New to Rust and don't yet know what crates to use? stdx has the best crates.
Current revision: stdx
0.119.0-rc, for Rust 1.19, July 20, 2017.
Β Β Β
bitflags = "0.9.1"
β π
The only thing this crate does is export the bitflags!
macro, but
it's a heckuva-useful macro. bitflags!
produces typesafe bitmasks,
types with named values that are efficiently packed together as bits
to express sets of options.
Example: examples/bitflags.rs
#[macro_use]
extern crate bitflags;
bitflags! {
struct Flags: u32 {
const FLAG_A = 0b00000001;
const FLAG_B = 0b00000010;
const FLAG_C = 0b00000100;
const FLAG_ABC = FLAG_A.bits
| FLAG_B.bits
| FLAG_C.bits;
}
}
fn main() {
let e1 = FLAG_A | FLAG_C;
let e2 = FLAG_B | FLAG_C;
assert_eq!((e1 | e2), FLAG_ABC); // union
assert_eq!((e1 & e2), FLAG_C); // intersection
assert_eq!((e1 - e2), FLAG_A); // set difference
assert_eq!(!e2, FLAG_A); // set complement
}
Β Β Β
byteorder = "1.1.0"
β π
When serializing integers it's important to consider that not all computers store in memory the individual bytes of the number in the same order. The choice of byte order is called "endianness", and this simple crate provides the crucial functions for converting between numbers and bytes, in little-endian, or big-endian orders.
Example: examples/byteorder.rs
extern crate byteorder;
use std::io::Cursor;
use byteorder::{BigEndian, ReadBytesExt};
use byteorder::{LittleEndian, WriteBytesExt};
fn main() {
// Read unsigned 16 bit big-endian integers from a Read type:
let mut rdr = Cursor::new(vec![2, 5, 3, 0]);
// Note that we use type parameters to indicate which kind of byte
// order we want!
assert_eq!(517, rdr.read_u16::<BigEndian>().unwrap());
assert_eq!(768, rdr.read_u16::<BigEndian>().unwrap());
// Write unsigned 16 bit little-endian integers to a Write type:
let mut wtr = vec![];
wtr.write_u16::<LittleEndian>(517).unwrap();
wtr.write_u16::<LittleEndian>(768).unwrap();
assert_eq!(wtr, vec![5, 2, 0, 3]);
}
Β Β Β
chrono = "0.4.0"
β π
Date and time types.
Example: examples/chrono.rs
extern crate chrono;
use chrono::*;
fn main() {
let local: DateTime<Local> = Local::now();
let utc: DateTime<Utc> = Utc::now();
let dt = Utc.ymd(2014, 11, 28).and_hms(12, 0, 9);
assert_eq!((dt.year(), dt.month(), dt.day()), (2014, 11, 28));
assert_eq!((dt.hour(), dt.minute(), dt.second()), (12, 0, 9));
assert_eq!(dt.format("%Y-%m-%d %H:%M:%S").to_string(), "2014-11-28 12:00:09");
assert_eq!(dt.format("%a %b %e %T %Y").to_string(), "Fri Nov 28 12:00:09 2014");
assert_eq!(format!("{}", dt), "2014-11-28 12:00:09 UTC");
}
Β Β Β
clap = "2.25.0"
β π
Clap is a command line argument parser that is easy to use and is highly configurable.
Example: examples/clap.rs
extern crate clap;
use clap::{Arg, App, SubCommand};
fn main() {
let app = App::new("My Super Program")
.version("1.0")
.author("Kevin K. <kbknapp@gmail.com>")
.about("Does awesome things")
.arg(Arg::with_name("config")
.short("c")
.long("config")
.value_name("FILE")
.help("Sets a custom config file")
.takes_value(true))
.arg(Arg::with_name("INPUT")
.help("Sets the input file to use")
.required(true)
.index(1))
.subcommand(SubCommand::with_name("test")
.about("controls testing features")
.arg(Arg::with_name("debug")
.short("d")
.help("print debug information verbosely")));
// Parse the command line arguments
let matches = app.get_matches();
let config = matches.value_of("config").unwrap_or("default.conf");
let input = matches.value_of("INPUT").unwrap();
// Handle subcommands
match matches.subcommand() {
("clone", Some(sub_matches)) => {
if matches.is_present("d") {
// ...
