Huff RS: A Low-level Assembly Language for EVM Built in Rust

huff-rs • 

huff-rs is a Huff compiler built in rust.

What is a Huff?

Huff is a low-level programming language designed for developing highly optimized smart contracts that run on the Ethereum Virtual Machine (EVM). Huff does not hide the inner workings of the EVM. Instead, Huff exposes its programming stack to the developer for manual manipulation.

Rather than having functions, Huff has macros - individual blocks of bytecode that can be rigorously tested and evaluated using the Huff runtime testing suite.

Huff was originally developed by the Aztec Protocol team to write Weierstrudel. Weierstrudel is an on-chain elliptical curve arithmetic library that requires incredibly optimized code that neither Solidity nor Yul could provide.

While EVM experts can use Huff to write highly-efficient smart contracts for use in production, it can also serve as a way for beginners to learn more about the EVM.

To dive deeper into Huff, visit the Official Huff Docs(also available on github).

Installation

Something not working? Send a message in discord.

First run the command below to get huffup, the Huff installer:

curl -L get.huff.sh | bash

To avoid redirecting the script directly into bash, download and run the huffup installation script.

To install the Huff compiler, simply run huffup.

If you have the old huffc (TypeScript version) npm package installed globally, you can remove it with:

sudo yarn global remove huffc

To make sure you are running the rust version, you can run huffc --version and it should respond with huff_cli <version>. If it responds with 2.0.0 that means you are running the Typescript version.

$ huffc --version
huff_cli 0.1.0

Alternatively

Install from source by running:

git clone https://raw.githubusercontent.com/huff-language/huff-rs
cd huff-rs
cargo install --path ./huff_cli --bins --locked --force

OR

cargo install --git https://raw.githubusercontent.com/huff-language/huff-rs --locked huff_cli

How Fast?

Compilation Benchmarks

CompilerCold (No Cache)Light CacheDeep CacheFull Cache
[huff-language/huff-rs][huff-rs]XXXmsXXXmsXXXmsXXXms
[huff-language/huffc][huffc]XXXmsXXXmsXXXmsXXXms

Note: Compilation benchmarks were performed on huff-examples erc20.

Architecture

Huff Compiler Architecture

Modules

  • huff_core: The core module to huff-rs. Resolves source file paths, executes compilation, and exports artifacts.
  • huff_cli: The command line interface for the Huff compiler.
  • huff_lexer: Takes in the source of a .huff file and generates a vector of Tokens.
  • huff_parser: Crafts a Contract AST from the the vector of Tokens generated by huff_lexer.
  • huff_codegen: EVM Bytecode generation module that accepts an AST generated by huff_parser.
  • huff_utils: Various utilities and types used by all modules.
  • huffup: Update or revert to a specific huff-rs branch with ease. (Forked from foundry)

Contributing

All contributions are welcome! We want to make contributing to this project as easy and transparent as possible, whether it's:

  • Reporting a bug
  • Discussing the current state of the code
  • Submitting a fix
  • Proposing new features
  • Becoming a maintainer

We use GitHub issues to track public bugs. Report a bug by opening a new issue; it's that easy!

To run examples, make sure you update git submodules to pull down the huff-examples submodule by running git submodule update.

The branching convention used by huff-rs is a stage branch that is meant to be merged off of and is periodically merged into main. So, when creating a feature, branch off of the stage branch and create a pr from your branch into the stage branch!

i.e: Branching Conventions

To pass github actions, please run:

cargo check --all
cargo test --all --all-features
cargo +nightly fmt -- --check
cargo +nightly clippy --all --all-features -- -D warnings

In order to fix any formatting issues, run:

cargo +nightly fmt --all

Recommended PR Template

Here is an example PR template - not strictly required, but will greatly improve the speed at which your PR is reviewed & merged!

## Overview

<Provide a general overview of what your pr accomplishes, why, and how (including links)>

## Checklist

- [x] <Ex: Added a `new` method to the Huff Lexer [here](./huff_lexer/src/lib.rs#50)>
- [x] <Ex: Fully tested the `new` method [here](./huff_lexer/tests/new.rs)>
- [ ] <Ex: Wrote documentation for the `new` method [here](./huff_lexer/README.md#20)>

When the PR checklist isn't complete, it is highly recommended to make it a draft PR. NOTE: if your PR is not complete, it will likely be changed to a draft by one of the repository admins.

