Real-time dashboard for Optuna
Project description
optuna-dashboard
:link: Website | :page_with_curl: Docs | :gear: Install Guide | :pencil: Tutorial | :bulb: Examples
Real-time dashboard for Optuna. Code files were originally taken from Goptuna.
Installation
You can install optuna-dashboard via PyPI or Anaconda Cloud.
$ pip install optuna-dashboard
Getting Started
First, please specify the storage URL to persistent your study using the RDB backend.
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.
Please check out our documentation for more details.
Using an official Docker image
You can also use an official Docker image 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
Jupyter Lab Extension (Experimental)
You can install the Jupyter Lab extension via PyPI.
$ pip install jupyterlab jupyterlab-optuna
To use, click the tile to launch the extension, and enter your Optuna’s storage URL (e.g. sqlite:///db.sqlite3) in the dialog.
Browser-only version (Experimental)
We’ve developed the version that operates solely within your web browser, which internally uses SQLite3 Wasm and Rust. There’s no need to install Python or any other dependencies. Simply open the following URL in your browser, drag and drop your SQLite3 file onto the page, and you’re ready to view your Optuna studies!
https://optuna.github.io/optuna-dashboard/
Please note that only a subset of features is available. However, you can still check the optimization history, hyperparameter importances, and etc. in graphs and tables.
VS Code and code-server Extension (Experimental)
You can install the VS Code extension via Visual Studio Marketplace, or install the code-server extension via Open VSX.
Please right-click the SQLite3 files (*.db or *.sqlite3) in the VS Code file explorer and select the "Open in Optuna Dashboard" command from the dropdown menu.
This extension leverages the browser-only version of Optuna Dashboard, so the same limitations apply.
Submitting patches
If you want to contribute, please check Developers Guide.
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Hashes for optuna_dashboard-0.15.1-py3-none-any.whl
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 3e8f8b28d671f1781c2ff9bca7b65ea6f3c4d82fa8ac785f250a094735868483 |
|
| MD5 | 43b787d4558185f4d35dfa80fd892451 |
|
| BLAKE2b-256 | eb35e8677e82820402f84661eb37f7c1a407b6bbc02833cb22c3cfa2ce8cd58e |
