Nextstrain CLI Development

Development of nextstrain-cli happens at https://github.com/nextstrain/cli.

We currently target compatibility with Python 3.6 and higher.

Versions for this project follow the Semantic Versioning rules.

Setup

You can use Pipenv to spin up an isolated development environment:

pipenv sync --dev
pipenv run nextstrain --help

The Pipenv development environment includes our dev tools (described below):

pipenv run pytest           # runs doctests as well as mypy and flake8
pipenv run mypy nextstrain
pipenv run flake8

Running with local changes

From within a clone of the git repository you can run ./bin/nextstrain to test your local changes without installing them. (Note that ./bin/nextstrain is not the script that gets installed by pip as nextstrain; that script is generated by the entry_points configuration in setup.py.)

Releasing

New releases are made frequently and tagged in git using a signed tag. The source and wheel (binary) distributions are uploaded to the nextstrain-cli project on PyPi.

There is a ./devel/release script which will prepare a new release from your local repository. It ends with instructions for you on how to push the release commit/tag and how to upload the built distributions to PyPi. You’ll need a PyPi account and twine installed.

Tests

Tests are run with pytest. To run everything, use:

pytest

This includes the type annotation and static analysis checks described below.

Type annotations and static analysis

Our goal is to gradually add type annotations to our code so that we can catch errors earlier and be explicit about the interfaces expected and provided. Annotation pairs well with the functional approach taken by the package.

During development you can run static type checks using mypy:

$ mypy nextstrain
# No output is good!

There are also many editor integrations for mypy.

The typing_extensions module should be used for features added to the standard typings module after 3.6. (Currently this isn’t necessary since we don’t use those features.)

We also use Flake8 for some static analysis checks focusing on runtime safety and correctness. You can run them like this:

$ flake8
# No output is good!