of programs, but correctness is complex and not easy to prove. Cairo's linear type system shoulders a huge part of this burden, but the type system cannot catch everything. As such, Cairo includes support for writing tests.

Testing is a complex skill: although we can’t cover every detail about how to write good tests in one chapter, we’ll discuss the mechanics of Cairo's testing facilities. We’ll talk about the annotations and macros available to you when writing your tests, the default behavior and options provided for running your tests, and how to organize tests into unit tests and integration tests.

Cómo Escribir Tests

The Anatomy of a Test Function

Las pruebas son funciones en Cairo que verifican que el código no relacionado con las pruebas está funcionando de la manera esperada. Los cuerpos de las funciones de prueba típicamente realizan estas tres acciones:

• Set up any needed data or state.
• Run the code you want to test.
• Assert the results are what you expect.

Let’s look at the features Cairo provides for writing tests that take these actions, which include:

• #[test] attribute.
• assert!macro.
• assert_eq!, assert_ne!, assert_lt!, assert_le!, assert_gt! and assert_ge! macros. In order to use them, you will need to add assert_macros = "2.8.2" as a dev dependency.
• #[should_panic] attribute.

Note: Make sure to select Starknet Foundry as a test runner when creating your project.

The Anatomy of a Test Function

At its simplest, a test in Cairo is a function that’s annotated with the #[test] attribute. Attributes are metadata about pieces of Cairo code; one example is the #[derive()] attribute we used with structs in Chapter 5. To change a function into a test function, add #[test] on the line before fn. When you run your tests with the scarb test command, Scarb runs Starknet Foundry's test runner binary that runs the annotated functions and reports on whether each test function passes or fails.

Let's create a new project called adder using Scarb with the command scarb new adder. Remove the tests folder.

adder
├── Scarb.toml
└── src
    └── lib.cairo

In lib.cairo, let's remove the existing content and add a tests module containing the first test, as shown in Listing 10-1.

Filename: src/lib.cairo

pub fn add(left: usize, right: usize) -> usize {
    left + right
}

#[cfg(test)]
mod tests {
    use super::*;

    #[test]
    fn it_works() {
        let result = add(2, 2);
        assert_eq!(result, 4);
    }
}

Listing 10-1: A simple test function

Note the #[test] annotation: this attribute indicates this is a test function, so the test runner knows to treat this function as a test. We might also have non-test functions to help set up common scenarios or perform common operations, so we always need to indicate which functions are tests.

We use the #[cfg(test)] attribute for the tests module, so that the compiler knows the code it contains needs to be compiled only when running tests. This is actually not an option: if you put a simple test with the #[test] attribute in a lib.cairo file, it will not compile. We will talk more about the #[cfg(test)] attribute in the next Test Organization section.

The example function body uses the assert_eq! macro, which contains the result of adding 2 and 2, which equals 4. This assertion serves as an example of the format for a typical test. We'll explain in more detail how assert_eq! works later in this chapter. Let’s run it to see that this test passes.

The scarb test command runs all tests found in our project, and shows the following output:

$ scarb test 
     Running test listing_10_01 (snforge test)
   Compiling snforge_scarb_plugin v0.31.0 (git+https://github.com/foundry-rs/starknet-foundry.git?tag=v0.31.0#72ea785ca354e9e506de3e5d687da9fb2c1b3c67)
    Blocking waiting for file lock on build directory
    Finished `release` profile [optimized] target(s) in 0.90s
   Compiling test(listings/ch10-testing-cairo-programs/listing_10_01/Scarb.toml)
    Finished `dev` profile target(s) in 6 seconds


Collected 2 test(s) from listing_10_01 package
Running 2 test(s) from src/
[PASS] listing_10_01::tests::it_works (gas: ~1)
[PASS] listing_10_01::other_tests::exploration (gas: ~1)
Tests: 2 passed, 0 failed, 0 skipped, 0 ignored, 0 filtered out

scarb test compiled and ran the test. We see the line Collected 1 test(s) from adder package followed by the line Running 1 test(s) from src/. The next line shows the name of the test function, called it_works, and that the result of running that test is ok. The test runner also provides an estimation of the gas consumption. The overall summary shows that all the tests passed, and the portion that reads 1 passed; 0 failed totals the number of tests that passed or failed.

It’s possible to mark a test as ignored so it doesn’t run in a particular instance; we’ll cover that in the Ignoring Some Tests Unless Specifically Requested section later in this chapter. Because we haven’t done that here, the summary shows 0 ignored. We can also pass an argument to the scarb test command to run only a test whose name matches a string; this is called filtering and we’ll cover that in the Running Single Tests section. Since we haven’t filtered the tests being run, the end of the summary shows 0 filtered out.

Comencemos a personalizar la prueba según nuestras necesidades. Primero, cambie el nombre de la función it_works a un nombre diferente, como exploration, así:

    #[test]
    fn exploration() {
        let result = 2 + 2;
        assert_eq!(result, 4);
    }

Then run scarb test again. The output now shows exploration instead of it_works:

$ scarb test 
     Running test listing_10_01 (snforge test)
   Compiling snforge_scarb_plugin v0.31.0 (git+https://github.com/foundry-rs/starknet-foundry.git?tag=v0.31.0#72ea785ca354e9e506de3e5d687da9fb2c1b3c67)
    Blocking waiting for file lock on build directory
    Finished `release` profile [optimized] target(s) in 0.90s
   Compiling test(listings/ch10-testing-cairo-programs/listing_10_01/Scarb.toml)
    Finished `dev` profile target(s) in 6 seconds


Collected 2 test(s) from listing_10_01 package
Running 2 test(s) from src/
[PASS] listing_10_01::tests::it_works (gas: ~1)
[PASS] listing_10_01::other_tests::exploration (gas: ~1)
Tests: 2 passed, 0 failed, 0 skipped, 0 ignored, 0 filtered out

Now we’ll add another test, but this time we’ll make a test that fails! Tests fail when something in the test function panics. Each test is run in a new thread, and when the main thread sees that a test thread has died, the test is marked as failed. Enter the new test as a function named another, so your src/lib.cairo file looks like in Listing 10-2.

Filename: src/lib.cairo

#[cfg(test)]
mod tests {
    #[test]
    fn exploration() {
        let result = 2 + 2;
        assert_eq!(result, 4);
    }

    #[test]
    fn another() {
        let result = 2 + 2;
        assert!(result == 6, "Make this test fail");
    }
}

Listing 10-2: Adding a second test in lib.cairo that will fail

Run scarb test and you will see the following output:

Collected 2 test(s) from adder package
Running 2 test(s) from src/
[FAIL] adder::tests::another

Failure data:
    "Make this test fail"

[PASS] adder::tests::exploration (gas: ~1)
Tests: 1 passed, 1 failed, 0 skipped, 0 ignored, 0 filtered out

Failures:
    adder::tests::another

Instead of [PASS], the line adder::tests::another shows [FAIL]. A new section appears between the individual results and the summary. It displays the detailed reason for each test failure. In this case, we get the details that another failed because it panicked with "Make this test fail" error.

After that, the summary line is displayed: we had one test pass and one test fail. At the end, we see a list of the failing tests.

Now that you've seen what the test results look like in different scenarios, let’s look at some functions that are useful in tests.

Checking Results with the assert! Macro

The assert! macro, provided by Cairo, is useful when you want to ensure that some condition in a test evaluates to true. We give the assert! macro the first argument that evaluates to a boolean. If the value is true, nothing happens and the test passes. If the value is false, the assert! macro calls panic() to cause the test to fail with a message we defined as the second argument. Using the assert! macro helps us check that our code is functioning in the way we intended.

Remember in Chapter 5, we used a Rectangle struct and a can_hold method, which are repeated here in Listing 10-3. Let’s put this code in the src/lib.cairo file, then write some tests for it using the assert! macro.

Filename: src/lib.cairo

#[derive(Drop)]
struct Rectangle {
    width: u64,
    height: u64,
}

trait RectangleTrait {
    fn can_hold(self: @Rectangle, other: @Rectangle) -> bool;
}

impl RectangleImpl of RectangleTrait {
    fn can_hold(self: @Rectangle, other: @Rectangle) -> bool {
        *self.width > *other.width && *self.height > *other.height
    }
}

Listing 10-3: Using the Rectangle struct and its can_hold method from Chapter 5

The can_hold method returns a bool, which means it’s a perfect use case for the assert! macro. We can write a test that exercises the can_hold method by creating a Rectangle instance that has a width of 8 and a height of 7 and asserting that it can hold another Rectangle instance that has a width of 5 and a height of 1.

#[derive(Drop)]
struct Rectangle {
    width: u64,
    height: u64,
}

trait RectangleTrait {
    fn can_hold(self: @Rectangle, other: @Rectangle) -> bool;
}

impl RectangleImpl of RectangleTrait {
    fn can_hold(self: @Rectangle, other: @Rectangle) -> bool {
        *self.width > *other.width && *self.height > *other.height
    }
}

#[cfg(test)]
mod tests {
    use super::*;

    #[test]
    fn larger_can_hold_smaller() {
        let larger = Rectangle { height: 7, width: 8 };
        let smaller = Rectangle { height: 1, width: 5 };

        assert!(larger.can_hold(@smaller), "rectangle cannot hold");
    }
}
#[cfg(test)]
mod tests2 {
    use super::*;

    #[test]
    fn smaller_cannot_hold_larger() {
        let larger = Rectangle { height: 7, width: 8 };
        let smaller = Rectangle { height: 1, width: 5 };

        assert!(!smaller.can_hold(@larger), "rectangle cannot hold");
    }
}

Note the use super::*; line inside the tests module. The tests module is a regular module that follows the usual visibility rules we covered in Chapter 7 in the “Paths for Referring to an Item in the Module Tree” section. Because the tests module is an inner module, we need to bring the code under test in the outer module into the scope of the inner module. We use a glob here, so anything we define in the outer module is available to this tests module.

We’ve named our test larger_can_hold_smaller, and we’ve created the two Rectangle instances that we need. Then we called the assert! macro and passed it the result of calling larger.can_hold(@smaller). This expression is supposed to return true, so our test should pass. Let’s find out!

$ scarb test 
     Running test listing_10_03 (snforge test)
   Compiling snforge_scarb_plugin v0.31.0 (git+https://github.com/foundry-rs/starknet-foundry.git?tag=v0.31.0#72ea785ca354e9e506de3e5d687da9fb2c1b3c67)
    Finished `release` profile [optimized] target(s) in 1.04s
   Compiling test(listings/ch10-testing-cairo-programs/listing_10_03/Scarb.toml)
    Finished `dev` profile target(s) in 5 seconds


Collected 2 test(s) from listing_10_03 package
Running 2 test(s) from src/
[PASS] listing_10_03::tests::larger_can_hold_smaller (gas: ~1)
[PASS] listing_10_03::tests2::smaller_cannot_hold_larger (gas: ~1)
Tests: 2 passed, 0 failed, 0 skipped, 0 ignored, 0 filtered out

¡Pasó la prueba! Ahora agreguemos otra prueba, esta vez afirmamos que un rectángulo más pequeño no puede contener un rectángulo más grande:

Filename: src/lib.cairo

#[derive(Drop)]
struct Rectangle {
    width: u64,
    height: u64,
}

trait RectangleTrait {
    fn can_hold(self: @Rectangle, other: @Rectangle) -> bool;
}

impl RectangleImpl of RectangleTrait {
    fn can_hold(self: @Rectangle, other: @Rectangle) -> bool {
        *self.width > *other.width && *self.height > *other.height
    }
}

#[cfg(test)]
mod tests {
    use super::*;

    #[test]
    fn larger_can_hold_smaller() {
        let larger = Rectangle { height: 7, width: 8 };
        let smaller = Rectangle { height: 1, width: 5 };

        assert!(larger.can_hold(@smaller), "rectangle cannot hold");
    }
}
#[cfg(test)]
mod tests2 {
    use super::*;

    #[test]
    fn smaller_cannot_hold_larger() {
        let larger = Rectangle { height: 7, width: 8 };
        let smaller = Rectangle { height: 1, width: 5 };

        assert!(!smaller.can_hold(@larger), "rectangle cannot hold");
    }
}

Listing 10-4: Adding another test in lib.cairo that will pass

Because the correct result of the can_hold method, in this case, is false, we need to negate that result before we pass it to the assert! macro. As a result, our test will pass if can_hold returns false:

$ scarb test 
     Running test listing_10_03 (snforge test)
   Compiling snforge_scarb_plugin v0.31.0 (git+https://github.com/foundry-rs/starknet-foundry.git?tag=v0.31.0#72ea785ca354e9e506de3e5d687da9fb2c1b3c67)
    Finished `release` profile [optimized] target(s) in 1.04s
   Compiling test(listings/ch10-testing-cairo-programs/listing_10_03/Scarb.toml)
    Finished `dev` profile target(s) in 5 seconds


Collected 2 test(s) from listing_10_03 package
Running 2 test(s) from src/
[PASS] listing_10_03::tests::larger_can_hold_smaller (gas: ~1)
[PASS] listing_10_03::tests2::smaller_cannot_hold_larger (gas: ~1)
Tests: 2 passed, 0 failed, 0 skipped, 0 ignored, 0 filtered out

Two tests that pass! Now let’s see what happens to our test results when we introduce a bug in our code. We’ll change the implementation of the can_hold method by replacing the > sign with a < sign when it compares the widths:

impl RectangleImpl of RectangleTrait {
    fn can_hold(self: @Rectangle, other: @Rectangle) -> bool {
        *self.width < *other.width && *self.height > *other.height
    }
}

Ejecutando los test ahora produce lo siguiente:

$ scarb test 
     Running test no_listing_01_wrong_can_hold_impl (snforge test)
   Compiling snforge_scarb_plugin v0.31.0 (git+https://github.com/foundry-rs/starknet-foundry.git?tag=v0.31.0#72ea785ca354e9e506de3e5d687da9fb2c1b3c67)
    Blocking waiting for file lock on build directory
    Finished `release` profile [optimized] target(s) in 1.11s
   Compiling test(listings/ch10-testing-cairo-programs/no_listing_01_wrong_can_hold_impl/Scarb.toml)
    Finished `dev` profile target(s) in 6 seconds


Collected 0 test(s) from no_listing_01_wrong_can_hold_impl package
Running 0 test(s) from src/
Tests: 0 passed, 0 failed, 0 skipped, 0 ignored, 0 filtered out

Our tests caught the bug! Because larger.width is 8 and smaller.width is 5, the comparison of the widths in can_hold now returns false (8 is not less than 5) in the larger_can_hold_smaller test. Notice that the smaller_cannot_hold_larger test still passes: to make this test fail, the height comparison should also be modified in can_hold method, replacing the > sign with a < sign.

Testing Equality and Comparisons with the assert_xx! Macros

assert_eq! and assert_ne! Macros

A common way to verify functionality is to test for equality between the result of the code under test and the value you expect the code to return. You could do this using the assert! macro and passing it an expression using the == operator. However, this is such a common test that the standard library provides a pair of macros — assert_eq! and assert_ne! — to perform this test more conveniently. These macros compare two arguments for equality or inequality, respectively. They’ll also print the two values if the assertion fails, which makes it easier to see why the test failed; conversely, the assert! macro only indicates that it got a false value for the == expression, without printing the values that led to the false value.

In Listing 10-5, we write a function named add_two that adds 2 to its parameter, then we test this function using assert_eq! and assert_ne! macros.

Filename: src/lib.cairo

pub fn add_two(a: u32) -> u32 {
    a + 2
}

#[cfg(test)]
mod tests {
    use super::*;

    #[test]
    fn it_adds_two() {
        assert_eq!(4, add_two(2));
    }

    #[test]
    fn wrong_check() {
        assert_ne!(0, add_two(2));
    }
}

Listing 10-5: Testing the function add_two using assert_eq! and assert_ne! macros

Let’s check that it passes!

$ scarb test 
     Running test listing_10_04 (snforge test)
   Compiling snforge_scarb_plugin v0.31.0 (git+https://github.com/foundry-rs/starknet-foundry.git?tag=v0.31.0#72ea785ca354e9e506de3e5d687da9fb2c1b3c67)
    Blocking waiting for file lock on build directory
    Finished `release` profile [optimized] target(s) in 1.00s
   Compiling test(listings/ch10-testing-cairo-programs/listing_10_04/Scarb.toml)
    Finished `dev` profile target(s) in 5 seconds


Collected 2 test(s) from listing_10_04 package
Running 2 test(s) from src/
[PASS] listing_10_04::add_two::tests::it_adds_two (gas: ~1)
[PASS] listing_10_04::add_two::tests::wrong_check (gas: ~1)
Tests: 2 passed, 0 failed, 0 skipped, 0 ignored, 0 filtered out

In the it_adds_two test, we pass 4 as argument to assert_eq! macro, which is equal to the result of calling add_two(2). The line for this test is [PASS] adder::tests::it_adds_two (gas: ~1).

In the wrong_check test, we pass 0 as argument to assert_ne! macro, which is not equal to the result of calling add_two(2). Tests that use the assert_ne! macro will pass if the two values we give it are not equal and fail if they’re equal. This macro is most useful for cases when we’re not sure what a value will be, but we know what the value definitely shouldn’t be. For example, if we’re testing a function that is guaranteed to change its input in some way, but how the input is changed depends on the day of the week that we run our tests, the best thing to assert might be that the output of the function is not equal to the input.

Let’s introduce a bug into our code to see what assert_eq! looks like when it fails. Change the implementation of the add_two function to instead add 3:

pub fn add_two(a: u32) -> u32 {
    a + 3
}

Run the tests again:

$ scarb test 
     Running test listing_10_04 (snforge test)
   Compiling snforge_scarb_plugin v0.31.0 (git+https://github.com/foundry-rs/starknet-foundry.git?tag=v0.31.0#72ea785ca354e9e506de3e5d687da9fb2c1b3c67)
    Blocking waiting for file lock on build directory
    Finished `release` profile [optimized] target(s) in 1.00s
   Compiling test(listings/ch10-testing-cairo-programs/listing_10_04/Scarb.toml)
    Finished `dev` profile target(s) in 5 seconds


Collected 2 test(s) from listing_10_04 package
Running 2 test(s) from src/
[PASS] listing_10_04::add_two::tests::it_adds_two (gas: ~1)
[PASS] listing_10_04::add_two::tests::wrong_check (gas: ~1)
Tests: 2 passed, 0 failed, 0 skipped, 0 ignored, 0 filtered out

Our test caught the bug! The it_adds_two test failed with the following message: "assertion `4 == add_two(2)` failed. It tells us that the assertion that failed was "assertion `left == right` failed and the left and right values are printed on the next lines as left: left_value and right: right_value. This helps us start debugging: the left argument was 4 but the right argument, where we had add_two(2), was 5. You can imagine that this would be especially helpful when we have a lot of tests going on.

