celery-types
python-feedstock
| celery-types | python-feedstock | |
|---|---|---|
| 1 | 2 | |
| 66 | 44 | |
| - | - | |
| 6.4 | 7.8 | |
| 7 days ago | 12 days ago | |
| Python | Shell | |
| Apache License 2.0 | BSD 3-clause "New" or "Revised" License |
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.
celery-types
-
Python 3.11.0 final is now available
While it's of course not ideal, stub files can help with this issue. For example you can get stubs for Celery that make both `shared_task` and `delay` properly typed: https://github.com/sbdchd/celery-types
python-feedstock
-
Python 3.11.0 final is now available
It's already there:
https://anaconda.org/conda-forge/python
https://github.com/conda-forge/python-feedstock/pull/577
Using mamba to create a new encoding called py311 with python 3.11:
mamba create -n py311 python=3.11 -
Notes from the Meeting on Python GIL Removal Between Python Core and Sam Gross
https://news.ycombinator.com/item?id=18040664
Today, conda-forge compiles CPython to relocatable platform+architecture-specific binaries with LLVM. https://github.com/conda-forge/python-feedstock/blob/master/...
Pyodide (JupyterLite) compiles CPython to WASM (or LLVM IR?) with LLVM/emscripten IIRC. Hopefully there's a clear way to implement the new GIL-less multithreading support with Web Workers in WASM, too?
The https://rapids.ai/ org has a bunch a fast Python for HPC; with Dask and pick a scheduler. Less process overhead and less need for interprocess locking of memory handles that transgress contexts due to a new GIL removal approach would be even faster than debuggable one process per core Python.
What are some alternatives?
sigstore-website - Codebase for sigstore.dev
nogil - Multithreaded Python without the GIL
public-conventions - In-house conventions and styles
import-linter - Import Linter allows you to define and enforce rules for the internal and external imports within your Python project.
django-stubs - PEP-484 stubs for Django
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
conda - A system-level, binary package and environment manager running on all major operating systems and platforms.
Flake8 - flake8 is a python tool that glues together pycodestyle, pyflakes, mccabe, and third-party plugins to check the style and quality of some python code.