PyInRs

A Rust type library that is as easy to use as Python built-in types.

1. Attribute

• Name: PyInRs.
• Language: Rust, requires version rustc >= 1.75.0.
• Goal: Write a Rust type library that is as easy to use as Python built-in types.
• Module: List, Set, Dict, Int, Str, Deque, Fraction
• Style: Follow Rust's official recommended style.
• Test: Using rstest for unit testing and ensure that all tests passed.
• Security: There is no unsafe code block.
• Document: Using cargo doc --open to open documents.

2. Feature

• Simple: Stay simple, stay young. While ensuring friendly and robust, try to be concise and easy to maintain and read.
• Friendly: With my careful design, it can be used as conveniently as Python's built-in types. Very Pythonic.
• Robust: There are corresponding checks for the addition, deletion, modification, and inspection of containers.
• Efficiency: The performance of the parts with the same function as the standard library is almost the same.

3. Usage

To use it, add the following lines to your Cargo.toml file:

[dependencies]
pyinrs = "1"

There are a total of 7 classes, refer to the 7 commonly used classes in Python:

Some simple examples:

use pyinrs::*;

// List support negative index
List::from([1, 2, 3, 4, 5])[-1]; // 5
// List uniquify
List::from([1, 2, 3, 1, 2, 3, 1, 2, 3]).uniquify(); // [1, 2, 3]

// test whether a Set is proper subset of another Set
Set::from([5, 1]) < Set::from([1, 2, 3, 4, 5]); // true
// intersection of Sets, support intersection, union, difference, and symmetric difference
Set::from([1, 2, 3, 4, 5]) & Set::from([1, 3, 5, 7, 9]); // {1, 3, 5}

// Dict access
Dict::from([("one", 1), ("two", 2), ("three", 3)])[&"one"]; // 1
// Dict get values as a Set
Dict::from([("one", 1), ("two", 2), ("three", 3)]).values().collect::<Set<&i32>>(); // {1, 2, 3}

// Int modular power, very fast
Int::from("1024").pow(&"1024".into(), &"100".into()); // 76
// Int factorial
Int::from("5").factorial().factorial(); // 66895029134491270575881180540903725867527463...

// Str split
Str::from("one, two, three").split(", "); // ["one", "two", "three"]
// Str join
Str::from(".").join(["192", "168", "0", "1"].into()); // "192.168.0.1"

// Deque element reference
Deque::from([1, 2, 3, 4, 5]).front(); // 1
// Deque rotate to right (or left), very vivid!
Deque::from([1, 2, 3, 4, 5]) >> 1; // <5, 1, 2, 3, 4>

// Fraction addition
Fraction::from((1, 2)) + Fraction::from((1, 3)); // 5/6
// Fraction modulo
Fraction::from((1, 2)) % Fraction::from((1, 3)); // 1/6

4. Advantage

The advantage of PyInRs is that it combines the high performance of Rust with the ease of use of Python, and can also be easily combined with other libraries, for example:

use pyinrs::*;

// 1. All types can be printed and easily combined:
let dict: Dict<Str, List<Int>> = [
    ("first".into(), ["123".into(), "456".into()].into()),
    ("second".into(), ["789".into()].into()),
    ("third".into(), ["12345678987654321".into(), "5".into()].into()),
].into();
print!("{dict}"); // {"first": [123, 456], "second": [789], "third": [12345678987654321, 5]}
dict.keys().cloned().collect::<Set<Str>>(); // {"first", "second", "third"}
dict[&"third".into()][-1].factorial(); // 120

// 2. All container types support iterators, such as:
for (k, v) in Dict::from([(1, 1), (2, 4), (3, 9)]) {
    assert_eq!(k * k, v);
}

// 3. Using pyinrs::Fraction in mymatrix to display accurate matrix.
use mymatrix::Matrix;

let a = Matrix::from([[1, 2], [3, 4]]);
let b = Matrix::create(2, 2, 0.into());
let c = Matrix::create(2, 2, 1.into());
let d = Matrix::eye(2);

print!("{}", ((a + b) * (c + d)).inv().unwrap());
/*
[[
-11/6 5/6;
5/3 -2/3;
]]
*/

If you want to use a similar library in C++, please see: PyInCpp.