Note that in some languages and test frameworks, the parameters for equality assertion functions are called expected and actual, and the order in which we specify the arguments matters. However, in Cairo, they’re called left and right, and the order in which we specify the value we expect and the value the code produces doesn’t matter. We could write the assertion in this test as assert_eq!(add_two(2), 4), which would result in the same failure message that displays assertion failed: `(left == right)`.

Here is a simple example comparing two structs, showing how to use assert_eq! and assert_ne! macros:

#[derive(Drop, Debug, PartialEq)]
struct MyStruct {
    var1: u8,
    var2: u8,
}

#[cfg(test)]
#[test]
fn test_struct_equality() {
    let first = MyStruct { var1: 1, var2: 2 };
    let second = MyStruct { var1: 1, var2: 2 };
    let third = MyStruct { var1: 1, var2: 3 };

    assert_eq!(first, second);
    assert_eq!(first, second, "{:?},{:?} should be equal", first, second);
    assert_ne!(first, third);
    assert_ne!(first, third, "{:?},{:?} should not be equal", first, third);
}

Under the surface, assert_eq! and assert_ne! macros use the operators == and !=, respectively. They both take snapshots of values as arguments. When the assertions fail, these macros print their arguments using debug formatting ({:?} syntax), which means the values being compared must implement PartialEq and Debug traits. All primitive types and most of the core library types implement these traits. For structs and enums that you define yourself, you’ll need to implement PartialEq to assert equality of those types. You’ll also need to implement Debug to print the values when the assertion fails. Because both traits are derivable, this is usually as straightforward as adding the #[derive(Drop, Debug, PartialEq)] annotation to your struct or enum definition. See Appendix C for more details about these and other derivable traits.

assert_lt!, assert_le!, assert_gt! and assert_ge! Macros

Comparisons in tests can be done using the assert_xx! macros:

• assert_lt! checks if a given value is lower than another value, and reverts otherwise.
• assert_le! checks if a given value is lower or equal than another value, and reverts otherwise.
• assert_gt! checks if a given value is greater than another value, and reverts otherwise.
• assert_ge! checks if a given value is greater or equal than another value, and reverts otherwise.

Listing 10-6 demonstrates how to use these macros:

#[derive(Drop, Copy, Debug, PartialEq)]
struct Dice {
    number: u8,
}

impl DicePartialOrd of PartialOrd<Dice> {
    fn lt(lhs: Dice, rhs: Dice) -> bool {
        lhs.number < rhs.number
    }

    fn le(lhs: Dice, rhs: Dice) -> bool {
        lhs.number <= rhs.number
    }

    fn gt(lhs: Dice, rhs: Dice) -> bool {
        lhs.number > rhs.number
    }

    fn ge(lhs: Dice, rhs: Dice) -> bool {
        lhs.number >= rhs.number
    }
}

#[cfg(test)]
#[test]
fn test_struct_equality() {
    let first_throw = Dice { number: 5 };
    let second_throw = Dice { number: 2 };
    let third_throw = Dice { number: 6 };
    let fourth_throw = Dice { number: 5 };

    assert_gt!(first_throw, second_throw);
    assert_ge!(first_throw, fourth_throw);
    assert_lt!(second_throw, third_throw);
    assert_le!(
        first_throw, fourth_throw, "{:?},{:?} should be lower or equal", first_throw, fourth_throw,
    );
}

Listing 10-6: Example of tests that use the assert_xx! macros for comparisons

In this example, we roll a Dice struct multiple times and compare the results. We need to manually implement the PartialOrd trait for our struct so that we can compare Dice instances with lt, le, gt and ge functions, which are used by assert_lt!, assert_le!, assert_gt! and assert_ge! macros, respectively. We also need to derive the Copy trait on our Dice struct to use the instantiated structs multiple times, as the comparison functions take ownership of the variables.

Adding Custom Failure Messages

You can also add a custom message to be printed with the failure message as optional arguments to assert!, assert_eq!, and assert_ne! macros. Any arguments specified after the required arguments are passed along to the format! macro (discussed in the Printing chapter), so you can pass a format string that contains {} placeholders and values to go in those placeholders. Custom messages are useful for documenting what an assertion means; when a test fails, you’ll have a better idea of what the problem is with the code.

Let’s add a custom failure message composed of a format string with a placeholder filled in with the actual value we got from the previous add_two function:

    #[test]
    fn it_adds_two() {
        assert_eq!(4, add_two(2), "Expected {}, got add_two(2)={}", 4, add_two(2));
    }

Now when we run the test, we’ll get a more informative error message:

$ scarb test 
     Running test no_listing_02_custom_messages (snforge test)
   Compiling snforge_scarb_plugin v0.31.0 (git+https://github.com/foundry-rs/starknet-foundry.git?tag=v0.31.0#72ea785ca354e9e506de3e5d687da9fb2c1b3c67)
    Blocking waiting for file lock on build directory
    Finished `release` profile [optimized] target(s) in 0.39s
   Compiling test(listings/ch10-testing-cairo-programs/no_listing_02_custom_messages/Scarb.toml)
    Finished `dev` profile target(s) in 4 seconds


Collected 1 test(s) from no_listing_02_custom_messages package
Running 1 test(s) from src/
[FAIL] no_listing_02_custom_messages::tests::it_adds_two

Failure data:
    "assertion `4 == add_two(2)` failed: Expected 4, got add_two(2)=5
    4: 4
    add_two(2): 5"

Tests: 0 passed, 1 failed, 0 skipped, 0 ignored, 0 filtered out

Failures:
    no_listing_02_custom_messages::tests::it_adds_two

We can see the value we actually got in the test output, which would help us debug what happened instead of what we were expecting to happen.

Checking for panics with should_panic

In addition to checking return values, it’s important to check that our code handles error conditions as we expect. For example, consider the Guess type in Listing 10-7:

Filename: src/lib.cairo

#[derive(Drop)]
struct Guess {
    value: u64,
}

pub trait GuessTrait {
    fn new(value: u64) -> Guess;
}

impl GuessImpl of GuessTrait {
    fn new(value: u64) -> Guess {
        if value < 1 || value > 100 {
            panic!("Guess must be >= 1 and <= 100");
        }

        Guess { value }
    }
}

Listing 10-7: Guess struct and its new method

Other code that uses Guess depends on the guarantee that Guess instances will contain only values between 1 and 100. We can write a test that ensures that attempting to create a Guess instance with a value outside that range panics.

Lo hacemos agregando el atributo should_panic a nuestra función de prueba. La prueba pasa si el código dentro de la función entra en pánico; la prueba falla si el código dentro de la función no entra en pánico.

#[cfg(test)]
mod tests {
    use super::*;

    #[test]
    #[should_panic]
    fn greater_than_100() {
        GuessTrait::new(200);
    }
}

We place the #[should_panic] attribute after the #[test] attribute and before the test function it applies to. Let’s look at the result to see that this test passes:

$ scarb test 
     Running test listing_09_08 (snforge test)
   Compiling snforge_scarb_plugin v0.31.0 (git+https://github.com/foundry-rs/starknet-foundry.git?tag=v0.31.0#72ea785ca354e9e506de3e5d687da9fb2c1b3c67)
    Blocking waiting for file lock on build directory
    Finished `release` profile [optimized] target(s) in 0.21s
   Compiling test(listings/ch10-testing-cairo-programs/listing_10_05/Scarb.toml)
    Finished `dev` profile target(s) in 4 seconds


Collected 1 test(s) from listing_09_08 package
Running 1 test(s) from src/
[PASS] listing_09_08::tests::greater_than_100 (gas: ~1)

Success data:
    "Guess must be >= 1 and <= 100"

Tests: 1 passed, 0 failed, 0 skipped, 0 ignored, 0 filtered out

Looks good! Now let’s introduce a bug in our code by removing the condition that the new function will panic if the value is greater than 100:

#[derive(Drop)]
struct Guess {
    value: u64,
}

trait GuessTrait {
    fn new(value: u64) -> Guess;
}

impl GuessImpl of GuessTrait {
    fn new(value: u64) -> Guess {
        if value < 1 {
            panic!("Guess must be >= 1 and <= 100");
        }

        Guess { value }
    }
}

When we run the test, it will fail:

$ scarb test 
     Running test no_listing_03_wrong_new_impl (snforge test)
   Compiling snforge_scarb_plugin v0.31.0 (git+https://github.com/foundry-rs/starknet-foundry.git?tag=v0.31.0#72ea785ca354e9e506de3e5d687da9fb2c1b3c67)
    Finished `release` profile [optimized] target(s) in 0.14s
   Compiling test(listings/ch10-testing-cairo-programs/no_listing_03_wrong_new_impl/Scarb.toml)
    Finished `dev` profile target(s) in 4 seconds


Collected 0 test(s) from no_listing_03_wrong_new_impl package
Running 0 test(s) from src/
Tests: 0 passed, 0 failed, 0 skipped, 0 ignored, 0 filtered out

We don’t get a very helpful message in this case, but when we look at the test function, we see that it’s annotated with #[should_panic] attribute. The failure we got means that the code in the test function did not cause a panic.

Tests that use should_panic can be imprecise. A should_panic test would pass even if the test panics for a different reason from the one we were expecting. To make should_panic tests more precise, we can add an optional expected parameter to the #[should_panic] attribute. The test harness will make sure that the failure message contains the provided text. For example, consider the modified code for GuessImpl in Listing 10-8 where the new function panics with different messages depending on whether the value is too small or too large:

Filename: src/lib.cairo

#[derive(Drop)]
struct Guess {
    value: u64,
}

trait GuessTrait {
    fn new(value: u64) -> Guess;
}

impl GuessImpl of GuessTrait {
    fn new(value: u64) -> Guess {
        if value < 1 {
            panic!("Guess must be >= 1");
        } else if value > 100 {
            panic!("Guess must be <= 100");
        }

        Guess { value }
    }
}

#[cfg(test)]
mod tests {
    use super::*;

    #[test]
    #[should_panic(expected: "Guess must be <= 100")]
    fn greater_than_100() {
        GuessTrait::new(200);
    }
}

Listing 10-8: new implementation that panics with different error messages

The test will pass because the value we put in the should_panic attribute’s expected parameter is the string that the Guess::new method panics with. We need to specify the entire panic message that we expect.

To see what happens when a should_panic test with an expected message fails, let’s again introduce a bug into our code by swapping the bodies of the if value < 1 and the else if value > 100 blocks:

impl GuessImpl of GuessTrait {
    fn new(value: u64) -> Guess {
        if value < 1 {
            panic!("Guess must be <= 100");
        } else if value > 100 {
            panic!("Guess must be >= 1");
        }

        Guess { value }
    }
}

#[cfg(test)]
mod tests {
    use super::*;

    #[test]
    #[should_panic(expected: "Guess must be <= 100")]
    fn greater_than_100() {
        GuessTrait::new(200);
    }
}

Esta vez, cuando ejecutamos la prueba should_panic, fallará:

$ scarb test 
     Running test no_listing_04_new_bug (snforge test)
   Compiling snforge_scarb_plugin v0.31.0 (git+https://github.com/foundry-rs/starknet-foundry.git?tag=v0.31.0#72ea785ca354e9e506de3e5d687da9fb2c1b3c67)
    Blocking waiting for file lock on build directory
    Finished `release` profile [optimized] target(s) in 1.01s
   Compiling test(listings/ch10-testing-cairo-programs/no_listing_04_new_bug/Scarb.toml)
    Finished `dev` profile target(s) in 6 seconds


Collected 1 test(s) from no_listing_04_new_bug package
Running 1 test(s) from src/
[FAIL] no_listing_04_new_bug::tests::greater_than_100

Failure data:
    Incorrect panic data
    Actual:    [0x46a6158a16a947e5916b2a2ca68501a45e93d7110e81aa2d6438b1c57c879a3, 0x0, 0x4775657373206d757374206265203e3d2031, 0x12] (Guess must be >= 1)
    Expected:  [0x46a6158a16a947e5916b2a2ca68501a45e93d7110e81aa2d6438b1c57c879a3, 0x0, 0x4775657373206d757374206265203c3d20313030, 0x14] (Guess must be <= 100)

Tests: 0 passed, 1 failed, 0 skipped, 0 ignored, 0 filtered out

Failures:
    no_listing_04_new_bug::tests::greater_than_100

El mensaje de fallo indica que este test realmente causó un pánico como esperábamos, pero el mensaje de pánico no incluyó la cadena esperada. El mensaje de pánico que obtuvimos en este caso fue Guess must be >= 1. ¡Ahora podemos comenzar a descubrir dónde está nuestro error!

Running Single Tests

Sometimes, running a full test suite can take a long time. If you’re working on code in a particular area, you might want to run only the tests pertaining to that code. You can choose which tests to run by passing scarb test the name of the test you want to run as an argument.

To demonstrate how to run a single test, we’ll first create two test functions, as shown in Listing 10-9, and choose which ones to run.

Filename: src/lib.cairo

#[cfg(test)]
mod tests {
    #[test]
    fn add_two_and_two() {
        let result = 2 + 2;
        assert_eq!(result, 4);
    }

    #[test]
    fn add_three_and_two() {
        let result = 3 + 2;
        assert!(result == 5, "result is not 5");
    }
}

Listing 10-9: Two tests with two different names

We can pass the name of any test function to scarb test to run only that test:

$ scarb test 
     Running test listing_10_07 (snforge test)
   Compiling snforge_scarb_plugin v0.31.0 (git+https://github.com/foundry-rs/starknet-foundry.git?tag=v0.31.0#72ea785ca354e9e506de3e5d687da9fb2c1b3c67)
    Blocking waiting for file lock on build directory
    Finished `release` profile [optimized] target(s) in 0.71s
   Compiling test(listings/ch10-testing-cairo-programs/listing_10_07/Scarb.toml)
    Finished `dev` profile target(s) in 6 seconds


Collected 2 test(s) from listing_10_07 package
Running 2 test(s) from src/
[PASS] listing_10_07::tests::add_two_and_two (gas: ~1)
[PASS] listing_10_07::tests::add_three_and_two (gas: ~1)
Tests: 2 passed, 0 failed, 0 skipped, 0 ignored, 0 filtered out

Only the test with the name add_two_and_two ran; the other test didn’t match that name. The test output lets us know we had one more test that didn’t run by displaying 1 filtered out; at the end.

También podemos especificar parte del nombre de una prueba y se ejecutarán todas las pruebas cuyo nombre contenga ese valor.

Ignoring Some Tests Unless Specifically Requested

Sometimes a few specific tests can be very time-consuming to execute, so you might want to exclude them during most runs of scarb test. Rather than listing as arguments all tests you do want to run, you can instead annotate the time-consuming tests using the #[ignore] attribute to exclude them, as shown here:

pub fn add(left: usize, right: usize) -> usize {
    left + right
}

#[cfg(test)]
mod tests {
    use super::*;

    #[test]
    fn it_works() {
        let result = add(2, 2);
        assert_eq!(result, 4);
    }

    #[test]
    #[ignore]
    fn expensive_test() { // code that takes an hour to run
    }
}

Después de #[test] agregamos la línea #[ignore] al test que queremos excluir. Ahora, cuando ejecutamos nuestros tests, it_works se ejecuta pero expensive_test no lo hace:

$ scarb test 
     Running test no_listing_05_ignore_tests (snforge test)
   Compiling snforge_scarb_plugin v0.31.0 (git+https://github.com/foundry-rs/starknet-foundry.git?tag=v0.31.0#72ea785ca354e9e506de3e5d687da9fb2c1b3c67)
    Blocking waiting for file lock on build directory
    Finished `release` profile [optimized] target(s) in 0.79s
   Compiling test(listings/ch10-testing-cairo-programs/no_listing_05_ignore_tests/Scarb.toml)
    Finished `dev` profile target(s) in 5 seconds


Collected 2 test(s) from no_listing_05_ignore_tests package
Running 2 test(s) from src/
[IGNORE] no_listing_05_ignore_tests::tests::expensive_test
[PASS] no_listing_05_ignore_tests::tests::it_works (gas: ~1)
Tests: 1 passed, 0 failed, 0 skipped, 1 ignored, 0 filtered out

La función expensive_test está listada como ignorada.

When you’re at a point where it makes sense to check the results of the ignored tests and you have time to wait for the results, you can run scarb test --include-ignored to run all tests, whether they’re ignored or not.

Testing Recursive Functions or Loops

When testing recursive functions or loops, the test is instantiated by default with a maximum amount of gas that it can consume. This prevents running infinite loops or consuming too much gas, and can help you benchmark the efficiency of your implementations. This value is assumed reasonably large enough, but you can override it by adding the #[available_gas(<Number>)] attribute to the test function. The following example shows how to use it:

fn sum_n(n: usize) -> usize {
    let mut i = 0;
    let mut sum = 0;
    while i <= n {
        sum += i;
        i += 1;
    };
    sum
}

#[cfg(test)]
mod tests {
    use super::*;

    #[test]
    #[available_gas(2000000)]
    fn test_sum_n() {
        let result = sum_n(10);
        assert!(result == 55, "result is not 55");
    }
}

Benchmarking Cairo Programs

Starknet Foundry contains a profiling feature that is useful to analyze and optimize the performance of your Cairo programs.

The profiling feature generates execution traces for successful tests, which are used to create profile outputs. This allows you to benchmark specific parts of your code.

To use the profiler, you will need to:

1. Install Cairo Profiler from Software Mansion.
2. Install Go, Graphviz and pprof, all of them are required to visualize the generated profile output.
3. Run snforge test --build-profile command, which generates a trace file for each passing test, stored in the snfoundry_trace directory of your project. This command also generates the corresponding output files in the profile directory.
4. Run go tool pprof -http=":8000" path/to/profile/output.pb.gz to analyse a profile. This will start a web server at the specified port.

Let's reuse the sum_n function studied above:

fn sum_n(n: usize) -> usize {
    let mut i = 0;
    let mut sum = 0;
    while i <= n {
        sum += i;
        i += 1;
    };
    sum
}

#[cfg(test)]
mod tests {
    use super::*;

    #[test]
    #[available_gas(2000000)]
    fn test_sum_n() {
        let result = sum_n(10);
        assert!(result == 55, "result is not 55");
    }
}

After generating the trace file and the profile output, running go tool pprof in your project will start the web server where you can find many useful information about the test that you ran:

• The test includes one function call, corresponding to the call to the test function. Calling sum_n multiple times in the test function will still return 1 call. This is because snforge simulates a contract call when executing a test.