}
},
("push", Some(sub_matches)) => {},
("commit", Some(sub_matches)) => {},
_ => {},
}
}
Alternatives: docopt
Β Β Β
encoding_rs = "0.6.11"
β π
encoding_rs is a Gecko-oriented Free Software / Open Source implementation of the Encoding Standard in Rust. Gecko-oriented means that converting to and from UTF-16 is supported in addition to converting to and from UTF-8, that the performance and streamability goals are browser-oriented, and that FFI-friendliness is a goal.
Example: examples/encoding_rs.rs
extern crate encoding_rs;
use encoding_rs::*;
fn main() {
let expected = "\u{30CF}\u{30ED}\u{30FC}\u{30FB}\u{30EF}\u{30FC}\u{30EB}\u{30C9}";
let encoded = b"\x83n\x83\x8D\x81[\x81E\x83\x8F\x81[\x83\x8B\x83h";
let (decoded, encoding_used, had_errors) = SHIFT_JIS.decode(encoded);
assert_eq!(&decoded[..], expected);
assert_eq!(encoding_used, SHIFT_JIS);
assert!(!had_errors);
println!("Decoded result: {}", decoded);
}
Β Β Β
error-chain = "0.10.0"
β π
Rust programs that handle errors consistently are reliable programs.
Even after one understands error handling in Rust, it can be
difficult to grasp and implement its best practices. error-chain
helps you define your own error type that works with the ?
operator
to make error handling in Rust simple and elegant.
Example: examples/error-chain.rs
// `error_chain!` can recurse deeply
#![recursion_limit = "1024"]
#[macro_use]
extern crate error_chain;
// We'll put our errors in an `errors` module, and other modules in
// this crate will `use errors::*;` to get access to everything
// `error_chain!` creates.
mod errors {
// Create the Error, ErrorKind, ResultExt, and Result types
error_chain! { }
}
use errors::*;
fn main() {
if let Err(ref e) = run() {
use ::std::io::Write;
let stderr = &mut ::std::io::stderr();
let errmsg = "Error writing to stderr";
writeln!(stderr, "error: {}", e).expect(errmsg);
for e in e.iter().skip(1) {
writeln!(stderr, "caused by: {}", e).expect(errmsg);
}
// The backtrace is not always generated. Try to run this example
// with `RUST_BACKTRACE=1`.
if let Some(backtrace) = e.backtrace() {
writeln!(stderr, "backtrace: {:?}", backtrace).expect(errmsg);
}
::std::process::exit(1);
}
}
// Most functions will return the `Result` type, imported from the
// `errors` module. It is a typedef of the standard `Result` type
// for which the error type is always our own `Error`.
fn run() -> Result<()> {
use std::fs::File;
// Use chain_err to attach your own context to errors
File::open("my secret file")
.chain_err(|| "unable to open my secret file")?;
// Use the `bail!` macro to return an error Result, ala `println!`
bail!("giving up");
}
Alternatives: quick-error
Β Β Β
flate2 = "0.2.19"
β π
Compression and decompression using the DEFLATE algorithm.
Example: examples/flate2.rs
extern crate flate2;
extern crate tar;
use flate2::read::GzDecoder;
use std::env;
use std::fs::File;
use std::io::{self, BufReader};
use tar::Archive;
fn run() -> Result<(), io::Error> {
let mut args = env::args().skip(1);
let tarball = args.next().expect("incorrect argument");
let outdir = args.next().expect("incorrect argument");
let archive = File::open(tarball)?;
let archive = BufReader::new(archive);
let archive = GzDecoder::new(archive)?;
let mut archive = Archive::new(archive);
archive.unpack(outdir)?;
Ok(())
}
fn main() { run().unwrap() }
Β Β Β
fnv = "1.0.5"
β π
The standard library's hash maps are notoriously slow for small keys (like
integers). That's because they provide strong protection against a class of
denial-of-service attacks called "hash flooding". And that's a reasonable
default. But when your HashMap
s are a bottleneck consider reaching for this
crate. It provides the Fowler-Noll-Vo hash function, and conveniences for
creating FNV hash maps that are considerably faster than those in std.
