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Notes for Developers

This section provides details on how to configure and/or develop this codebase.

Continuos Integration/Continuous Deployment (CI/CD) Workflow

This project uses GitHub Workflows to automate or ease a number of development tasks. These workflows can be found within the ./.github/workflows/ directory and include: 1. pull_request.yml

This workflow is run whenever a pull request is opened, updated or reopened.  The following things are enforced by this workflow:

- linting and code formatting standards
- proper maintainance of the Poetry project
- successful building of the project
- successful building of the documentation
- successful running of tests

  1. bump.yml

    This workflow leverages the colocated bump.sh bash script to automatically increment the project version whenever code is pushed to the main branch. It is controlled by adding the text [version:minor] or [version:major] to the message of the pull request's head commit.

  2. publish.yml

    This workflow is run whenever a new release is generated through GitHub (see below for details on how to do this). Documentation is updated on GitHub Pages and a new version of the code is published on the Python Package Index (PyPI).

Setting-up the Code

A local development copy of the code base can be obtained and configured as follows:

  • Navigate to the GitHub page hosting the project
  • If you want to fork the code so that you work on your own version of the repository (not generally needed or recommended):
    • Click on the fork button at the top of the page;
    • Edit the details you want to have for the new repoitory; and
    • Press Create fork.
  • Obtain the URL for the repository you're going to use (denoted <url>) by clicking on the green Code button on the repository GitHub page
  • On your local machine, navigate with your terminal to the location where you want to place the code
  • Generate a local copy using git clone <url>;

Note

Although not strictly necessary, it is recommended that you configure the branch permissions of any forked repositories as detailed in the GitHub configuration section below.

Poetry and Python environments for development

Poetry is used to manage this project (see here for an introduction). It simplifies & helps with managing the following:

  1. Creation and activation of a Python environment for the project

    Python development should always be managed using a Python environment. Poetry makes this easy for you. You simply run the following from within the project:

    $ poetry shell

    Note

    You don't have to use Poetry to manage your Python environment if you would rather not. You can instruct Poetry to respect your Python environemnts (e.g. created with pyenv) by setting the following option: 

    $ poetry config virtualenvs.prefer-active-python true

  2. Dependency management

    Poetry manages a "lock file" (which should be committed and maintained within the code repository) ensuring repeatible installs for all versions.

  3. Publication of the project to the Python Package Index (PyPI) so that people can easily install it for themselves

    Once properly configured, publishing to PyPI with Poetry is extremely easy. This is generally managed by the CI/CD workflow for the project though, and developers should never have to manually do this.

Installing Development Dependencies

Once the code is locally installed, development dependencies should be installed by moving to the project's root directory and executing the following:

$ poetry install

In what follows, it will be assumed that this has been done.

Guidelines

In the following, we lay-out some important guidelines for developing on this codebase.

Branches

Development should never be conducted on the main branch. If GitHub has been properly configured (see below), then merges to this branch are limited to Pull Requests (PRs) only. Once a PR is opened for the main branch, the project tests are run. When it is closed and code is committed to the main branch, the project version is automatically incremented (see below).

Versioning

Semantic versioning (i.e. a scheme that follows a vMAJOR.MINOR.PATCH format; see https://semver.org for details) is used for this project. The single point of truth for the current production version is the last git tag on the main branch with a v[0-9]* format. When developing locally, the reported version will appear as v0.0.0-dev.

Changes are handled by a GitHub Workflow which increments the version and creates a new tag whenever a push occurs to the main branch. This ensures that every commit on the main branch is assigned a unique version. The logic by which it modifies the version is as follows:

  1. if the message of the PR's head commit contains the text [version:major], then MAJOR is incremented;
  2. else if it contains the text [version:minor], then MINOR is incremented;
  3. else PATCH is incremented.

A MAJOR version change should be indicated if the PR introduces a breaking change. A MINOR version change should be indicated if the PR introduces new functionality.

Note

Make sure you think carefully about what type of changes you are committing. If you are adding functionality, make sure you bump the MINOR version; if you are making breaking changes, make sure you bump the MAJOR version. Users will be very thankful that you did!

