Dependency Management, Packaging, and Distribution

General Considerations

There are a number of tasks necessary to develop and distribute a Python package, and a number of tools to assist with these processes. The Python Packaging User Guide lists the following, among others:

Task	poetry	Hatch	pipenv	venv	build	setuptools	flit	twine
Dependency management	X		X
Virtual environment	X	X	X	X
Build frontend	X	X			X
Build backend	X	X				X	X
Publishing to pypi.org	X	X					X	X

DSP-TOOLS uses poetry for all of these tasks. This allows us to use one single tool for all processes, and to keep the number of configuration files at a minimum.

Poetry needs only 2 config files:

pyproject.toml: Manifest file, a modern configuration/metadata file replacing the deprecated files listed below
poetry.lock: Lock file, containing the pinned versions of all (sub-)dependencies, allowing a deterministic installation

Dependency Management

The classic way to manage the dependencies was to write the required packages by hand into a requirements.txt and into a setup.py file. But this is cumbersome and error-prone. Moreover, setup.py is problematic and not recommended anymore, especially calling setup.py sdist bdist_wheel. Python projects should define their dependencies and metadata in the modern pyproject.toml file.

So it is necessary to dynamically manage the dependencies in pyproject.toml. And poetry seems to be the only tool capable of doing this.

Poetry is one of the few tools that cleanly distinguishes

dependencies necessary to run the application,
dependencies necessary for development, and
sub-dependencies, i.e. dependencies of your dependencies.

It is also one of the few tools that makes the distinction between

the manifest file, i.e. a human-friendly list of (mostly unpinned) direct dependencies and
the lock file, i.e. a machine-friendly definition of exact (pinned) versions of all dependencies.

Packaging

All project metadata, together with the dependencies and the configuration of the packaging tool poetry, is defined in pyproject.toml. The authoritative resource on how to create this file is https://packaging.python.org/en/latest/guides/writing-pyproject-toml/#writing-pyproject-toml.

The table [build-system] of pyproject.toml tells frontend build tools what backend build tool to use. The backend doesn't need to be installed. It will be installed by the frontend in a temporary, isolated environment for use during the build process. DSP-TOOLS uses poetry as both frontend and backend.

What happens when a distribution package of DSP-TOOLS is created? Poetry creates two files in the dist folder: a . tar.gz compressed archive (the sdist or source distribution) and a .whl file (a wheel). Both contain the contents of the src folder plus some metadata - they are equivalent. They are then uploaded to the Python Package Index (PyPI).

When a user installs DSP-TOOLS with pip install dsp-tools, pip takes the sdist or the wheel, unpacks it, and copies it into the site-packages folder of the user's Python installation. As a result, the user has the same packages in his site-packages folder as the src folder of the dsp-tools repository. In our case, this is the dsp_tools package. Since site-packages is on sys.path, the user can then import the package dsp_tools in his script.

Advantages of the src Layout

Putting all packages into a src folder has an important consequence: It forces the developer to work with an editable installation of his package. Why? Without an editable installation, it is impossible to write correct import statements. from src.package import module will not work, because the user has package installed, not src. And relative imports like import module will not work either, because when the test code (situated in a separate test folder) imports the actual code, the relative imports in the actual code fail. This is because relative imports depend on the location of the file that is run, not on the file that contains the import statement.

The solution is to always have an editable installation of the package under development. Poetry does this automatically when you execute poetry install. This makes the package dsp_tools importable - just like on a user's machine. And exactly this is the big advantage: With the src layout and an editable installation, the setup on the developer's machine is more similar to the user's setup.

The advantages of the src layout are:

import parity
The tests run against the package as it will be installed by the user - not against the situation in the developer's repository.
It is obvious to both humans and tools if a folder is a package to be distributed, or not.
The editable installation is only able to import modules that will also be importable in a regular installation.
For the developer, the working directory is the root of the repository, so the root will implicitly be included in sys.path. Users will never have the same current working directory than the developer. So, removing the packages from the root by putting them into src prevents some practices that will not work on the user's machine.

For more in-depth explanations, please visit the following pages:

Publishing and Distribution

Publishing is automated with GitHub Actions and should not be done manually. If you still need to do it, follow the steps below.

Generate the distribution package:

poetry build

You can install the package locally from the dist:

pip install dist/some_name.whl

Upload package:

poetry publish