codon
Numba
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codon | Numba | |
---|---|---|
34 | 124 | |
13,809 | 9,404 | |
0.9% | 1.6% | |
7.9 | 9.9 | |
13 days ago | 7 days ago | |
C++ | Python | |
GNU General Public License v3.0 or later | BSD 3-clause "New" or "Revised" License |
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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.
codon
- Should I Open Source my Company?
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Python running on the Dart VM?
I found at least one project that managed to compile python AOT to LLVM https://github.com/exaloop/codon. Even if LLVM is more expressive than Dart Kernel, that should at least be some evidence that this might not be too impractical.
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Codon: Python Compiler
Their fannkuch benchmark seems to be a bit dishonest. They claim an enormous perf delta on https://exaloop.io/benchmarks.html but fannkuch uses factorial a lot and they define factorial with a very small (n=20) table: https://github.com/exaloop/codon/blob/fb461371613049539654c1...
Disclaimer: I've worked on several Python runtimes and compilers, but I'm not by any means out to get Codon. Just happened across this by accident while looking at their inline LLVM, which is neat.
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The father of Swift made another baby: Mojo: looks to be based on Python using MLIR
If you literally want Python, but compiled ... Look at Codon: https://github.com/exaloop/codon
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Mojo – a new programming language for all AI developers
Another "Python with high-performance compiled builds" would be https://github.com/exaloop/codon.
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MIT Turbocharges Python’s Notoriously Slow Compiler
This is the project being discussed: https://github.com/exaloop/codon
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Is there a way to use turn a project into a single executable file that doesn't require anyone to do anything like install Python before using it?
Try Codon? https://github.com/exaloop/codon
- Since when did Python haters spread out everywhere? Maybe DNF5 would be faster because of ditched it, maybe.
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Budget HomeLab converted to endless money-pit
https://github.com/exaloop/codon might save you from the rewrite.
- What are your thoughts on Codon compiler having a paid licence?
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.
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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"
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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?
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.
NetworkX - Network Analysis in Python
Cython - The most widely used Python to C compiler
jax - Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
taichi - Productive, portable, and performant GPU programming in Python.
Dask - Parallel computing with task scheduling
julia - The Julia Programming Language
cupy - NumPy & SciPy for GPU
Nim - Nim is a statically typed compiled systems programming language. It combines successful concepts from mature languages like Python, Ada and Modula. Its design focuses on efficiency, expressiveness, and elegance (in that order of priority).
Pyjion - Pyjion - A JIT for Python based upon CoreCLR
Django - The Web framework for perfectionists with deadlines.
SymPy - A computer algebra system written in pure Python