Example: examples/fnv.rs
extern crate fnv;
use fnv::FnvHashMap;
fn main() {
let mut map = FnvHashMap::default();
map.insert(1, "one");
map.insert(2, "two");
map.insert(3, "three");
for (number, word) in map.iter() {
println!("Number {}: {}", number, word);
}
map.remove(&(2));
println!("The length of HashMap is {}.", map.len());
println!("The first element is {}.", map.get(&(1)).unwrap());
}
Β Β Β
itertools = "0.6.0"
β π
The Rust standard Iterator
type provides a powerful abstraction for
operating over sequences of values, and is used pervasively throughout
Rust. There are though a number of common operations one might want to perform
on sequences that are not provided by the standard library, and that's where
itertools comes in. This crate has everything including the kitchen sink (in
the form of the batching
adaptor). Highlights include dedup
, group_by
,
mend_slices
, merge
, sorted
, join
and more.
Example: examples/itertools.rs
extern crate itertools;
use itertools::{join, max, sorted};
fn main(){
let a = [3, 2, 5, 8, 7];
// Combine all iterator elements into one String,
// seperated by *.
println!("{:?}", join(&a, "*"));
// Return the maximum value of the iterable.
println!("{:?}", max(a.iter()).unwrap());
// Collect all the iterable's elements into a
// sorted vector in ascending order.
println!("{:?}", sorted(a.iter()));
}
Β Β Β
lazy_static = "0.2.8"
β π
Rust has strict rules about accessing global state. In particular
there is no 'life before main' in Rust, so it's not possible to
write a programmatic constructor for a global value that will be run
at startup. Instead, Rust prefers lazy execution for global
initialization, and the lazy_static!
macro does just that.
Example: examples/lazy_static.rs
#[macro_use]
extern crate lazy_static;
use std::collections::HashMap;
lazy_static! {
static ref HASHMAP: HashMap<u32, &'static str> = {
let mut m = HashMap::new();
m.insert(0, "foo");
m.insert(1, "bar");
m.insert(2, "baz");
m
};
static ref COUNT: usize = HASHMAP.len();
static ref NUMBER: u32 = times_two(21);
}
fn times_two(n: u32) -> u32 { n * 2 }
fn main() {
println!("The map has {} entries.", *COUNT);
println!("The entry for `0` is \"{}\".", HASHMAP.get(&0).unwrap());
println!("A expensive calculation on a static results in: {}.", *NUMBER);
}
Β Β Β
libc = "0.2.25"
β π
If you need to talk to foreign code, you need this crate. It exports C
type and function definitions appropriate to each target platform Rust
supports. It defines the standardized C features that are common
across all platforms as well as non-standard features specific to the
platform C libraries. For more platform-specific FFI definitions
see nix
and winapi
.
Example: examples/libc.rs
extern crate libc;
fn main() {
unsafe {
libc::exit(0);
}
}
Β Β Β
log = "0.3.8"
β π
The most common way to perform basic logging in Rust, with the
error!
, warn!
, info!
, and debug!
macros. It is often
combined with the env_logger
crate to get logging to the console,
controlled by the RUST_LOG
environment variable. This is the
traditional logging crate used by rustc
, and its functionality was
once built in to the language.
