
   The document assumes you are using a source repository service that promotes a
   contribution model similar to [GitHub's fork and pull request workflow].
   While this is true for the majority of services (like GitHub, GitLab,
   BitBucket), it might not be the case for private repositories (e.g., when
   using Gerrit).

   Also notice that the code examples might refer to GitHub URLs or the text
   might use GitHub specific terminology (e.g., *Pull Request* instead of *Merge
   Request*).

   Please make sure to check the document having these assumptions in mind
   and update things accordingly.


   especially if your project is open source. The text should be very similar to
   this template, but there are a few extra contents that you might decide to
   also include, like mentioning labels of your issue tracker or automated
   releases.

Contributing

Welcome to honegumi contributor's guide.

This document focuses on getting any potential contributor familiarized with the development processes, but other kinds of contributions are also appreciated.

If you are new to using git or have never collaborated in a project previously, please have a look at contribution-guide.org. Other resources are also listed in the excellent guide created by FreeCodeCamp ¹.

Please notice, all users and contributors are expected to be open, considerate, reasonable, and respectful. When in doubt, Python Software Foundation's Code of Conduct is a good reference in terms of behavior guidelines.

Issue Reports

If you experience bugs or general issues with honegumi, please have a look on the issue tracker. If you don't see anything useful there, please feel free to fire an issue report.

:::{tip} Please don't forget to include the closed issues in your search. Sometimes a solution was already reported, and the problem is considered solved. :::

New issue reports should include information about your programming environment (e.g., operating system, Python version) and steps to reproduce the problem. Please try also to simplify the reproduction steps to a very minimal example that still illustrates the problem you are facing. By removing other factors, you help us to identify the root cause of the issue.

Documentation Improvements

You can help improve honegumi docs by making them more readable and coherent, or by adding missing information and correcting mistakes.

honegumi documentation uses Sphinx as its main documentation compiler. This means that the docs are kept in the same repository as the project code, and that any documentation update is done in the same way was a code contribution.


    e.g.,  [reStructuredText] or [CommonMark] with [MyST] extensions.

:::{tip} Please notice that the GitHub web interface provides a quick way of propose changes in honegumi's files. While this mechanism can be tricky for normal code contributions, it works perfectly fine for contributing to the docs, and can be quite handy.

  If you are interested in trying this method out, please navigate to
  the `docs` folder in the source [repository], find which file you
  would like to propose changes and click in the little pencil icon at the
  top, to open [GitHub's code editor]. Once you finish editing the file,
  please write a message in the form at the bottom of the page describing
  which changes have you made and what are the motivations behind them and
  submit your proposal.

:::

When working on documentation changes in your local machine, you can compile them using tox :

tox -e docs

and use Python's built-in web server for a preview in your web browser (http://localhost:8000):

python3 -m http.server --directory 'docs/_build/html'

Code Contributions

For a high-level roadmap of Honegumi's development, see #2. Honegumi uses Python, Javascript, Jinja2, pytest, and GitHub actions to automate the generation, testing, and deployment of templates with a focus on Bayesian optimization packages. As of 2023-08-21, only a single package (Meta's Ax Platform for a small set of features. However, the plumbing and logic that creates this is thorough and scalable. I focused first on getting all the pieces together before scaling up to many features (and thus slowing down the development cycle).

Here are some ways you can help with the project:

Use the tool and let us know what you think 😉
Provide feedback on the overall organization, logic, and workflow of the project
Extend the Ax features to additional options (i.e., additional rows and options within rows) via direct edits to ax/main.py.jinja
Improve the honegumi.html and honegumi.ipynb templates (may also need to update generate_scripts.py). See below for more information.
Extend Honegumi to additional platforms such as BoFire or Atlas
Spread the word about the tool

For those unfamiliar with Jinja2, see the Google Colab tutorial: A Gentle Introduction to Jinja2. The main template file for Meta's Adaptive Experimentation (Ax) Platform is ax/main.py.jinja. The main file that interacts with this template is at scripts/generate_scripts.py. The generated scripts are available on GitHub. Each script is tested via pytest and GitHub Actions to ensure it can run error-free. Finally, the results are passed to core/honegumi.html.jinja and core/honegumi.ipynb.jinja to create the scripts and notebooks, respectively.