Tests

PyTest is used to run tests for this codebase. Make sure you run them before submitting any code to a PR by executing the following from the project root directory:

$ pytest

Some further comments about how testing has been configured for this project:

Coverage

PyTest has been configured for this project to create a coverage report after running. This report will inform the developer of what fraction of the code base is exercised by the tests and give a list of lines of code in each Python filename which has not been exercised by the tests run.

While not strictly enforced, we encourage developers to make sure that anything they do to the codebase does not reduce this metric. This report can be used to inform what parts of the codebase need further testing.

Type Hints

Type hints are used in this codebase but presently not configured to be enforced. Developers are encouraged to use them and use mypy (which has been added to the list of developer dependencies to this project) to check for a host of errors that this tool can efficiently identify. This can be done by running mypy, passing it the path to the code you want to check as follows:

$ mypy  --explicit-package-bases <path>
This can be a specific file or a path underwhich all code is checked. To run mypy on the whole project codebase, simply run the following from the code's root directory:

$ mypy  --explicit-package-bases python

Git Hooks

This project has been set-up with pre-configured git hooks. They should be used as a means for developers to quickly check that (at least some) of the code standards of the project are being met by commited code. Ultimately, all standards are actually enforced by the continuous integration pipeline (see below). Running quick checks (like linting) at the point of commiting code can save time that might otherwise be lost later (for example) at the PR or release stage when testing needs to be rigorous and policy enforcement generally fails slower. Developers can choose to either:

  1. use the git hooks defined by this project (recommended, for the reasons given above; see below for instructions),
  2. not to use them, and rely purely on the CI workflow to enforce all project policies, or
  3. configure their IDE of choice to manage things, in which case it is up to them to make sure that this aligns with the policies being enforced by the CI.

If developers would like to utilise the git hooks provided by this project they just need to run the following command from within the project: 

$ pre-commit install

Some of these hooks require internet access to work. If you are trying to commit to the repository locally and are being prevented from doing so because you are working online, the hooks can be ignored by using the --no-verify flag when running git commit, like so: 

$ git commit --no-verify

Alternatively, you can disable them by running: 

$ pre-commit uninstall

They can subsequently be re-enabled by reinstalling them.

Maintaining Git Hooks

The git hooks are defined in the .pre-commit-config.yaml file. Specific revisions for many of the tools listed should be managed with Poetry, with syncing managed with the sync_with_poetry hook. Developers should take care not to use git hooks to enforce any project policies. That should all be done within the continuous integration workflows. Instead: these should just be quality-of-life checks that fix minor issues or prevent the propagation of quick-and-easy-to-detect problems which would otherwise be caught by the CI later with considerably more latency. Furthermore, ensure that the checks performed here are consistant between the hooks and the CI. For example: make sure that any linting/code quality checks are executed with the same tools and options.

Releases

Releases are generated through the GitHub UI. A GitHub Workflow has been configured to do the following when a new release is produced:

  1. Run the tests for the project,
  2. Ensure that the project builds,
  3. Rebuild the documentation on GitHub Pages, and
  4. Publish a new version of the code on PyPI.

Note

If a release is flagged as a "pre-release" through the GitHub interface, then documentation will not be built and the project will be published on test.PyPI.org instead.

Generating a new release

To generate a new release, do the following:

  1. Navigate to the project's GitHub page,
  2. Click on Releases in the sidebar,
  3. Click on Create a new release (if this is the first release you have generated) or Draft release if this is a subsequent release,
  4. Click on Choose a tag and select the most recent version listed,
  5. Write some text describing the nature of the release to prospective users, and
  6. Click Publish Release.

Documentation

Documentation for this project is generated using Material for MkDocs and is hosted on GitHub Pages for the latest release version. The documentation system is configured with the following features:

  1. Pure Markdown content with Material Design theme

    All documentation is written in standard Markdown format, making it easy for developers to contribute and maintain.

  2. Automatic API documentation generation

    API documentation is automatically generated from docstrings using mkdocstrings which extracts documentation directly from the Python codebase.

  3. Mathematical notation support

    LaTeX equations are supported using KaTeX for fast client-side rendering of mathematical expressions.

