Rust testing, data generation and const asserts

栏目: IT技术 · 发布时间: 4年前

内容简介:Luckily getting starting with testing Rust code is reasonably straightforward and no external libraries are needed.Using the right tools will help make your tests more effective. Below are data generation libraries that can increase the coverage of your te

Basic Rust test example

Luckily getting starting with testing Rust code is reasonably straightforward and no external libraries are needed. cargo test will run all test code in a Rust project. Test code is identified with the code attributes #[cfg(test)] and #[test] . For the placement of the test code, units tests are added at the end of a source code file and integration tests can be placed in their own tests directory.

// Minimal Rust tests examplefn double(x: u8)
  -> u8
  {
x * 2
}
#[cfg(test)]
mod tests {
// import all from the parent scope into this scope
use super::*;
#[test]
fn test_double() {
assert_eq!(double(2), 4);
}
#[test]
fn test_error_and_none() {
assert!("not a number".parse::<u32>().is_err());
assert_eq!("not a number".parse::<u32>().ok(), None);
assert_eq!("4".parse::<u32>(), Ok(4));
}
}
$ cargo test
test result: ok. 1 passed; 0 failed; 0 ignored; 0 measured; 0 filtered out

Data generation

Using the right tools will help make your tests more effective. Below are data generation libraries that can increase the coverage of your tests.

Mock data

The fake-rs library contains an extensive list of functions to generate mock data (Lorem, Name, Internet, HTTP, Company, Address, Date/Time).

use fake::{Faker};
use fake::locales::{EN, ZH_TW};
assert!(test_person(FirstName(EN).fake(), LastName(EN).fake()));
assert!(test_ip_processing(IPv6(EN).fake(), MACAddress(EN).fake()));
let hash_map: HashMap<u8, u32> = Faker.fake();
println!("HashMap {:?}", hash_map);

Regex and arbitrary input tests

proptest tests that certain properties of rust code hold for arbitrary inputs and, if a failure is found, automatically finds the minimal test case to reproduce the problem.

proptest! {
#[test]
fn parses_all_valid_dates(s in "[0-9]{4}-[0-9]{2}-[0-9]{2}") {
parse_date(&s).unwrap();
}
}

Machine learning generated tests

The test-data-generation library trains a model on sample data, and then can generate additional data matching the format of the samples. The library uses a Markov decision process to build a model of the data.

use test_data_generation::data_sample_parser::DataSampleParser;let mut dsp = DataSampleParser::new();
// train on data contained in a CSV file
dsp.analyze_csv_file("user_data.csv".to_string())?;
// generate data from a trained model
println!(dsp.generate_record());

Add these libraries under your [dev-dependencies] in the Cargo.toml file

# Cargo.toml[dev-dependencies]
fake = "2.0"
test-data-generation = "0.1.1"
proptest = "0.9.5"

Debug asserts

debug_asserts statements can check preconditions, postconditions and invariants in the body of your code. They are only included and executed when your code is run in debug mode and are removed for production builds.

fn double(x: u8) {
debug_assert!(x > 0, "Precondition - x must be positive");
let doubled = x * 2;
debug_assert_eq!(doubled, x * 2);
return doubled;
}

Doc tests

Built into the compiler is the ability to run tests in documentation comments. By default cargo test will execute tests in documentation and report failures

/// # Examples
///
/// ```
/// let x = 5;
/// assert_eq!(x, 5);
/// ```

Const asserts

static_assertions ensure conditions are met for const functions and const data. The const asserts will prevent code from compiling if they don’t pass.

// static_assertions = "1.1.0"
#[macro_use]
extern crate static_assertions;
const MY_CONFIG: Config = ConfigConfig {
foo: 10,
bar: 20,
};
const_assert!(MY_CONFIG.bar > MY_CONFIG.foo);

Other cargo commands

Run only tests matching a pattern

cargo test test_double

Run tests not marked with the #[ignore] attribute

cargo test -- --ignored

Watch the project and run cargo test after any code changes

cargo install cargo-watch
cargo watch -x test

Examples Tests

For an examples of well-done tests check out the Rust standard library code

About me

I’m a freelance developer from New Zealand. I spend my time teaching people about bitcoin or coding Rust. Find me on twitter https://twitter.com/BenMcDonald___

Rust testing, data generation and const asserts


以上就是本文的全部内容,希望本文的内容对大家的学习或者工作能带来一定的帮助,也希望大家多多支持 码农网

查看所有标签

猜你喜欢:

本站部分资源来源于网络,本站转载出于传递更多信息之目的,版权归原作者或者来源机构所有,如转载稿涉及版权问题,请联系我们

计算机和难解性

计算机和难解性

M.R 加里、D.S. 约翰逊 / 张立昂、沈泓 / 科学出版社 / 1987年 / 4.50

本书系统地介绍了NP完全性理论的概念和方法,全书共分为7章和两个附录。第一章粗略地介绍了计算复杂性的一些基本概念和NP完全性理论的意义。第二章至第五章介绍了NP完全性的基本理论和证明的方法。第六章集中研究NP难问题的近似算法。第七章概述了大量计算复杂性中的有关理论课题。 附录A收集了范围广泛、内容丰富的NP完全性和NP难的问题、附录B补充了NP问题的一些最新的进展,既有理论方面的,又有关于具体问题......一起来看看 《计算机和难解性》 这本书的介绍吧!

RGB转16进制工具
RGB转16进制工具

RGB HEX 互转工具

图片转BASE64编码
图片转BASE64编码

在线图片转Base64编码工具

RGB HSV 转换
RGB HSV 转换

RGB HSV 互转工具