hpy
Pyjion
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hpy | Pyjion | |
---|---|---|
20 | 23 | |
1,005 | 1,407 | |
1.2% | - | |
8.2 | 5.0 | |
about 2 months ago | 24 days ago | |
Python | C++ | |
MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
hpy
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RustPython
There is a merge request up to add autogen rust bindings to hpy
https://github.com/hpyproject/hpy/pull/457
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Ruby 3.2βs YJIT is Production-Ready
Are you referencing https://github.com/hpyproject/hpy?
I do hope it takes off.
- HPy - A better C API for Python
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Codon: A high-performance Python compiler
The HPy project [0] seems like a promising way out of this.
[0] https://hpyproject.org/
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New record breaking for Python in TechEmPower
socketify.py breaks the record for Python no other Python WebFramework/Server as able to reach 6.2 mi requests per second before in TechEmPower Benchmarks, this puts Python at the same level of performance that Golang, Rust and C++ for web development, in fact Golang got 5.2 mi req/s in this same round. Almost every server or web framework tries to use JIT to boost the performance, but only socketify.py deliveries this level of performance, and even without JIT socketify.py is twice as fast any other web framework/server in active development, and still can be much more optimized using HPy (https://hpyproject.org/). Python will get even faster and faster in future!
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Is it time to leave Python behind? (My personal rant)
I think Propose a better messaging for Python is the option and a lot of languages will learn it from Rust, because rust erros are the best described errors I see in my life lol. Cargo is amazing and I think we will need a better poetry/pip for sure, HPy project will modernize extensions and packages π¦ too https://hpyproject.org/
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A Look on Python Web Performance at the end of 2022
It also show that PyPy3 will not magically boost your performance, you need to integrate in a manner that PyPy3 can optimize and delivery CPU performance, with a more complex example maybe it can help more. But why socketify is so much faster using PyPy3? The answer is CFFI, socketify did not use Cython for integration and cannot delivery the full performance on Python3, this will be solved with HPy.
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socketify.py - Bringing WebSockets, Http/Https High Peformance servers for PyPy3 and Python3
HPy integration to better support CPython, PyPy and GraalPython
- HPy: A better C API for Python
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Your Data Fits in RAM
Absolutely everything in CPython is a PyObject, and that canβt be changed without breaking the C API. A PyObject contains (among other things) a type pointer, a reference count, and a data field; none of these things can be changed without (again) breaking the C API.
There have definitely been attempts to modernize; the HPy project (https://hpyproject.org/), for instance, moves towards a handle-oriented API that keeps implementation details private and thus enables certain optimizations.
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 βA drop-in JIT Compiler for Python 3.10β (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 π CPython.
What are some alternatives?
nogil - Multithreaded Python without the GIL
Numba - NumPy aware dynamic Python compiler using LLVM
graalpython - A Python 3 implementation built on GraalVM
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.
cinder - Cinder is Meta's internal performance-oriented production version of CPython.
py2js
pgcopy - fast data loading with binary copy
Cython - The most widely used Python to C compiler
psycopg2cffi - Port to cffi with some speed improvements
falcon - The no-magic web data plane API and microservices framework for Python developers, with a focus on reliability, correctness, and performance at scale.