nogil
PDM
nogil | PDM | |
---|---|---|
31 | 47 | |
2,854 | 6,584 | |
- | 3.3% | |
5.7 | 9.6 | |
2 months ago | 7 days ago | |
Python | Python | |
GNU General Public License v3.0 or later | MIT License |
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nogil
- Proof-of-Concept Multithreaded Python Without the GIL
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Our Plan for Python 3.13
This might be a dumb question, but why would removing the GIL break FFI? Is it just that existing no-GIL implementations/proposals have discarded/ignored it, or is there a fundamental requirement, e.g. C programs unavoidably interact directly with the GIL? I know that the C-API is only stable between minor releases [0] compiled in the same manner [1], so it's not like the ecosystem is dependent upon it never changing.
I cannot seem to find much discussion about this. I have found a no-GIL interpreter that works with numpy, scikit, etc. [2][3] so it doesn't seem to be a hard limit. (That said, it was not stated if that particular no-GIL implementation requires specially built versions of C-API libs or if it's a drop-in replacement.)
[0]: https://docs.python.org/3/c-api/stable.html#c-api-stability
[1]: https://docs.python.org/3/c-api/stable.html#platform-conside...
[2]: https://github.com/colesbury/nogil
[3]: https://discuss.python.org/t/pep-703-making-the-global-inter...
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Real Multithreading Is Coming to Python
https://github.com/colesbury/nogil does manage to get rid of the GIL, but it's not certain to make it into Python core. The main problem is the amount of existing libraries that depend on the existence of the GIL without realizing it - breaking those would be extremely disruptive.
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[D] The hype around Mojo lang
CPython is also investigating the removal of the GIL (PEP703, nogil). I think requiring the GIL is a wider thing that libraries will need to address anyway. But also, for the same reason as above I'd be surprised if the Modular team thought that saying "you can run all your python code unchanged" was a good idea if there was a secret "except for code that uses numpy" muttered under the breath.
- PEP 684 was accepted – Per-interpreter GIL in Python 3.12
- PEP 703 – Making the Global Interpreter Lock Optional in CPython
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Python 3.11.0 final is now available
I'm worried about the speedup
My understanding is that it's based on the most recent attempt to remove the GIL by Sam Gross
https://github.com/colesbury/nogil
In addition to some ways to try to not have nogil have as much overhead he added a lot of unrelated speed improvements so that python without the gil would still be faster not slower in single thread mode. They seem to have merged those performance patches first that means if they add his Gil removal patches in say python 3.12 it will still be substantially slower then 3.11 although faster then 3.10. I hope that doesn't stop them from removing the gil (at least by default)
- Removed the GIL back in 1996 from Python 1.4, primarily to create a re-entrant Python interpreter.
- I Tried Removing Python's GIL Back in 1996
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Faster CPython 3.12 Plan
Looks like it's still active to me:
https://github.com/colesbury/nogil/
PDM
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Implementing Quality Checks In Your Git Workflow With Hooks and pre-commit
# See https://pre-commit.com for more information # See https://pre-commit.com/hooks.html for more hooks repos: - repo: https://github.com/pre-commit/pre-commit-hooks rev: v3.2.0 hooks: - id: trailing-whitespace - id: end-of-file-fixer - id: check-yaml - id: check-toml - id: check-added-large-files - repo: local hooks: - id: tox lint name: tox-validation entry: pdm run tox -e test,lint language: system files: ^src\/.+py$|pyproject.toml|^tests\/.+py$ types_or: [python, toml] pass_filenames: false - id: tox docs name: tox-docs language: system entry: pdm run tox -e docs types_or: [python, rst, toml] files: ^src\/.+py$|pyproject.toml|^docs\/ pass_filenames: false - repo: https://github.com/pdm-project/pdm rev: 2.10.4 # a PDM release exposing the hook hooks: - id: pdm-lock-check - repo: https://github.com/jumanjihouse/pre-commit-hooks rev: 3.0.0 hooks: - id: markdownlint
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Beginning Python: Project Management With PDM
PDM is a solution that allows for easy creation and management of python projects. Some of the key features that will improve the management of python projects include:
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A question about good practice when using docker.
You'd need a proper dependencies management tool like PDM or Poetry to exhaustively resolve and lock down all the transitive dependencies if you want to have anything closed to reproducible build.
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pdm-dotenv: Simplify Your Project's Environment Variable Management
Are you working on a Python project that uses pdm for dependency management and dotenv for local environment variable and secrets management? Do you find it frustrating when CLI tools like pgcli don't automatically pick up your .env file, forcing you to resort to npm install -g dotenv-cli? I've got a more convenient solution for you!
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PEP 582 rejected - consensus among the community needed
I first learned about PDM from a blog post written by one of the PDM contributers. The post was about OOPifying argparse to allow for easy creation/modification of subcommands that exist as their own classes/files, and to avoid maintaining a single long script with an endless number of subparser.add_argument(...) lines.
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PEP 704 – Require virtual environments by default for package installers
That's more or less what PEP 582 plans to do, but it's been stalled and mired in discussions for years. The PDM tool went ahead and implemented it though if you want to use it: https://github.com/pdm-project/pdm
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This Week In Python
pdm – A modern Python package and dependency manager
- Pdm: A modern Python dependency manager supporting the latest PEP standards
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How does a virtual environment work?
pdm and PEP 582 enter the chat
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Boring Python: Code Quality
I'm liking PDM for a while now. Quicker than Poetry and built according to the Python package spec in mind and not as an afterthought. While it was originally meant to work with PEP 582, it works with virtual environments too (now default).
https://github.com/pdm-project/pdm
What are some alternatives?
hpy - HPy: a better API for Python
Poetry - Python packaging and dependency management made easy
mypyc - Compile type annotated Python to fast C extensions
conda - A system-level, binary package and environment manager running on all major operating systems and platforms.
numpy - The fundamental package for scientific computing with Python.
pip-tools - A set of tools to keep your pinned Python dependencies fresh.
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
pip - The Python package installer
python-feedstock - A conda-smithy repository for python.
Pipenv - Python Development Workflow for Humans.
sbcl - Mirror of Steel Bank Common Lisp (SBCL)'s official repository
PyFlow - Visual scripting framework for python - https://wonderworks-software.github.io/PyFlow