rules_python
pip-upgrade
rules_python | pip-upgrade | |
---|---|---|
7 | 4 | |
495 | 33 | |
0.4% | - | |
9.5 | 6.0 | |
8 days ago | 3 months ago | |
Starlark | Python | |
Apache License 2.0 | MIT 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.
rules_python
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Things I've learned about building CLI tools in Python
What's SV?
I honestly don't know why anyone would use that... as in what does Bazel do better than virtually anything else that can provide this functionality. But, I used to be an ops engineer in a big company which wanted everything to be Maven, regardless of whether it does it well or not. So we built and deployed with Maven a lot of weird and unrelated stuff.
Not impossible, but not anything I'd advise anyone to do on their free time.
Specifically wrt' the link you posted, if you look here: https://github.com/bazelbuild/rules_python/blob/main/python/... it says that only pure Python wheels are supported, but that's also a lie, they don't support half of the functionality of pure Python wheels.
So, definitely not worth using, since lots of functionality is simply not there.
- Python coverage in Bazel has been broken for nearly 6 years
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Build faster with Buck2: Our open source build system
Regarding bazel, the rules_python has a py_wheel rule that helps you creating wheels that you can upload to pypi (https://github.com/bazelbuild/rules_python/blob/52e14b78307a...).
If you want to see an approach of bazel to pypi taken a bit to the extreme you can have a look at tensorflow on GitHub to see how they do it. They don't use the above-mentioned building rule because I think their build step is quite complicated (C/C++ stuff, Vida/ROCm support, python bindings, and multiOS support all in one before you can publish to pypi).
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Incremental Builds for Haskell with Bazel
Python support in Bazel now looks more promising with `rules_python`: https://github.com/bazelbuild/rules_python
`rules_go` to my understanding is great too.
Over years, Bazel is not as opinionated as before, mostly because adoptions in different orgs force it to be so.
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Advantages of Monorepos
I have personally run converted build systems to Bazel, and use it for personal projects as well.
Bazel 1.0 was released in October 2019. If you were using it "a few years ago", I'm guessing you were using a pre-1.0 version. There's not some cutoff where Bazel magically got easy to use, and I still wouldn't describe it as "easy", but the problem it solves is hard to solve well, and the community support for Bazel has gotten a lot better over the past years.
https://github.com/bazelbuild/rules_python
The difficulty and complexity of using Bazel is highly variable. I've seen some projects where using Bazel is just super simple and easy, and some projects where using Bazel required a massive effort (custom toolchains and the like).
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Experimentations on Bazel: Python & FastAPI (1)
load("@bazel_tools//tools/build_defs/repo:http.bzl", "http_archive") #------------------------------------------------------------------------------ # Python #------------------------------------------------------------------------------ # enable python rules http_archive( name = "rules_python", url = "https://github.com/bazelbuild/rules_python/releases/download/0.2.0/rules_python-0.2.0.tar.gz", sha256 = "778197e26c5fbeb07ac2a2c5ae405b30f6cb7ad1f5510ea6fdac03bded96cc6f", )
pip-upgrade
- My first code PR to an open source project and it was to optimize Pip's new resolver!
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Pip update all with dependency management
Hey guys, I found a neat little project a few months ago and it's been super helpful to me, so I figured that I'd share it here. It's called pip-upgrade-tool and as the title says, it allows for an "upgrade all" mechanic in pip, since it currently doesn't have an official way of doing this. There is the way to upgrade everything by piping pip freeze to grep and cut and xargs, but that doesn't take into account the dependencies that each package has. This project, on the other hand, does take into account dependencies, just like a normal package manager. After installation with pip3 install pip-upgrade-tool, you can just run pip-upgrade in a terminal to upgrade everything. This package can run in and out of virtual environments, and has the ability to exclude packages as well. I actually contributed to it when I first found out about it, and added the ability to use a configuration file for permanent configurations (e.g. permanent excluded packages). Hope you guys find this as useful as I do!
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How often are you supposed to update Python and libraries?
I really like to use the pip-upgrade pip package to upgrade all of my packages, it doesn't break dependencies like normal pip would do with something like pip3 list --outdated --format=freeze | grep -v '^\-e' | cut -d = -f 1 | xargs -n1 pip3 install -U. Here's the link: https://github.com/realiti4/pip-upgrade
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Contributing to FOSS projects
https://github.com/realiti4/pip-upgrade - Updates all packages in pip, and takes into account dependencies, something that pip cannot currently do
What are some alternatives?
uwsgi-nginx-flask-docker - Docker image with uWSGI and Nginx for Flask applications in Python running in a single container.
FetchCord - FetchCord grabs your OS info and displays it as Discord Rich Presence
black - The uncompromising Python code formatter
doorstop - Requirements management using version control.
python-streams - A Library to support Writing concise functional code in python
legendary - Legendary - A free and open-source replacement for the Epic Games Launcher
bazel-coverage-report-renderer - Haskell rules for Bazel.
pip - The Python package installer
TypeRig - Proxy API and Font Development Toolkit for FontLab
ImaginaryInfinity-Calculator
rules_pyenv - Bazel rules for pyenv (simple python version management)
pigar - :coffee: A tool to generate requirements.txt for Python project, and more than that. (IT IS NOT A PACKAGE MANAGEMENT TOOL)