• The sum_n function execution uses 256 Cairo steps:

Other information is also available such as memory holes (i.e., unused memory cells) or builtins usage. The Cairo Profiler is under active development, and many other features will be made available in the future.

Test Organization

We'll think about tests in terms of two main categories: unit tests and integration tests. Unit tests are small and more focused, testing one module in isolation at a time, and can test private functions. Integration tests use your code in the same way any other external code would, using only the public interface and potentially exercising multiple modules per test.

Escribir ambos tipos de pruebas es importante para asegurarse de que las piezas de su biblioteca estén haciendo lo que se espera de ellas, tanto separadas como juntas.

Unit Tests

El propósito de las pruebas unitarias es probar cada unidad de código en aislamiento del resto del código para identificar rápidamente dónde el código funciona y dónde no lo hace como se esperaba. Colocará las pruebas unitarias en el directorio src en cada archivo con el código que están probando.

The convention is to create a module named tests in each file to contain the test functions and to annotate the module with #[cfg(test)] attribute.

The Tests Module and #[cfg(test)]

The #[cfg(test)] annotation on the tests module tells Cairo to compile and run the test code only when you run scarb test, not when you run scarb build. This saves compile time when you only want to build the project and saves space in the resulting compiled artifact because the tests are not included. You’ll see that because integration tests go in a different directory, they don’t need the #[cfg(test)] annotation. However, because unit tests go in the same files as the code, you’ll use #[cfg(test)] to specify that they shouldn’t be included in the compiled result.

Recuerde que cuando creamos el nuevo proyecto adder en la primera sección de este capítulo, escribimos esta primera prueba:

pub fn add(left: usize, right: usize) -> usize {
    left + right
}

#[cfg(test)]
mod tests {
    use super::*;

    #[test]
    fn it_works() {
        let result = add(2, 2);
        assert_eq!(result, 4);
    }
}

The attribute cfg stands for configuration and tells Cairo that the following item should only be included given a certain configuration option. In this case, the configuration option is test, which is provided by Cairo for compiling and running tests. By using the cfg attribute, Cairo compiles our test code only if we actively run the tests with scarb test. This includes any helper functions that might be within this module, in addition to the functions annotated with #[test].

Testing Private Functions

There’s debate within the testing community about whether or not private functions should be tested directly, and other languages make it difficult or impossible to test private functions. Regardless of which testing ideology you adhere to, Cairo's privacy rules do allow you to test private functions. Consider the code below with the private function internal_adder.

Filename: src/lib.cairo

pub fn add(a: u32, b: u32) -> u32 {
    internal_adder(a, 2)
}

fn internal_adder(a: u32, b: u32) -> u32 {
    a + b
}

#[cfg(test)]
mod tests {
    use super::*;

    #[test]
    fn add() {
        assert_eq!(4, internal_adder(2, 2));
    }
}

Listing 10-10: Testing a private function

Note that the internal_adder function is not marked as pub. Tests are just Cairo code, and the tests module is just another module. As we discussed in the "Paths for Referring to an Item in the Module Tree" section, items in child modules can use the items in their ancestor modules. In this test, we bring the tests module’s parent internal_adder into scope with use super::internal_adder; and then the test can call internal_adder. If you don’t think private functions should be tested, there’s nothing in Cairo that will compel you to do so.

Integration Tests

Integration tests use your library in the same way any other code would. Their purpose is to test whether many parts of your library work together correctly. Units of code that work correctly on their own could have problems when integrated, so test coverage of the integrated code is important as well. To create integration tests, you first need a tests directory.

The tests Directory

We create a tests directory at the top level of our project directory, next to src. Scarb knows to look for integration test files in this directory. We can then make as many test files as we want, and Scarb will compile each of the files as an individual crate.

Let’s create an integration test. With the code in Listing 10-10 still in the src/lib.cairo file, make a tests directory, and create a new file named tests/integration_test.cairo. Your directory structure should look like this:

adder
├── Scarb.lock
├── Scarb.toml
├── src
│   └── lib.cairo
└── tests
    └── integration_tests.cairo

Enter the code in Listing 10-11 into the tests/integration_test.cairo file:

Filename: tests/integration_tests.cairo

use adder::add_two;

#[test]
fn it_adds_two() {
    assert_eq!(4, add_two(2));
}

Listing 10-11: An integration test of a function in the adder crate

Each file in the tests directory is a separate crate, so we need to bring our library into each test crate’s scope. For that reason we add use adder::add_two at the top of the code, which we didn’t need in the unit tests.

We don’t need to annotate any code in tests/integration_test.cairo with #[cfg(test)]. Scarb treats the tests directory specially and compiles files in this directory only when we run scarb test. Run scarb test now:

$ scarb test 
     Running test adder (snforge test)
   Compiling snforge_scarb_plugin v0.31.0 (git+https://github.com/foundry-rs/starknet-foundry.git?tag=v0.31.0#72ea785ca354e9e506de3e5d687da9fb2c1b3c67)
    Blocking waiting for file lock on build directory
    Finished `release` profile [optimized] target(s) in 0.88s
   Compiling test(listings/ch10-testing-cairo-programs/no_listing_09_integration_test/Scarb.toml)
   Compiling test(listings/ch10-testing-cairo-programs/no_listing_09_integration_test/Scarb.toml)
    Finished `dev` profile target(s) in 9 seconds


Collected 2 test(s) from adder package
Running 1 test(s) from tests/
[PASS] adder_integrationtest::integration_tests::it_adds_two (gas: ~1)
Running 1 test(s) from src/
[PASS] adder::tests::internal (gas: ~1)
Tests: 2 passed, 0 failed, 0 skipped, 0 ignored, 0 filtered out

The two sections of output include the unit tests and the integration tests. Note that if any test in a section fails, the following sections will not be run. For example, if a unit test fails, there won’t be any output for integration tests because those tests will only be run if all unit tests are passing.

The first displayed section is for the integration tests. Each integration test file has its own section, so if we add more files in the tests directory, there will be more integration test sections.

The second displayed section is the same as we’ve been seeing: one line for each unit test (one named add that we added just above) and then a summary line for the unit tests.

We can still run a particular integration test function by specifying the test function’s name as an argument of the option -f to scarb test like for instance scarb test -f integration_tests::internal. To run all the tests in a particular integration test file, we use the same option of scarb test but using only the name of the file.

Then, to run all of our integration tests, we can just add a filter to only run tests whose path contains integration_tests.

$ scarb test -f integration_tests
     Running cairo-test adder
   Compiling test(adder_unittest) adder v0.1.0 (cairo-book/listings/ch10-testing-cairo-programs/no_listing_09_integration_test/Scarb.toml)
   Compiling test(adder_integration_tests) adder_integration_tests v0.1.0 (cairo-book/listings/ch10-testing-cairo-programs/no_listing_09_integration_test/Scarb.toml)
    Finished release target(s) in 7 seconds
testing adder ...
running 1 test
test adder_integration_tests::integration_tests::internal ... ok (gas usage est.: 23110)
test result: ok. 1 passed; 0 failed; 0 ignored; 0 filtered out;

running 0 tests
test result: ok. 0 passed; 0 failed; 0 ignored; 1 filtered out;

We see that in the second section for the unit tests, 1 has been filtered out because it is not in the integration_tests file.

Submodules in Integration Tests

As you add more integration tests, you might want to make more files in the tests directory to help organize them; for example, you can group the test functions by the functionality they’re testing. As mentioned earlier, each file in the tests directory is compiled as its own separate crate, which is useful for creating separate scopes to more closely imitate the way end users will be using your crate. However, this means files in the tests directory don’t share the same behavior as files in src do, as you learned in Chapter 7 regarding how to separate code into modules and files.

The different behavior of tests directory files is most noticeable when you have a set of helper functions to use in multiple integration test files and you try to follow the steps in the Separating Modules into Different Files section of Chapter 7 to extract them into a common module. For example, if we create tests/common.cairo and place a function named setup in it, we can add some code to setup that we want to call from multiple test functions in multiple test files:

Filename: tests/common.cairo

pub fn setup() {
    println!("Setting up tests...");
}

Filename: tests/integration_tests.cairo

use adder::it_adds_two;

#[test]
fn internal() {
    assert!(it_adds_two(2, 2) == 4, "internal_adder failed");
}

Filename: src/lib.cairo

pub fn it_adds_two(a: u8, b: u8) -> u8 {
    a + b
}

#[cfg(test)]
mod tests {
    #[test]
    fn add() {
        assert_eq!(4, super::it_adds_two(2, 2));
    }
}

When we run the tests with scarb test, we’ll see a new section in the test output for the common.cairo file, even though this file doesn’t contain any test functions nor did we call the setup function from anywhere:

$ scarb test 
     Running test adder (snforge test)
   Compiling snforge_scarb_plugin v0.31.0 (git+https://github.com/foundry-rs/starknet-foundry.git?tag=v0.31.0#72ea785ca354e9e506de3e5d687da9fb2c1b3c67)
    Finished `release` profile [optimized] target(s) in 0.64s
   Compiling test(listings/ch10-testing-cairo-programs/no_listing_12_submodules/Scarb.toml)
   Compiling test(listings/ch10-testing-cairo-programs/no_listing_12_submodules/Scarb.toml)
    Finished `dev` profile target(s) in 8 seconds


Collected 2 test(s) from adder package
Running 1 test(s) from src/
[PASS] adder::tests::add (gas: ~1)
Running 1 test(s) from tests/
[PASS] adder_integrationtest::integration_tests::internal (gas: ~1)
Tests: 2 passed, 0 failed, 0 skipped, 0 ignored, 0 filtered out

To avoid systematically getting a section for each file of the tests folder, we also have the option of making the tests/ directory behave like a regular crate, by adding a tests/lib.cairo file. In that case, the tests directory will no longer compile as one crate per file, but as one crate for the whole directory.

Let's create this tests/lib.cairo file :

Filename: tests/lib.cairo

mod integration_tests;
mod common;

The project directory will now look like this :

adder
├── Scarb.lock
├── Scarb.toml
├── src
│   └── lib.cairo
└── tests
    ├── common.cairo
    ├── integration_tests.cairo
    └── lib.cairo

When we run the scarb test command again, here is the output :

$ scarb test 
     Running test adder (snforge test)
   Compiling snforge_scarb_plugin v0.31.0 (git+https://github.com/foundry-rs/starknet-foundry.git?tag=v0.31.0#72ea785ca354e9e506de3e5d687da9fb2c1b3c67)
    Finished `release` profile [optimized] target(s) in 0.51s
   Compiling test(listings/ch10-testing-cairo-programs/no_listing_13_single_integration_crate/Scarb.toml)
   Compiling test(listings/ch10-testing-cairo-programs/no_listing_13_single_integration_crate/Scarb.toml)
    Finished `dev` profile target(s) in 7 seconds


Collected 2 test(s) from adder package
Running 1 test(s) from tests/
[PASS] adder_tests::integration_tests::internal (gas: ~1)
Running 1 test(s) from src/
[PASS] adder::tests::add (gas: ~1)
Tests: 2 passed, 0 failed, 0 skipped, 0 ignored, 0 filtered out

This way, only the test functions will be tested and the setup function can be imported without being tested.

Resumen

Cairo's testing features provide a way to specify how code should function to ensure it continues to work as you expect, even as you make changes. Unit tests exercise different parts of a library separately and can test private implementation details. Integration tests check that many parts of the library work together correctly, and they use the library’s public API to test the code in the same way external code will use it. Even though Cairo's type system and ownership rules help prevent some kinds of bugs, tests are still important to reduce logic bugs having to do with how your code is expected to behave.

Functional Language Features: Iterators and Closures

Cairo’s design has taken strong inspiration from Rust, which itself has taken inspiration from many existing languages and techniques, and one significant influence is functional programming. Programming in a functional style often includes using functions as values by passing them in arguments, returning them from other functions, assigning them to variables for later execution, and so forth.

In this chapter, we won’t debate the issue of what functional programming is or isn’t but will instead discuss some features of Cairo that are similar to features in Rust and many languages often referred to as functional.

More specifically, we’ll cover:

• Closures, a function-like construct you can store in a variable

• Iterators, a way of processing a series of elements<!-- * How to use closures and iterators to improve the I/O project in Chapter 12

  -->

We’ve already covered some other Cairo features, such as pattern matching and enums, that are also influenced by the Rust and the functional style. Because mastering closures and iterators is an important part of writing idiomatic, fast Cairo code, we’ll devote this entire chapter to them.

Closures

Closures are anonymous functions you can save in a variable or pass as arguments to other functions. You can create the closure in one place and then call the closure elsewhere to evaluate it in a different context. Unlike functions, closures can capture values from the scope in which they’re defined. We’ll demonstrate how these closure features allow for code reuse and behavior customization.

Note: Closures were introduced in Cairo 2.9 and are still under development. Some new features will be introduced in future versions of Cairo, so this page will evolve accordingly.

Understanding Closures

When writing Cairo programs, you'll often need to pass behavior as a parameter to another function. Closures provide a way to define this behavior inline, without creating a separate named function. They are particularly valuable when working with collections, error handling, and any scenario where you want to customize how a function behaves using a function as a parameter.

Consider a simple example where we want to process numbers differently based on some condition. Instead of writing multiple functions, we can use closures to define the behavior where we need it:

#[generate_trait]
impl ArrayExt of ArrayExtTrait {
    // Needed in Cairo 2.9.2 because of a bug in inlining analysis.
    #[inline(never)]
    fn map<T, +Drop<T>, F, +Drop<F>, impl func: core::ops::Fn<F, (T,)>, +Drop<func::Output>>(
        self: Array<T>, f: F,
    ) -> Array<func::Output> {
        let mut output: Array<func::Output> = array![];
        for elem in self {
            output.append(f(elem));
        };
        output
    }
}

#[generate_trait]
impl ArrayFilterExt of ArrayFilterExtTrait {
    // Needed in Cairo 2.9.2 because of a bug in inlining analysis.
    #[inline(never)]
    fn filter<
        T,
        +Copy<T>,
        +Drop<T>,
        F,
        +Drop<F>,
        impl func: core::ops::Fn<F, (T,)>[Output: bool],
        +Drop<func::Output>,
    >(
        self: Array<T>, f: F,
    ) -> Array<T> {
        let mut output: Array<T> = array![];
        for elem in self {
            if f(elem) {
                output.append(elem);
            }
        };
        output
    }
}

fn main() {
    let double = |value| value * 2;
    println!("Double of 2 is {}", double(2_u8));
    println!("Double of 4 is {}", double(4_u8));

    // This won't work because `value` type has been inferred as `u8`.
    //println!("Double of 6 is {}", double(6_u16));

    let sum = |x: u32, y: u32, z: u16| {
        x + y + z.into()
    };
    println!("Result: {}", sum(1, 2, 3));

    let x = 8;
    let my_closure = |value| {
        x * (value + 3)
    };

    println!("my_closure(1) = {}", my_closure(1));

    let double = array![1, 2, 3].map(|item: u32| item * 2);
    let another = array![1, 2, 3].map(|item: u32| {
        let x: u64 = item.into();
        x * x
    });

    println!("double: {:?}", double);
    println!("another: {:?}", another);

    let even = array![3, 4, 5, 6].filter(|item: u32| item % 2 == 0);
    println!("even: {:?}", even);
}

The closure's arguments go between the pipes (|). Note that we don't have to specify the types of arguments and of the return value (see double closure), they will be inferred from the closure usage, as it is done for any variables. Of course, if you use a closure with different types, you will get a Type annotations needed error, telling you that you have to choose and specify the closure argument types.

The body is an expression, on a single line without {} like double or on several lines with {} like sum.

Capturing the Environment with Closures

One of the interests of closures is that they can include bindings from their enclosing scope.

In the following example, my_closure use a binding to x to compute x + value * 3.

#[generate_trait]
impl ArrayExt of ArrayExtTrait {
    // Needed in Cairo 2.9.2 because of a bug in inlining analysis.
    #[inline(never)]
    fn map<T, +Drop<T>, F, +Drop<F>, impl func: core::ops::Fn<F, (T,)>, +Drop<func::Output>>(
        self: Array<T>, f: F,
    ) -> Array<func::Output> {
        let mut output: Array<func::Output> = array![];
        for elem in self {
            output.append(f(elem));
        };
        output
    }
}

#[generate_trait]
impl ArrayFilterExt of ArrayFilterExtTrait {
    // Needed in Cairo 2.9.2 because of a bug in inlining analysis.
    #[inline(never)]
    fn filter<
        T,
        +Copy<T>,
        +Drop<T>,
        F,
        +Drop<F>,
        impl func: core::ops::Fn<F, (T,)>[Output: bool],
        +Drop<func::Output>,
    >(
        self: Array<T>, f: F,
    ) -> Array<T> {
        let mut output: Array<T> = array![];
        for elem in self {
            if f(elem) {
                output.append(elem);
            }
        };
        output
    }
}

fn main() {
    let double = |value| value * 2;
    println!("Double of 2 is {}", double(2_u8));
    println!("Double of 4 is {}", double(4_u8));

    // This won't work because `value` type has been inferred as `u8`.
    //println!("Double of 6 is {}", double(6_u16));

    let sum = |x: u32, y: u32, z: u16| {
        x + y + z.into()
    };
    println!("Result: {}", sum(1, 2, 3));

    let x = 8;
    let my_closure = |value| {
        x * (value + 3)
    };

    println!("my_closure(1) = {}", my_closure(1));

    let double = array![1, 2, 3].map(|item: u32| item * 2);
    let another = array![1, 2, 3].map(|item: u32| {
        let x: u64 = item.into();
        x * x
    });

    println!("double: {:?}", double);
    println!("another: {:?}", another);

    let even = array![3, 4, 5, 6].filter(|item: u32| item % 2 == 0);
    println!("even: {:?}", even);
}

Note that, at the moment, closures are still not allowed to capture mutable variables, but this will be supported in future Cairo versions.

Closure Type Inference and Annotation

There are more differences between functions and closures. Closures don’t usually require you to annotate the types of the parameters or the return value like fn functions do. Type annotations are required on functions because the types are part of an explicit interface exposed to your users. Defining this interface rigidly is important for ensuring that everyone agrees on what types of values a function uses and returns. Closures, on the other hand, aren’t used in an exposed interface like this: they’re stored in variables and used without naming them and exposing them to users of our library.

Closures are typically short and relevant only within a narrow context rather than in any arbitrary scenario. Within these limited contexts, the compiler can infer the types of the parameters and the return type, similar to how it’s able to infer the types of most variables (there are rare cases where the compiler needs closure type annotations too).

