π IntroductionΒΆ
UniDep streamlines Python project dependency management by unifying Conda and Pip packages in a single system. Learn when to use UniDep in our FAQ.
Handling dependencies in Python projects can be challenging, especially when juggling Python and non-Python packages. This often leads to confusion and inefficiency, as developers juggle between multiple dependency files.
π Unified Dependency File: Use either
requirements.yaml
orpyproject.toml
to manage both Conda and Pip dependencies in one place.βοΈ Build System Integration: Integrates with Setuptools and Hatchling for automatic dependency handling during
pip install ./your-package
.π» One-Command Installation:
unidep install
handles Conda, Pip, and local dependencies effortlessly.π’ Monorepo-Friendly: Render (multiple)
requirements.yaml
orpyproject.toml
files into one Condaenvironment.yaml
file and maintain fully consistent global and per sub packageconda-lock
files.π Platform-Specific Support: Specify dependencies for different operating systems or architectures.
π§
pip-compile
Integration: Generate fully pinnedrequirements.txt
files fromrequirements.yaml
orpyproject.toml
files usingpip-compile
.π Integration with
conda-lock
: Generate fully pinnedconda-lock.yml
files from (multiple)requirements.yaml
orpyproject.toml
file(s), leveragingconda-lock
.π€ Nerd stats: written in Python, >99% test coverage, fully-typed, all Ruffβs rules enabled, easily extensible, and minimal dependencies
unidep
is designed to make dependency management in Python projects as simple and efficient as possible.
Try it now and streamline your development process!
Tip
Check out the example requirements.yaml
and pyproject.toml
below.