autoflake
pip-tools
Our great sponsors
autoflake | pip-tools | |
---|---|---|
8 | 58 | |
858 | 7,472 | |
1.7% | 1.3% | |
8.1 | 8.9 | |
4 days ago | 11 days ago | |
Python | Python | |
MIT License | 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.
autoflake
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Embracing Modern Python for Web Development
Ruff is not only much faster, but it is also very convenient to have an all-in-one solution that replaces multiple other widely used tools: Flake8 (linter), isort (imports sorting), Black (code formatter), autoflake, many Flake8 plugins and more. And it has drop-in parity with these tools, so it is really straightforward to migrate from them to Ruff.
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Improve your Django Code with pre-commit
Ruff can be used to replace Flake8 (plus dozens of plugins), isort, pydocstyle, yesqa, eradicate, pyupgrade, and autoflake, all while executing tens or hundreds of times faster than any individual tool.
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Quick wins in improving your Python codebase health
Having unused imports in a Python file is a prevalent issue, with a very easy solution: autoflake. Running it over your files will remove any unused imports in place.
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Makefile for your Django project
cleanimports: runs isort and removes unused imports with Autoflake. Be sure to set up profile=black in isort settings to avoid conflicts with Black.
- Automatically find and remove unused import statements in your project.
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Formatting Code with Black
We use isort[0] for this. It even has a "black" compatible profile that line spits along black's defaults. Additionally we use autoflake[1] to remove unused import statements in place.
[0](https://github.com/PyCQA/isort)
[1](https://github.com/PyCQA/autoflake)
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Python Code Quality - Improve the quality of your Python code with linters, code formatters, and security vulnerability scanners
yaml repos: - repo: https://github.com/myint/autoflake rev: v1.4 hooks: - id: autoflake args: - --in-place - --remove-all-unused-imports - --expand-star-imports - --remove-duplicate-keys - --remove-unused-variables - repo: https://github.com/asottile/pyupgrade rev: v2.29.0 hooks: - id: pyupgrade args: [--py36-plus] - repo: https://github.com/PyCQA/isort rev: 5.9.3 hooks: - id: isort - repo: https://github.com/psf/black rev: 21.10b0 hooks: - id: black args: [--safe, --quiet] - repo: https://github.com/PyCQA/flake8 rev: 4.0.1 hooks: - id: flake8 - repo: local hooks: - id: pylint name: pylint entry: pylint language: system types: [python] args: [ "-rn", "-sn", ] - repo: https://github.com/pre-commit/mirrors-mypy rev: v0.910-1 hooks: - id: mypy name: mypy entry: mypy language: python types: [python] args: [] require_serial: true - repo: https://github.com/pre-commit/mirrors-prettier rev: v2.4.1 hooks: - id: prettier args: [--prose-wrap=always, --print-width=88]
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Automate Clean Code and Linting in Python
autoflake 400+⭐️
pip-tools
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Pyenv – lets you easily switch between multiple versions of Python
> Why is the "requirements.txt" file a stupid flat listing of all transitive dependencies with pinned versions? It makes it harder to change library versions even if there are no true conflicts.
My friend, here is what you seek: https://github.com/jazzband/pip-tools
requirements.txt is flat because it's really the output of `pip freeze`. It's supposed to completely and exactly rebuild the environment. Unfortunately it's far too flexible and people abuse it by putting in only direct dependencies etc.
If you're writing packages, you don't need a requirements.txt at all, by the way. Package dependencies (only direct dependencies) live in pyproject.toml with the rest of the package config. requirements.txt (and pip tools) are only for when you want to freeze the whole environment, like for a server deployment.
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lockfiles for hatch projects
For all my projects I found myself regenerating manual lock files using complex shell commands with pip-compile to get a reproducible environments across devices using a custom pre-install-command. I finally decided that instead of hacking together the same solution on all my projects I would build a plugin that handles this complexity for me.
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Setting up Django in a Better Way in 5 Minutes and Understanding How It Works
Instead of venv, we are using pip-tools in this starter kit. pip-tools take things further in dependency management. Check out what pip-tools does in their official GitHub repo. In short, it helps your project find the best match for the dependent packages. For example, you might need two packages A and B in your project that requires same package C under the hood. But A requires any version of C from 1.0.1 to 1.0.10 and B requires any version of C from 1.0.7 to 1.0.15. Pip tools will automatically compile the version of 'C' that suits for both of your packages.
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just-pip-tools: An example of managing python dependencies as layered lock files with just and pip-tools
I've created a small project called just-pip-tools that combines pip-tools and just to manage Python dependencies in a layered approach. This isn't a magic bullet; it's a set of files you can adapt to your needs.
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Maintaining virtual environments
For small projects I recommend pip-tools. Just write packet list in requirements.in and pip-compile compile a requirements.txt with comments.
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how to upgrade psycopg2 to psycopg3 as per django latest documentation
Take a look at pip-tools, great package. https://github.com/jazzband/pip-tools
- Single-file scripts that download their dependencies
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What are people using to organize virtual environments these days?
pip-tools
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How to know what a package depend on when pip is installing it?
I recommend generating a lockfile to document this information, as you might do with pip-tools.
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A not so unfortunate sharp edge in Pipenv
Check out pip-tools [1] which does exactly that, albeit in a slightly more polished way.
[1]: https://github.com/jazzband/pip-tools
What are some alternatives?
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.
Poetry - Python packaging and dependency management made easy
black - The uncompromising Python code formatter
PDM - A modern Python package and dependency manager supporting the latest PEP standards
autopep8 - A tool that automatically formats Python code to conform to the PEP 8 style guide.
Pipenv - Python Development Workflow for Humans.
isort - A Python utility / library to sort imports.
conda - A system-level, binary package and environment manager running on all major operating systems and platforms.
Pylint - It's not just a linter that annoys you!
pip - The Python package installer
pyupgrade - A tool (and pre-commit hook) to automatically upgrade syntax for newer versions of the language.
miniforge - A conda-forge distribution.