As with variables, we can add type annotations if we want to increase explicitness and clarity at the cost of being more verbose than is strictly necessary. Annotating the types for a closure would look like the definition shown in Listing 11-1. In this example, we’re defining a closure and storing it in a variable rather than defining the closure in the spot we pass it as an argument as we did in Listing 13-1.

fn generate_workout(intensity: u32, random_number: u32) {
    let expensive_closure = |num: u32| -> u32 {
        num
    };

    if intensity < 25 {
        println!("Today, do {} pushups!", expensive_closure(intensity));
        println!("Next, do {} situps!", expensive_closure(intensity));
    } else {
        if random_number == 3 {
            println!("Take a break today! Remember to stay hydrated!");
        } else {
            println!("Today, run for {} minutes!", expensive_closure(intensity));
        }
    }
}

fn main() {
    let simulated_user_specified_value = 10;
    let simulated_random_number = 7;

    generate_workout(simulated_user_specified_value, simulated_random_number);
}

Listing 11-1: Adding optional type annotations of the parameter and return value types in the closure

With type annotations added, the syntax of closures looks more similar to the syntax of functions. Here we define a function that adds 1 to its parameter and a closure that has the same behavior, for comparison. We’ve added some spaces to line up the relevant parts. This illustrates how closure syntax is similar to function syntax except for the use of pipes and the amount of syntax that is optional:

fn  add_one_v1   (x: u32) -> u32 { x + 1 }
let add_one_v2 = |x: u32| -> u32 { x + 1 };
let add_one_v3 = |x|             { x + 1 };
let add_one_v4 = |x|               x + 1  ;

The first line shows a function definition, and the second line shows a fully annotated closure definition. In the third line, we remove the type annotations from the closure definition. In the fourth line, we remove the brackets, which are optional because the closure body has only one expression. These are all valid definitions that will produce the same behavior when they’re called. The add_one_v3 and add_one_v4 lines require the closures to be evaluated to be able to compile because the types will be inferred from their usage. This is similar to let array = array![]; needing either type annotations or values of some type to be inserted into the array for Cairo to be able to infer the type.

For closure definitions, the compiler will infer one concrete type for each of their parameters and for their return value. For instance, Listing 11-2 shows the definition of a short closure that just returns the value it receives as a parameter. This closure isn’t very useful except for the purposes of this example. Note that we haven’t added any type annotations to the definition. Because there are no type annotations, we can call the closure with any type, which we’ve done here with u64 the first time. If we then try to call example_closure with a u32, we’ll get an error.

//TAG: does_not_compile
fn main() {
    let example_closure = |x| x;

    let s = example_closure(5_u64);
    let n = example_closure(5_u32);
}

Listing 11-2: Attempting to call a closure whose types are inferred with two different types

The compiler gives us this error:

$ scarb build 
   Compiling listing_closure_different_types v0.1.0 (listings/ch11-functional-features/listing_closure_different_types/Scarb.toml)
warn[E0001]: Unused variable. Consider ignoring by prefixing with `_`.
 --> listings/ch11-functional-features/listing_closure_different_types/src/lib.cairo:6:9
    let s = example_closure(5_u64);
        ^

warn[E0001]: Unused variable. Consider ignoring by prefixing with `_`.
 --> listings/ch11-functional-features/listing_closure_different_types/src/lib.cairo:7:9
    let n = example_closure(5_u32);
        ^

error: Type annotations needed. Failed to infer ?7.
 --> listings/ch11-functional-features/listing_closure_different_types/src/lib.cairo:7:13
    let n = example_closure(5_u32);
            ^********************^

error: could not compile `listing_closure_different_types` due to previous error

The first time we call example_closure with the u64 value, the compiler infers the type of x and the return type of the closure to be u64. Those types are then locked into the closure in example_closure, and we get a type error when we next try to use a different type with the same closure.

Moving Captured Values Out of Closures and the Fn Traits

Once a closure has captured a reference or captured ownership of a value from the environment where the closure is defined (thus affecting what, if anything, is moved into the closure), the code in the body of the closure defines what happens to the references or values when the closure is evaluated later (thus affecting what, if anything, is moved out of the closure). A closure body can do any of the following: move a captured value out of the closure, neither move nor mutate the value, or capture nothing from the environment to begin with.

The way a closure captures and handles values from the environment affects which traits the closure implements, and traits are how functions and structs can specify what kinds of closures they can use. Closures will automatically implement one, two, or all three of these Fn traits, in an additive fashion, depending on how the closure’s body handles the values:

1. FnOnce applies to closures that can be called once. All closures implement at least this trait, because all closures can be called. A closure that moves captured values out of its body will only implement FnOnce and none of the other Fn traits, because it can only be called once.

2. Fn applies to closures that don’t move captured values out of their body and that don’t mutate captured values, as well as closures that capture nothing from their environment. These closures can be called more than once without mutating their environment, which is important in cases such as calling a closure multiple times concurrently.

Let’s look at the definition of the unwrap_or_else method on OptionTrait<T> that we used in Listing 13-1:

pub impl OptionTraitImpl<T> of OptionTrait<T> {
    #[inline]
    fn unwrap_or_else<F, +Drop<F>, impl func: core::ops::FnOnce<F, ()>[Output: T], +Drop<func::Output>>(
        self: Option<T>, f: F,
    ) -> T {
        match self {
            Option::Some(x) => x,
            Option::None => f(),
        }
    }
}

Recall that T is the generic type representing the type of the value in the Some variant of an Option. That type T is also the return type of the unwrap_or_else function: code that calls unwrap_or_else on an Option<ByteArray>, for example, will get a ByteArray.

Next, notice that the unwrap_or_else function has the additional generic type parameter F. The F type is the type of the parameter named f, which is the closure we provide when calling unwrap_or_else.

The trait bound specified on the generic type F is impl func: core::ops::FnOnce<F, ()>[Output: T], which means F must be able to be called once, take no arguments (the unit type () is used), and return a T as output. Using FnOnce in the trait bound expresses the constraint that unwrap_or_else is only going to call f at most one time. In the body of unwrap_or_else, we can see that if the Option is Some, f won’t be called. If the Option is None, f will be called once. Because all closures implement FnOnce, unwrap_or_else accepts all two kinds of closures and is as flexible as it can be.

The Fn traits are important when defining or using functions or types that make use of closures. In the next section, we’ll discuss iterators. Many iterator methods take closure arguments, so keep these closure details in mind as we continue!

Under the hood, closures are implemented through FnOnce and Fn traits. FnOnce is implemented for closures that may consume captured variables, where Fn is implemented for closures that capture only copyable variables.

Implementing Your Functional Programming Patterns with Closures

Another great interest of closures is that, like any type of variables, you can pass them as function arguments. This mechanism is massively used in functional programming, through classic functions like map, filter or reduce.

Here is a potential implementation of map to apply a same function to all the items of an array:

#[generate_trait]
impl ArrayExt of ArrayExtTrait {
    // Needed in Cairo 2.9.2 because of a bug in inlining analysis.
    #[inline(never)]
    fn map<T, +Drop<T>, F, +Drop<F>, impl func: core::ops::Fn<F, (T,)>, +Drop<func::Output>>(
        self: Array<T>, f: F,
    ) -> Array<func::Output> {
        let mut output: Array<func::Output> = array![];
        for elem in self {
            output.append(f(elem));
        };
        output
    }
}

#[generate_trait]
impl ArrayFilterExt of ArrayFilterExtTrait {
    // Needed in Cairo 2.9.2 because of a bug in inlining analysis.
    #[inline(never)]
    fn filter<
        T,
        +Copy<T>,
        +Drop<T>,
        F,
        +Drop<F>,
        impl func: core::ops::Fn<F, (T,)>[Output: bool],
        +Drop<func::Output>,
    >(
        self: Array<T>, f: F,
    ) -> Array<T> {
        let mut output: Array<T> = array![];
        for elem in self {
            if f(elem) {
                output.append(elem);
            }
        };
        output
    }
}

fn main() {
    let double = |value| value * 2;
    println!("Double of 2 is {}", double(2_u8));
    println!("Double of 4 is {}", double(4_u8));

    // This won't work because `value` type has been inferred as `u8`.
    //println!("Double of 6 is {}", double(6_u16));

    let sum = |x: u32, y: u32, z: u16| {
        x + y + z.into()
    };
    println!("Result: {}", sum(1, 2, 3));

    let x = 8;
    let my_closure = |value| {
        x * (value + 3)
    };

    println!("my_closure(1) = {}", my_closure(1));

    let double = array![1, 2, 3].map(|item: u32| item * 2);
    let another = array![1, 2, 3].map(|item: u32| {
        let x: u64 = item.into();
        x * x
    });

    println!("double: {:?}", double);
    println!("another: {:?}", another);

    let even = array![3, 4, 5, 6].filter(|item: u32| item % 2 == 0);
    println!("even: {:?}", even);
}

Note that, due to a bug in inlining analysis, this analysis process should be disabled using #[inline(never)].

In this implementation, you'll notice that, while T is the element type of the input array self, the element type of the output array is defined by the output type of the f closure (the associated type func::Output from the Fn trait).

This means that your f closure can return the same type of elements like as for _double in the following code, or any other type of elements like as for _another:

#[generate_trait]
impl ArrayExt of ArrayExtTrait {
    // Needed in Cairo 2.9.2 because of a bug in inlining analysis.
    #[inline(never)]
    fn map<T, +Drop<T>, F, +Drop<F>, impl func: core::ops::Fn<F, (T,)>, +Drop<func::Output>>(
        self: Array<T>, f: F,
    ) -> Array<func::Output> {
        let mut output: Array<func::Output> = array![];
        for elem in self {
            output.append(f(elem));
        };
        output
    }
}

#[generate_trait]
impl ArrayFilterExt of ArrayFilterExtTrait {
    // Needed in Cairo 2.9.2 because of a bug in inlining analysis.
    #[inline(never)]
    fn filter<
        T,
        +Copy<T>,
        +Drop<T>,
        F,
        +Drop<F>,
        impl func: core::ops::Fn<F, (T,)>[Output: bool],
        +Drop<func::Output>,
    >(
        self: Array<T>, f: F,
    ) -> Array<T> {
        let mut output: Array<T> = array![];
        for elem in self {
            if f(elem) {
                output.append(elem);
            }
        };
        output
    }
}

fn main() {
    let double = |value| value * 2;
    println!("Double of 2 is {}", double(2_u8));
    println!("Double of 4 is {}", double(4_u8));

    // This won't work because `value` type has been inferred as `u8`.
    //println!("Double of 6 is {}", double(6_u16));

    let sum = |x: u32, y: u32, z: u16| {
        x + y + z.into()
    };
    println!("Result: {}", sum(1, 2, 3));

    let x = 8;
    let my_closure = |value| {
        x * (value + 3)
    };

    println!("my_closure(1) = {}", my_closure(1));

    let double = array![1, 2, 3].map(|item: u32| item * 2);
    let another = array![1, 2, 3].map(|item: u32| {
        let x: u64 = item.into();
        x * x
    });

    println!("double: {:?}", double);
    println!("another: {:?}", another);

    let even = array![3, 4, 5, 6].filter(|item: u32| item % 2 == 0);
    println!("even: {:?}", even);
}

Currently, Cairo 2.9 provides an experimental feature allowing you to specify the associated type of trait, using experimental-features = ["associated_item_constraints"] in your Scarb.toml.

Let's say we want to implement the filter function for arrays, to filter out elements which do not match a criteria. This criteria will be provided through a closure which takes an element as input, and return true if the element has to be kept, false otherwise. That means, we need to specify that the closure must return a boolean.

#[generate_trait]
impl ArrayExt of ArrayExtTrait {
    // Needed in Cairo 2.9.2 because of a bug in inlining analysis.
    #[inline(never)]
    fn map<T, +Drop<T>, F, +Drop<F>, impl func: core::ops::Fn<F, (T,)>, +Drop<func::Output>>(
        self: Array<T>, f: F,
    ) -> Array<func::Output> {
        let mut output: Array<func::Output> = array![];
        for elem in self {
            output.append(f(elem));
        };
        output
    }
}

#[generate_trait]
impl ArrayFilterExt of ArrayFilterExtTrait {
    // Needed in Cairo 2.9.2 because of a bug in inlining analysis.
    #[inline(never)]
    fn filter<
        T,
        +Copy<T>,
        +Drop<T>,
        F,
        +Drop<F>,
        impl func: core::ops::Fn<F, (T,)>[Output: bool],
        +Drop<func::Output>,
    >(
        self: Array<T>, f: F,
    ) -> Array<T> {
        let mut output: Array<T> = array![];
        for elem in self {
            if f(elem) {
                output.append(elem);
            }
        };
        output
    }
}

fn main() {
    let double = |value| value * 2;
    println!("Double of 2 is {}", double(2_u8));
    println!("Double of 4 is {}", double(4_u8));

    // This won't work because `value` type has been inferred as `u8`.
    //println!("Double of 6 is {}", double(6_u16));

    let sum = |x: u32, y: u32, z: u16| {
        x + y + z.into()
    };
    println!("Result: {}", sum(1, 2, 3));

    let x = 8;
    let my_closure = |value| {
        x * (value + 3)
    };

    println!("my_closure(1) = {}", my_closure(1));

    let double = array![1, 2, 3].map(|item: u32| item * 2);
    let another = array![1, 2, 3].map(|item: u32| {
        let x: u64 = item.into();
        x * x
    });

    println!("double: {:?}", double);
    println!("another: {:?}", another);

    let even = array![3, 4, 5, 6].filter(|item: u32| item % 2 == 0);
    println!("even: {:?}", even);
}

#[generate_trait]
impl ArrayExt of ArrayExtTrait {
    // Needed in Cairo 2.9.2 because of a bug in inlining analysis.
    #[inline(never)]
    fn map<T, +Drop<T>, F, +Drop<F>, impl func: core::ops::Fn<F, (T,)>, +Drop<func::Output>>(
        self: Array<T>, f: F,
    ) -> Array<func::Output> {
        let mut output: Array<func::Output> = array![];
        for elem in self {
            output.append(f(elem));
        };
        output
    }
}

#[generate_trait]
impl ArrayFilterExt of ArrayFilterExtTrait {
    // Needed in Cairo 2.9.2 because of a bug in inlining analysis.
    #[inline(never)]
    fn filter<
        T,
        +Copy<T>,
        +Drop<T>,
        F,
        +Drop<F>,
        impl func: core::ops::Fn<F, (T,)>[Output: bool],
        +Drop<func::Output>,
    >(
        self: Array<T>, f: F,
    ) -> Array<T> {
        let mut output: Array<T> = array![];
        for elem in self {
            if f(elem) {
                output.append(elem);
            }
        };
        output
    }
}

fn main() {
    let double = |value| value * 2;
    println!("Double of 2 is {}", double(2_u8));
    println!("Double of 4 is {}", double(4_u8));

    // This won't work because `value` type has been inferred as `u8`.
    //println!("Double of 6 is {}", double(6_u16));

    let sum = |x: u32, y: u32, z: u16| {
        x + y + z.into()
    };
    println!("Result: {}", sum(1, 2, 3));

    let x = 8;
    let my_closure = |value| {
        x * (value + 3)
    };

    println!("my_closure(1) = {}", my_closure(1));

    let double = array![1, 2, 3].map(|item: u32| item * 2);
    let another = array![1, 2, 3].map(|item: u32| {
        let x: u64 = item.into();
        x * x
    });

    println!("double: {:?}", double);
    println!("another: {:?}", another);

    let even = array![3, 4, 5, 6].filter(|item: u32| item % 2 == 0);
    println!("even: {:?}", even);
}

Funciones Avanzadas

Now, let's learn about more advanced features offered by Cairo.

Estructura de Dato Personalizadas

Cuando empieces a programar en Cairo, probablemente querrás usar arrays (Array<T>) para almacenar colecciones de datos. Sin embargo, rápidamente te darás cuenta de que los arrays tienen una gran limitación - los datos almacenados en ellos son inmutables. Una vez que añades un valor a un array, no puedes modificarlo.

Esto puede resultar frustrante cuando se desea utilizar una estructura de datos mutable. Por ejemplo, digamos que estás haciendo un juego donde los jugadores tienen un nivel, y pueden subir de nivel. Podrías intentar almacenar el nivel de los jugadores en un array:

    let mut level_players = array![5, 1, 10];

Pero entonces te das cuenta de que no puedes aumentar el nivel en un índice específico una vez que está fijado. Si un jugador muere, no puedes eliminarlo de la matriz a menos que casualmente esté en la primera posición.

Fortunately, Cairo provides a handy built-in dictionary type called Felt252Dict<T> that allows us to simulate the behavior of mutable data structures. Let's first explore how to create a struct that contains, among others, a Felt252Dict<T>.

Note: Several concepts used in this chapter were already presented earlier in the book. We recommend checking out the following chapters if you need to revise them: Structs, Methods, Generic types, Traits.

Diccionarios como miembros del Struct

Definir diccionarios como miembros de struct es posible en Cairo, pero interactuar correctamente con ellos puede no ser del todo fluido. Intentemos implementar una user database personalizada que nos permita añadir usuarios y consultarlos. Necesitaremos definir un struct para representar el nuevo tipo y un trait para definir su funcionalidad:

struct UserDatabase<T> {
    users_updates: u64,
    balances: Felt252Dict<T>,
}

trait UserDatabaseTrait<T> {
    fn new() -> UserDatabase<T>;
    fn update_user<+Drop<T>>(ref self: UserDatabase<T>, name: felt252, balance: T);
    fn get_balance<+Copy<T>>(ref self: UserDatabase<T>, name: felt252) -> T;
}

Nuestro nuevo tipo UserDatabase<T> representa una base de datos de usuarios. Es genérico sobre los saldos de los usuarios, dando mayor flexibilidad a quien utilice nuestro tipo de datos. Sus dos miembros son:

• users_updates, the number of users updates in the dictionary.
• balances, una asignación de cada usuario a su balance.

La funcionalidad central de la base de datos está definida por UserDatabaseTrait. Donde se definen los siguientes métodos:

• new para crear fácilmente nuevos tipos de UserDatabase.
• update_user to update the balance of users in the database.
• get_balance para encontrar el saldo del usuario en la base de datos.

The only remaining step is to implement each of the methods in UserDatabaseTrait, but since we are working with Generic types we also need to correctly establish the requirements of T so it can be a valid Felt252Dict<T> value type:

1. T debería implementar el Copy<T> ya que es necesario para obtener valores de un Felt252Dict<T>.
2. Todos los tipos de valor de un diccionario implementan el Felt252DictValue<T>, nuestro tipo genérico debería hacerlo también.
3. To insert values, Felt252DictTrait<T> requires all value types to be droppable (implement the Drop<T> trait).

