synapse/docs/development/dependencies.md

Managing dependencies with Poetry

This is a quick cheat sheet for developers on how to use poetry.

Background

Synapse uses a variety of third-party Python packages to function as a homeserver. Some of these are direct dependencies, listed in pyproject.toml under the [tool.poetry.dependencies] section. The rest are transitive dependencies (the things that our direct dependencies themselves depend on, and so on recursively.)

We maintain a locked list of all our dependencies (transitive included) so that we can track exactly which version of each dependency appears in a given release. See here for discussion of why we wanted this for Synapse. We chose to use poetry to manage this locked list; see this comment for the reasoning.

The locked dependencies get included in our "self-contained" releases: namely, our docker images and our debian packages. We also use the locked dependencies in development and our continuous integration.

Separately, our "broad" dependencies—the version ranges specified in pyproject.toml—are included as metadata in our "sdists" and "wheels" uploaded to PyPI. Installing from PyPI or from the Synapse source tree directly will not use the locked dependencies; instead, they'll pull in the latest version of each package available at install time.

Example dependency

An example may help. We have a broad dependency on phonenumbers, as declared in this snippet from pyproject.toml as of Synapse 1.57:

[tool.poetry.dependencies]
# ...
phonenumbers = ">=8.2.0"

In our lockfile this is pinned to version 8.12.44, even though newer versions are available.

[[package]]
name = "phonenumbers"
version = "8.12.44"
description = "Python version of Google's common library for parsing, formatting, storing and validating international phone numbers."
category = "main"
optional = false
python-versions = "*"

The lockfile also includes a cryptographic checksum of the sdists and wheels provided for this version of phonenumbers.

[metadata.files]
# ...
phonenumbers = [
    {file = "phonenumbers-8.12.44-py2.py3-none-any.whl", hash = "sha256:cc1299cf37b309ecab6214297663ab86cb3d64ae37fd5b88e904fe7983a874a6"},
    {file = "phonenumbers-8.12.44.tar.gz", hash = "sha256:26cfd0257d1704fe2f88caff2caabb70d16a877b1e65b6aae51f9fbbe10aa8ce"},
]

We can see this pinned version inside the docker image for that release:

$ docker pull matrixdotorg/synapse:v1.57.0
...
$ docker run --entrypoint pip matrixdotorg/synapse:v1.57.0 show phonenumbers
Name: phonenumbers
Version: 8.12.44
Summary: Python version of Google's common library for parsing, formatting, storing and validating international phone numbers.
Home-page: https://github.com/daviddrysdale/python-phonenumbers
Author: David Drysdale
Author-email: dmd@lurklurk.org
License: Apache License 2.0
Location: /usr/local/lib/python3.9/site-packages
Requires:
Required-by: matrix-synapse

Whereas the wheel metadata just contains the broad dependencies:

$ cd /tmp
$ wget https://files.pythonhosted.org/packages/ca/5e/d722d572cc5b3092402b783d6b7185901b444427633bd8a6b00ea0dd41b7/matrix_synapse-1.57.0rc1-py3-none-any.whl
...
$ unzip -c matrix_synapse-1.57.0rc1-py3-none-any.whl matrix_synapse-1.57.0rc1.dist-info/METADATA | grep phonenumbers
Requires-Dist: phonenumbers (>=8.2.0)

Tooling recommendation: direnv

direnv is a tool for activating environments in your shell inside a given directory. Its support for poetry is unofficial (a community wiki recipe only), but works solidly in our experience. We thoroughly recommend it for daily use. To use it:

1. Install direnv - it's likely packaged for your system already.
2. Teach direnv about poetry. The shell config here needs to be added to ~/.config/direnv/direnvrc (or more generally $XDG_CONFIG_HOME/direnv/direnvrc).
3. Mark the synapse checkout as a poetry project: echo layout poetry > .envrc.
4. Convince yourself that you trust this .envrc configuration and project. Then formally confirm this to direnv by running direnv allow.

Then whenever you navigate to the synapse checkout, you should be able to run e.g. mypy instead of poetry run mypy; python instead of poetry run python; and your shell commands will automatically run in the context of poetry's venv, without having to run poetry shell beforehand.