Supplemental crates: env_logger = "0.4.3"
Example: examples/log.rs
#[macro_use]
extern crate log;
extern crate env_logger;
use log::LogLevel;
fn main() {
env_logger::init().unwrap();
debug!("this is a debug {}", "message");
error!("this is printed by default");
if log_enabled!(LogLevel::Info) {
let x = 3 * 4; // expensive computation
info!("the answer was: {}", x);
}
}
Β Β Β
memmap = "0.5.2"
β π
Cross-platform access to memory-mapped I/O, a technique for sharing
memory between processes, and for accessing the content of files as a
simple array of bytes. It is implemented by binding the mmap
syscall on Unix, and the CreateFileMapping
/ MapViewOfFile
functions on Windows. This is a low-level feature used to build other
abstractions. Note that it's not generally possible to create safe
abstractions for memory mapping, since memory mapping entails shared
access to resources outside of Rust's control. As such, the APIs
in this crate are unsafe.
Example: examples/memmap.rs
extern crate memmap;
use memmap::{Mmap, Protection};
use std::env;
use std::io;
use std::str;
fn run() -> Result<(), io::Error> {
let mut args = env::args().skip(1);
let input = args.next().expect("incorrect argument");
let map = Mmap::open_path(input, Protection::Read)?;
unsafe {
let all_bytes = map.as_slice();
if let Ok(file_str) = str::from_utf8(all_bytes) {
println!("{}", file_str);
} else {
println!("not utf8");
}
}
Ok(())
}
fn main() { run().unwrap() }
Β Β Β
ndarray = "0.9.1"
β π
The ndarray crate provides an N-dimensional container for general elements and for numerics. The multidimensional array, otherwise known as a "matrix", is a core data structure for numerical applications, and Rust does not have one in the language or standard library.
Example: examples/ndarray.rs
#[macro_use(s)]
extern crate ndarray;
use ndarray::{Array3, arr3};
fn main() {
// Create a three-dimensional f64 array, initialized with zeros
let mut temperature = Array3::<f64>::zeros((3, 4, 5));
// Increase the temperature in this location, notice the
// double-brackets indexing `temperature`
temperature[[2, 2, 2]] += 0.5;
// Create a 3-dimensional matrix,
// 2 submatrices of 2 rows with 3 elements per row, means a shape
// of `[2, 2, 3]`.
let a = arr3(&[[[ 1, 2, 3], // -- 2 rows \_
[ 4, 5, 6]], // -- /
[[ 7, 8, 9], // \_ 2 submatrices
[10, 11, 12]]]); // /
// 3 columns ..../.../.../
// This is a 2 x 2 x 3 array
assert_eq!(a.shape(), &[2, 2, 3]);
// Letβs create a slice of `a` with
//
// - Both of the submatrices of the greatest dimension: `..`
// - Only the first row in each submatrix: `0..1`
// - Every element in each row: `..`
let b = a.slice(s![.., 0..1, ..]);
// This is the result of the above slice into `a`
let c = arr3(&[[[ 1, 2, 3]],
[[ 7, 8, 9]]]);
assert_eq!(b, c);
assert_eq!(b.shape(), &[2, 1, 3]);
}
Β Β Β
num = "0.1.40"
β π
Big integers, rational numbers, complex numbers, and numeric traits. This crate has a long history, beginning life in the standard library, being moved into the rust-lang organization, and finally being adopted by community maintainers. It remains a common way to access the kinds of features it provides.
Example: examples/num.rs
extern crate num;
use num::FromPrimitive;
use num::bigint::BigInt;
use num::rational::{Ratio, BigRational};
fn approx_sqrt(number: u64, iterations: usize) -> BigRational {
let start: Ratio<BigInt>
= Ratio::from_integer(FromPrimitive::from_u64(number).unwrap());
let mut approx = start.clone();
for _ in 0..iterations {
approx = (&approx + (&start / &approx)) /
Ratio::from_integer(FromPrimitive::from_u64(2).unwrap());
}
approx
}
fn main() {
println!("{}", approx_sqrt(10, 4)); // prints 4057691201/1283082416
}
Β Β Β
num_cpus = "1.6.2"
β π
When you need to make things parallel, you need to know how many CPUs to use! This is the simple way to get that information.