The implementation, with all restrictions in place, would be as follows:

impl UserDatabaseImpl<T, +Felt252DictValue<T>> of UserDatabaseTrait<T> {
    // Creates a database
    fn new() -> UserDatabase<T> {
        UserDatabase { users_updates: 0, balances: Default::default() }
    }

    // Get the user's balance
    fn get_balance<+Copy<T>>(ref self: UserDatabase<T>, name: felt252) -> T {
        self.balances.get(name)
    }

    // Add a user
    fn update_user<+Drop<T>>(ref self: UserDatabase<T>, name: felt252, balance: T) {
        self.balances.insert(name, balance);
        self.users_updates += 1;
    }
}

Our database implementation is almost complete, except for one thing: the compiler doesn't know how to make a UserDatabase<T> go out of scope, since it doesn't implement the Drop<T> trait, nor the Destruct<T> trait. Since it has a Felt252Dict<T> as a member, it cannot be dropped, so we are forced to implement the Destruct<T> trait manually (refer to the Ownership chapter for more information). Using #[derive(Destruct)] on top of the UserDatabase<T> definition won't work because of the use of Generic types in the struct definition. We need to code the Destruct<T> trait implementation by ourselves:

impl UserDatabaseDestruct<T, +Drop<T>, +Felt252DictValue<T>> of Destruct<UserDatabase<T>> {
    fn destruct(self: UserDatabase<T>) nopanic {
        self.balances.squash();
    }
}

Implementar Destruct<T> para UserDatabase fue nuestro último paso para conseguir una base de datos completamente funcional. Ahora podemos probarla:

use core::dict::Felt252Dict;

struct UserDatabase<T> {
    users_updates: u64,
    balances: Felt252Dict<T>,
}

trait UserDatabaseTrait<T> {
    fn new() -> UserDatabase<T>;
    fn update_user<+Drop<T>>(ref self: UserDatabase<T>, name: felt252, balance: T);
    fn get_balance<+Copy<T>>(ref self: UserDatabase<T>, name: felt252) -> T;
}

impl UserDatabaseImpl<T, +Felt252DictValue<T>> of UserDatabaseTrait<T> {
    // Creates a database
    fn new() -> UserDatabase<T> {
        UserDatabase { users_updates: 0, balances: Default::default() }
    }

    // Get the user's balance
    fn get_balance<+Copy<T>>(ref self: UserDatabase<T>, name: felt252) -> T {
        self.balances.get(name)
    }

    // Add a user
    fn update_user<+Drop<T>>(ref self: UserDatabase<T>, name: felt252, balance: T) {
        self.balances.insert(name, balance);
        self.users_updates += 1;
    }
}

impl UserDatabaseDestruct<T, +Drop<T>, +Felt252DictValue<T>> of Destruct<UserDatabase<T>> {
    fn destruct(self: UserDatabase<T>) nopanic {
        self.balances.squash();
    }
}

fn main() {
    let mut db = UserDatabaseTrait::<u64>::new();

    db.update_user('Alex', 100);
    db.update_user('Maria', 80);

    db.update_user('Alex', 40);
    db.update_user('Maria', 0);

    let alex_latest_balance = db.get_balance('Alex');
    let maria_latest_balance = db.get_balance('Maria');

    assert!(alex_latest_balance == 40, "Expected 40");
    assert!(maria_latest_balance == 0, "Expected 0");
}

Simulating a Dynamic Array with Dicts

En primer lugar, pensemos en cómo queremos que se comporte nuestro array dinámico mutable. ¿Qué operaciones debería soportar?

Deberia:

• Allow us to append items at the end.
• Let us access any item by index.
• Allow setting the value of an item at a specific index.
• Return the current length.

Podemos definir esta interfaz en Cairo como:

trait MemoryVecTrait<V, T> {
    fn new() -> V;
    fn get(ref self: V, index: usize) -> Option<T>;
    fn at(ref self: V, index: usize) -> T;
    fn push(ref self: V, value: T) -> ();
    fn set(ref self: V, index: usize, value: T);
    fn len(self: @V) -> usize;
}

This provides a blueprint for the implementation of our dynamic array. We named it MemoryVec as it is similar to the Vec<T> data structure in Rust.

Note: The core library of Cairo already includes a Vec<T> data structure, strictly used as a storage type in smart contracts. To differentiate our data structure from the core library's one, we named our implementation MemoryVec.

Implementing a Dynamic Array in Cairo

Para almacenar nuestros datos, utilizaremos un Felt252Dict<T> que asigna números de índice (felts) a valores. También almacenaremos un campo len separado para rastrear la longitud.

Este es el aspecto de nuestra estructura. Envolvemos el tipo T dentro del puntero Nullable para permitir el uso de cualquier tipo T en nuestra estructura de datos, como se explica en la sección Dictionaries:

use core::dict::Felt252Dict;
use core::nullable::NullableTrait;
use core::num::traits::WrappingAdd;

trait MemoryVecTrait<V, T> {
    fn new() -> V;
    fn get(ref self: V, index: usize) -> Option<T>;
    fn at(ref self: V, index: usize) -> T;
    fn push(ref self: V, value: T) -> ();
    fn set(ref self: V, index: usize, value: T);
    fn len(self: @V) -> usize;
}

struct MemoryVec<T> {
    data: Felt252Dict<Nullable<T>>,
    len: usize,
}

impl DestructMemoryVec<T, +Drop<T>> of Destruct<MemoryVec<T>> {
    fn destruct(self: MemoryVec<T>) nopanic {
        self.data.squash();
    }
}

impl MemoryVecImpl<T, +Drop<T>, +Copy<T>> of MemoryVecTrait<MemoryVec<T>, T> {
    fn new() -> MemoryVec<T> {
        MemoryVec { data: Default::default(), len: 0 }
    }

    fn get(ref self: MemoryVec<T>, index: usize) -> Option<T> {
        if index < self.len() {
            Option::Some(self.data.get(index.into()).deref())
        } else {
            Option::None
        }
    }

    fn at(ref self: MemoryVec<T>, index: usize) -> T {
        assert!(index < self.len(), "Index out of bounds");
        self.data.get(index.into()).deref()
    }

    fn push(ref self: MemoryVec<T>, value: T) -> () {
        self.data.insert(self.len.into(), NullableTrait::new(value));
        self.len.wrapping_add(1_usize);
    }
    fn set(ref self: MemoryVec<T>, index: usize, value: T) {
        assert!(index < self.len(), "Index out of bounds");
        self.data.insert(index.into(), NullableTrait::new(value));
    }
    fn len(self: @MemoryVec<T>) -> usize {
        *self.len
    }
}

Since we again have Felt252Dict<T> as a struct member, we need to implement the Destruct<T> trait to tell the compiler how to make MemoryVec<T> go out of scope.

use core::dict::Felt252Dict;
use core::nullable::NullableTrait;
use core::num::traits::WrappingAdd;

trait MemoryVecTrait<V, T> {
    fn new() -> V;
    fn get(ref self: V, index: usize) -> Option<T>;
    fn at(ref self: V, index: usize) -> T;
    fn push(ref self: V, value: T) -> ();
    fn set(ref self: V, index: usize, value: T);
    fn len(self: @V) -> usize;
}

struct MemoryVec<T> {
    data: Felt252Dict<Nullable<T>>,
    len: usize,
}

impl DestructMemoryVec<T, +Drop<T>> of Destruct<MemoryVec<T>> {
    fn destruct(self: MemoryVec<T>) nopanic {
        self.data.squash();
    }
}

impl MemoryVecImpl<T, +Drop<T>, +Copy<T>> of MemoryVecTrait<MemoryVec<T>, T> {
    fn new() -> MemoryVec<T> {
        MemoryVec { data: Default::default(), len: 0 }
    }

    fn get(ref self: MemoryVec<T>, index: usize) -> Option<T> {
        if index < self.len() {
            Option::Some(self.data.get(index.into()).deref())
        } else {
            Option::None
        }
    }

    fn at(ref self: MemoryVec<T>, index: usize) -> T {
        assert!(index < self.len(), "Index out of bounds");
        self.data.get(index.into()).deref()
    }

    fn push(ref self: MemoryVec<T>, value: T) -> () {
        self.data.insert(self.len.into(), NullableTrait::new(value));
        self.len.wrapping_add(1_usize);
    }
    fn set(ref self: MemoryVec<T>, index: usize, value: T) {
        assert!(index < self.len(), "Index out of bounds");
        self.data.insert(index.into(), NullableTrait::new(value));
    }
    fn len(self: @MemoryVec<T>) -> usize {
        *self.len
    }
}

La clave que hace que este vector sea mutable es que podemos insertar valores en el diccionario para establecer o actualizar valores en nuestra estructura de datos. Por ejemplo, para actualizar un valor en un índice específico, hacemos:

use core::dict::Felt252Dict;
use core::nullable::NullableTrait;
use core::num::traits::WrappingAdd;

trait MemoryVecTrait<V, T> {
    fn new() -> V;
    fn get(ref self: V, index: usize) -> Option<T>;
    fn at(ref self: V, index: usize) -> T;
    fn push(ref self: V, value: T) -> ();
    fn set(ref self: V, index: usize, value: T);
    fn len(self: @V) -> usize;
}

struct MemoryVec<T> {
    data: Felt252Dict<Nullable<T>>,
    len: usize,
}

impl DestructMemoryVec<T, +Drop<T>> of Destruct<MemoryVec<T>> {
    fn destruct(self: MemoryVec<T>) nopanic {
        self.data.squash();
    }
}

impl MemoryVecImpl<T, +Drop<T>, +Copy<T>> of MemoryVecTrait<MemoryVec<T>, T> {
    fn new() -> MemoryVec<T> {
        MemoryVec { data: Default::default(), len: 0 }
    }

    fn get(ref self: MemoryVec<T>, index: usize) -> Option<T> {
        if index < self.len() {
            Option::Some(self.data.get(index.into()).deref())
        } else {
            Option::None
        }
    }

    fn at(ref self: MemoryVec<T>, index: usize) -> T {
        assert!(index < self.len(), "Index out of bounds");
        self.data.get(index.into()).deref()
    }

    fn push(ref self: MemoryVec<T>, value: T) -> () {
        self.data.insert(self.len.into(), NullableTrait::new(value));
        self.len.wrapping_add(1_usize);
    }
    fn set(ref self: MemoryVec<T>, index: usize, value: T) {
        assert!(index < self.len(), "Index out of bounds");
        self.data.insert(index.into(), NullableTrait::new(value));
    }
    fn len(self: @MemoryVec<T>) -> usize {
        *self.len
    }
}

Esto sobrescribe el valor existente anteriormente en ese índice del diccionario.

Mientras que las arrays son inmutables, los diccionarios proporcionan la flexibilidad que necesitamos para las estructuras de datos modificables, como los vectores.

La implementación del resto de la interfaz es sencilla. La implementación de todos los métodos definidos en nuestra interfaz se puede hacer de la siguiente manera:

use core::dict::Felt252Dict;
use core::nullable::NullableTrait;
use core::num::traits::WrappingAdd;

trait MemoryVecTrait<V, T> {
    fn new() -> V;
    fn get(ref self: V, index: usize) -> Option<T>;
    fn at(ref self: V, index: usize) -> T;
    fn push(ref self: V, value: T) -> ();
    fn set(ref self: V, index: usize, value: T);
    fn len(self: @V) -> usize;
}

struct MemoryVec<T> {
    data: Felt252Dict<Nullable<T>>,
    len: usize,
}

impl DestructMemoryVec<T, +Drop<T>> of Destruct<MemoryVec<T>> {
    fn destruct(self: MemoryVec<T>) nopanic {
        self.data.squash();
    }
}

impl MemoryVecImpl<T, +Drop<T>, +Copy<T>> of MemoryVecTrait<MemoryVec<T>, T> {
    fn new() -> MemoryVec<T> {
        MemoryVec { data: Default::default(), len: 0 }
    }

    fn get(ref self: MemoryVec<T>, index: usize) -> Option<T> {
        if index < self.len() {
            Option::Some(self.data.get(index.into()).deref())
        } else {
            Option::None
        }
    }

    fn at(ref self: MemoryVec<T>, index: usize) -> T {
        assert!(index < self.len(), "Index out of bounds");
        self.data.get(index.into()).deref()
    }

    fn push(ref self: MemoryVec<T>, value: T) -> () {
        self.data.insert(self.len.into(), NullableTrait::new(value));
        self.len.wrapping_add(1_usize);
    }
    fn set(ref self: MemoryVec<T>, index: usize, value: T) {
        assert!(index < self.len(), "Index out of bounds");
        self.data.insert(index.into(), NullableTrait::new(value));
    }
    fn len(self: @MemoryVec<T>) -> usize {
        *self.len
    }
}

The full implementation of the MemoryVec structure can be found in the community-maintained library Alexandria.

Simulating a Stack with Dicts

A continuación veremos un segundo ejemplo y sus detalles de implementación: un Stack.

Un Stack es una colección LIFO (último en entrar, primero en salir). La inserción de un nuevo elemento y la eliminación de un elemento existente tiene lugar en el mismo extremo, representado como la parte superior de la pila.

Let us define what operations we need to create a stack:

• Push an item to the top of the stack.
• Pop an item from the top of the stack.
• Check si todavía hay elementos en la stack.

A partir de estas especificaciones podemos definir la siguiente interfaz:

trait StackTrait<S, T> {
    fn push(ref self: S, value: T);
    fn pop(ref self: S) -> Option<T>;
    fn is_empty(self: @S) -> bool;
}

Implementar un Stack Mutable en Cairo

Para crear una estructura de datos de stack en Cairo, podemos utilizar de nuevo un Felt252Dict<T> para almacenar los valores de la pila junto con un campo usize para llevar la cuenta de la longitud de la stack para iterar sobre ella.

La estructura Stack se define como:

struct NullableStack<T> {
    data: Felt252Dict<Nullable<T>>,
    len: usize,
}

A continuación, veamos cómo se implementan nuestras funciones principales push y pop.

use core::dict::Felt252Dict;
use core::nullable::{match_nullable, FromNullableResult, NullableTrait};

trait StackTrait<S, T> {
    fn push(ref self: S, value: T);
    fn pop(ref self: S) -> Option<T>;
    fn is_empty(self: @S) -> bool;
}

struct NullableStack<T> {
    data: Felt252Dict<Nullable<T>>,
    len: usize,
}

impl DestructNullableStack<T, +Drop<T>> of Destruct<NullableStack<T>> {
    fn destruct(self: NullableStack<T>) nopanic {
        self.data.squash();
    }
}


impl NullableStackImpl<T, +Drop<T>, +Copy<T>> of StackTrait<NullableStack<T>, T> {
    fn push(ref self: NullableStack<T>, value: T) {
        self.data.insert(self.len.into(), NullableTrait::new(value));
        self.len += 1;
    }

    fn pop(ref self: NullableStack<T>) -> Option<T> {
        if self.is_empty() {
            return Option::None;
        }
        self.len -= 1;
        Option::Some(self.data.get(self.len.into()).deref())
    }

    fn is_empty(self: @NullableStack<T>) -> bool {
        *self.len == 0
    }
}

The code uses the insert and get methods to access the values in the Felt252Dict<T>. To push an element to the top of the stack, the push function inserts the element in the dict at index len and increases the len field of the stack to keep track of the position of the stack top. To remove a value, the pop function decreases the value of len to update the position of the stack top and then retrieves the last value at position len.

The full implementation of the Stack, along with more data structures that you can use in your code, can be found in the community-maintained Alexandria library, in the "data_structures" crate.

Resumen

Well done! Now you have knowledge of arrays, dictionaries and even custom data structures. While Cairo's memory model is immutable and can make it difficult to implement mutable data structures, we can fortunately use the Felt252Dict<T> type to simulate mutable data structures. This allows us to implement a wide range of data structures that are useful for many applications, effectively hiding the complexity of the underlying memory model.

Smart Pointers

A pointer is a general concept for a variable that contains a memory address. This address refers to, or “points at,” some other data. While pointers are a powerful feature, they can also be a source of bugs and security vulnerabilities. For example, a pointer can reference an unassigned memory cell, which means that attempting to access the data at that address would cause the program to crash, making it unprovable. To prevent such issues, Cairo uses Smart Pointers.

Smart pointers are data structures that act like a pointer, but also have additional metadata and capabilities. The concept of smart pointers isn’t unique to Cairo: smart pointers originated in C++ and exist in other languages like Rust as well. In the specific case of Cairo, smart pointers ensure that memory is not addressed in an unsafe way that could cause a program to be unprovable, by providing a safe way to access memory through strict type checking and ownership rules.

Though we didn’t call them as such at the time, we’ve already encountered a few smart pointers in this book, including Felt252Dict<T> and Array<T> in Chapter 3. Both these types count as smart pointers because they own a memory segment and allow you to manipulate it. They also have metadata and extra capabilities or guarantees. Arrays keep track of their current length to ensure that existing elements are not overwritten, and that new elements are only appended to the end.

The Cairo VM memory is composed by multiple segments that can store data, each identified by a unique index. When you create an array, you allocate a new segment in the memory to store the future elements. The array itself is just a pointer to that segment where the elements are stored.

The Box<T> Type to Manipulate Pointers

The principal smart pointer type in Cairo is a box, denoted as Box<T>. Manually defining boxes allow you to store data in a specific memory segment of the Cairo VM called the boxed segment. This segment is dedicated to store all boxed values, and what remains in the execution segment is only a pointer to the boxed segment. Whenever you instantiate a new pointer variable of type Box<T>, you append the data of type T to the boxed segment.

Boxes have very little performance overhead, other than writing their inner values to the boxed segment. But they don’t have many extra capabilities either. You’ll use them most often in these situations:

• When you have a type whose size can’t be known at compile time and you want to use a value of that type in a context that requires an exact size
• When you have a large amount of data and you want to transfer ownership but ensure the data won’t be copied when you do so

We’ll demonstrate the first situation in the “Enabling Recursive Types with Boxes” section. In the second case, transferring ownership of a large amount of data can take a long time because the data is copied around in memory. To improve performance in this situation, we can store the large amount of data in the boxed segment using a box type. Then, only the small amount of pointer data is copied around in memory, while the data it references stays in one place on the boxed segment.

Using a Box<T> to Store Data in the Boxed Segment

Before we discuss the boxed segment storage use cases for Box<T>, we’ll cover the syntax and how to interact with values stored within a Box<T>.

