PDM
pip-tools
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PDM | pip-tools | |
---|---|---|
47 | 58 | |
6,431 | 7,451 | |
3.4% | 1.0% | |
9.6 | 8.9 | |
6 days ago | 23 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.
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.
It's per project, check out pdm if you want a preview https://github.com/pdm-project/pdm
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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
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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).
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.
- 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.
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Show HN: Panoptisch – A recursive dependency scanner for Python projects
I've been using pip-compile from https://github.com/jazzband/pip-tools for this use case; a standard project Makefile defines "make update" which pip-compiles the current requirements, and "make install" installs the frozen requirements list.
This way I can install the same bill of materials every time
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Vent: I'm tired of the 1001 libraries of virtual environments.
I like pip-tools for this use case—it lets you write a separate requirements file with “loose” dependencies, which then gets compiled to a requirements.txt with pinned version numbers (it essentially becomes your “lock” file). It also supports layered dependencies, which allows you to create “dev dependencies”.
What are some alternatives?
Poetry - Python packaging and dependency management made easy
conda - A system-level, binary package and environment manager running on all major operating systems and platforms.
pip - The Python package installer
Pipenv - Python Development Workflow for Humans.
PyFlow - Visual scripting framework for python - https://wonderworks-software.github.io/PyFlow
pyenv - Simple Python version management
dephell - :package: :fire: Python project management. Manage packages: convert between formats, lock, install, resolve, isolate, test, build graph, show outdated, audit. Manage venvs, build package, bump version.
miniforge - A conda-forge distribution.