  4. Enhanced features

    • Responsive Material Design theme with dark/light mode support
    • Enhanced search functionality with suggestions
    • Syntax highlighting with copy-to-clipboard functionality
    • Tabbed content and admonitions for rich formatting

Generating the Documentation

Documentation can be generated locally by running the following from the root directory of the project:

$ make docs

This will generate an HTML version of the documentation in the site/ directory which can be opened in your browser. On a Mac (for example), this can be done by running the following:

$ open site/index.html

For development with live reload, use:

$ make serve

This will start a local development server at http://127.0.0.1:8000 with automatic reloading when files change.

Editing the Documentation

The majority of documentation changes can be managed in one of the following ways:

  1. Edits to existing Markdown files:

    Edit the Markdown files directly in the docs/ directory. The main content files include: - index.md - Landing page - getting_started.md - Installation and setup - contributing.md - Contributing guidelines - state_space.md - Technical documentation - notes_for_developers.md - Developer notes

  2. Project Docstrings:

    Documentation for API functions, classes, and methods should be managed directly in the docstrings of the project's .py files. This content will automatically be harvested by mkdocstrings and appear in the API reference section.

  3. Add new documentation:

    Create new .md files in the docs/ directory and add them to the navigation structure in mkdocs.yml. The navigation order determines how they appear in the final documentation.

  4. Examples and tutorials:

    Add example documentation to the docs/examples/ directory. Use the existing placeholder files as templates.

Adding images and assets

Place any images, plots, etc. used in the documentation in the docs/assets/ directory. Reference them in Markdown using relative paths like ![Description](assets/image.png).

Configuring Services

Develpers and project owners/maintainers will require accounts with one or all of the following services to work with this codebase. This section details how these services need to be configured. Following these steps should only be necessarry - or partially necessary - if a developer chooses to fork the project.

  1. GitHub

    To work with this codebase, you will require a GitHub account (go here to get one).

    Branch permissions for the main project repository should be configured only permit merges from pull requests. To do so, navigate to Settings->Branches->Add branch ruleset and:

    - give the Ruleset whatever name you'd like (e.g. `Protect Main`)
- set `Enforecement status` to `Active`
- add a `Target Branch` targeting criteria by pattern and type `main`
- select `Require a pull request before merging`
- select `Require status checks to pass` and add `Run all build and unit tests` from GitHub Actions as a required check

    This will ensure that all CI/CD tests pass before a merge to the main branch can be made.

    Several secrets need to be configured by navigating to Settings->Secrets->Actions and adding the following:

    • To make code releases available on the Python Package Index (see below), then the following secret needs to be set (see below for where to find this value):

      • PYPI_TOKEN,

    • To test code releases with the Test Python Package Index (see below), then the following secret needs to be set (see below for where to find this value):

      • TEST_PYPI_TOKEN,

  2. GitHub Pages

    GitHub Pages is used to host the project documentation. No additional account setup is required beyond your existing GitHub account. The documentation is automatically deployed via GitHub Actions when code is pushed to the main branch.

    To enable GitHub Pages for your repository:

    1. Go to your repository's Settings → Pages
    2. Under Source, select "Deploy from a branch"
    3. Select the gh-pages branch (created automatically by the deployment workflow)
    4. Select / (root) as the folder
    5. Click Save

    Once configured, documentation will be automatically updated and available at https://username.github.io/repository-name/ whenever changes are merged to the main branch.

  3. The Python Package Index (PyPI)

    This service is used to publish project releases. An account is needed if you are the owner of the project, but not generally needed if you are simply a contributing developer. An API token will need to be created and added to your GitHub project as PYPI_TOKEN (as detailed above). This can be generated from the PyPI UI by navigating to Account Settings->Add API Token.

    To test releases, a parallel account on test.PyPI is needed and a similar token to PYPI_TOKEN - named TEST_PYPI_TOKEN needs to be set, in the same way as above. To create a test release, flag it as a "pre-release" through the GitHub interface when you generate a release, and it will be published on test.PyPI.org rather than PyPI.org.

    Note

    Although poetry can be used to directly publish this project to PyPI, users should not do this. The proper way to publish the project is through the GitHub interface, which leverages the GitHub Workflows of this project to ensure the enforcement of project standards before a new version can be created.