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Python Dependency
Management
Patrick Muehlbauer (@tmuxbee)
2018-10-24
• Predicting bananas
• ...with Python
Blue Yonder
Python Dependency Management
banana_predictions.py
How to provide this to others?
$ python setup.py sdist
banana-predictions-1.0.0.tar.gz
$ python setup.py bdist_wheel
banana_predictions-1.0.0-py3-none-any.whl
How to upload to PyPI?
$ python setup.py upload
but no HTTPS
twine
How to specify dependencies?
setuptools’ install_requires
How to install other uploaded packages?
pip
Different versions of ‘banana_predictions’ in
different projects?
virtualenv
$ virtualenv –p python3.7 venv
Reproducible environments? (I)
$ pip freeze > requirements.txt
$ pip install –r requirements.txt
• multiple tools for the whole workflow
• no real dependency resolution in pip
• multiple files needed for reproducible environments
(requirements.txt, dev-requirements.txt, …)
Reproducible environments? (II)
Pipfile and Pipfile.lock
https://github.com/pypa/pipfile
distutils/setuptools limitations
pyproject.toml
PEP 517 -- A build-system independent format for source trees
PEP 518 -- Specifying Minimum Build System Requirements for Python Projects
Python Dependency Managers
pip-tools
Pipenv
poetry hatch
condaflit
Bento
Pants / pex
pip-tools
Pipenv
poetry hatch
pip-tools
• set of command line tools: pip-compile and pip-sync
• pip-compile for dependency resolution: generates requirements.txt
from setup.py or a requirements.in
• pip-sync for dependency synchronization
setup.py
pip-compile
requirements.txt
$ pip-compile --generate-hashes
$ pip-compile --upgrade
pip-tools brings dependency resolution and a
nicer pinning workflow
Pipenv
• wrapper around pip and virtual environments
• lots of convenience features (e.g. automatic virtualenv creation,
python installation)
• uses Pipfile and Pipfile.lock in addtion to setup.py
• main focus on applications rather than libraries
Pipfile
• separate sections for dev and
main dependencies instead of
requirements.txt and dev-
requirements.txt
• optional section to define
required Python version
Pipfile.lock
$ pipenv install scipy
$ pipenv uninstall scipy
update Pipfile and Pipfile.lock
Poetry
• tool to manage dependencies, build and publish packages
• automatic virtualenv creation
• single config file for everything: pyproject.toml, poetry.lock for
reproduciblity
• reliable dependency resolution
• project scaffolding
$ poetry new my-project
$ poetry add scipy
$ poetry version
$ poetry build
sdist and .whl
$ poetry publish
poetry.lock
hatch
• simplifies development workflow
• wraps multiple tools (pip, virtualenv, twine, pytest, coverage.py, …)
• setup.py + requirements.txt
$ hatch new my-project
$ hatch install
$ hatch test
$ hatch grow
$ hatch build
sdist and .whl
$ hatch release
So...which tool should I use?
It depends...
• building a library?
• or an application?
• does it fit my infrastructure?
Thanks
Python Dependency Management - PyconDE 2018

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Python Dependency Management - PyconDE 2018