Example: examples/num_cpus.rs
extern crate threadpool;
extern crate num_cpus;
use threadpool::ThreadPool;
use std::sync::mpsc::channel;
fn main() {
// Get the number of cpus on current machine
let n_workers = num_cpus::get();
let n_jobs = 8;
// Create the thread pool with amount of workers equal to cores
let pool = ThreadPool::new(n_workers);
// Create transmitter and receiver channel
let (tx, rx) = channel();
// For each job grab a free worker from the pool and execute
for _ in 0..n_jobs {
let tx = tx.clone();
pool.execute(move || {
tx.send(1).unwrap();
});
}
assert_eq!(rx.iter().take(n_jobs).fold(0, |a, b| a + b), 8);
}
Β Β Β
rand = "0.3.15"
β π
Random number generators. The defaults are cryptographically strong. This is another crate with a long history, beginning life in the standard library.
Example: examples/rand.rs
extern crate rand;
use rand::Rng;
fn main() {
let mut rng = rand::thread_rng();
if rng.gen() { // random bool
println!("i32: {}, u32: {}", rng.gen::<i32>(), rng.gen::<u32>())
}
let tuple = rand::random::<(f64, char)>();
println!("{:?}", tuple)
}
Β Β Β
rayon = "0.8.2"
β π
When people say that Rust makes parallelism easy, this is why. Rayon provides parallel iterators that make expressing efficient parallel operations simple and foolproof.
Example: examples/rayon.rs
extern crate rayon;
use rayon::prelude::*;
fn main() {
let mut input = (0..1000).collect::<Vec<_>>();
// Calculate the sum of squares
let sq_sum: i32 = input.par_iter()
.map(|&i| i * i)
.sum();
// Increment each element in parallel
input.par_iter_mut()
.for_each(|p| *p += 1);
// Parallel quicksort
let mut input = (0..1000).rev().collect::<Vec<_>>();
quick_sort(&mut input);
}
fn quick_sort<T: PartialOrd + Send>(v: &mut [T]) {
if v.len() <= 1 {
return;
}
let mid = partition(v);
let (lo, hi) = v.split_at_mut(mid);
rayon::join(|| quick_sort(lo), || quick_sort(hi));
}
fn partition<T: PartialOrd + Send>(v: &mut [T]) -> usize {
let pivot = v.len() - 1;
let mut i = 0;
for j in 0..pivot {
if v[j] <= v[pivot] {
v.swap(i, j);
i += 1;
}
}
v.swap(i, pivot);
i
}
Β Β Β
regex = "0.2.2"
β π
Rust's regular expressions are fast, like Rust is fast. Part of their power comes from a careful design that disallows back-references and arbitrary lookahead, creating predictable worst-case performance.
Example: examples/regex.rs
extern crate regex;
use regex::Regex;
fn main() {
// Find a date
let re = Regex::new(r"^\d{4}-\d{2}-\d{2}$").unwrap();
assert!(re.is_match("2014-01-01"));
// Iterating over capture groups
let re = Regex::new(r"(\d{4})-(\d{2})-(\d{2})").unwrap();
let text = "2012-03-14, 2013-01-01 and 2014-07-05";
for cap in re.captures_iter(text) {
println!("Month: {} Day: {} Year: {}", &cap[2], &cap[3], &cap[1]);
}
}
Β Β Β
reqwest = "0.7.1"
β π
A simple HTTP and HTTPS client. It is built on the popular Rust HTTP implementation, hyper, which is the HTTP stack developed for Servo.
Example: examples/reqwest.rs
extern crate reqwest;
use std::collections::HashMap;
use std::io::{BufRead, BufReader};
fn main() {
// Make a GET request
let resp = reqwest::get("https://www.rust-lang.org").unwrap();
assert!(resp.status().is_success());
let lines = BufReader::new(resp)
.lines()
.filter_map(|l| l.ok())
.take(10);
for line in lines {
println!("{}", line);
}
// Make a POST request
let client = reqwest::Client::new().unwrap();
let res = client.post("http://httpbin.org/post").unwrap()
.body("the exact body that is sent")
.send();
// Convert to/from JSON automatically
let mut map = HashMap::new();
map.insert("lang", "rust");
map.insert("body", "json");
// This will POST a body of `{"lang":"rust","body":"json"}`
let client = reqwest::Client::new().unwrap();
let res = client.post("http://httpbin.org/post").unwrap()
.json(&map).unwrap()
.send();
}
Β Β Β
semver = "0.7.0"
β π
Rust uses semantic versioning (also known as "semver") for crate versioning. This crate provides the canonical semver representation for Rust.
