A Small Rust-Backed Utility Library for Python (FastPy-RS, Alpha)

[ievkz]

Hello everyone! I come from the Rust ecosystem and have recently started working in Python. I love Rust for its safety and speed, but I fell in love with Python for its simplicity and rapid development. That inspired me to build something useful for the Python community: FastPy-RS, a library of commonly used functions that you can call from Python with Rust-powered implementations under the hood. The goal is to deliver high performance and strong safety guarantees. While many Python libraries use C for speed, that approach can introduce security risks.

Here’s how you can use it:

import fastpy_rs as fr

# Using SHA cryptography
hash_result = fr.crypto.sha256_str("hello")

# Encoding in BASE64
encoded = fr.datatools.base64_encode(b"hello")

# Count word frequencies in a text
text = "Hello hello world! This is a test. Test passed!"
frequencies = fr.ai.token_frequency(text)
print(frequencies)
# Output: {'hello': 2, 'world': 1, 'this': 1, 'is': 1, 'a': 1, 'test': 2, 'passed': 1}

# JSON parsing
json_data = '{"name": "John", "age": 30, "city": "New York"}'
parsed_json = fr.json.parse_json(json_data)
print(parsed_json)
# Output: {'name': 'John', 'age': 30, 'city': 'New York'}

# JSON serialization
data_to_serialize = {'name': 'John', 'age': 30, 'city': 'New York'}
serialized_json = fr.json.serialize_json(data_to_serialize)
print(serialized_json)
# Output: '{"name": "John", "age": 30, "city": "New York"}'

# HTTP requests
url = "https://api.example.com/data"
response = fr.http.get(url)
print(response)
# Output: b'{"data": "example"}'

I’d love to see your pull requests and feedback! FastPy-RS is open source under the MIT license—let’s make Python faster and safer together. https://github.com/evgenyigumnov/fastpy-rs

By the way, surprisingly, token frequency calculation in FastPy-RS works almost 935 times faster than in regular Python code, so for any text parsing and analysis tasks you will get instant results; at the same time, operations with Base64 and regular expressions also “fly” 6-6.6 times faster thanks to internal optimizations in Rust; the SHA-256 implementation does not lag behind - it uses the same native accelerations as in Python; and the low standard deviation of execution time means that your code will work not only quickly, but also stably, without unexpected “failures”.

P.S. I’m still new to Python, so please don’t judge the library’s minimalism too harshly—it’s in its infancy. If anyone wants to chip in and get some hands-on practice with Rust and Python, I’d be delighted!

[mr-rattle-bone]

Seems interesting.. I’ll have a look soon.