NOTE: If you are committing some of the generated scripts or notebooks on Windows, you will likely need to run this command in a terminal (e.g., git bash) as an administrator to avoid an lstat(...) Filename too long error:

git config --system core.longpaths true

If working in GitHub Desktop, you will likely need to follow these instructions.

In its current form (as of 2024-06-04), Honegumi generates many files. This can become unwieldy when working with git, and you may find the command line interface of git to be less frustrating. For example, you can use the following to check for changes in the non-generated files.

git status -- :!docs/generated_scripts :!docs/generated_notebooks :!tests/generated_scripts

To only commit non-generated files, you can add all files and reset the generated ones.

git add .
git reset docs/generated_scripts docs/generated_notebooks tests/generated_scripts

Project Organization

├── AUTHORS.md              <- List of developers and maintainers.
├── CHANGELOG.md            <- Changelog to keep track of new features and fixes.
├── CONTRIBUTING.md         <- Guidelines for contributing to this project.
├── Dockerfile              <- Build a docker container with `docker build .`.
├── LICENSE.txt             <- License as chosen on the command-line.
├── README.md               <- The top-level README for developers.
├── configs                 <- Directory for configurations of model & application.
├── data
│   ├── external            <- Data from third party sources.
│   ├── interim             <- Intermediate data that has been transformed.
│   ├── processed           <- The final, canonical data sets for modeling.
│   └── raw                 <- The original, immutable data dump.
├── docs                    <- Directory for Sphinx documentation in rst or md.
├── environment.yml         <- The conda environment file for reproducibility.
├── models                  <- Trained and serialized models, model predictions,
│                              or model summaries.
├── notebooks               <- Jupyter notebooks. Naming convention is a number (for
│                              ordering), the creator's initials and a description,
│                              e.g. `1.0-fw-initial-data-exploration`.
├── pyproject.toml          <- Build configuration. Don't change! Use `pip install -e .`
│                              to install for development or to build `tox -e build`.
├── references              <- Data dictionaries, manuals, and all other materials.
├── reports                 <- Generated analysis as HTML, PDF, LaTeX, etc.
│   └── figures             <- Generated plots and figures for reports.
├── scripts                 <- Analysis and production scripts which import the
│                              actual PYTHON_PKG, e.g. train_model.
├── setup.cfg               <- Declarative configuration of your project.
├── setup.py                <- [DEPRECATED] Use `python setup.py develop` to install for
│                              development or `python setup.py bdist_wheel` to build.
├── src
│   └── core              <- Actual Python package where the main functionality goes.
├── tests                   <- Unit tests which can be run with `pytest`.
├── .coveragerc             <- Configuration for coverage reports of unit tests.
├── .isort.cfg              <- Configuration for git hook that sorts imports.
└── .pre-commit-config.yaml <- Configuration of pre-commit git hooks.

Submit an issue

Before you work on any non-trivial code contribution it's best to first create a report in the issue tracker to start a discussion on the subject. This often provides additional considerations and avoids unnecessary work.

Create an environment

Before you start coding, we recommend creating an isolated virtual environment to avoid any problems with your installed Python packages. This can easily be done via either virtualenv:

virtualenv <PATH TO VENV>
source <PATH TO VENV>/bin/activate

or Miniconda:

conda create -n honegumi python=3 six virtualenv pytest pytest-cov
conda activate honegumi

Clone the repository

Create an user account on GitHub if you do not already have one.
Fork the project repository: click on the Fork button near the top of the page. This creates a copy of the code under your account on GitHub.

Clone this copy to your local disk:

git clone git@github.com:YourLogin/honegumi.git
cd honegumi

You should run:
```
pip install -U pip setuptools -e .
```
to be able to import the package under development in the Python REPL.
Install pre-commit:
```
pip install pre-commit
pre-commit install
```
honegumi comes with a lot of hooks configured to automatically help the developer to check the code being written.

Implement your changes

Create a branch to hold your changes:
```
git checkout -b my-feature
```
and start making changes. Never work on the main branch!
Start your work on this branch. Don't forget to add docstrings to new functions, modules and classes, especially if they are part of public APIs.
Add yourself to the list of contributors in AUTHORS.rst.
When you’re done editing, do:
```
git add <MODIFIED FILES>
git commit
```
to record your changes in git.
Please make sure to see the validation messages from pre-commit and fix any eventual issues. This should automatically use flake8/black to check/fix the code style in a way that is compatible with the project.

:::{important} Don't forget to add unit tests and documentation in case your contribution adds an additional feature and is not just a bugfix.