Example: examples/semver.rs
extern crate semver;
use semver::Version;
fn main() {
// Construct Version objects
assert!(Version::parse("1.2.3") == Ok(Version {
major: 1,
minor: 2,
patch: 3,
pre: vec!(),
build: vec!(),
}));
// Compare Versions
assert!(Version::parse("1.2.3-alpha") != Version::parse("1.2.3-beta"));
assert!(Version::parse("1.2.3-alpha2") > Version::parse("1.2.0"));
// Increment patch number of mutable Version
let mut bugfix_release = Version::parse("1.0.0").unwrap();
bugfix_release.increment_patch();
assert_eq!(Ok(bugfix_release), Version::parse("1.0.1"));
}
Β Β Β
serde = "1.0.10"
β π
Serialization and deserialization of Rust datastructures is fast
and easy using the serde
serialization framework. Simply
tag your data structures with #[derive(Serialize, Deserialize)]
and serde will automatically convert them between formats like
JSON, TOML, YAML, and more. To best understand serde, read
its documentation at serde.rs.
Supplemental crates: serde_derive = "1.0.10"
,
serde_json = "1.0.2"
,
toml = "0.4.2"
Example: examples/serde.rs
#[macro_use]
extern crate serde_derive;
extern crate serde_json;
use serde_json::Value;
#[derive(Serialize, Deserialize, Debug)]
struct Contact {
name: String,
age: u32,
}
fn main() {
let contact = Contact {
name: "Brian".to_string(),
age: 21,
};
// Serialize data structures to strings in JSON format
let contact: String = serde_json::to_string(&contact).unwrap();
println!("{}", contact);
// Deserialize data structures from JSON strings
let contact: Contact = serde_json::from_str(&contact).unwrap();
println!("{:?}", contact);
// Convert to arbitrary JSON `Value` type
let contact: Value = serde_json::to_value(&contact).unwrap();
println!("{:?}", contact);
}
Alternatives: rustc-serialize
Β Β Β
serde_json = "1.0.2"
β π
Access to JSON, the "JavaScript Object Notation" format, widely used for transmission and storage of data on the Internet. This crate can be used for reading, writing, and manipulation of arbitrary JSON in addition to its use for automatic serialization with serde.
Example: examples/json.rs
extern crate serde_json;
use serde_json::Value;
fn main() {
// 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).unwrap();
// Access parts of the data by indexing with square brackets.
println!("Please call {} at the number {}", v["name"], v["phones"][0]);
}
Alternatives: json
Β Β Β
tar = "0.4.23"
β π
The "tar" archive format is in common use on the web. It is most often
found in the form of .tar.gz
files (called "tarballs") that have
been compressed with the DEFLATE algorithm, which the tar
crate
can decompress when paired with the flate2
crate.
Example: examples/tar.rs
extern crate flate2;
extern crate tar;
use flate2::read::GzDecoder;
use std::env;
use std::fs::File;
use std::io::{self, BufReader};
use tar::Archive;
fn run() -> Result<(), io::Error> {
let mut args = env::args().skip(1);
let tarball = args.next().expect("incorrect argument");
let outdir = args.next().expect("incorrect argument");
let archive = File::open(tarball)?;
let archive = BufReader::new(archive);
let archive = GzDecoder::new(archive)?;
let mut archive = Archive::new(archive);
archive.unpack(outdir)?;
Ok(())
}
fn main() { run().unwrap() }
Β Β Β
tempdir = "0.3.5"
β π
The most common way to create temporary directories in Rust, this crate was once part of the standard library.