For breaking changes: make sure to edit the excalidraw asset and export the file to ./assets/huffc.excalidraw along with an image to ./assets/huffc.png.

Safety

Warning

This is experimental software and is provided on an "as is" and "as available" basis. Expect rapid iteration and use at your own risk.

This code is not designed for safety.

  • There are untested invariants in the code that may break.
  • You can easily shoot yourself in the foot if you're not careful.
  • You should thoroughly read the documentation and examples.

We do not give any warranties and will not be liable for any loss incurred through any use of this codebase.

Acknowledgements

The original Huff Language compiler: huffc.

An exemplary, minimal rust compiler: ripc.

Foundry, for the many scripts, documentation, devops, and code on which huff-rs is based on.

All huff-rs contributors, users, advocates, and enthusiasts!

Download details:

Author: huff-language
Source code: https://github.com/huff-language/huff-rs
License: Apache-2.0 license

#solidity #smartcontract #ethereum #blockchain #rust #evm

What is GEEK

Buddha Community

Huff RS: A Low-level Assembly Language for EVM Built in Rust

Huff RS: A Low-level Assembly Language for EVM Built in Rust

huff-rs • 

huff-rs is a Huff compiler built in rust.

What is a Huff?

Huff is a low-level programming language designed for developing highly optimized smart contracts that run on the Ethereum Virtual Machine (EVM). Huff does not hide the inner workings of the EVM. Instead, Huff exposes its programming stack to the developer for manual manipulation.

Rather than having functions, Huff has macros - individual blocks of bytecode that can be rigorously tested and evaluated using the Huff runtime testing suite.

Huff was originally developed by the Aztec Protocol team to write Weierstrudel. Weierstrudel is an on-chain elliptical curve arithmetic library that requires incredibly optimized code that neither Solidity nor Yul could provide.

While EVM experts can use Huff to write highly-efficient smart contracts for use in production, it can also serve as a way for beginners to learn more about the EVM.

To dive deeper into Huff, visit the Official Huff Docs(also available on github).

Installation

Something not working? Send a message in discord.

First run the command below to get huffup, the Huff installer:

curl -L get.huff.sh | bash

To avoid redirecting the script directly into bash, download and run the huffup installation script.

To install the Huff compiler, simply run huffup.

If you have the old huffc (TypeScript version) npm package installed globally, you can remove it with:

sudo yarn global remove huffc

To make sure you are running the rust version, you can run huffc --version and it should respond with huff_cli <version>. If it responds with 2.0.0 that means you are running the Typescript version.

$ huffc --version
huff_cli 0.1.0

Alternatively

Install from source by running:

git clone https://raw.githubusercontent.com/huff-language/huff-rs
cd huff-rs
cargo install --path ./huff_cli --bins --locked --force

OR

cargo install --git https://raw.githubusercontent.com/huff-language/huff-rs --locked huff_cli

How Fast?

Compilation Benchmarks

CompilerCold (No Cache)Light CacheDeep CacheFull Cache
[huff-language/huff-rs][huff-rs]XXXmsXXXmsXXXmsXXXms
[huff-language/huffc][huffc]XXXmsXXXmsXXXmsXXXms

Note: Compilation benchmarks were performed on huff-examples erc20.

Architecture

Huff Compiler Architecture

Modules

  • huff_core: The core module to huff-rs. Resolves source file paths, executes compilation, and exports artifacts.
  • huff_cli: The command line interface for the Huff compiler.
  • huff_lexer: Takes in the source of a .huff file and generates a vector of Tokens.
  • huff_parser: Crafts a Contract AST from the the vector of Tokens generated by huff_lexer.
  • huff_codegen: EVM Bytecode generation module that accepts an AST generated by huff_parser.
  • huff_utils: Various utilities and types used by all modules.
  • huffup: Update or revert to a specific huff-rs branch with ease. (Forked from foundry)

Contributing

All contributions are welcome! We want to make contributing to this project as easy and transparent as possible, whether it's:

  • Reporting a bug
  • Discussing the current state of the code
  • Submitting a fix
  • Proposing new features
  • Becoming a maintainer

We use GitHub issues to track public bugs. Report a bug by opening a new issue; it's that easy!

