mypyc
pex
Our great sponsors
mypyc | pex | |
---|---|---|
25 | 9 | |
1,667 | 2,454 | |
1.3% | 0.8% | |
0.0 | 8.9 | |
about 1 year ago | 7 days ago | |
Python | ||
- | 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.
mypyc
- Making use of type hints
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Writing Python like it's Rust
That would be interesting! You might already be aware. But there's mypyc[0], which is an AOT compiler for Python code with type hints (that, IIRC, mypy uses to compile itself into a native extension).
Wanted to give you a head-start on the lit-review for your students I guess :)
[0] https://github.com/mypyc/mypyc
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The different uses of Python type hints
https://github.com/mypyc/mypyc
> Mypyc compiles Python modules to C extensions. It uses standard Python type hints to generate fast code. Mypyc uses mypy to perform type checking and type inference.
> Mypyc can compile anything from one module to an entire codebase. The mypy project has been using mypyc to compile mypy since 2019, giving it a 4x performance boost over regular Python.
I have not experience a 4x boost, rather between 1.5x and 2x. I guess it depends on the code.
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The Python Paradox
Funny how emergence works with tools. Give a language too few tools but viral circumstances - the ecosystem diverges (Lisps, Javascript). Give it too long an iteration time but killer guarantees, you end up with committees. Python not falling into either of these traps should be understood as nothing short of magic in emergence.
I only recently discovered that python's reference typechecker, mypy, has a small side project for typed python to emit C [1], written entirely in python. Nowadays with python's rich specializer ecosystem (LLVM, CUDA, and just generally vectorized math), the value of writing a small program in anything else diminishes quickly.
Imagine reading the C++wg release notes in the same mood that you would the python release notes.
[1] https://github.com/mypyc/mypyc
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Codon: A high-performance Python compiler
> Note that the mypyc issue tracker lives in this repository! Please don't file mypyc issues in the mypy issue tracker.
See https://github.com/mypyc/mypyc/blob/master/show_me_the_code....
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ELI5: Can’t one write a compiler for Python and make everything go brrrr?
And mypyc https://github.com/mypyc/mypyc
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Is it time for Python to have a statically-typed, compiled, fast superset?
More recent approaches include mypyc which is (on the tin) quite close to what you describe, and taichi that lives in between.
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Pholyglot version 0.0.0 (PHP to PHP+C polyglot transpiler)
Have you encountered mypyc?
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Python 3.11 is 25% faster than 3.10 on average
https://github.com/mypyc/mypyc
> Mypyc compiles Python modules to C extensions. It uses standard Python type hints to generate fast code. Mypyc uses mypy to perform type checking and type inference.
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Comparing implementations of the Monkey language VIII: The Spectacular Interpreted Special (Ruby, Python and Lua)
Regarding the large execution time mentioned in your article, I discovered (mypyc)[https://github.com/mypyc/mypyc] on this subreddit in a post from the black formatter team https://www.reddit.com/r/Python/comments/v2009i/im_that_person_who_got_black_compiled_with_mypyc/?utm_medium=android_app&utm_source=share
pex
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Our Plan for Python 3.13
We get (very) close to cross-environment reproducible builds for Python with https://github.com/pantsbuild/pex (via Pants). For instance, we build Linux x86-64 artifacts that run on AWS Lambda, and can build them natively on ARM macOS.
This is not raw requirements.txt, but isn’t too far off: Pants/PEX can consume one to produce a hash-pinned lock file.
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Is it possible pickle a function with its dependencies?
You should look into pex, or it’s parent build system pants. A PEX (Python EXecutable) file can package up all your code including dependencies and run on another machine of similar OS with just an available compatible interpreter.
- Pex: Python EXecutable
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security risks in python libs
For well-supported libraries, pip-audit might do the trick. Where I've worked, we have used a central build system with library version enforcement. The build system produces a deployable archive, like PEX or similar. Rock-solid tests and sandbox validation environments provide good paths for version upgrades. Restricting libraries to a small set, making sure those repos remain actively developed, performing audits and centralizing builds has helped organizations I've worked in keep on top of potential security issues.
- My latest blogpost, python packaging has moved forward, but we're still missing a crucial part - what do you think?
- PyBake: Create single file standalone Python scripts with builtin frozen file system
- I am frustrated with packaging python, please educate me.
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A function decorator that rewrites the bytecode to enable goto in Python
Don't know if I agree about the goto thing, but there are actually a number of options now for delivering varying degrees of self-contained Python executable.
When I evaluated the landscape a few years ago, I settled on PEX [1] as the solution that happened to fit my use-case the best— it uses a system-provided Python + stdlib, but otherwise brings everything (including compiled modules) with it in a self-extracting executable. Other popular options include pyinstaller and cx_freeze, which have different tradeoffs as far as size, speed, convenience, etc.
[1]: https://github.com/pantsbuild/pex
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Mypyc: Compile type-annotated Python to C
Somewhat related, I had a devil of a time a little bit ago trying to ship a small Python app as a fully standalone environment runnable on "any Linux" (but for practical purposes, Ubuntu 16.04, 18.04, and 20.04). It turns out that if you don't want to use pip, and you don't want to build separate bundles for different OSes and Python versions, it can be surprisingly tricky to get this right. Just bundling the whole interpreter doesn't work either because it's tied to a particular stdlib which is then linked to specific versions of a bunch of system dependencies, so if you go that route, you basically end up taking an entire rootfs/container with you.
After evaluating a number of different solutions, I ended up being quite happy with pex: https://github.com/pantsbuild/pex
It basically bundles up the wheels for whatever your workspace needs, and then ships them in an archive with a bootstrap script that can recreate that environment on your target. But critically, it natively supports the idea of targeting multiple OS and Python versions, you just explicitly tell it which ones to include, eg:
--platform=manylinux2014_x86_64-cp-38-cp38 # 16.04
What are some alternatives?
Cython - The most widely used Python to C compiler
setup.py - 📦 A Human's Ultimate Guide to setup.py.
mypy - Optional static typing for Python
python-goto - A function decorator, that rewrites the bytecode, to enable goto in Python
beartype - Unbearably fast near-real-time hybrid runtime-static type-checking in pure Python.
pyBake - Create single file standalone Python scripts with builtin frozen file system
CPython - The Python programming language
plusplus - Enables increment operators in Python using a bytecode hack
pyccel - Python extension language using accelerators
typed_python - An llvm-based framework for generating and calling into high-performance native code from Python.
typeguard - Run-time type checker for Python
mypyc-benchmark-results - Mypyc benchmark result data