Example: examples/tempdir.rs
extern crate tempdir;
use std::fs::File;
use std::io::Write;
use tempdir::TempDir;
fn main() {
// Create a directory inside of `std::env::temp_dir()`, named with
// the prefix "example".
let tmp_dir = TempDir::new("example").expect("create temp dir");
let file_path = tmp_dir.path().join("my-temporary-note.txt");
let mut tmp_file = File::create(file_path).expect("create temp file");
writeln!(tmp_file, "Brian was here. Briefly.").expect("write temp file");
// By closing the `TempDir` explicitly, we can check that it has
// been deleted successfully. If we don't close it explicitly,
// the directory will still be deleted when `tmp_dir` goes out
// of scope, but we won't know whether deleting the directory
// succeeded.
drop(tmp_file);
tmp_dir.close().expect("delete temp dir");
}
Β Β Β
threadpool = "1.4.0"
β π
A thread pool for running a number of jobs on a fixed set of worker threads.
Example: examples/threadpool.rs
extern crate threadpool;
extern crate num_cpus;
use threadpool::ThreadPool;
use std::sync::mpsc::channel;
fn main() {
// Get the number of cpus on current machine
let n_workers = num_cpus::get();
let n_jobs = 8;
// Create the thread pool with amount of workers equal to cores
let pool = ThreadPool::new(n_workers);
// Create transmitter and receiver channel
let (tx, rx) = channel();
// For each job grab a free worker from the pool and execute
for _ in 0..n_jobs {
let tx = tx.clone();
pool.execute(move || {
tx.send(1).unwrap();
});
}
assert_eq!(rx.iter().take(n_jobs).fold(0, |a, b| a + b), 8);
}
Alternatives: scoped_threadpool
Β Β Β
toml = "0.4.2"
β π
TOML is a common format for
configuration files, like Cargo.toml. It's easy on the eyes, simple
to parse, and serializes from Rust types with serde
.
Example: examples/toml.rs
extern crate toml;
use toml::Value;
fn main() {
let toml = r#"
[test]
foo = "bar"
"#;
let value = toml.parse::<Value>().unwrap();
println!("{:?}", value);
}
Β Β Β
url = "1.5.1"
β π
The URL parser and type, originally created for Servo.
Example: examples/url.rs
extern crate url;
use url::{Url, Host};
fn main() {
let issue_list_url = Url::parse(
"https://github.com/rust-lang/rust/issues?labels=E-easy&state=open"
).unwrap();
assert!(issue_list_url.scheme() == "https");
assert!(issue_list_url.username() == "");
assert!(issue_list_url.password() == None);
assert!(issue_list_url.host_str() == Some("github.com"));
assert!(issue_list_url.host() == Some(Host::Domain("github.com")));
assert!(issue_list_url.port() == None);
assert!(issue_list_url.path() == "/rust-lang/rust/issues");
assert!(issue_list_url.path_segments().map(|c| c.collect::<Vec<_>>()) ==
Some(vec!["rust-lang", "rust", "issues"]));
assert!(issue_list_url.query() == Some("labels=E-easy&state=open"));
assert!(issue_list_url.fragment() == None);
assert!(!issue_list_url.cannot_be_a_base());
}
Β Β Β
walkdir = "1.0.7"
β π
A cross platform Rust library for efficiently walking a directory
recursively. Note the filter_entry
method on the directory
iterator that short-circuits decent into subdirectories.
Example: examples/walkdir.rs
extern crate walkdir;
use walkdir::{WalkDir, Error};
fn run() -> Result<(), Error> {
let wd = WalkDir::new(".");
for entry in wd {
let entry = entry?;
println!("{}", entry.path().display());
}
Ok(())
}
fn main() { run().unwrap(); }
Β Β Β
Rust has a lovely and portable standard library, but it is not featureful enough to write software of any great sophistication. Compared to common platforms including Java, Python, and Go, Rust's standard library is small.
