topaz
Cython
topaz | Cython | |
---|---|---|
2 | 79 | |
999 | 8,912 | |
0.0% | 1.0% | |
0.0 | 9.8 | |
almost 2 years ago | 7 days ago | |
Python | Python | |
BSD 3-clause "New" or "Revised" License | Apache License 2.0 |
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.
topaz
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Codon: A high-performance Python compiler
It's not like you can just "merge" pypy into python, they are totally different implementations. CPython is written in C and PyPy is written in RPython which is a subset of the python language that gets compiled, into into an interpreter with JIT support. You can actually write an interpreter for any language using RPython and their toolset, for example Ruby https://github.com/topazproject/topaz
- I quit my job to focus on SerenityOS full time
Cython
- Ask HN: C/C++ developer wanting to learn efficient Python
- Ask HN: Is there a way to use Python statically typed or with any type-checking?
- Cython 3.0
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How to make a c++ python extension?
The approach that I favour is to use Cython. The nice thing with this approach is that your code is still written as (almost) Python, but so long as you define all required types correctly it will automatically create the C extension for you. Early versions of Cython required using Cython specific typing (Python didn't have type hints when Cython was created), but it can now use Python's type hints.
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Never again
and again, everything that was released after using an older version of cython.
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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
- Slow Rust Compiler is a Feature, not a Bug.
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Any faster Python alternatives?
Profile and optimize the hotspots with cython (or whatever the cool kids are using these days... It's been a while.)
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What exactly is 'JIT'?
JIT essentially means generating machine code for the language on the fly, either during loading of the interpreter (method JIT), or by profiling and optimizing hotspots (tracing JIT). The language itself can be statically or dynamically typed. You could also compile a dynamic language ahead of time, for example, cython.
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Python executable makers
Cython - - embed demo
What are some alternatives?
openfga - A high performance and flexible authorization/permission engine built for developers and inspired by Google Zanzibar
SWIG - SWIG is a software development tool that connects programs written in C and C++ with a variety of high-level programming languages.
DSP-Shared_Collection
PyPy
topaz - 💎 A server emulator for Final Fantasy XI.
mypyc - Compile type annotated Python to fast C extensions
wings
Pyston - A faster and highly-compatible implementation of the Python programming language.
wings - The server control plane for Pterodactyl Panel. Written from the ground-up with security, speed, and stability in mind.
Pyjion
codon - A high-performance, zero-overhead, extensible Python compiler using LLVM
Stackless Python