Moreover, writing a descriptive commit message is highly recommended. In case of doubt, you can check the commit history with:
```
git log --graph --decorate --pretty=oneline --abbrev-commit --all
```
to look for recurring communication patterns. :::
Please check that your changes don't break any unit tests with:
```
tox
```
(after having installed tox with pip install tox or pipx).

You can also use tox to run several other pre-configured tasks in the repository. Try tox -av to see a list of the available checks.

Submit your contribution

If everything works fine, push your local branch to the remote server with:
```
git push -u origin my-feature
```

Go to the web page of your fork and click "Create pull request" to send your changes for review.


   Find more detailed information in [creating a PR]. You might also want to open
   the PR as a draft first and mark it as ready for review after the feedbacks
   from the continuous integration (CI) system or any required fixes.

Troubleshooting

The following tips can be used when facing problems to build or test the package:

Make sure to fetch all the tags from the upstream repository. The command git describe --abbrev=0 --tags should return the version you are expecting. If you are trying to run CI scripts in a fork repository, make sure to push all the tags. You can also try to remove all the egg files or the complete egg folder, i.e., .eggs, as well as the *.egg-info folders in the src folder or potentially in the root of your project.
Sometimes tox misses out when new dependencies are added, especially to setup.cfg and docs/requirements.txt. If you find any problems with missing dependencies when running a command with tox, try to recreate the tox environment using the -r flag. For example, instead of:
```
tox -e docs
```
Try running:
```
tox -r -e docs
```
Make sure to have a reliable tox installation that uses the correct Python version (e.g., 3.7+). When in doubt you can run:
```
tox --version
# OR
which tox
```
If you have trouble and are seeing weird errors upon running tox, you can also try to create a dedicated virtual environment with a tox binary freshly installed. For example:
```
virtualenv .venv
source .venv/bin/activate
.venv/bin/pip install tox
.venv/bin/tox -e all
```
Pytest can drop you in an interactive session in the case an error occurs. In order to do that you need to pass a --pdb option (for example by running tox -- -k <NAME OF THE FALLING TEST> --pdb). You can also setup breakpoints manually instead of using the --pdb option.

Maintainer tasks

Releases


   If instead you are using a different/private package index, please update
   the instructions accordingly.

If you are part of the group of maintainers and have correct user permissions on PyPI, the following steps can be used to release a new version for honegumi:

Make sure all unit tests are successful.
Tag the current commit on the main branch with a release tag, e.g., v1.2.3.
Push the new tag to the upstream repository, e.g., git push upstream v1.2.3
Clean up the dist and build folders with tox -e clean (or rm -rf dist build) to avoid confusion with old builds and Sphinx docs.
Run tox -e build and check that the files in dist have the correct version (no .dirty or git hash) according to the git tag. Also check the sizes of the distributions, if they are too big (e.g., > 500KB), unwanted clutter may have been accidentally included.
Run tox -e publish -- --repository pypi and check that everything was uploaded to PyPI correctly.

Dependency Management & Reproducibility

Always keep your abstract (unpinned) dependencies updated in environment.yml and eventually in setup.cfg if you want to ship and install your package via pip later on.
Create concrete dependencies as environment.lock.yml for the exact reproduction of your environment with:
```
conda env export -n honegumi -f environment.lock.yml
```
For multi-OS development, consider using --no-builds during the export.
Update your current environment with respect to a new environment.lock.yml using:
```
conda env update -f environment.lock.yml --prune
```

Footnotes

Even though, these resources focus on open source projects and communities, the general ideas behind collaborating with other developers to collectively create software are general and can be applied to all sorts of environments, including private companies and proprietary code bases. ↩

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CONTRIBUTING.md

CONTRIBUTING.md

Contributing

Issue Reports

Documentation Improvements

Code Contributions

Project Organization

Submit an issue

Create an environment

Clone the repository

Implement your changes

Submit your contribution

Troubleshooting

Maintainer tasks

Releases

Dependency Management & Reproducibility

Files

CONTRIBUTING.md

Latest commit

History

CONTRIBUTING.md

File metadata and controls

Contributing

Issue Reports

Documentation Improvements

Code Contributions

Project Organization

Submit an issue

Create an environment

Clone the repository

Implement your changes

Submit your contribution

Troubleshooting

Maintainer tasks

Releases

Dependency Management & Reproducibility

Footnotes