mypyc
pytype
mypyc | pytype | |
---|---|---|
25 | 21 | |
1,667 | 4,602 | |
0.1% | 1.8% | |
0.0 | 9.8 | |
about 1 year ago | 13 days ago | |
Python | ||
- | GNU General Public License v3.0 or later |
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
pytype
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Google lays off its Python team
it's open source! check out https://github.com/google/pytype and https://github.com/google/pytype/blob/main/docs/developers/t... for more on the multi-file runner
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Enhance Your Project Quality with These Top Python Libraries
Pytype checks and infers types for your Python code - without requiring type annotations. Pytype can catch type errors in your Python code before you even run it.
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A Tale of Two Kitchens - Hypermodernizing Your Python Code Base
Pyre from Meta, pyright from Microsoft and PyType from Google provide additional assistance. They can 'infer' types based on code flow and existing types within the code.
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Mypy 1.6 Released
we've written a little bit about what pytype does differently here: https://google.github.io/pytype/
our main focus is to be able to work with unannotated and partially-annotated code, and treat it on par with fully annotated code.
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Mypy 1.5 Released
So, I tried out pytype the other day, and it was a not a good experience. It doesn't support PEP 420 (implicit namespace packages), which means you have to litter __init__.py files everywhere, or it will create filename collisions. See https://github.com/google/pytype/issues/198 for more information. I've since started testing out pyre.
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Writing Python like it's Rust
What is the smart money doing for type checking in Python? I've used mypy which seems to work well but is incredibly slow (3-4s to update linting after I change code). I've tried pylance type checking in VS Code, which seems to work well + fast but is less clear and comprehensive than mypy. I've also seen projects like pytype [1] and pyre [2] used by Google/Meta, but people say those tools don't really make sense to use unless you're an engineer for those companies.
Am just curious if mypy is really the best option right now?
[1] https://github.com/google/pytype
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PyMEL's new type stubs
At Luma, we're using mypy to check nearly our entire code-base, including our Maya-related code, thanks to these latest changes. Fully adopting mypy (or an alternative like pytype) is no small feat, but working within a fully type-annotated code base with a type checker to enforce accuracy is like coding in a higher plane of existence: fewer bugs, easier code navigation, faster dev onboarding, easier refactoring, and dramatically increased confidence about every change. I wrote about some deeper insights in these posts.
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The Python Paradox
Check out https://github.com/google/pytype
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Forma: An efficient vector-graphics renderer
i work on https://github.com/google/pytype which is largely developed internally and then pushed to github every few days. the github commits are associated with the team's personal github accounts. pytype is not an "official google product" insofar as the open source version is presented as is without official google support, but it is "production code" in the sense that it is very much used extensively within google.
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Ruff – an fast Python Linter written in Rust
pytype dev here - thanks for the kind words :) whole-program analysis on unannotated or partially-annotated code is our particular focus, but there's surprisingly little dark PLT magic involved; in particular you don't need to be an academic type theory wizard to understand how it works. our developer docs[1] have more info, but at a high level we have an interpreter that virtually executes python bytecode, tracking types where the cpython interpreter would have tracked values.
it's worth exploring some of the other type checkers as well, since they make different tradeoffs - in particular, microsoft's pyright[2] (written in typescript!) can run incrementally within vscode, and tends to add new and experimentally proposed typing PEPs faster than we do.
[1] https://github.com/google/pytype/blob/main/docs/developers/i...
What are some alternatives?
Cython - The most widely used Python to C compiler
mypy - Optional static typing for Python
pyright - Static Type Checker for Python
beartype - Unbearably fast near-real-time hybrid runtime-static type-checking in pure Python.
pyre-check - Performant type-checking for python.
CPython - The Python programming language
pyannotate - Auto-generate PEP-484 annotations
pex - A tool for generating .pex (Python EXecutable) files, lock files and venvs.
pyanalyze - A Python type checker
pyccel - Python extension language using accelerators
ruff - An extremely fast Python linter and code formatter, written in Rust.