How do I...

...reset my venv to the locked environment?

poetry install --extras all --remove-untracked

...delete everything and start over from scratch?

# Stop the current virtualenv if active
$ deactivate

# Remove all of the files from the current environment.
# Don't worry, even though it says "all", this will only
# remove the Poetry virtualenvs for the current project.
$ poetry env remove --all

# Reactivate Poetry shell to create the virtualenv again
$ poetry shell
# Install everything again
$ poetry install --extras all

...run a command in the poetry virtualenv?

Use poetry run cmd args when you need the python virtualenv context. To avoid typing poetry run all the time, you can run poetry shell to start a new shell in the poetry virtualenv context. Within poetry shell, python, pip, mypy, trial, etc. are all run inside the project virtualenv and isolated from the rest o the system.

Roughly speaking, the translation from a traditional virtualenv is:

• env/bin/activate -> poetry shell, and
• deactivate -> close the terminal (Ctrl-D, exit, etc.)

See also the direnv recommendation above, which makes poetry run and poetry shell unnecessary.

...inspect the poetry virtualenv?

Some suggestions:

# Current env only
poetry env info
# All envs: this allows you to have e.g. a poetry managed venv for Python 3.7,
# and another for Python 3.10.
poetry env list --full-path
poetry run pip list

Note that poetry show describes the abstract lock file rather than your on-disk environment. With that said, poetry show --tree can sometimes be useful.

...add a new dependency?

Either:

• manually update pyproject.toml; then poetry lock --no-update; or else
• poetry add packagename. See poetry add --help; note the --dev, --extras and --optional flags in particular.
  • NB: this specifies the new package with a version given by a "caret bound". This won't get forced to its lowest version in the old deps CI job: see this TODO.

Include the updated pyproject.toml and poetry.lock files in your commit.

...remove a dependency?

This is not done often and is untested, but

poetry remove packagename

ought to do the trick. Alternatively, manually update pyproject.toml and poetry lock --no-update. Include the updated pyproject.toml and poetry.lock` files in your commit.

...update the version range for an existing dependency?

Best done by manually editing pyproject.toml, then poetry lock --no-update. Include the updated pyproject.toml and poetry.lock in your commit.

...update a dependency in the locked environment?

Use

poetry update packagename

to use the latest version of packagename in the locked environment, without affecting the broad dependencies listed in the wheel.

There doesn't seem to be a way to do this whilst locking a specific version of packagename. We can workaround this (crudely) as follows:

poetry add packagename==1.2.3
# This should update pyproject.lock.

# Now undo the changes to pyproject.toml. For example
# git restore pyproject.toml

# Get poetry to recompute the content-hash of pyproject.toml without changing
# the locked package versions.
poetry lock --no-update

Either way, include the updated poetry.lock file in your commit.

...export a requirements.txt file?

poetry export --extras all

Be wary of bugs in poetry export and pip install -r requirements.txt.

Note: poetry export will be made a plugin in Poetry 1.2. Additional config may be required.

...build a test wheel?

I usually use

poetry run pip install build && poetry run python -m build

because build is a standardish tool which doesn't require poetry. (It's what we use in CI too). However, you could try poetry build too.

Troubleshooting

Check the version of poetry with poetry --version.

The minimum version of poetry supported by Synapse is 1.2.

It can also be useful to check the version of poetry-core in use. If you've installed poetry with pipx, try pipx runpip poetry list | grep poetry-core.

Clear caches: poetry cache clear --all pypi.

Poetry caches a bunch of information about packages that isn't readily available from PyPI. (This is what makes poetry seem slow when doing the first poetry install.) Try poetry cache list and poetry cache clear --all <name of cache> to see if that fixes things.

Remove outdated egg-info

Delete the matrix_synapse.egg-info/ directory from the root of your Synapse install.

This stores some cached information about dependencies and often conflicts with letting Poetry do the right thing.

Try --verbose or --dry-run arguments.

Sometimes useful to see what poetry's internal logic is.