---
id: optuna-dashboard
version: "0.20.0"
license: MIT License
license_treatment: permissive
maintenance: active
---

# optuna-dashboard — Real-time dashboard for Optuna

License: permissive · Maintenance: active · Downloads: 231.6K/mo

## What it is and what it does

optuna-dashboard is a web-based visualization tool for Optuna hyperparameter optimization studies. It connects to an existing Optuna study stored in a database backend (SQLite, MySQL, or PostgreSQL) and presents the optimization history, trial results, and parameter importances through an interactive browser interface. The package runs as a lightweight web server that listens on localhost:8080 by default.

The dashboard is designed as a companion to Optuna itself—you run your optimization study separately using Optuna's API with a persistent RDB backend, then launch the dashboard to inspect results. It depends on bottle for the web framework, optuna for study access, and tomli for configuration parsing. The package is in Alpha status but actively maintained, with support for Python 3.8 through 3.13.

Use it for:

- Monitor hyperparameter optimization progress in real-time while an Optuna study is running on a remote machine
- Inspect trial history, best parameters, and convergence plots after completing a hyperparameter search
- Share optimization results with team members via a web interface without requiring Python or Optuna knowledge
- Analyze parameter importance and trial distributions to understand which hyperparameters most affect model performance
- Embed optimization dashboards in Jupyter notebooks or VS Code for integrated development workflows

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Provides a real-time web dashboard for visualizing and monitoring Optuna hyperparameter optimization studies stored in a database backend.

Yes, if you use Optuna for hyperparameter tuning and want a user-friendly way to inspect results. Installation is straightforward, maintenance is active, and there are no known security issues. The Alpha status reflects ongoing development but not instability—the package is widely used and suitable for production study visualization.

## Install

pip install optuna-dashboard
uv add optuna-dashboard
poetry add optuna-dashboard

## Installing optuna-dashboard

Before you install: Low friction installation with a pure Python wheel. Actively maintained with recent commits and no known vulnerabilities. Supports current Python versions from 3.8 onwards.

License in practice: MIT License permits unrestricted use, modification, and distribution with minimal restrictions, making it suitable for both open-source and commercial projects.

Quickstart:

pip install optuna-dashboard

# After running an Optuna study with RDB storage:
optuna-dashboard sqlite:///db.sqlite3
# Then open http://localhost:8080/ in your browser

Requires an existing Optuna study persisted to a database backend (SQLite, MySQL, or PostgreSQL); the dashboard is a viewer, not a study runner.

Verify before relying:

- Whether the dashboard supports real-time updates as new trials complete, or requires manual refresh
- Performance characteristics when visualizing studies with thousands of trials
- Whether custom metrics or user-defined visualizations can be added beyond the built-in graphs

## Package facts

- License: MIT License (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 231.6K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

optuna dashboard visualization, hyperparameter optimization monitoring, optuna study viewer, real-time optimization dashboard, optuna web interface, hyperparameter tuning dashboard, optuna results explorer, hyperparameter-optimization, visualization, web-dashboard

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