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ideas
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Type information for faster Python C extensions
Lower latency native calls in Python would be extremely useful, thank you for your work! Is the following GitHub issue the right place to monitor progress? https://github.com/faster-cpython/ideas/issues/546
I'm open to doing some benchmarking. Several of my libraries have pure CPython bindings (StringZilla, UCall, SimSIMD), and all perform low-latency SIMD-accelerated ops, so might be a good testing ground :)
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How Many Lines of C It Takes to Execute a and B in Python?
Recent CPython development has been towards optimizations and addressing use cases that benefit from optimizations, some coming from the faster CPython initiative. You might just get your JIT[1].
[1] https://github.com/faster-cpython/ideas/wiki/Workflow-for-3....
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GIL removal and the Faster CPython project
The faster-cpython folks seem to be working towards a JIT (https://github.com/faster-cpython/ideas/tree/main/3.13) and both pyston and cinder have JITs. So I don't think anyone has ruled one out.
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Our Plan for Python 3.13
faster-cpython team has done a lot of work to experiment on it: https://github.com/faster-cpython/ideas/issues/485#issuecomm...
It kind of sounds like migration to register based is a foregone conclusion, but it's not very clear to me.
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Faster CPython at PyCon, part two
lots of big ideas are still remaining to be done. One example is the register based interpreter, see https://github.com/faster-cpython/ideas/issues/485
A previous plan called for the beginning of a JIT in 3.12, seen as "Trace optimized interpreter" here: https://github.com/faster-cpython/ideas/wiki/Workflow-for-3....
- EdgeDB – A graph-relational database built on top of Postgres
- Python 3.12 Nogil Benchmark
Pyjion
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Python 3.13 Gets a JIT
It exists, was created by microsoft employees, and is referenced in the article: https://www.trypyjion.com/
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Is anyone using PyPy for real work?
I've actually come across and started using Pyjion recently (https://github.com/tonybaloney/pyjion); how does Pypy compare, both in terms of performance and purpose? There seems to be a lot of overlap...
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funAndEasyToUse
Python is capable of doing things at runtime that are really hard to statically compile around, such as monkeypatching methods onto existing objects. You can compile it, but it's complicated. One strategy is to use a JIT that can observe application state at runtime and then invalidate code as it becomes obsoleted by changes, but it's complicated. See pyjion for an example.
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Javascript has Typescript. WHY WE DONT HAVE TYPY !
When I say "Python" I am referring to the standard CPython interpreter which most people use. But there is also PyPy, which includes a Just In Time compile that compiles selected code into machine language on the fly, as needed. pyjion is another JIT compiler that generates machine language on the fly, and you can install it with pip. Or you could work for Facebook and use Cinder. Cython, Nuitka and Pyston are other alternatives.
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How is Golang websocket better than FastAPI websocket?
and if you need more speed you can try https://www.pypy.org/ or https://github.com/tonybaloney/Pyjion or https://www.pyston.org/
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CPython vs PyPy
Finally, there is also Pyjion which based on its website is “A drop-in JIT Compiler for Python 3.10” (https://www.trypyjion.com/). We will be covering it on a separate writeup. See you next time ;-).
- Accelerate Python code 100x by import taichi as ti
- Create CPython extensions in .NET?
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Instant upvotes
Though some exciting stuff happening over the next few years, Python is getting faster, has been for awhile, and stuff like Pyjion https://www.trypyjion.com/, a drop in C# powered JIT compiler is starting to approach usable. Rust and Python seem to be best buds right now, so more extension libraries in rust, a newer more approachable language than say C/C++ but with a similar speed. Sign me up!
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You think python is slow ?
Pyjion Easy to use, small compiler. Increase performance of our 🐌 CPython.
What are some alternatives?
Nuitka - Nuitka 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. You feed it your Python app, it does a lot of clever things, and spits out an executable or extension module.
Numba - NumPy aware dynamic Python compiler using LLVM
faster-cpython - How to make CPython faster.
pyenv-virtualenv - a pyenv plugin to manage virtualenv (a.k.a. python-virtualenv)
cinder - Cinder is Meta's internal performance-oriented production version of CPython.
nogil - Multithreaded Python without the GIL
graalpython - A Python 3 implementation built on GraalVM
jnumpy - Writing Python C extensions in Julia within 5 minutes.
Cython - The most widely used Python to C compiler
hpy - HPy: a better API for Python