pip-deepfreeze

A simple pip freeze workflow for Python application developers.

About

pip-deepfreeze aims at doing one thing and doing it well, namely managing the dependencies of a Python application in a virtual environment.

This includes:

• installing the project and its dependencies,
• updating the environment with new dependencies as the project evolves,
• uninstalling unused dependencies,
• refreshing dependencies,
• maintaining pinned in requirements.txt lock files,
• pinning versions for extras in requirements-{extra}.txt lock files,
• displaying installed dependencies as a tree.

A few characteristics of this project:

• It is easy to use.
• It is fast, with very little overhead on top of a regular pip install + pip freeze.
• It relies on the documented pip command line interface and its ubiquitous requirements file format.
• It assumes your project is configured using a PEP 517/660 compliant build backend but otherwise makes no assumption on the specific backend used.
• It has first class support for dependencies specified as VCS references.
• It is written in Python 3.6+, yet works in any virtual environment that has pip installed, including python 2.
• It is reasonably small and simple, with good test coverage and is hopefully easy to maintain.

Installation

Using pipx (recommended):

pipx install pip-deepfreeze

Using pip:

pip install --user pip-deepfreeze

Quick start

Make sure your application declares its direct dependencies in pyproject.toml, or any other mechanism supported by your PEP 517/660 compliant build backend.

Create and activate a virtual environment using your favorite tool. Run pip list to make sure pip, setuptools and wheel are installed in the virtualenv.

To install your project in editable mode in the active virtual environment, go to your project root directory and run:

pip-df sync

If you don't have one yet, this will generate a file named requirements.txt, containing the exact version of all your application dependencies, as they were installed.

You can then add this requirement.txt to version control, and other people collaborating on the project can install the project and its known good dependencies using pip-df sync (or pip install -r requirements.txt -e . in a fresh virtualenv).

When you add or remove dependencies of your project, run pip-df sync again to update your environment and requirements.txt.

To update one or more dependencies to the latest allowed version, run:

pip-df sync --update DEPENDENCY1,DEPENDENCY2 ...

If you need to add some dependencies from VCS references (e.g. when a library with a patch you need is not available as a release on a package index), add the dependency as usual in your project, then add the VCS reference to a file named requirements.txt.in like this:

DEPENDENCYNAME @ git+https://g.c/org/project@branch

Then run pip-df sync. It will update requirements.txt with a VCS reference pinned at the exact commit that was installed (you need pip version 20.1 or greater for this to work). If later you need to update to the HEAD of the same branch, simply use pip-df sync --update DEPENDENCYNAME.

When, later again, your branch is merged upstream and the project has published a release, remove the line from requirements.txt.in and run pip-df sync --update DEPENDENCYNAME to update to the latest released version.

How to

Creating a new project.

Follow the instructions of your favorite PEP 517/660 compliant build tool, such as hatch, setuptools, flit or others. After declaring the first dependencies, create and activate a virtualenv, then run pip-df sync in the project directory to generate pinned dependencies in requirements.txt.

Installing an existing project.

After checking out the project from source control, create and activate activate virtualenv, the run pip-df sync to install the project.

Updating to the latest version of a project.

After dependencies have been added to the project by others, update the source code from VCS, then run pip-df sync while in your activated virtualenv to bring it to the desired state: dependencies will be updated, removed or uninstalled as needed.

Adding or removing dependencies.

After you have added or removed dependencies to your build tool configuration, simply run pip-df sync to update your virtualenv. You will be prompted to uninstall unneeded dependencies.

Refreshing some pinned dependencies.

After a while you may want to refresh some or all of your dependencies to an up-to-date version. You can do so with pip-df sync --update dep1,dep2,....

Refreshing all pinned dependencies.

To update all dependencies to the latest allowed version, you can use pip-df sync --update-all. This is equivalent to removing requirements.txt then running pip-df sync. This is also roughly equivalent to reinstalling in an empty virtualenv with pip install -e . -c requirements.txt.in then running pip freeze > requirements.txt.

Using another package index than PyPI.

Create a file named requirements.txt.in in your project root, and add pip options to it, such as --extra-index-url or --find-links. You can add any option that pip supports in requirements files.

Installing dependencies from VCS.

When one of your direct or indirect dependencies has a bug or a missing feature, it is convenient to do an upstream pull request then install from it. Assume for instance your project depends on the packaging library and you want to install a pull request you made to it. To do so, make sure packaging is declared as a regular dependency of your project. Then add the VCS reference in requirements.txt.in like so:

packaging @ git+https://github.com/you/packaging@your-branch

Then run pip-df sync --update packaging to install from the branch and pin the exact commit in requirements.txt for reproducibility. When upstream merges your PR and cuts a release, you can simply remove the line from requirements.txt.in and run pip-df sync --update packaging to refresh to the latest released version.

Working with extras.

Assuming your project configuration declares extra dependencies such as tests or docs, you can run pip-df sync --extras tests,docs to update your virtualenv with the necessary dependencies. This will also pin extra dependencies in requirements-tests.txt and requirements-docs.txt. Note that pip-deepfreeze assumes that the extras mechanism is used to specify additional dependencies to the base dependencies of the project.

