aiofiles
Numba
aiofiles | Numba | |
---|---|---|
4 | 124 | |
2,540 | 9,452 | |
- | 1.1% | |
7.4 | 9.9 | |
3 months ago | 8 days ago | |
Python | Python | |
Apache License 2.0 | BSD 3-clause "New" or "Revised" License |
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aiofiles
- Python Asyncio: The Complete Guide
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Python library for asynchronously writing audio files in chunks?
I'm unaware of a library that facilitates any of this, so unless I find one or more suitable libraries with this matter, then I'm looking at using Numba and either aiofiles or aiofile—I'm not yet sure what the difference between the two is—and writing my own encoder(s).
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Async HTTP Requests with Aiohttp & Aiofiles
Aiofiles: Makes writing to disk (such as creating and writing bytes to files) a non-blocking task, such that multiple writes can happen on the same thread without blocking one another - even when multiple tasks are bound to the same file.
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After months of learning, I finally was able to code a discord bot!
To solve this, you need an async version of function/library. hopefully, requests has a good async alternative- aiohttp. API structure is nearly identical to requests, so It won't be a big pain to migrate. for doing file I/O, there's aiofiles.
Numba
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Mojo🔥: Head -to-Head with Python and Numba
Around the same time, I discovered Numba and was fascinated by how easily it could bring huge performance improvements to Python code.
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Is anyone using PyPy for real work?
Simulations are, at least in my experience, numba’s [0] wheelhouse.
[0]: https://numba.pydata.org/
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Any data folks coding C++ and Java? If so, why did you leave Python?
That's very cool. Numba introduces just-in-time compilation to Python via decorators and its sole reason for being is to turn everything it can into abstract syntax trees.
- Using Matplotlib with Numba to accelerate code
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Python Algotrading with Machine Learning
A super-fast backtesting engine built in NumPy and accelerated with Numba.
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PYTHON vs OCTAVE for Matlab alternative
Regarding speed, I don't agree this is a good argument against Python. For example, it seems no one here has yet mentioned numba, a Python JIT compiler. With a simple decorator you can compile a function to machine code with speeds on par with C. Numba also allows you to easily write cuda kernels for GPU computation. I've never had to drop down to writing C or C++ to write fast and performant Python code that does computationally demanding tasks thanks to numba.
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Codon: Python Compiler
Just for reference,
* Nuitka[0] "is a Python compiler written in Python. It's fully compatible with Python 2.6, 2.7, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 3.10, and 3.11."
* Pypy[1] "is a replacement for CPython" with builtin optimizations such as on the fly JIT compiles.
* Cython[2] "is an optimising static compiler for both the Python programming language and the extended Cython programming language... makes writing C extensions for Python as easy as Python itself."
* Numba[3] "is an open source JIT compiler that translates a subset of Python and NumPy code into fast machine code."
* Pyston[4] "is a performance-optimizing JIT for Python, and is drop-in compatible with ... CPython 3.8.12"
[0] https://github.com/Nuitka/Nuitka
[1] https://www.pypy.org/
[2] https://cython.org/
[3] https://numba.pydata.org/
[4] https://github.com/pyston/pyston
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This new programming language has the potential to make python (the dominant language for AI) run 35,000X faster.
For the benefit of future readers: https://numba.pydata.org/
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Two-tier programming language
Taichi (similar to numba) is a python library that allows you to write high speed code within python. So your program consists of slow python that gets interpreted regularly, and fast python (fully type annotated and restricted to a subset of the language) that gets parallellized and jitted for CPU or GPU. And you can mix the two within the same source file.
- Numba Supports Python 3.11
What are some alternatives?
aiofile - Real asynchronous file operations with asyncio support.
NetworkX - Network Analysis in Python
fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production
jax - Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
httpx - A next generation HTTP client for Python. 🦋
Dask - Parallel computing with task scheduling
asyncio-tutorial-part1 - 🐍🔁 Intro to concurrency in Python with Asyncio.
cupy - NumPy & SciPy for GPU
NumPy - The fundamental package for scientific computing with Python.
Pyjion - Pyjion - A JIT for Python based upon CoreCLR
aiohttp-aiofiles-tutorial - 🔄 🌐 Handle thousands of HTTP requests, disk writes, and other I/O-bound tasks simultaneously with Python's quintessential async libraries.
SymPy - A computer algebra system written in pure Python