Listing 12-1 shows how to use a box to store a value in the boxed segment:

fn main() {
    let b = BoxTrait::new(5_u128);
    println!("b = {}", b.unbox())
}

Listing 12-1: Storing a u128 value in the boxed segment using a box

We define the variable b to have the value of a Box that points to the value 5, which is stored in the boxed segment. This program will print b = 5; in this case, we can access the data in the box similar to how we would if this data was simply in the execution memory. Putting a single value in a box isn’t very useful, so you won’t use boxes by themselves in this way very often. Having values like a single u128 in the execution memory, where they’re stored by default, is more appropriate in the majority of situations. Let’s look at a case where boxes allow us to define types that we wouldn’t be allowed to if we didn’t have boxes.

Enabling Recursive Types with Boxes

A value of recursive type can have another value of the same type as part of itself. Recursive types pose an issue because at compile time because Cairo needs to know how much space a type takes up. However, the nesting of values of recursive types could theoretically continue infinitely, so Cairo can’t know how much space the value needs. Because boxes have a known size, we can enable recursive types by inserting a box in the recursive type definition.

As an example of a recursive type, let’s explore the implementation of a binary tree. The binary tree type we’ll define is straightforward except for the recursion; therefore, the concepts in the example we’ll work with will be useful any time you get into more complex situations involving recursive types.

A binary tree is a tree data structure in which each node has at most two children, which are referred to as the left child and the right child. The last element of a branch is a leaf, which is a node without children.

Listing 12-2 shows an attempt to implement a binary tree of u32 values. Note that this code won’t compile yet because the BinaryTree type doesn’t have a known size, which we’ll demonstrate.

#[derive(Copy, Drop)]
enum BinaryTree {
    Leaf: u32,
    Node: (u32, BinaryTree, BinaryTree),
}

fn main() {
    let leaf1 = BinaryTree::Leaf(1);
    let leaf2 = BinaryTree::Leaf(2);
    let leaf3 = BinaryTree::Leaf(3);
    let node = BinaryTree::Node((4, leaf2, leaf3));
    let _root = BinaryTree::Node((5, leaf1, node));
}

Listing 12-2: The first attempt at implementing a binary tree of u32 values

Note: We’re implementing a binary tree that holds only u32 values for the purposes of this example. We could have implemented it using generics, as we discussed in Chapter 8, to define a binary tree that could store values of any type.

The root node contains 5 and two child nodes. The left child is a leaf containing 1. The right child is another node containing 4, which in turn has two leaf children: one containing 2 and another containing 3. This structure forms a simple binary tree with a depth of 2.

If we try to compile the code in listing 12-2, we get the following error:

$ scarb build 
   Compiling listing_recursive_types_wrong v0.1.0 (listings/ch12-advanced-features/listing_recursive_types_wrong/Scarb.toml)
error: Recursive type "(core::integer::u32, listing_recursive_types_wrong::BinaryTree, listing_recursive_types_wrong::BinaryTree)" has infinite size.
 --> listings/ch12-advanced-features/listing_recursive_types_wrong/src/lib.cairo:6:5
    Node: (u32, BinaryTree, BinaryTree),
    ^*********************************^

error: Recursive type "listing_recursive_types_wrong::BinaryTree" has infinite size.
 --> listings/ch12-advanced-features/listing_recursive_types_wrong/src/lib.cairo:10:17
    let leaf1 = BinaryTree::Leaf(1);
                ^*****************^

error: Recursive type "(core::integer::u32, listing_recursive_types_wrong::BinaryTree, listing_recursive_types_wrong::BinaryTree)" has infinite size.
 --> listings/ch12-advanced-features/listing_recursive_types_wrong/src/lib.cairo:13:33
    let node = BinaryTree::Node((4, leaf2, leaf3));
                                ^***************^

error: could not compile `listing_recursive_types_wrong` due to previous error

The error shows this type “has infinite size.” The reason is that we’ve defined BinaryTree with a variant that is recursive: it holds another value of itself directly. As a result, Cairo can’t figure out how much space it needs to store a BinaryTree value.

Hopefully, we can fix this error by using a Box<T> to store the recursive variant of BinaryTree. Because a Box<T> is a pointer, Cairo always knows how much space a Box<T> needs: a pointer’s size doesn’t change based on the amount of data it’s pointing to. This means we can put a Box<T> inside the Node variant instead of another BinaryTree value directly. The Box<T> will point to the child BinaryTree values that will be stored in their own segment, rather than inside the Node variant. Conceptually, we still have a binary tree, created with binary trees holding other binary trees, but this implementation is now more like placing the items next to one another rather than inside one another.

We can change the definition of the BinaryTree enum in Listing 12-2 and the usage of the BinaryTree in Listing 12-2 to the code in Listing 12-3, which will compile:

use core::box::{BoxTrait};

mod display;
use display::DebugBinaryTree;

#[derive(Copy, Drop)]
enum BinaryTree {
    Leaf: u32,
    Node: (u32, Box<BinaryTree>, Box<BinaryTree>),
}


fn main() {
    let leaf1 = BinaryTree::Leaf(1);
    let leaf2 = BinaryTree::Leaf(2);
    let leaf3 = BinaryTree::Leaf(3);
    let node = BinaryTree::Node((4, BoxTrait::new(leaf2), BoxTrait::new(leaf3)));
    let root = BinaryTree::Node((5, BoxTrait::new(leaf1), BoxTrait::new(node)));

    println!("{:?}", root);
}

Listing 12-3: Defining a recursive Binary Tree using Boxes

The Node variant now holds a (u32, Box<BinaryTree>, Box<BinaryTree>), indicating that the Node variant will store a u32 value, and two Box<BinaryTree> values. Now, we know that the Node variant will need a size of u32 plus the size of the two Box<BinaryTree> values. By using a box, we’ve broken the infinite, recursive chain, so the compiler can figure out the size it needs to store a BinaryTree value.

Using Boxes to Improve Performance

Passing pointers between functions allows you to reference data without copying the data itself. Using boxes can improve performance as it allows you to pass a pointer to some data from one function to another, without the need to copy the entire data in memory before performing the function call. Instead of having to write n values into memory before calling a function, only a single value is written, corresponding to the pointer to the data. If the data stored in the box is very large, the performance improvement can be significant, as you would save n-1 memory operations before each function call.

Let's take a look at the code in Listing 12-4, which shows two ways of passing data to a function: by value and by pointer.

#[derive(Drop)]
struct Cart {
    paid: bool,
    items: u256,
    buyer: ByteArray,
}

fn pass_data(cart: Cart) {
    println!("{} is shopping today and bought {} items", cart.buyer, cart.items);
}

fn pass_pointer(cart: Box<Cart>) {
    let cart = cart.unbox();
    println!("{} is shopping today and bought {} items", cart.buyer, cart.items);
}

fn main() {
    let new_struct = Cart { paid: true, items: 1, buyer: "Eli" };
    pass_data(new_struct);

    let new_box = BoxTrait::new(Cart { paid: false, items: 2, buyer: "Uri" });
    pass_pointer(new_box);
}

Listing 12-4: Storing large amounts of data in a box for performance.

The main function includes 2 function calls:

• pass_data that takes a variable of type Cart.
• pass_pointer that takes a pointer of type Box<Cart>.

When passing data to a function, the entire data is copied into the last available memory cells right before the function call. Calling pass_data will copy all 3 fields of Cart to memory, while pass_pointer only requires the copy of the new_box pointer which is of size 1.

CairoVM Memory layout when using boxes

The illustration above demonstrates how the memory behaves in both cases. The first instance of Cart is stored in the execution segment, and we need to copy all its fields to memory before calling the pass_data function. The second instance of Cart is stored in the boxed segment, and the pointer to it is stored in the execution segment. When calling the pass_pointer function, only the pointer to the struct is copied to memory right before the function call. In both cases, however, instantiating the struct will store all its values in the execution segment: the boxed segment can only be filled with data taken from the execution segment.

The Nullable<T> Type for Dictionaries

Nullable<T> is another type of smart pointer that can either point to a value or be null in the absence of value. It is defined at the Sierra level. This type is mainly used in dictionaries that contain types that don't implement the zero_default method of the Felt252DictValue<T> trait (i.e., arrays and structs).

If we try to access an element that does not exist in a dictionary, the code will fail if the zero_default method cannot be called.

Chapter 3 about dictionaries thoroughly explains how to store a Span<felt252> variable inside a dictionary using the Nullable<T> type. Please refer to it for further information.

Deref Coercion

Deref coercion simplifies the way we interact with nested or wrapped data structures by allowing an instance of one type to behave like an instance of another type. This mechanism is enabled by implementing the Deref trait, which allows implicit conversion (or coercion) to a different type, providing direct access to the underlying data.

Note: For now, deref coercion allows you to access a member of a type T as if it was a type K, but will not allow you to call functions whose self argument is of the original type when holding an instance of the coerced type.

Deref coercion is implemented via the Deref and DerefMut traits. When a type T implements Deref or DerefMut to type K, instances of T can access the members of K directly.

The Deref trait in Cairo is defined as follows:

pub trait Deref<T> {
    type Target;
    fn deref(self: T) -> Self::Target;
}

pub trait DerefMut<T> {
    type Target;
    fn deref_mut(ref self: T) -> Self::Target;
}

The Target type specifies the result of dereferencing, and the deref method defines how to transform T into K.

Using Deref Coercion

To better understand how deref coercion works, let's look at a practical example. We'll create a simple generic wrapper type around a type T called Wrapper<T>, and use it to wrap a UserProfile struct.

#[derive(Drop, Copy)]
struct UserProfile {
    username: felt252,
    email: felt252,
    age: u16,
}

#[derive(Drop, Copy)]
struct Wrapper<T> {
    value: T,
}

impl DerefWrapper<T> of Deref<Wrapper<T>> {
    type Target = T;
    fn deref(self: Wrapper<T>) -> T {
        self.value
    }
}

fn main() {
    let wrapped_profile = Wrapper {
        value: UserProfile { username: 'john_doe', email: 'john@example.com', age: 30 },
    };
    // Access fields directly via deref coercion
    println!("Username: {}", wrapped_profile.username);
    println!("Current age: {}", wrapped_profile.age);
}

The Wrapper struct wraps a single value generic of type T. To simplify access to the wrapped value, we implement the Deref trait for Wrapper<T>.

#[derive(Drop, Copy)]
struct UserProfile {
    username: felt252,
    email: felt252,
    age: u16,
}

#[derive(Drop, Copy)]
struct Wrapper<T> {
    value: T,
}

impl DerefWrapper<T> of Deref<Wrapper<T>> {
    type Target = T;
    fn deref(self: Wrapper<T>) -> T {
        self.value
    }
}

fn main() {
    let wrapped_profile = Wrapper {
        value: UserProfile { username: 'john_doe', email: 'john@example.com', age: 30 },
    };
    // Access fields directly via deref coercion
    println!("Username: {}", wrapped_profile.username);
    println!("Current age: {}", wrapped_profile.age);
}

This implementation is quite simple. The deref method returns the wrapped value, allowing instances of Wrapper<T> to access the members of T directly.

In practice, this mechanism is totally transparent. The following example demonstrates how, holding an instance of Wrapper<UserProfile>, we can print the username and age fields of the underlying UserProfile instance.

#[derive(Drop, Copy)]
struct UserProfile {
    username: felt252,
    email: felt252,
    age: u16,
}

#[derive(Drop, Copy)]
struct Wrapper<T> {
    value: T,
}

impl DerefWrapper<T> of Deref<Wrapper<T>> {
    type Target = T;
    fn deref(self: Wrapper<T>) -> T {
        self.value
    }
}

fn main() {
    let wrapped_profile = Wrapper {
        value: UserProfile { username: 'john_doe', email: 'john@example.com', age: 30 },
    };
    // Access fields directly via deref coercion
    println!("Username: {}", wrapped_profile.username);
    println!("Current age: {}", wrapped_profile.age);
}

Restricting Deref Coercion to Mutable Variables

While Deref works for both mutable and immutable variables, DerefMut will only be applicable to mutable variables. Contrary to what the name might suggest, DerefMut does not provide mutable access to the underlying data.

//TAG: does_not_compile

use core::ops::DerefMut;

#[derive(Drop, Copy)]
struct UserProfile {
    username: felt252,
    email: felt252,
    age: u16,
}

#[derive(Drop, Copy)]
struct Wrapper<T> {
    value: T,
}

impl DerefMutWrapper<T, +Copy<T>> of DerefMut<Wrapper<T>> {
    type Target = T;
    fn deref_mut(ref self: Wrapper<T>) -> T {
        self.value
    }
}

fn error() {
    let wrapped_profile = Wrapper {
        value: UserProfile { username: 'john_doe', email: 'john@example.com', age: 30 },
    };
    // Uncommenting the next line will cause a compilation error
    println!("Username: {}", wrapped_profile.username);
}

fn main() {
    let mut wrapped_profile = Wrapper {
        value: UserProfile { username: 'john_doe', email: 'john@example.com', age: 30 },
    };

    println!("Username: {}", wrapped_profile.username);
    println!("Current age: {}", wrapped_profile.age);
}

If you try to use DerefMut with an immutable variable, the compiler would throw an error. Here’s an example:

//TAG: does_not_compile

use core::ops::DerefMut;

#[derive(Drop, Copy)]
struct UserProfile {
    username: felt252,
    email: felt252,
    age: u16,
}

#[derive(Drop, Copy)]
struct Wrapper<T> {
    value: T,
}

impl DerefMutWrapper<T, +Copy<T>> of DerefMut<Wrapper<T>> {
    type Target = T;
    fn deref_mut(ref self: Wrapper<T>) -> T {
        self.value
    }
}

fn error() {
    let wrapped_profile = Wrapper {
        value: UserProfile { username: 'john_doe', email: 'john@example.com', age: 30 },
    };
    // Uncommenting the next line will cause a compilation error
    println!("Username: {}", wrapped_profile.username);
}

fn main() {
    let mut wrapped_profile = Wrapper {
        value: UserProfile { username: 'john_doe', email: 'john@example.com', age: 30 },
    };

    println!("Username: {}", wrapped_profile.username);
    println!("Current age: {}", wrapped_profile.age);
}

Compiling this code will result in the following error:

$ scarb build 
   Compiling no_listing_09_deref_coercion_example v0.1.0 (listings/ch12-advanced-features/no_listing_09_deref_mut_example/Scarb.toml)
error: Type "no_listing_09_deref_coercion_example::Wrapper::<no_listing_09_deref_coercion_example::UserProfile>" has no member "username"
 --> listings/ch12-advanced-features/no_listing_09_deref_mut_example/src/lib.cairo:32:46
    println!("Username: {}", wrapped_profile.username);
                                             ^******^

error: could not compile `no_listing_09_deref_coercion_example` due to previous error

For the above code to work, we need to define wrapped_profile as a mutable variable.

//TAG: does_not_compile

use core::ops::DerefMut;

#[derive(Drop, Copy)]
struct UserProfile {
    username: felt252,
    email: felt252,
    age: u16,
}

#[derive(Drop, Copy)]
struct Wrapper<T> {
    value: T,
}

impl DerefMutWrapper<T, +Copy<T>> of DerefMut<Wrapper<T>> {
    type Target = T;
    fn deref_mut(ref self: Wrapper<T>) -> T {
        self.value
    }
}

fn error() {
    let wrapped_profile = Wrapper {
        value: UserProfile { username: 'john_doe', email: 'john@example.com', age: 30 },
    };
    // Uncommenting the next line will cause a compilation error
    println!("Username: {}", wrapped_profile.username);
}

fn main() {
    let mut wrapped_profile = Wrapper {
        value: UserProfile { username: 'john_doe', email: 'john@example.com', age: 30 },
    };

    println!("Username: {}", wrapped_profile.username);
    println!("Current age: {}", wrapped_profile.age);
}

Resumen

By using the Deref and DerefMut traits, we can transparently convert one type into another, simplifying the access to nested or wrapped data structures. This feature is particularly useful when working with generic types or building abstractions that require seamless access to the underlying data and can help reduce boilerplate code. However, this functionality is quite limited, as you cannot call functions whose self argument is of the original type when holding an instance of the coerced type.

Associated Items

Associated Items are the items declared in traits or defined in implementations. Specifically, there are associated functions (including methods, that we already covered in Chapter 5), associated types, associated constants, and associated implementations.

Associated items are useful when they are logically related to the implementation. For example, the is_some method on Option is intrinsically related to Options, so should be associated.

Every associated item kind comes in two varieties: definitions that contain the actual implementation and declarations that declare signatures for definitions.

Associated Types

Associated types are type aliases allowing you to define abstract type placeholders within traits. Instead of specifying concrete types in the trait definition, associated types let trait implementers choose the actual types to use.

Let's consider the following Pack trait:

trait Pack<T> {
    type Result;

    fn pack(self: T, other: T) -> Self::Result;
}

impl PackU32Impl of Pack<u32> {
    type Result = u64;

    fn pack(self: u32, other: u32) -> Self::Result {
        let shift: u64 = 0x100000000; // 2^32
        self.into() * shift + other.into()
    }
}

fn bar<T, impl PackImpl: Pack<T>>(self: T, b: T) -> PackImpl::Result {
    PackImpl::pack(self, b)
}

trait PackGeneric<T, U> {
    fn pack_generic(self: T, other: T) -> U;
}

impl PackGenericU32 of PackGeneric<u32, u64> {
    fn pack_generic(self: u32, other: u32) -> u64 {
        let shift: u64 = 0x100000000; // 2^32
        self.into() * shift + other.into()
    }
}

fn foo<T, U, +PackGeneric<T, U>>(self: T, other: T) -> U {
    self.pack_generic(other)
}

fn main() {
    let a: u32 = 1;
    let b: u32 = 1;

    let x = foo(a, b);
    let y = bar(a, b);

    // result is 2^32 + 1
    println!("x: {}", x);
    println!("y: {}", y);
}

The Result type in our Pack trait acts as placeholder for a type that will be filled in later. Think of associated types as leaving a blank space in your trait for each implementation to write in the specific type it needs. This approach keeps your trait definition clean and flexible. When you use the trait, you don't need to worry about specifying these types - they're already chosen for you by the implementation. In our Pack trait, the type Result is such a placeholder. The method's definition shows that it will return values of type Self::Result, but it doesn't specify what Result actually is. This is left to the implementers of the Pack trait, who will specify the concrete type for Result. When the pack method is called, it will return a value of that chosen concrete type, whatever it may be.

