Requirements¶

TLDR

When you import a package for the first time in your application code, add its name to requirements.in in alphabetical order.
When you import a package for the first time in your test code, that is never imported in your application code, add its name to requirements_dev.in in alphabetical order.
After updating a .in file, update the .txt files with pip-compile; pip-compile requirements_dev.in. Never edit the .txt files directly.
To update your local environment, run pip-sync requirements_dev.txt.

Now that you have a directory layout, you can declare the project’s requirements.

The requirements of applications (not packages) are managed by four files:

requirements.in names all direct requirements needed in the production environment, i.e. all packages import’ed by the application.
- If the application is incompatible with older or newer versions of a requirement, use the least specific version specifier possible, for example:
  - Newer versions: foo>=1.2, not foo>=1.2.3
  - Older versions: foo<2
  - Versions range: foo>=1.2,<2
requirements_dev.in names all direct requirements needed exclusively in the development environment, and not in the production environment, e.g. pytest or pip-tools itself.
- This file should include the direct requirements needed in the production environment, by having a first line of -r requirements.txt.
requirements.txt names all direct and indirect requirements needed in the production environment, all locked to specific versions by pip-tools.
requirements_dev.txt names all direct and indirect requirements needed in the development environment, all locked to specific versions by pip-tools.

This ensures that:

All environments use the same versions of production requirements, to ensure consistent and replicable deployments and to avoid errors or surprises during or after deployment due to differences between versions (e.g. a new version of Django requires upgrading application code).
Different developers and continuous integration use the same versions of development requirements, to avoid test failures due to differences between versions (e.g. a new version of pytest requires upgrading test code, or a new version of flake8 has stricter linting rules).

Get started¶

pip install pip-tools

A common starter requirements.in for Django is:

dj-database-url
django<5
psycopg2
sentry-sdk

A common starter requirements_dev.in for linting in Django is:

-r requirements.txt
black
coverage
coveralls
flake8
isort
pip-tools
pre-commit

If not using Django, remove coverage and add:

pytest
pytest-cov

Add a requirement¶

Add the requirement in alphabetical order to the appropriate .in file. Then, run:

pip-compile
pip-compile requirements_dev.in

If running pip-compile introduces unexpected differences, upgrade pip-tools to the latest version, and check that you are using the same version of Python as for other runs.

psycopg2¶

psycopg2 is recommended for production. However, installing psycopg2 for development can be difficult on operating systems like macOS. In that case, you can:

Put psycopg2 in requirements.in
Put psycopg2-binary in requirements_dev.in
Run: pip install psycopg2-binary

Note

You must keep the locked versions of psycopg2 and psycopg2-binary in sync.

Install requirements¶

In development:

pip-sync requirements_dev.txt

In production:

pip-sync -q --pip-args "--exists-action w"

Upgrade requirements¶

Requirements should be periodically updated, both for security updates and to better distribute the maintenance burden of upgrading versions over time.

Upgrade one requirement, for example:

pip-compile -P requests
pip-compile -P requests requirements_dev.in

Upgrade all requirements:

pip-compile --upgrade
pip-compile --upgrade requirements_dev.in

Linting¶

Continuous integration runs test_requirements.py, which checks whether any requirements are missing or unused.

If a requirement is reported as unused but is required:

Make sure that a related package sets extras correctly. For example, moto has optional dependencies for each AWS service. You must do, for example:
```
moto[s3]
```
If the package is optional – for example, it is imported in a try and except ImportError block – use the STANDARD_MAINTENANCE_SCRIPTS_IGNORE environment variable.
If the package is used exclusively outside of application code – for example, as a command in the production environment or in a GitHub workflow, or in an entry point or as a Sphinx extension – use the STANDARD_MAINTENANCE_SCRIPTS_IGNORE environment variable.

If the repository uses Pre-commit hooks, and you see errors originating from pip, it is likely that you need to upgrade pip-tools in both .pre-commit-config.yaml and requirements_dev.txt.