FAQ

What should I put in requirements.txt.in? Should I add all my dependencies there?

requirements.txt.in is optional. The dependencies of your project must be declared primarily in pyproject.toml (or the legacy setup.py/setup.cfg). requirements.txt.in may contain additional constraints if needed, such as version constraints on indirect dependencies that you don't control, or VCS links for dependencies that you need to install from VCS source.

I have added a constraint in requirements.txt.in but pip-df sync does not honor it. What is going on?

pip-df sync always gives priority to versions pinned in requirements.txt, unless explicitly asked to do otherwise. After adding or changing constraints or VCS references for already pinned requirements, use the --update option like so:

pip-df sync --update DEPENDENCY1,DEPENDENCY2,...

pip-deepfreeze erroneously complains python is not running in a virtualenv.

The most probable cause is that you used an older version of virtualenv which does not generate PEP 405 compliant virtual environments. virtualenv version 20 and later are supported, as well as the Python 3 native venv module. Should this problem be prevalent in practice, we may add support for older virtualenv versions, or add an option to ignore the virtualenv sanity check (which is only there to prevent pip-deepfreeze to corrupt the system Python packages by accident).

How can I pass options to pip?

The most reliable and repeatable way to pass options to pip is to add them in requirements.txt.in. The pip documentation lists options that are allowed in requirements files. Global options can also be set in the pip configuration file or passed via PIP_* environment variables (see the pip documentation for more information).

Why not using pip install and pip freeze manually?

pip-df sync combines both commands in one and ensures your environment and pinned requirements remain correct and up-to-date. Some error prone operations it facilitates include: uninstalling unneeded dependencies, updating selected dependencies, overriding dependencies with VCS references, etc.

Is there a recommended way to deploy my project in the production environment?

There are many possibilities. One approach that works well (and is recommended in the pip documentation) works with two simple steps. First you build the wheel files for your project and dependencies, using:

pip wheel --no-deps -r requirements.txt -e . --wheel-dir=./wheel-dir

Then you ship the content of the wheel-dir directory to your target environment or docker image, and run:

pip install --no-index --find-links=./wheel-dir project-name

Note the use of --no-deps when building and --no-index when installing. This will ensure that all the required dependencies are effectively pinned in requirements.txt.

CLI reference

Global options

Usage: pip-df [OPTIONS] COMMAND [ARGS]...

  A simple pip freeze workflow for Python application developers.

Options:
  -p, --python PYTHON           The python executable to use. Determines the
                                python environment to work on. Defaults to the
                                'python' executable found in PATH.

  -r, --project-root DIRECTORY  The project root directory.  [default: .]
  -v, --verbose
  --install-completion          Install completion for the current shell.
  --show-completion             Show completion for the current shell, to copy
                                it or customize the installation.

  --help                        Show this message and exit.

Commands:
  sync  Install/update the environment to match the project requirements.
  tree  Print the installed dependencies of the project as a tree.

pip-df sync

Usage: pip-df sync [OPTIONS]

  Install/update the environment to match the project requirements, and lock new
  dependencies.

  Install/reinstall the project. Install/update dependencies to the latest
  allowed version according to pinned dependencies in requirements.txt or
  constraints in requirements.txt.in. On demand update of dependencies to to
  the latest version that matches constraints. Optionally uninstall unneeded
  dependencies.

Options:
  -u, --update DEP1,DEP2,...      Make sure selected dependencies are upgraded
                                  (or downgraded) to the latest allowed
                                  version. If DEP is not part of your
                                  application dependencies anymore, this
                                  option has no effect.

  --update-all                    Upgrade (or downgrade) all dependencies of
                                  your application to the latest allowed
                                  version.

  -x, --extras EXTRAS             Extras to install and freeze to
                                  requirements-{EXTRA}.txt.

  --uninstall-unneeded / --no-uninstall-unneeded
                                  Uninstall distributions that are not
                                  dependencies of the project. If not
                                  specified, ask confirmation.

  --help                          Show this message and exit.

pip-df tree

Usage: pip-df tree [OPTIONS]

  Print the installed dependencies of the project as a tree.

Options:
  -x, --extras EXTRAS  Extras of project to consider when looking for
                       dependencies.

  --help               Show this message and exit.

Other tools

Several other tools exist with a similar or overlapping scope as pip-deepfreeze.

• pip itself. pip-deepfreeze relies extensively on the pip CLI for installation and querying the database of installed distributions. In essence it is a thin wrapper around pip install and pip freeze. Some of the features here may serve as inspiration for future pip evolutions.
• pip-tools. This is the one with the most similar features. Besides the reasons explained in About above I wanted to see if it was possible to do such a thing using the pip CLI only.
• pipdeptree. Works similarly as pip-df tree.
• Poetry
• pipenv

Development

To run tests, use tox. You will get a test coverage report in htmlcov/index.html. An easy way to install tox is pipx install tox.

This project uses pre-commit to enforce linting (among which black for code formating, isort for sorting imports, and mypy for type checking).

To make sure linters run locally on each of your commits, install pre-commit (pipx install pre-commit is recommended), and run pre-commit install in your local clone of the pip-deepfreeze repository.

To release:

• Select the next version number of the form X.Y.Z.
• towncrier --version vX.Y.Z.
• Inspect and commit the updated HISTORY.rst.
• git tag vX.Y.Z ; git push --tags.

Contributing

We welcome contributions of all kinds.

Please consult the issue tracker to discover the roadmap and known bugs.

Before opening a pull request, please create an issue first to discuss the bug or feature request.