pip-tools

pip-tools = pip-compile + pip-sync A set of command line tools to help you keep your pip-based packages fresh, even when you've pinned them. You do pin them, right? (In building your Python application and its dependencies for production, you want to make sure that your builds are predictable and deterministic.) Installation Similar to pip, pip-tools must be installed in each of your project's virtual environments: $ source /path/to/venv/bin/activate (venv) $ python -m pip install pip-tools Note: all of the remaining example commands assume you've activated your project's virtual environment. Example usage for pip-compile The pip-compile command lets you compile a requirements.txt file from your dependencies, specified in either pyproject.toml, setup.cfg, setup.py, or requirements.in. Run it with pip-compile or python -m piptools compile (or pipx run --spec pip-tools pip-compile if pipx was installed with the appropriate Python version). If you use multiple Python versions, you can also run py -X.Y -m piptools compile on Windows and pythonX.Y -m piptools compile on other systems. pip-compile should be run from the same virtual environment as your project so conditional dependencies that require a specific Python version, or other environment markers, resolve relative to your project's environment. Note: If pip-compile finds an existing requirements.txt file that fulfils the dependencies then no changes will be made, even if updates are available. To compile from scratch, first delete the existing requirements.txt file, or see Updating requirements for alternative approaches. Requirements from pyproject.toml The pyproject.toml file is the latest standard for configuring packages and applications, and is recommended for new projects. pip-compile supports both installing your project.dependencies as well as your project.optional-dependencies. Thanks to the fact that this is an official standard, you can use pip-compile to pin the dependencies in projects that use modern standards-adhering packaging tools like Setuptools, Hatch or flit. Suppose you have a 'foobar' Python application that is packaged using Setuptools, and you want to pin it for production. You can declare the project metadata as: [build-system] requires = ["setuptools", "setuptools-scm"] build-backend = "setuptools.build_meta" [project] requires-python = ">=3.9" name = "foobar" dynamic = ["dependencies", "optional-dependencies"] [tool.setuptools.dynamic] dependencies = { file = ["requirements.in"] } optional-dependencies.test = { file = ["requirements-test.txt"] } If you have a Django application that is packaged using Hatch, and you want to pin it for production. You also want to pin your development tools in a separate pin file. You declare django as a dependency and create an optional dependency dev that includes pytest: [build-system] requires = ["hatchling"] build-backend = "hatchling.build" [project] name = "my-cool-django-app" version = "42" dependencies = ["django"] [project.optional-dependencies] dev = ["pytest"] You can produce your pin files as easily as: $ pip-compile -o requirements.txt pyproject.toml # # This file is autogenerated by pip-compile with Python 3.10 # by the following command: # # pip-compile --output-file=requirements.txt pyproject.toml # asgiref==3.6.0 # via django django==4.1.7 # via my-cool-django-app (pyproject.toml) sqlparse==0.4.3 # via django $ pip-compile --extra dev -o dev-requirements.txt pyproject.toml # # This file is autogenerated by pip-compile with Python 3.10 # by the following command: # # pip-compile --extra=dev --output-file=dev-requirements.txt pyproject.toml # asgiref==3.6.0 # via django attrs==22.2.0 # via pytest django==4.1.7 # via my-cool-django-app (pyproject.toml) exceptiongroup==1.1.1 # via pytest iniconfig==2.0.0 # via pytest packaging==23.0 # via pytest pluggy==1.0.0 # via pytest pytest==7.2.2 # via my-cool-django-app (pyproject.toml) sqlparse==0.4.3 # via django tomli==2.0.1 # via pytest This is great for both pinning your applications, but also to keep the CI of your open-source Python package stable. Requirements from setup.py and setup.cfg pip-compile has also full support for setup.py- and setup.cfg-based projects that use setuptools. Just define your dependencies and extras as usual and run pip-compile as above. Requirements from requirements.in You can also use plain text files for your requirements (e.g. if you don't want your application to be a package). To use a requirements.in file to declare the Django dependency: # requirements.in django Now, run pip-compile requirements.in: $ pip-compile requirements.in # # This file is autogenerated by pip-compile with Python 3.10 # by the following command: # # pip-compile requirements.in # asgiref==3.6.0 # via django django==4.1.7 # via -r requirements.in sqlparse==0.4.3 # via django And it will produce your requirements.txt, with all the Django dependencies (and all underlying dependencies) pinned. (updating-requirements)= Updating requirements pip-compile generates a requirements.txt file using the latest versions that fulfil the dependencies you specify in the supported files. If pip-compile finds an existing requirements.txt file that fulfils the dependencies then no changes will be made, even if updates are available. To force pip-compile to update all packages in an existing requirements.txt, run pip-compile --upgrade. To update a specific package to the latest or a specific version use the --upgrade-package or -P flag: # only update the django package $ pip-compile --upgrade-package django # update both the django and requests packages $ pip-compile --upgrade-package django --upgrade-package requests # update the django package to the latest, and requests to v2.0.0 $ pip-compile --upgrade-package django --upgrade-package requests==2.0.0 You can combine --upgrade and --upgrade-package in one command, to provide constraints on the a