To run examples, make sure you update git submodules to pull down the huff-examples submodule by running git submodule update.

The branching convention used by huff-rs is a stage branch that is meant to be merged off of and is periodically merged into main. So, when creating a feature, branch off of the stage branch and create a pr from your branch into the stage branch!

i.e: Branching Conventions

To pass github actions, please run:

cargo check --all
cargo test --all --all-features
cargo +nightly fmt -- --check
cargo +nightly clippy --all --all-features -- -D warnings

In order to fix any formatting issues, run:

cargo +nightly fmt --all

Recommended PR Template

Here is an example PR template - not strictly required, but will greatly improve the speed at which your PR is reviewed & merged!

## Overview

<Provide a general overview of what your pr accomplishes, why, and how (including links)>

## Checklist

- [x] <Ex: Added a `new` method to the Huff Lexer [here](./huff_lexer/src/lib.rs#50)>
- [x] <Ex: Fully tested the `new` method [here](./huff_lexer/tests/new.rs)>
- [ ] <Ex: Wrote documentation for the `new` method [here](./huff_lexer/README.md#20)>

When the PR checklist isn't complete, it is highly recommended to make it a draft PR. NOTE: if your PR is not complete, it will likely be changed to a draft by one of the repository admins.

For breaking changes: make sure to edit the excalidraw asset and export the file to ./assets/huffc.excalidraw along with an image to ./assets/huffc.png.

Safety

Warning

This is experimental software and is provided on an "as is" and "as available" basis. Expect rapid iteration and use at your own risk.

This code is not designed for safety.

  • There are untested invariants in the code that may break.
  • You can easily shoot yourself in the foot if you're not careful.
  • You should thoroughly read the documentation and examples.

We do not give any warranties and will not be liable for any loss incurred through any use of this codebase.

Acknowledgements

The original Huff Language compiler: huffc.

An exemplary, minimal rust compiler: ripc.

Foundry, for the many scripts, documentation, devops, and code on which huff-rs is based on.

All huff-rs contributors, users, advocates, and enthusiasts!

Download details:

Author: huff-language
Source code: https://github.com/huff-language/huff-rs
License: Apache-2.0 license

#solidity #smartcontract #ethereum #blockchain #rust #evm

Serde Rust: Serialization Framework for Rust

Serde

*Serde is a framework for serializing and deserializing Rust data structures efficiently and generically.*

You may be looking for:

Serde in action

Click to show Cargo.toml. Run this code in the playground.

[dependencies]

# The core APIs, including the Serialize and Deserialize traits. Always
# required when using Serde. The "derive" feature is only required when
# using #[derive(Serialize, Deserialize)] to make Serde work with structs
# and enums defined in your crate.
serde = { version = "1.0", features = ["derive"] }

# Each data format lives in its own crate; the sample code below uses JSON
# but you may be using a different one.
serde_json = "1.0"

 

use serde::{Serialize, Deserialize};

#[derive(Serialize, Deserialize, Debug)]
struct Point {
    x: i32,
    y: i32,
}

fn main() {
    let point = Point { x: 1, y: 2 };

    // Convert the Point to a JSON string.
    let serialized = serde_json::to_string(&point).unwrap();

    // Prints serialized = {"x":1,"y":2}
    println!("serialized = {}", serialized);

    // Convert the JSON string back to a Point.
    let deserialized: Point = serde_json::from_str(&serialized).unwrap();

    // Prints deserialized = Point { x: 1, y: 2 }
    println!("deserialized = {:?}", deserialized);
}

Getting help

Serde is one of the most widely used Rust libraries so any place that Rustaceans congregate will be able to help you out. For chat, consider trying the #rust-questions or #rust-beginners channels of the unofficial community Discord (invite: https://discord.gg/rust-lang-community), the #rust-usage or #beginners channels of the official Rust Project Discord (invite: https://discord.gg/rust-lang), or the #general stream in Zulip. For asynchronous, consider the [rust] tag on StackOverflow, the /r/rust subreddit which has a pinned weekly easy questions post, or the Rust Discourse forum. It's acceptable to file a support issue in this repo but they tend not to get as many eyes as any of the above and may get closed without a response after some time.

