# optuna-dashboard ![Software License](https://img.shields.io/badge/license-MIT-brightgreen.svg?style=flat-square) [![PyPI - Downloads](https://img.shields.io/pypi/dm/optuna-dashboard)](https://pypistats.org/packages/optuna-dashboard) Real-time dashboard for [Optuna](https://github.com/optuna/optuna). Code files were originally taken from [Goptuna](https://github.com/c-bata/goptuna). ## Installation You can install optuna-dashboard via [PyPI](https://pypi.org/project/optuna-dashboard/) or [Anaconda Cloud](https://anaconda.org/conda-forge/optuna-dashboard). ``` $ pip install optuna-dashboard ``` Also you can install following optional dependencies to make optuna-dashboard faster. ```console $ pip install optuna-fast-fanova gunicorn ``` ## Getting Started First, please specify the storage URL to persistent your study using the [RDB backend](https://optuna.readthedocs.io/en/stable/tutorial/20_recipes/001_rdb.html). ```python import optuna def objective(trial): x = trial.suggest_float("x", -100, 100) y = trial.suggest_categorical("y", [-1, 0, 1]) return x**2 + y if __name__ == "__main__": study = optuna.create_study( storage="sqlite:///db.sqlite3", # Specify the storage URL here. study_name="quadratic-simple" ) study.optimize(objective, n_trials=100) print(f"Best value: {study.best_value} (params: {study.best_params})") ``` After running the above script, please execute the `optuna-dashboard` command with Optuna storage URL. ``` $ optuna-dashboard sqlite:///db.sqlite3 Listening on http://localhost:8080/ Hit Ctrl-C to quit. ```
More command line options ```console $ optuna-dashboard -h usage: optuna-dashboard [-h] [--port PORT] [--host HOST] [--version] [--quiet] storage Real-time dashboard for Optuna. positional arguments: storage DB URL (e.g. sqlite:///example.db) optional arguments: -h, --help show this help message and exit --port PORT port number (default: 8080) --host HOST hostname (default: 127.0.0.1) --server {wsgiref,gunicorn} server (default: auto) --version, -v show program's version number and exit --quiet, -q quiet ```
Python Interface **`run_server(storage: Union[str, BaseStorage], host: str = 'localhost', port: int = 8080) -> None`** Start running optuna-dashboard and blocks until the server terminates. This function uses wsgiref module which is not intended for the production use. **`wsgi(storage: Union[str, BaseStorage]) -> WSGIApplication`** This function exposes WSGI interface for people who want to run on the production-class WSGI servers like Gunicorn or uWSGI.
## Using an official Docker image You can also use [an official Docker image](https://github.com/optuna/optuna-dashboard/pkgs/container/optuna-dashboard) instead of setting up your Python environment. The Docker image only supports SQLite3, MySQL(PyMySQL), and PostgreSQL(Psycopg2). ``` $ docker run -it --rm -p 8080:8080 -v `pwd`:/app -w /app \ > ghcr.io/optuna/optuna-dashboard sqlite:///db.sqlite3 ```
MySQL (PyMySQL) ``` $ docker run -it --rm -p 8080:8080 ghcr.io/optuna/optuna-dashboard mysql+pymysql://username:password@hostname:3306/dbname ```
PostgreSQL (Psycopg2) ``` $ docker run -it --rm -p 8080:8080 ghcr.io/optuna/optuna-dashboard postgresql+psycopg2://username:password@hostname:5432/dbname ```
## Features ### Manage Studies You can create and delete studies from Dashboard. ![optuna-dashboard-create-delete-study](https://user-images.githubusercontent.com/5564044/205545958-305f2354-c7cd-4687-be2f-9e46e7401838.gif) ### Visualize with Interactive Graphs & Rich Trials Data Grid You can check the optimization history, hyperparameter importances, etc. in graphs and tables. ![optuna-dashboard-realtime-graph](https://user-images.githubusercontent.com/5564044/205545965-278cd7f4-da7d-4e2e-ac31-6d81b106cada.gif) ## Submitting patches If you want to contribute, please check [Developers Guide](./CONTRIBUTING.md).