Let's see how associated types compare to a more traditional generic approach. Suppose we need a function foo that can pack two variables of type T. Without associated types, we might define a PackGeneric trait and an implementation to pack two u32 like this:

trait Pack<T> {
    type Result;

    fn pack(self: T, other: T) -> Self::Result;
}

impl PackU32Impl of Pack<u32> {
    type Result = u64;

    fn pack(self: u32, other: u32) -> Self::Result {
        let shift: u64 = 0x100000000; // 2^32
        self.into() * shift + other.into()
    }
}

fn bar<T, impl PackImpl: Pack<T>>(self: T, b: T) -> PackImpl::Result {
    PackImpl::pack(self, b)
}

trait PackGeneric<T, U> {
    fn pack_generic(self: T, other: T) -> U;
}

impl PackGenericU32 of PackGeneric<u32, u64> {
    fn pack_generic(self: u32, other: u32) -> u64 {
        let shift: u64 = 0x100000000; // 2^32
        self.into() * shift + other.into()
    }
}

fn foo<T, U, +PackGeneric<T, U>>(self: T, other: T) -> U {
    self.pack_generic(other)
}

fn main() {
    let a: u32 = 1;
    let b: u32 = 1;

    let x = foo(a, b);
    let y = bar(a, b);

    // result is 2^32 + 1
    println!("x: {}", x);
    println!("y: {}", y);
}

With this approach, foo would be implemented as:

trait Pack<T> {
    type Result;

    fn pack(self: T, other: T) -> Self::Result;
}

impl PackU32Impl of Pack<u32> {
    type Result = u64;

    fn pack(self: u32, other: u32) -> Self::Result {
        let shift: u64 = 0x100000000; // 2^32
        self.into() * shift + other.into()
    }
}

fn bar<T, impl PackImpl: Pack<T>>(self: T, b: T) -> PackImpl::Result {
    PackImpl::pack(self, b)
}

trait PackGeneric<T, U> {
    fn pack_generic(self: T, other: T) -> U;
}

impl PackGenericU32 of PackGeneric<u32, u64> {
    fn pack_generic(self: u32, other: u32) -> u64 {
        let shift: u64 = 0x100000000; // 2^32
        self.into() * shift + other.into()
    }
}

fn foo<T, U, +PackGeneric<T, U>>(self: T, other: T) -> U {
    self.pack_generic(other)
}

fn main() {
    let a: u32 = 1;
    let b: u32 = 1;

    let x = foo(a, b);
    let y = bar(a, b);

    // result is 2^32 + 1
    println!("x: {}", x);
    println!("y: {}", y);
}

Notice how foo needs to specify both T and U as generic parameters. Now, let's compare this to our Pack trait with an associated type:

trait Pack<T> {
    type Result;

    fn pack(self: T, other: T) -> Self::Result;
}

impl PackU32Impl of Pack<u32> {
    type Result = u64;

    fn pack(self: u32, other: u32) -> Self::Result {
        let shift: u64 = 0x100000000; // 2^32
        self.into() * shift + other.into()
    }
}

fn bar<T, impl PackImpl: Pack<T>>(self: T, b: T) -> PackImpl::Result {
    PackImpl::pack(self, b)
}

trait PackGeneric<T, U> {
    fn pack_generic(self: T, other: T) -> U;
}

impl PackGenericU32 of PackGeneric<u32, u64> {
    fn pack_generic(self: u32, other: u32) -> u64 {
        let shift: u64 = 0x100000000; // 2^32
        self.into() * shift + other.into()
    }
}

fn foo<T, U, +PackGeneric<T, U>>(self: T, other: T) -> U {
    self.pack_generic(other)
}

fn main() {
    let a: u32 = 1;
    let b: u32 = 1;

    let x = foo(a, b);
    let y = bar(a, b);

    // result is 2^32 + 1
    println!("x: {}", x);
    println!("y: {}", y);
}

With associated types, we can define bar more concisely:

trait Pack<T> {
    type Result;

    fn pack(self: T, other: T) -> Self::Result;
}

impl PackU32Impl of Pack<u32> {
    type Result = u64;

    fn pack(self: u32, other: u32) -> Self::Result {
        let shift: u64 = 0x100000000; // 2^32
        self.into() * shift + other.into()
    }
}

fn bar<T, impl PackImpl: Pack<T>>(self: T, b: T) -> PackImpl::Result {
    PackImpl::pack(self, b)
}

trait PackGeneric<T, U> {
    fn pack_generic(self: T, other: T) -> U;
}

impl PackGenericU32 of PackGeneric<u32, u64> {
    fn pack_generic(self: u32, other: u32) -> u64 {
        let shift: u64 = 0x100000000; // 2^32
        self.into() * shift + other.into()
    }
}

fn foo<T, U, +PackGeneric<T, U>>(self: T, other: T) -> U {
    self.pack_generic(other)
}

fn main() {
    let a: u32 = 1;
    let b: u32 = 1;

    let x = foo(a, b);
    let y = bar(a, b);

    // result is 2^32 + 1
    println!("x: {}", x);
    println!("y: {}", y);
}

Finally, let's see both approaches in action, demonstrating that the end result is the same:

trait Pack<T> {
    type Result;

    fn pack(self: T, other: T) -> Self::Result;
}

impl PackU32Impl of Pack<u32> {
    type Result = u64;

    fn pack(self: u32, other: u32) -> Self::Result {
        let shift: u64 = 0x100000000; // 2^32
        self.into() * shift + other.into()
    }
}

fn bar<T, impl PackImpl: Pack<T>>(self: T, b: T) -> PackImpl::Result {
    PackImpl::pack(self, b)
}

trait PackGeneric<T, U> {
    fn pack_generic(self: T, other: T) -> U;
}

impl PackGenericU32 of PackGeneric<u32, u64> {
    fn pack_generic(self: u32, other: u32) -> u64 {
        let shift: u64 = 0x100000000; // 2^32
        self.into() * shift + other.into()
    }
}

fn foo<T, U, +PackGeneric<T, U>>(self: T, other: T) -> U {
    self.pack_generic(other)
}

fn main() {
    let a: u32 = 1;
    let b: u32 = 1;

    let x = foo(a, b);
    let y = bar(a, b);

    // result is 2^32 + 1
    println!("x: {}", x);
    println!("y: {}", y);
}

As you can see, bar doesn't need to specify a second generic type for the packing result. This information is hidden in the implementation of the Pack trait, making the function signature cleaner and more flexible. Associated types allow us to express the same functionality with less verbosity, while still maintaining the flexibility of generic programming.

Associated Constants

Associated constants are constants associated with a type. They are declared using the const keyword in a trait and defined in its implementation. In our next example, we define a generic Shape trait that we implement for a Triangle and a Square. This trait includes an associated constant, defining the number of sides of the type that implements the trait.

trait Shape<T> {
    const SIDES: u32;
    fn describe() -> ByteArray;
}

struct Triangle {}

impl TriangleShape of Shape<Triangle> {
    const SIDES: u32 = 3;
    fn describe() -> ByteArray {
        "I am a triangle."
    }
}

struct Square {}

impl SquareShape of Shape<Square> {
    const SIDES: u32 = 4;
    fn describe() -> ByteArray {
        "I am a square."
    }
}

fn print_shape_info<T, impl ShapeImpl: Shape<T>>() {
    println!("I have {} sides. {}", ShapeImpl::SIDES, ShapeImpl::describe());
}

fn main() {
    print_shape_info::<Triangle>();
    print_shape_info::<Square>();
}

After that, we create a print_shape_info generic function, which requires that the generic argument implements the Shape trait. This function will use the associated constant to retrieve the number of sides of the geometric figure, and print it along with its description.

trait Shape<T> {
    const SIDES: u32;
    fn describe() -> ByteArray;
}

struct Triangle {}

impl TriangleShape of Shape<Triangle> {
    const SIDES: u32 = 3;
    fn describe() -> ByteArray {
        "I am a triangle."
    }
}

struct Square {}

impl SquareShape of Shape<Square> {
    const SIDES: u32 = 4;
    fn describe() -> ByteArray {
        "I am a square."
    }
}

fn print_shape_info<T, impl ShapeImpl: Shape<T>>() {
    println!("I have {} sides. {}", ShapeImpl::SIDES, ShapeImpl::describe());
}

fn main() {
    print_shape_info::<Triangle>();
    print_shape_info::<Square>();
}

Associated constants allow us to bind a constant number to the Shape trait rather than adding it to the struct or just hardcoding the value in the implementation. This approach provides several benefits:

1. It keeps the constant closely tied to the trait, improving code organization.
2. It allows for compile-time checks to ensure all implementors define the required constant.
3. It ensures two instances of the same type have the same number of sides.

Associated constants can also be used for type-specific behavior or configuration, making them a versatile tool in trait design.

We can ultimately run the print_shape_info and see the output for both Triangle and Square:

trait Shape<T> {
    const SIDES: u32;
    fn describe() -> ByteArray;
}

struct Triangle {}

impl TriangleShape of Shape<Triangle> {
    const SIDES: u32 = 3;
    fn describe() -> ByteArray {
        "I am a triangle."
    }
}

struct Square {}

impl SquareShape of Shape<Square> {
    const SIDES: u32 = 4;
    fn describe() -> ByteArray {
        "I am a square."
    }
}

fn print_shape_info<T, impl ShapeImpl: Shape<T>>() {
    println!("I have {} sides. {}", ShapeImpl::SIDES, ShapeImpl::describe());
}

fn main() {
    print_shape_info::<Triangle>();
    print_shape_info::<Square>();
}

Associated Implementations

Associated implementations allow you to declare that a trait implementation must exist for an associated type. This feature is particularly useful when you want to enforce relationships between types and implementations at the trait level. It ensures type safety and consistency across different implementations of a trait, which is important in generic programming contexts.

To understand the utility of associated implementations, let's examine the Iterator and IntoIterator traits from the Cairo core library, with their respective implementations using ArrayIter<T> as the collection type:

// Collection type that contains a simple array
#[derive(Drop)]
pub struct ArrayIter<T> {
    array: Array<T>,
}

// T is the collection type
pub trait Iterator<T> {
    type Item;
    fn next(ref self: T) -> Option<Self::Item>;
}

impl ArrayIterator<T> of Iterator<ArrayIter<T>> {
    type Item = T;
    fn next(ref self: ArrayIter<T>) -> Option<T> {
        self.array.pop_front()
    }
}

/// Turns a collection of values into an iterator
pub trait IntoIterator<T> {
    /// The iterator type that will be created
    type IntoIter;
    impl Iterator: Iterator<Self::IntoIter>;

    fn into_iter(self: T) -> Self::IntoIter;
}

impl ArrayIntoIterator<T> of IntoIterator<Array<T>> {
    type IntoIter = ArrayIter<T>;
    fn into_iter(self: Array<T>) -> ArrayIter<T> {
        ArrayIter { array: self }
    }
}

fn main() {
    let mut arr: Array<felt252> = array![1, 2, 3];

    // Converts the array into an iterator
    let mut iter = arr.into_iter();

    // Uses the iterator to print each element
    loop {
        match iter.next() {
            Option::Some(item) => println!("Item: {}", item),
            Option::None => { break; },
        };
    }
}

1. The IntoIterator trait is designed to convert a collection into an iterator.
2. The IntoIter associated type represents the specific iterator type that will be created. This allows different collections to define their own efficient iterator types.
3. The associated implementation Iterator: Iterator<Self::IntoIter> (the key feature we're discussing) declares that this IntoIter type must implement the Iterator trait.
4. This design allows for type-safe iteration without needing to specify the iterator type explicitly every time, improving code ergonomics.

The associated implementation creates a binding at the trait level, guaranteeing that:

• The into_iter method will always return a type that implements Iterator.
• This relationship is enforced for all implementations of IntoIterator, not just on a case-by-case basis.

The following main function demonstrates how this works in practice for an Array<felt252>:

// Collection type that contains a simple array
#[derive(Drop)]
pub struct ArrayIter<T> {
    array: Array<T>,
}

// T is the collection type
pub trait Iterator<T> {
    type Item;
    fn next(ref self: T) -> Option<Self::Item>;
}

impl ArrayIterator<T> of Iterator<ArrayIter<T>> {
    type Item = T;
    fn next(ref self: ArrayIter<T>) -> Option<T> {
        self.array.pop_front()
    }
}

/// Turns a collection of values into an iterator
pub trait IntoIterator<T> {
    /// The iterator type that will be created
    type IntoIter;
    impl Iterator: Iterator<Self::IntoIter>;

    fn into_iter(self: T) -> Self::IntoIter;
}

impl ArrayIntoIterator<T> of IntoIterator<Array<T>> {
    type IntoIter = ArrayIter<T>;
    fn into_iter(self: Array<T>) -> ArrayIter<T> {
        ArrayIter { array: self }
    }
}

fn main() {
    let mut arr: Array<felt252> = array![1, 2, 3];

    // Converts the array into an iterator
    let mut iter = arr.into_iter();

    // Uses the iterator to print each element
    loop {
        match iter.next() {
            Option::Some(item) => println!("Item: {}", item),
            Option::None => { break; },
        };
    }
}

Sobrecarga de Operadores

Operator overloading is a feature in some programming languages that allows the redefinition of standard operators, such as addition (+), subtraction (-), multiplication (*), and division (/), to work with user-defined types. This can make the syntax of the code more intuitive, by enabling operations on user-defined types to be expressed in the same way as operations on primitive types.

In Cairo, operator overloading is achieved through the implementation of specific traits. Each operator has an associated trait, and overloading that operator involves providing an implementation of that trait for a custom type. However, it's essential to use operator overloading judiciously. Misuse can lead to confusion, making the code more difficult to maintain, for example when there is no semantic meaning to the operator being overloaded.

Consideremos un ejemplo en el que hay que combinar dos Potions. Las Potions tienen dos campos de datos, maná y salud. Al combinar dos Potions se deben añadir sus respectivos campos.

struct Potion {
    health: felt252,
    mana: felt252,
}

impl PotionAdd of Add<Potion> {
    fn add(lhs: Potion, rhs: Potion) -> Potion {
        Potion { health: lhs.health + rhs.health, mana: lhs.mana + rhs.mana }
    }
}

fn main() {
    let health_potion: Potion = Potion { health: 100, mana: 0 };
    let mana_potion: Potion = Potion { health: 0, mana: 100 };
    let super_potion: Potion = health_potion + mana_potion;
    // Both potions were combined with the `+` operator.
    assert(super_potion.health == 100, '');
    assert(super_potion.mana == 100, '');
}

En el código anterior, estamos implementando el rasgo Add para el tipo Potion. La función add toma dos argumentos: lhs y rhs (izquierda y derecha). El cuerpo de la función devuelve una nueva instancia de Poción, cuyos valores de campo son una combinación de lhs y rhs.

Como se ilustra en el ejemplo, la sobrecarga de un operador requiere la especificación del tipo concreto que se sobrecarga. El trait genérico sobrecargado es Add<T>, y definimos una implementación concreta para el tipo Potion con Add<Potion>.

Hashes

At its essence, hashing is a process of converting input data (often called a message) of any length into a fixed-size value, typically referred to as a "hash." This transformation is deterministic, meaning that the same input will always produce the same hash value. Hash functions are a fundamental component in various fields, including data storage, cryptography and data integrity verification. They are very often used when developing smart contracts, especially when working with Merkle trees.

In this chapter, we will present the two hash functions implemented natively in the Cairo core library: Poseidon and Pedersen. We will discuss when and how to use them, and see examples with Cairo programs.

Hash Functions in Cairo

The Cairo core library provides two hash functions: Pedersen and Poseidon.

Pedersen hash functions are cryptographic algorithms that rely on elliptic curve cryptography. These functions perform operations on points along an elliptic curve — essentially, doing math with the locations of these points — which are easy to do in one direction and hard to undo. This one-way difficulty is based on the Elliptic Curve Discrete Logarithm Problem (ECDLP), which is a problem so hard to solve that it ensures the security of the hash function. The difficulty of reversing these operations is what makes the Pedersen hash function secure and reliable for cryptographic purposes.

Poseidon is a family of hash functions designed to be very efficient as algebraic circuits. Its design is particularly efficient for Zero-Knowledge proof systems, including STARKs (so, Cairo). Poseidon uses a method called a 'sponge construction,' which soaks up data and transforms it securely using a process known as the Hades permutation. Cairo's version of Poseidon is based on a three-element state permutation with specific parameters.

When to Use Them?

Pedersen was the first hash function used on Starknet, and is still used to compute the addresses of variables in storage (for example, LegacyMap uses Pedersen to hash the keys of a storage mapping on Starknet). However, as Poseidon is cheaper and faster than Pedersen when working with STARK proofs system, it's now the recommended hash function to use in Cairo programs.

Working with Hashes

The core library makes it easy to work with hashes. The Hash trait is implemented for all types that can be converted to felt252, including felt252 itself. For more complex types like structs, deriving Hash allows them to be hashed easily using the hash function of your choice - given that all of the struct's fields are themselves hashable. You cannot derive the Hash trait on a struct that contains un-hashable values, such as Array<T> or Felt252Dict<T>, even if T itself is hashable.

The Hash trait is accompanied by the HashStateTrait and HashStateExTrait that define the basic methods to work with hashes. They allow you to initialize a hash state that will contain the temporary values of the hash after each application of the hash function, update the hash state and finalize it when the computation is completed. HashStateTrait and HashStateExTrait are defined as follows:

/// A trait for hash state accumulators.
trait HashStateTrait<S> {
    fn update(self: S, value: felt252) -> S;
    fn finalize(self: S) -> felt252;
}

/// Extension trait for hash state accumulators.
trait HashStateExTrait<S, T> {
    /// Updates the hash state with the given value.
    fn update_with(self: S, value: T) -> S;
}

/// A trait for values that can be hashed.
trait Hash<T, S, +HashStateTrait<S>> {
    /// Updates the hash state with the given value.
    fn update_state(state: S, value: T) -> S;
}

To use hashes in your code, you must first import the relevant traits and functions. In the following example, we will demonstrate how to hash a struct using both the Pedersen and Poseidon hash functions.

The first step is to initialize the hash with either PoseidonTrait::new() -> HashState or PedersenTrait::new(base: felt252) -> HashState depending on which hash function we want to work with. Then the hash state can be updated with the update(self: HashState, value: felt252) -> HashState or update_with(self: S, value: T) -> S functions as many times as required. Then the function finalize(self: HashState) -> felt252 is called on the hash state and it returns the value of the hash as a felt252.

use core::poseidon::PoseidonTrait;
use core::hash::{HashStateTrait, HashStateExTrait};

#[derive(Drop, Hash)]
struct StructForHash {
    first: felt252,
    second: felt252,
    third: (u32, u32),
    last: bool,
}

fn main() -> felt252 {
    let struct_to_hash = StructForHash { first: 0, second: 1, third: (1, 2), last: false };

    let hash = PoseidonTrait::new().update_with(struct_to_hash).finalize();
    hash
}

Pedersen is different from Poseidon, as it starts with a base state. This base state must be of felt252 type, which forces us to either hash the struct with an arbitrary base state using the update_with method, or serialize the struct into an array to loop through all of its fields and hash its elements together.