Download Details:
Author: serde-rs
Source Code: https://github.com/serde-rs/serde
License: View license

#rust  #rustlang 

Running Rust in the Browser with Web Assembly

I’ve recently been working on a Rust course for the Qvault app. In order to write a more engaging course, I want students to be able to write and execute code right in the browser. As I’ve learned from my previous posts on this topic, the easiest way to sandbox code execution on a server is to not execute code on a server. Enter Web Assembly, stage left.

For those of you who don’t care about how it works, and just want to give it a try, checkout the demo: Rust WASM Playground.

How It Works

The architecture is fairly simple:

  • User writes code in the browser
  • Browser sends code to server
  • Server adds some glue and compiles code to WASM
  • Server sends WASM bytes or compiler errors back to browser
  • Browser runs WASM and displays console output, or shows compiler errors

Writing code and shipping it to the server hopefully needs no explanation, it’s a simple text editor coupled with the fetch API. The first interesting thing we do is compile the code on the server.

Compiling the Code

Qvault’s server is written in Go. I have a simple HTTP handler with the following signature:

func (cfg config) compileRustHandler(w http.ResponseWriter, r *http.Request)

At the start of the function we unmarshal the code which was provided in a JSON body:

type parameters struct {
	Code string
}

decoder := json.NewDecoder(r.Body)
params := parameters{}
err := decoder.Decode(&params)
if err != nil {
	respondWithError(w, 500, "Couldn't decode parameters")
	return
}

Next, we create a temporary folder on disk that we’ll use as a “scratch pad” to create a Rust project.

usr, err := user.Current()
if err != nil {
	respondWithError(w, 500, "Couldn't get system user")
	return
}
workingDir := filepath.Join(usr.HomeDir, ".wasm", uuid.New().String())
err = os.MkdirAll(workingDir, os.ModePerm)
if err != nil {
	respondWithError(w, 500, "Couldn't create directory for compilation")
	return
}
defer func() {
	err = os.RemoveAll(workingDir)
	if err != nil {
		respondWithError(w, 500, "Couldn't clean up code from compilation")
		return
	}
}()

As you can see, we create the project under the .wasm/uuid path in the home directory. We also defer an os.RemoveAll function that will delete this folder when we are doing handling this request.

#golang #languages #rust #wasm #rust #rustlang #wasm #web assembly

Awesome  Rust

Awesome Rust

1654894080

Serde JSON: JSON Support for Serde Framework

Serde JSON

Serde is a framework for serializing and deserializing Rust data structures efficiently and generically.

[dependencies]
serde_json = "1.0"

You may be looking for:

JSON is a ubiquitous open-standard format that uses human-readable text to transmit data objects consisting of key-value pairs.

{
    "name": "John Doe",
    "age": 43,
    "address": {
        "street": "10 Downing Street",
        "city": "London"
    },
    "phones": [
        "+44 1234567",
        "+44 2345678"
    ]
}

There are three common ways that you might find yourself needing to work with JSON data in Rust.

  • As text data. An unprocessed string of JSON data that you receive on an HTTP endpoint, read from a file, or prepare to send to a remote server.
  • As an untyped or loosely typed representation. Maybe you want to check that some JSON data is valid before passing it on, but without knowing the structure of what it contains. Or you want to do very basic manipulations like insert a key in a particular spot.
  • As a strongly typed Rust data structure. When you expect all or most of your data to conform to a particular structure and want to get real work done without JSON's loosey-goosey nature tripping you up.

Serde JSON provides efficient, flexible, safe ways of converting data between each of these representations.