In Rust, the libraries we use for even simple tasks live and evolve on crates.io. This affords the Rust community freedom to experiment - discovering the Rustiest solutions to even common problems can take quite some iteration - but it also means that we're in for a slow evolutionary process to converge around the best of those solutions. In the meantime, you just have to know which crates to use for what.
stdx
contains some of the most important crates in Rust. I mean
it. If Rust had a more expansive standard library, many of the stdx
crates would be in it, or at least the features they provide. Many of
the crates of stdx
are maintained by the same authors as the Rust
standard library, and they are designed to be idiomatic and
interoperable. These are core elements of the crate ecosystem that
all Rusticians should be aware of.
stdx
is primarily a teaching tool. New and old Rust programmers
alike will get the most from it by digesting the list of
stdx
crates, each entry of which links to a description of the crate
along with an example of its basic use.
These examples are full working source and are intended to get you
up and running with any of the stdx
crates immediately. Just
copy the crate name and version exactly as written into the dependencies
section of your Cargo.toml
like so:
[dependencies]
bitflags = "0.9.1"
Then copy the full example into your examples
directory, like
so:
Example: examples/bitflags.rs
#[macro_use]
extern crate bitflags;
bitflags! {
struct Flags: u32 {
const FLAG_A = 0b00000001;
const FLAG_B = 0b00000010;
const FLAG_C = 0b00000100;
const FLAG_ABC = FLAG_A.bits
| FLAG_B.bits
| FLAG_C.bits;
}
}
fn main() {
let e1 = FLAG_A | FLAG_C;
let e2 = FLAG_B | FLAG_C;
assert_eq!((e1 | e2), FLAG_ABC); // union
assert_eq!((e1 & e2), FLAG_C); // intersection
assert_eq!((e1 - e2), FLAG_A); // set difference
assert_eq!(!e2, FLAG_A); // set complement
}
Then execute the following:
cargo run --example bitflags
And suddenly you are a slightly-experienced user of that crate. Now click on the π icon to get the rest of the story.
Convinced? Go check out that list.
As a learning tool, I hope the benefit will be evident from a straight
read-through. But stdx
, and tools like it, may provide important
benefits to users in the future.
To be clear, stdx
is experimental. A lot of the below is
speculative.
stdx
provides assurances that the versions of crates it specifes
work together correctly in a wide variety of configurations. Today
those assurances are few, but they will grow. And these types of
assurances will become increasingly valuable to Rust.
As of now, the only validation stdx
provides is that the exact
versions of the stdx
crates resolve correctly by Cargo, and that
they build on Linux and Windows. That is already beneficial by
uncovering problematic combinations and incorrect semver
specifications. Here are some other assurances that stdx
will
enable:
- Additional integration test cases between the
stdx
crates - Testing of all
stdx
crates' own test suites using thestdx
version lock - Testing on all tier 1 platforms
- Testing on tier 2 platforms
- Enforcement and coverage of
serde
features and interop - Enforcement of other compile-time feature standards
stdx
as version lock - you don't even have to call into it. Just link to it and it locks down a chunk of your crate graph to known-good combinaitons.- Ecosystem wide testing using
stdx
version lock - eventually we will be able to say which crates are known to work correctly withstdx
. - The more people use the
stdx
version lock the more assurance they get. This plays into future Rust's LTS directions.
By applying high quality standards to a small selection of critical crates we can create a high degree of confidence in a larger core of the Rust ecosystem.
The criteria for inclusion in stdx
is conservative, and fuzzy. It's
mostly crates that are pretty super important, considering criteria
like
- portability
- quality
- conformance to conventions
- documentation
- interoperability with other crates
- reliability of maintainers
- de-facto adoption
- historical context and precedent
stdx
is focused on core features, crates that are quintessentially
Rust and relied on by many Rust programs. It is intentionally
limited for the sake of simplicity and ease of comprehension.
All crates must work on Rust's tier-1 platforms, currently x86 Linux, OS X, and Windows.
See CONTRIBUTING.md.
stdx
and the crates it links to are licensed under various
permissive, BSD-like licenses. In lay-terms these licenses
allow their code to be used and distributed freely, and are compatible
with Rust's own license (MIT/Apache 2).
stdx
itself is dual MIT/Apache 2 licensed, like Rust, and the
copyright is owned by its contributors.