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Developers Guide

How to run

Compiling TypeScript files

Node.js v16 is required to compile TypeScript files.

$ npm install
$ npm run build:dev
Watch for files changes 
$ npm run watch
Production builds 
$ npm run build:prd

Building a Docker image

$ docker build -t optuna-dashboard .

When failed above command due to the out of heap memory error (Exit code: 137), please check "Resources" tab on your Docker engine's preference since it requires a lot of memory to compile TypeScript files. You can use the Docker image like below:

# SQLite3
$ docker run -it --rm -p 8080:8080 -v `pwd`:/app -w /app optuna-dashboard sqlite:///db.sqlite3

Running dashboard server

$ pip install -e .
$ OPTUNA_DASHBOARD_DEBUG=1 optuna-dashboard sqlite:///db.sqlite3

Note that OPTUNA_DASHBOARD_DEBUG=1 makes the server will automatically restart when the source codes are changed.

Running tests, lint checks and formatters

Run all tests and lint checks

$ tox -e ALL

Running Python unit tests

$ python -m unittest

or

$ pip install tox
$ tox -e py39

Running visual regression tests using pyppeteer

Please run following commands, then check screenshots in tmp/ directory.

$ pip install -r requirements.txt
$ python visual_regression_test.py --output-dir tmp

Note: When you run pyppeteer for the first time, it downloads the latest version of Chromium (~150MB) if it is not found on your system.

Linters (flake8, black and mypy)

$ pip install -r requirements.txt
$ flake8
$ black --check .
$ isort . --check
$ mypy optuna_dashboard python_tests

or

$ pip install tox
$ tox -e flake8 -e black -e mypy

Auto-formatting TypeScript files (by prettier)

$ npm run fmt

Auto-formatting Python files

$ black .
$ isort .

Release the new version

The release process(compiling TypeScript files, packaging Python distributions and uploading to PyPI) is fully automated by GitHub Actions.

  1. Replace optuna_dashboard.version.__version__ to the next version.
  2. Create a git tag and push it to GitHub. If succeeded, GitHub Action will build sdist/wheel packages and create a draft GitHub release.
  3. Edit a GitHub release, generate release note, and mark "Create a discussion for this release" checkbox. Then make it publish. GitHub Action will release the new version to PyPI.