Operating on untyped JSON values

Any valid JSON data can be manipulated in the following recursive enum representation. This data structure is serde_json::Value.

enum Value {
    Null,
    Bool(bool),
    Number(Number),
    String(String),
    Array(Vec<Value>),
    Object(Map<String, Value>),
}

A string of JSON data can be parsed into a serde_json::Value by the serde_json::from_str function. There is also from_slice for parsing from a byte slice &[u8] and from_reader for parsing from any io::Read like a File or a TCP stream.

use serde_json::{Result, Value};

fn untyped_example() -> Result<()> {
    // Some JSON input data as a &str. Maybe this comes from the user.
    let data = r#"
        {
            "name": "John Doe",
            "age": 43,
            "phones": [
                "+44 1234567",
                "+44 2345678"
            ]
        }"#;

    // Parse the string of data into serde_json::Value.
    let v: Value = serde_json::from_str(data)?;

    // Access parts of the data by indexing with square brackets.
    println!("Please call {} at the number {}", v["name"], v["phones"][0]);

    Ok(())
}

The result of square bracket indexing like v["name"] is a borrow of the data at that index, so the type is &Value. A JSON map can be indexed with string keys, while a JSON array can be indexed with integer keys. If the type of the data is not right for the type with which it is being indexed, or if a map does not contain the key being indexed, or if the index into a vector is out of bounds, the returned element is Value::Null.

When a Value is printed, it is printed as a JSON string. So in the code above, the output looks like Please call "John Doe" at the number "+44 1234567". The quotation marks appear because v["name"] is a &Value containing a JSON string and its JSON representation is "John Doe". Printing as a plain string without quotation marks involves converting from a JSON string to a Rust string with as_str() or avoiding the use of Value as described in the following section.

The Value representation is sufficient for very basic tasks but can be tedious to work with for anything more significant. Error handling is verbose to implement correctly, for example imagine trying to detect the presence of unrecognized fields in the input data. The compiler is powerless to help you when you make a mistake, for example imagine typoing v["name"] as v["nmae"] in one of the dozens of places it is used in your code.

Parsing JSON as strongly typed data structures

Serde provides a powerful way of mapping JSON data into Rust data structures largely automatically.

use serde::{Deserialize, Serialize};
use serde_json::Result;

#[derive(Serialize, Deserialize)]
struct Person {
    name: String,
    age: u8,
    phones: Vec<String>,
}

fn typed_example() -> Result<()> {
    // Some JSON input data as a &str. Maybe this comes from the user.
    let data = r#"
        {
            "name": "John Doe",
            "age": 43,
            "phones": [
                "+44 1234567",
                "+44 2345678"
            ]
        }"#;

    // Parse the string of data into a Person object. This is exactly the
    // same function as the one that produced serde_json::Value above, but
    // now we are asking it for a Person as output.
    let p: Person = serde_json::from_str(data)?;

    // Do things just like with any other Rust data structure.
    println!("Please call {} at the number {}", p.name, p.phones[0]);

    Ok(())
}

This is the same serde_json::from_str function as before, but this time we assign the return value to a variable of type Person so Serde will automatically interpret the input data as a Person and produce informative error messages if the layout does not conform to what a Person is expected to look like.

Any type that implements Serde's Deserialize trait can be deserialized this way. This includes built-in Rust standard library types like Vec<T> and HashMap<K, V>, as well as any structs or enums annotated with #[derive(Deserialize)].

Once we have p of type Person, our IDE and the Rust compiler can help us use it correctly like they do for any other Rust code. The IDE can autocomplete field names to prevent typos, which was impossible in the serde_json::Value representation. And the Rust compiler can check that when we write p.phones[0], then p.phones is guaranteed to be a Vec<String> so indexing into it makes sense and produces a String.

The necessary setup for using Serde's derive macros is explained on the Using derive page of the Serde site.

Constructing JSON values

Serde JSON provides a json! macro to build serde_json::Value objects with very natural JSON syntax.

use serde_json::json;

fn main() {
    // The type of `john` is `serde_json::Value`
    let john = json!({
        "name": "John Doe",
        "age": 43,
        "phones": [
            "+44 1234567",
            "+44 2345678"
        ]
    });

    println!("first phone number: {}", john["phones"][0]);

    // Convert to a string of JSON and print it out
    println!("{}", john.to_string());
}

The Value::to_string() function converts a serde_json::Value into a String of JSON text.

