General Notes

Getting Started

  • Make sure you have a GitHub account.

  • Submit a ticket for your issue, assuming one does not already exist.

    • Clearly describe the issue including steps to reproduce when it is a bug.

    • Make sure you fill in the earliest version that you know has the issue.

  • Fork the repository on GitHub

Making Changes

  • Create a topic branch from where you want to base your work.

    • This is usually the main branch.

    • Only target release branches if you are certain your fix must be on that branch.

    • To quickly create a topic branch based on main; git checkout -b my_branch_name main. Please avoid working directly on the main branch.

  • Make commits of logical units.

  • Check for unnecessary whitespace with git diff --check before committing.

  • Make sure your commit messages are in the proper format (see below)

  • Make sure you have added the necessary tests for your changes.

  • Run all the tests to assure nothing else was accidentally broken.

Writing the commit message

Commit messages should be clear and follow a few basic rules. Example:

ENH: add functionality X to bluesky.<submodule>.

The first line of the commit message starts with a capitalized acronym
(options listed below) indicating what type of commit this is.  Then a blank
line, then more text if needed.  Lines shouldn't be longer than 72
characters.  If the commit is related to a ticket, indicate that with
"See #3456", "See ticket 3456", "Closes #3456" or similar.

Describing the motivation for a change, the nature of a bug for bug fixes or some details on what an enhancement does are also good to include in a commit message. Messages should be understandable without looking at the code changes.

Standard acronyms to start the commit message with are:

API: an (incompatible) API change
BLD: change related to building numpy
BUG: bug fix
CI : continuous integration
DEP: deprecate something, or remove a deprecated object
DEV: development tool or utility
DOC: documentation
ENH: enhancement
MNT: maintenance commit (refactoring, typos, etc.)
REV: revert an earlier commit
STY: style fix (whitespace, PEP8)
TST: addition or modification of tests
REL: related to releases

The Pull Request

  • Now push to your fork

  • Submit a pull request to this branch. This is a start to the conversation.

At this point you’re waiting on us. We like to at least comment on pull requests within three business days (and, typically, one business day). We may suggest some changes or improvements or alternatives.

Hints to make the integration of your changes easy (and happen faster):

  • Keep your pull requests small

  • Don’t forget your unit tests

  • All algorithms need documentation, don’t forget the .rst file

  • Don’t take changes requests to change your code personally

Installation of the Queue Server for Development

Install Redis and create Conda environment as described in Installation Steps.

Install the Queue Server in editable mode:

$ pip install -e .

Install development dependencies:

$ pip install -r requirements-dev.txt

Setting up pre-commit

pre-commit` package is installed as part of the development requirements. Install pre-commit script by running

$ pre-commit install

Once installed, pre-commit will perform all the checks before each commit. As the new versions of validation packages are released, the pre-commit script can be updated by running

$ pre-commit autoupdate

Running Unit Tests Locally

The Queue Server must be tested separately with disabled IPython mode:

$ pytest -vvv


$ USE_IPYKERNEL=false pytest -vvv

and enabled IPython mode:

$ USE_IPYKERNEL=true pytest -vvv

Running Unit Tests on GitHub

Execution of the full test suite on CI takes too long and causes major inconvenience, therefore it is split into multiple groups (currently 3 groups) using pytest-split package. Since the goal is to reduce the execution time of the longest group, the splitting algorithm is calibrated based on execution time of the tests with enabled IPython kernel mode (more tests, each test takes a little longer to execute). Calibration is performed by running the script locally, which saves execution time for each test in the `.test_durations file. The file then has to be committed and pushed to the repository.

pytest-split will automatically guess execution time for new tests that are not listed in .test_durations file, so calibration may be needed rarely or after major changes to the test suite and should be left to the package maintainers.