Whl-Dash

Lightweight browser-based data analysis dashboard for visualizing and comparing autonomous-driving .record data (built with Dash + Plotly).

Quick Start

• Install (development):

python3 -m venv .venv
source .venv/bin/activate
python3 -m pip install --upgrade pip
python3 -m pip install -e .

• Run (installed console script):

# After installing the package you can run the console script
whl-dash
# Or run in-place while developing
python3 -m whl_dash.main

Usage

• Open http://127.0.0.1:8050 in your browser after the server starts.
• Use the left panel to choose or scan a directory containing .record files (Data Source), configure templates on the right, and click Render Canvas.
• Note: the CLI --record_path option has been removed — choose workspaces/records via the UI.

Performance Optimizations

• The app automatically down-samples very long time series and map trajectories for interactive performance, and switches to WebGL-backed traces (Scattergl) for large traces.
• For more aggressive down-sampling, adjust max_points in whl_dash/dashboard.py or implement multi-resolution caching in RecordDataLoader.

Packaging & Publishing

• The project uses pyproject.toml (setuptools) for builds.
• A GitHub Actions workflow .github/workflows/python-publish.yml is included to build and publish distributions when a Release is created — ensure PYPI_API_TOKEN is configured in repository Secrets.

Troubleshooting

• If you see ModuleNotFoundError: No module named 'dashboard', reinstall the package in your virtualenv (python3 -m pip install --upgrade .) and run the installed whl-dash script; the package uses package-qualified imports (whl_dash.*) to avoid collisions.

Developer Notes

• Key modules: whl_dash/dashboard.py (UI & callbacks), whl_dash/data.py (RecordDataLoader), whl_dash/template.py (template management).
• When changing dependencies or CI, update pyproject.toml and .github/workflows/python-publish.yml accordingly.