One neat thing about the json! macro is that variables and expressions can be interpolated directly into the JSON value as you are building it. Serde will check at compile time that the value you are interpolating is able to be represented as JSON.

let full_name = "John Doe";
let age_last_year = 42;

// The type of `john` is `serde_json::Value`
let john = json!({
    "name": full_name,
    "age": age_last_year + 1,
    "phones": [
        format!("+44 {}", random_phone())
    ]
});

This is amazingly convenient, but we have the problem we had before with Value: the IDE and Rust compiler cannot help us if we get it wrong. Serde JSON provides a better way of serializing strongly-typed data structures into JSON text.

Creating JSON by serializing data structures

A data structure can be converted to a JSON string by serde_json::to_string. There is also serde_json::to_vec which serializes to a Vec<u8> and serde_json::to_writer which serializes to any io::Write such as a File or a TCP stream.

use serde::{Deserialize, Serialize};
use serde_json::Result;

#[derive(Serialize, Deserialize)]
struct Address {
    street: String,
    city: String,
}

fn print_an_address() -> Result<()> {
    // Some data structure.
    let address = Address {
        street: "10 Downing Street".to_owned(),
        city: "London".to_owned(),
    };

    // Serialize it to a JSON string.
    let j = serde_json::to_string(&address)?;

    // Print, write to a file, or send to an HTTP server.
    println!("{}", j);

    Ok(())
}

Any type that implements Serde's Serialize trait can be serialized this way. This includes built-in Rust standard library types like Vec<T> and HashMap<K, V>, as well as any structs or enums annotated with #[derive(Serialize)].

Performance

It is fast. You should expect in the ballpark of 500 to 1000 megabytes per second deserialization and 600 to 900 megabytes per second serialization, depending on the characteristics of your data. This is competitive with the fastest C and C++ JSON libraries or even 30% faster for many use cases. Benchmarks live in the serde-rs/json-benchmark repo.

Getting help

Serde is one of the most widely used Rust libraries, so any place that Rustaceans congregate will be able to help you out. For chat, consider trying the #rust-questions or #rust-beginners channels of the unofficial community Discord (invite: https://discord.gg/rust-lang-community), the #rust-usage or #beginners channels of the official Rust Project Discord (invite: https://discord.gg/rust-lang), or the #general stream in Zulip. For asynchronous, consider the [rust] tag on StackOverflow, the /r/rust subreddit which has a pinned weekly easy questions post, or the Rust Discourse forum. It's acceptable to file a support issue in this repo, but they tend not to get as many eyes as any of the above and may get closed without a response after some time.

No-std support

As long as there is a memory allocator, it is possible to use serde_json without the rest of the Rust standard library. This is supported on Rust 1.36+. Disable the default "std" feature and enable the "alloc" feature:

[dependencies]
serde_json = { version = "1.0", default-features = false, features = ["alloc"] }

For JSON support in Serde without a memory allocator, please see the serde-json-core crate.

Link: https://crates.io/crates/serde_json

#rust  #rustlang  #encode   #json 

Ananya Gupta

Ananya Gupta

1594464365

Advantage of C Language Certification Online Training in 2020

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The companies which are using C language are Amazon, Martin, Apple, Samsung, Google, Oracle, Nokia, IBM, Intel, Novell, Microsoft, Facebook, Bloomberg, VM Ware, etc.
C language is used in different domains like banking, IT, Insurance, Education, Gaming, Networking, Firmware, Telecommunication, Graphics, Management, Embedded, Application Development, Driver level Development, Banking, etc.

The job opportunities after completing the C Language Online certificationAre Data Scientists, Back End Developer, Embedded Developer, C Analyst, Software Developer, Junior Programmer, Database Developer, Embedded Engineer, Programming Architect, Game Programmer, Quality Analyst, Senior Programmer, Full Stack Developer, DevOps Specialist, Front End Web Developer, App Developer, Java Software Engineer, Software Developer and many more.

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