Here is a short example of Pedersen hashing:

use core::pedersen::PedersenTrait;
use core::hash::{HashStateTrait, HashStateExTrait};

#[derive(Drop, Hash, Serde, Copy)]
struct StructForHash {
    first: felt252,
    second: felt252,
    third: (u32, u32),
    last: bool,
}

fn main() -> (felt252, felt252) {
    let struct_to_hash = StructForHash { first: 0, second: 1, third: (1, 2), last: false };

    // hash1 is the result of hashing a struct with a base state of 0
    let hash1 = PedersenTrait::new(0).update_with(struct_to_hash).finalize();

    let mut serialized_struct: Array<felt252> = ArrayTrait::new();
    Serde::serialize(@struct_to_hash, ref serialized_struct);
    let first_element = serialized_struct.pop_front().unwrap();
    let mut state = PedersenTrait::new(first_element);

    while let Option::Some(value) = serialized_struct.pop_front() {
        state = state.update(value);
    };

    // hash2 is the result of hashing only the fields of the struct
    let hash2 = state.finalize();

    (hash1, hash2)
}

Advanced Hashing: Hashing Arrays with Poseidon

Let us look at an example of hashing a struct that contains a Span<felt252>. To hash a Span<felt252> or a struct that contains a Span<felt252> you can use the built-in function poseidon_hash_span(mut span: Span<felt252>) -> felt252. Similarly, you can hash Array<felt252> by calling poseidon_hash_span on its span.

First, let us import the following traits and function:

use core::poseidon::PoseidonTrait;
use core::poseidon::poseidon_hash_span;
use core::hash::{HashStateTrait, HashStateExTrait};

Now we define the struct. As you might have noticed, we didn't derive the Hash trait. If you attempt to derive the Hash trait for this struct, it will result in an error because the structure contains a field that is not hashable.

#[derive(Drop)]
struct StructForHashArray {
    first: felt252,
    second: felt252,
    third: Array<felt252>,
}

In this example, we initialized a HashState (hash), updated it and then called the function finalize() on the HashState to get the computed hash hash_felt252. We used poseidon_hash_span on the Span of the Array<felt252> to compute its hash.

use core::poseidon::PoseidonTrait;
use core::poseidon::poseidon_hash_span;
use core::hash::{HashStateTrait, HashStateExTrait};

#[derive(Drop)]
struct StructForHashArray {
    first: felt252,
    second: felt252,
    third: Array<felt252>,
}

fn main() {
    let struct_to_hash = StructForHashArray { first: 0, second: 1, third: array![1, 2, 3, 4, 5] };

    let mut hash = PoseidonTrait::new().update(struct_to_hash.first).update(struct_to_hash.second);
    let hash_felt252 = hash.update(poseidon_hash_span(struct_to_hash.third.span())).finalize();
}

Macros

The Cairo language has some plugins that allow developers to simplify their code. They are called inline_macros and are a way of writing code that generates other code.

consteval_int! Macro

In some situations, a developer might need to declare a constant that is the result of a computation of integers. To compute a constant expression and use its result at compile time, it is required to use the consteval_int! macro.

Here is an example of consteval_int!:

const a: felt252 = consteval_int!(2 * 2 * 2);

This will be interpreted as const a: felt252 = 8; by the compiler.

selector! Macro

selector!("function_name") macro generates the entry point selector for the given function name.

print! and println! Macros

Please refer to the Printing page.

array! Macro

Please refer to the Arrays page.

panic! Macro

See Unrecoverable Errors with panic page.

assert! and assert_xx! Macros

See How to Write Tests page.

format! Macro

See Printing page.

write! and writeln! Macros

See Printing page.

get_dep_component!, get_dep_component_mut and component! Macros

Please refer to the Composability and Components chapter.

Procedural Macros

Cairo provides macros as a fundamental feature that lets you write code that generates other code (known as metaprogramming). When you use macros, you can extend Cairo's capabilities beyond what regular functions offer. Throughout this book, we've used macros like println! and assert!, but haven't fully explored how we can create our own macros.

Before diving into procedural macros specifically, let's understand why we need macros when we already have functions:

The Difference Between Macros and Functions

Fundamentally, macros are a way of writing code that writes other code, which is known as metaprogramming. In Appendix C, we discuss derivable traits and the derive attribute, which generates an implementation of various traits for you. We’ve also used the println! and array! macros throughout the book. All of these macros expand to produce more code than the code you’ve written manually.

Metaprogramming is useful for reducing the amount of code you have to write and maintain, which is also one of the roles of functions. However, macros have some additional powers that functions don’t.

A function signature must declare the number and type of parameters the function has. Macros, on the other hand, can take a variable number of parameters: we can call println!("hello") with one argument or println!("hello {}", name) with two arguments. Also, macros are expanded before the compiler interprets the meaning of the code, so a macro can, for example, implement a trait on a given type. A function can’t, because it gets called at runtime and a trait needs to be implemented at compile time.

Another important difference between macros and functions is that the design of Cairo macros is complex: they're written in Rust, but operate on Cairo code. Due to this indirection and the combination of the two languages, macro definitions are generally more difficult to read, understand, and maintain than function definitions.

We call procedural macros macros that allow you to run code at compile time that operates over Cairo syntax, both consuming and producing Cairo syntax. You can sort of think of procedural macros as functions from an AST to another AST. The three kinds of procedural macros are custom derive, attribute-like, and function-like, and all work in a similar fashion.

In this chapter, we'll explore what procedural macros are, how they're defined, and examine each of the three types in detail.

Cairo Procedural Macros are Rust Functions

Just as the Cairo compiler is written in Rust, procedural macros are Rust functions that transform Cairo code. These functions take Cairo code as input and return modified Cairo code as output. To implement macros, you'll need a package with both a Cargo.toml and a Scarb.toml file. The Cargo.toml defines the macro implementation dependencies, while the Scarb.toml marks the package as a macro and defines its metadata.

The function that defines a procedural macro operates on two key types:

• TokenStream: A sequence of Cairo tokens representing your source code. Tokens are the smallest units of code that the compiler recognizes (like identifiers, keywords, and operators).
• ProcMacroResult: An enhanced version of TokenStream that includes both the generated code and any diagnostic messages (warnings or errors) that should be shown to the user during compilation.

The function implementing the macro must be decorated with one of three special attributes that tell the compiler how the macro should be used:

• #[inline_macro]: For macros that look like function calls (e.g., println!())
• #[attribute_macro]: For macros that act as attributes (e.g., #[generate_trait])
• #[derive_macro]: For macros that implement traits automatically

Each attribute type corresponds to a different use case and affects how the macro can be invoked in your code.

Here are the signatures for each types :

#[inline_macro]
pub fn inline(code: TokenStream) -> ProcMacroResult {}

#[attribute_macro]
pub fn attribute(attr: TokenStream, code: TokenStream) -> ProcMacroResult {}

#[derive_macro]
pub fn derive(code: TokenStream) -> ProcMacroResult {}

Install dependencies

To use procedural macros, you need to have Rust toolchain (Cargo) installed on your machine. To install Rust using Rustup, you can run the following command in you terminal :

curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh

Create your macro

Creating a procedural macro requires setting up a specific project structure. Your macro project needs:

1. A Rust Project (where you implement the macro):

   • Cargo.toml: Defines Rust dependencies and build settings
   • src/lib.rs: Contains the macro implementation

2. A Cairo Project:

   • Scarb.toml: Declares the macro for Cairo projects
   • No Cairo source files needed

Let's walk through each component and understand its role:

├── Cargo.toml
├── Scarb.toml
├── src
│   └── lib.rs

The project contains a Scarb.toml and a Cargo.toml file in the root directory.

The Cargo manifest file needs to contain a crate-type = ["cdylib"] on the [lib] target, and the cairo-lang-macro crate on the [dependencies] target. Here is an example :

[package]
name = "pow"
version = "0.1.0"
edition = "2021"
publish = false

[lib]
crate-type = ["cdylib"]

[dependencies]
bigdecimal = "0.4.5"
cairo-lang-macro = "0.1.1"
cairo-lang-parser = "2.9.2"
cairo-lang-syntax = "2.9.2"

[workspace]

The Scarb manifest file must define a [cairo-plugin] target type. Here is an example :

[package]
name = "pow"
version = "0.1.0"

[cairo-plugin]

Finally the project needs to contain a Rust library (lib.rs), inside the src/ directory that implements the procedural macro API.

As you might have notice the project doesn't need any cairo code, it only requires the Scarb.toml manifest file mentioned.

Using your macro

From the user's perspective, you only need to add the package defining the macro in your dependencies. In the project using the macro you will have a Scarb manifest file with :

[package]
name = "no_listing_15_procedural_macro"
version = "0.1.0"
edition = "2024_07"

# See more keys and their definitions at https://docs.swmansion.com/scarb/docs/reference/manifest.html

[dependencies]
pow = { path = "../no_listing_16_procedural_macro_expression" }
hello_macro = { path = "../no_listing_17_procedural_macro_derive" }
rename_macro = { path = "../no_listing_18_procedural_macro_attribute" }


[dev-dependencies]
cairo_test = "2.9.2"

Expression Macros

Expression macros provide functionality similar to function calls but with enhanced capabilities. Unlike regular functions, they can:

• Accept a variable number of arguments
• Handle arguments of different types
• Generate code at compile time
• Perform more complex code transformations

This flexibility makes them powerful tools for generic programming and code generation. Let's examine a practical example: implementing a compile-time power function.

Creating an expression Macros

To understand how to create an expression macro, we will look at a pow macro implementation from the Alexandria library that computes the power of a number at compile time.

The core code of the macro implementation is a Rust code that uses three Rust crates : cairo_lang_macro specific to macros implementation, cairo_lang_parser crate with function related to the compiler parser and cairo_lang_syntax related to the compiler syntax. The two latters were initially created for the Cairo lang compiler, as macro functions operate at the Cairo syntax level, we can reuse the logic directly from the syntax functions created for the compiler to create macros.

Note: To understand better the Cairo compiler and some of the concepts we only mention here such as the Cairo parser or the Cairo syntax, you can read the Cairo compiler workshop.

In the pow function example below the input is processed to extract the value of the base argument and the exponent argument to return the result of \(base^{exponent}\).

use bigdecimal::{num_traits::pow, BigDecimal};
use cairo_lang_macro::{inline_macro, Diagnostic, ProcMacroResult, TokenStream};
use cairo_lang_parser::utils::SimpleParserDatabase;

#[inline_macro]
pub fn pow(token_stream: TokenStream) -> ProcMacroResult {
    let db = SimpleParserDatabase::default();
    let (parsed, _diag) = db.parse_virtual_with_diagnostics(token_stream);

    // extracting the args from the parsed input
    let macro_args: Vec<String> = parsed
        .descendants(&db)
        .next()
        .unwrap()
        .get_text(&db)
        .trim_matches(|c| c == '(' || c == ')')
        .split(',')
        .map(|s| s.trim().to_string())
        .collect();

    if macro_args.len() != 2 {
        return ProcMacroResult::new(TokenStream::empty()).with_diagnostics(
            Diagnostic::error(format!("Expected two arguments, got {:?}", macro_args)).into(),
        );
    }

    // getting the value from the base arg
    let base: BigDecimal = match macro_args[0].parse() {
        Ok(val) => val,
        Err(_) => {
            return ProcMacroResult::new(TokenStream::empty())
                .with_diagnostics(Diagnostic::error("Invalid base value").into());
        }
    };

    // getting the value from the exponent arg
    let exp: usize = match macro_args[1].parse() {
        Ok(val) => val,
        Err(_) => {
            return ProcMacroResult::new(TokenStream::empty())
                .with_diagnostics(Diagnostic::error("Invalid exponent value").into());
        }
    };

    // base^exp
    let result: BigDecimal = pow(base, exp);

    ProcMacroResult::new(TokenStream::new(result.to_string()))
}

Now that the macro is defined, we can use it. In a Cairo project we need to have pow = { path = "path/to/pow" } in the [dependencies] target of the Scarb.toml manifest file. And then we can use it without further import like this :

fn main() {
    let a = SomeType {};
    a.hello();

    let res = pow!(10, 2);
    println!("res : {}", res);

    let _a = RenamedType {};
}


#[derive(HelloMacro, Drop, Destruct)]
struct SomeType {}

#[rename]
struct OldType {}

#[derive(Drop, Destruct)]
trait Hello<T> {
    fn hello(self: @T);
}

Derive Macros

Derive macros let you define custom trait implementations that can be automatically applied to types. When you annotate a type with #[derive(TraitName)], your derive macro:

1. Receives the type's structure as input
2. Contains your custom logic for generating the trait implementation
3. Outputs the implementation code that will be included in the crate

Writing derive macros eliminates repetitive trait implementation code by using a generic logic on how to generate the trait implementation.

Creating a derive macro

In this example, we will implement a derive macro that will implement the Hello Trait. The Hello trait will have a hello() function that will print : Hello, StructName!, where StructName is the name of the struct.

Here is the definition of the Hello trait :

fn main() {
    let a = SomeType {};
    a.hello();

    let res = pow!(10, 2);
    println!("res : {}", res);

    let _a = RenamedType {};
}


#[derive(HelloMacro, Drop, Destruct)]
struct SomeType {}

#[rename]
struct OldType {}

#[derive(Drop, Destruct)]
trait Hello<T> {
    fn hello(self: @T);
}

Let's check the marcro implementation, first the hello_derive function parses the input token stream and then extracts the struct_name to implement the trait for that specific struct.

Then hello derived returns a hard-coded piece of code containing the implementation of Hello trait for the type StructName.

use cairo_lang_macro::{derive_macro, ProcMacroResult, TokenStream};
use cairo_lang_parser::utils::SimpleParserDatabase;
use cairo_lang_syntax::node::kind::SyntaxKind::{TerminalStruct, TokenIdentifier};

#[derive_macro]
pub fn hello_macro(token_stream: TokenStream) -> ProcMacroResult {
    let db = SimpleParserDatabase::default();
    let (parsed, _diag) = db.parse_virtual_with_diagnostics(token_stream);
    let mut nodes = parsed.descendants(&db);

    let mut struct_name = String::new();
    for node in nodes.by_ref() {
        if node.kind(&db) == TerminalStruct {
            struct_name = nodes
                .find(|node| node.kind(&db) == TokenIdentifier)
                .unwrap()
                .get_text(&db);
            break;
        }
    }

    ProcMacroResult::new(TokenStream::new(indoc::formatdoc! {r#"
            impl SomeHelloImpl of Hello<{0}> {{
                fn hello(self: @{0}) {{
                    println!("Hello {0}!");
                }}
            }}
        "#, struct_name}))
}

Now that the macro is defined, we can use it. In a Cairo project we need to have hello_macro = { path = "path/to/hello_macro" } in the [dependencies] target of the Scarb.toml manifest file. And we can then use it without further import on any struct :

#[derive(HelloMacro, Drop, Destruct)]
struct SomeType {}

And now we can call the implemented function hello on an variable of the type SomeType.

fn main() {
    let a = SomeType {};
    a.hello();

    let res = pow!(10, 2);
    println!("res : {}", res);

    let _a = RenamedType {};
}


#[derive(HelloMacro, Drop, Destruct)]
struct SomeType {}

#[rename]
struct OldType {}

#[derive(Drop, Destruct)]
trait Hello<T> {
    fn hello(self: @T);
}

Note that the Hello trait that is implemented in the macro has to be defined somewhere in the code or imported.

Attribute Macros

Attribute-like macros are similar to custom derive macros, but allowing more possibilities, they are not restricted to struct and enum and can be applied to other items as well, such as functions. They can be used for more diverse code generation than implementing trait. It could be used to modify the name of a struct, add fields in the structure, execute some code before a function, change the signature of a function and many other possibilities.

The extra possibilities also come from the fact that they are defined with a second argument TokenStream, indeed the signature looks like this :

#[attribute_macro]
pub fn attribute(attr: TokenStream, code: TokenStream) -> ProcMacroResult {}

With the first attribute (attr) for the attribute arguments (#[macro(arguments)]) and second for the actual code on which the attribute is applied to, the second attribute is the only one the two other macros have.

Creating an attribute macro

Now let's look at an example of a custom made attribute macro, in this example we will create a macro that will rename the struct.

use cairo_lang_macro::attribute_macro;
use cairo_lang_macro::{ProcMacroResult, TokenStream};

#[attribute_macro]
pub fn rename(_attr: TokenStream, token_stream: TokenStream) -> ProcMacroResult {
    ProcMacroResult::new(TokenStream::new(
        token_stream
            .to_string()
            .replace("struct OldType", "#[derive(Drop)]\n struct RenamedType"),
    ))
}

Again, to use the macro in a Cairo project we need to have rename_macro = { path = "path/to/rename_macro" } in the [dependencies] target of the Scarb.toml manifest file. And we can then use it without further import on any struct.

The rename macro can be derived as follow :

fn main() {
    let a = SomeType {};
    a.hello();

    let res = pow!(10, 2);
    println!("res : {}", res);

    let _a = RenamedType {};
}


#[derive(HelloMacro, Drop, Destruct)]
struct SomeType {}

#[rename]
struct OldType {}

#[derive(Drop, Destruct)]
trait Hello<T> {
    fn hello(self: @T);
}

Now the compiler knows the RenamedType struct, therefore we can create an instance as such :

fn main() {
    let a = SomeType {};
    a.hello();

    let res = pow!(10, 2);
    println!("res : {}", res);

    let _a = RenamedType {};
}


#[derive(HelloMacro, Drop, Destruct)]
struct SomeType {}

#[rename]
struct OldType {}

#[derive(Drop, Destruct)]
trait Hello<T> {
    fn hello(self: @T);
}

You can notice that the names OldType and RenamedType were hardcoded in the example but could be variables leveraging the second arg of rattribute macro. Also note that due to the order of compilation, the derive of other macro such as Drop here as to be done in the code generated by the macro. Some deeper understanding of Cairo compilation can be required for custom macro creation.

Inlining in Cairo

Inlining is a common code optimization technique supported by most compilers. It involves replacing a function call at the call site with the actual code of the called function, eliminating the overhead associated with the function call itself. This can improve performance by reducing the number of instructions executed, but may increase the total size of the program. When you're thinking about whether to inline a function, take into account things like how big it is, what parameters it has, how often it gets called, and how it might affect the size of your compiled code.

The inline Attribute

In Cairo, the inline attribute suggests whether or not the Sierra code corresponding to the attributed function should be directly injected in the caller function's context, rather than using a function_call libfunc to execute that code.