sain — Write safe Python code like Rust
a dependency-free which implements Rust's core crates, purely, in Python.
Offering core Rust items such as Vec<T>, Result<T, E>, Option<T> and more. See the built-in types section below.
Install
Python 3.10 or higher is required.
Using uv:
uv pip install sain
Using pip:
pip install sain
Overview
sain is built completely on-top of Python's stdlib, inspired by The Rust Standard Library, designed to bring modern, safe, and ergonomic data structures and utilities to Python.
The goal is to provide developers with high-level abstractions and low-level control similar to what Rust offers, making it easier to write robust, and maintainable code.
Example
In this example we are writing a simple app that takes advantage of Rust's types which're implemented in Python.
This example provides a simple library that contains a Vec of books. Here, we take advantage of the Vec type and its idiomatic methods.
from __future__ import annotations
from sain import Result, Ok, Err # used for safe error handling.
from sain import Option # used for absense of a value, similar to `T | None`.
from sain import Vec # A replacement for `list` type.
from dataclasses import dataclass, field
@dataclass
class Book:
name: str
author: str
tags: set[str]
pages = field(default_factory=set[str])
@dataclass
class Library:
# just like any other mutable sequences.
# it needs a default factory.
books = field(default_factory=Vec[Book])
# add a books to this library.
def add(self, *books: Book):
self.books.extend(books)
# finds the first book that contains a specific tag.
def find(self, pattern: str) -> Option[Book]:
return self.books.iter().find(lambda book: pattern in book.tags)
# finds the first book that contains a specific tag,
# mapping Option[Book] to Result[Book, str] where `str` is the context
# of the error.
def find_or(self, pattern: str) -> Result[Book, str]:
return self.find(pattern).ok_or(f"book with pattern {pattern} not found.")
# We simply filter books that matches `author` and collect
# them into a list[Book].
def books_for(self, author: str):
return self.books.iter().filter(lambda book: book.author == author).collect()
lib = Library()
lib.add(
Book("Twilight", "Stephenie Meyer", {"Vampire", "Romance"}),
Book("Silo", "Hugh Howey", {"Dystopian", "Sci-Fi"}),
Book("The Eternaut", "Héctor Germán", {"Invasion", "Mystery"}),
)
# find the first vampire book then maps the book to its pages.
# maps Option[Book] -> Option[set[str]]
for page in lib.find("Vampire").map(lambda book: book.pages).unwrap():
print(page) # {page1, page2, ...}
match lib.find_or("Sci-Fi"):
case Ok(book):
print(book) # Book("Silo", ...)
case Err(err):
print(err) # book with pattern Sci-Fi not found.
# show Hugh's books.
print(lib.books_for("Hugh Howey")) # [Book("Silo", ...)]
How to use this library
Option,Result,Iterator,*/collections,Default- The are core routines which are used almost everywhere within the library. You can easily opt these in your projects.sync,convert,error,macros,cfg- These are also core impls, but not widely used as the ones above.maybe_uninit,futures,boxed- You will probably see those used once or less anywhere, they're designed for lower-level, general use.
built-in types
| name in Rust | name in Python | note | restrictions |
|---|---|---|---|
| Option<T>, Some(T), None | Option[T], Some(T), Some(None) | Some(None) has the same layout as None in Rust |
|
| Result<T, E>, Ok(T), Err(E) | Result[T, E], Ok(T), Err(E) | Basically a better and more verbose try/except |
|
| Vec<T> | Vec[T] | Same layout as list[T] |
|
| HashMap<K, V> | HashMap[K, V] | Same layout as dict[K, V] |
|
| bytes::Bytes | Bytes | ||
| bytes::BytesMut | BytesMut | ||
| LazyLock<T> | Lazy[T] | ||
| OnceLock<T> | Once[T] | ||
| Box<T> | Box[T] | this isn't a heap box | |
| MaybeUninit<T> | MaybeUninit[T] | they serve the same purpose, but slightly different | |
| impl Default | Default[T] | ||
| &dyn Error | Error | ||
| impl Iterator<T> | Iterator[T] | ||
| Iter<'a, T> | Iter[T] | collections called by .iter() are built from this type |
|
| iter::once::<T>() | iter.once[T] | ||
| iter::empty::<T>() | iter.empty[T] | ||
| iter::repeat::<T>() | iter.repeat[T] | ||
| cfg!() | cfg() | runtime cfg, not all predictions are supported | |
| #[cfg_attr] | @cfg_attr() | runtime cfg, not all predictions are supported | |
| #[doc] | @doc() | the docs get generated at runtime | |
| todo!() | todo() | ||
| #[deprecated] | @deprecated() | will get removed when it get stabilized in warnings in Python 3.13 |
|
| unimplemented!() | @unimplemented() |
Contributing
See CONTRIBUTING.md.
Remaining work
This is still early days for sain, it is no where near as stable as Python's stdlib.
This project mainly started as a fun / learning experience but turned into something more inspiring.
The release cycles were breaking due to poor decision making at first, but it should be stable enough now.
Release files for sain 1.4.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| sain-1.4.0.tar.gz | 924.6 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| sain-1.4.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 1.9 MB
Release files / sain-1.4.0.tar.gz
| Download URL | sain-1.4.0.tar.gz |
|---|---|
| Size | 924.6 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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|
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BLAKE2b-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
uv/0.7.8
|
Release files / sain-1.4.0-py3-none-any.whl
| Download URL | sain-1.4.0-py3-none-any.whl |
|---|---|
| Size | 1.0 MB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
6ba4494b0be9e82f41e90f1537cb56c966777db6f4d47e835e258e407cc2ded7
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
uv/0.7.8
|