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Material Dashboard with Bokeh embedded in Flask

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Features

The package provides a starter pack with an interactive Bokeh plot embedded in a Material Design Dashboard, which can send parameters from a flask form to Bokeh.

Material Dashboard with Bokeh embedded in Flask

Note

Please keep in mind that this is only a lightweight example of how Flask can affect the rendering of the bokeh plot. The change in scale is out of scope.

Quickstart

Before you install Python packages, you must meet a few requirements.

  1. Make sure you use the desired Python version:

    $ python3 -V
    Python 3.13.2

    Only Python >=3.9 is supported.

  2. Install uv:

    • … on macOS and Linux:

      $ curl -LsSf https://astral.sh/uv/install.sh | sh
    • … on Windows

      > powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
  3. Download:

    $ curl -O https://github.com/veit/flask-bokeh-dashboard/archive/master.zip
    $ unzip master.zip
  4. Create virtual environment:

    $ cd flask-bokeh-dashboard
    $ uv sync
  5. Run the dashboard with the gunicorn command:

    $ uv run gunicorn -w 1 main:app
    [2021-09-08 10:10:16 +0200] [55490] [INFO] Starting gunicorn 20.1.0
    [2021-09-08 10:10:16 +0200] [55490] [INFO] Listening at: http://127.0.0.1:8000 (55490)
    [2021-09-08 10:10:16 +0200] [55490] [INFO] Using worker: sync
    [2021-09-08 10:10:16 +0200] [55498] [INFO] Booting worker with pid: 55498

    Note

    The w option can be used to specify the number of workers.

  6. Visit http://127.0.0.1:8000 and it should look like the screenshot above.

  7. You can shut down the service in the console with ctrl-c.

Pull requests

If you have differences in your preferred setup, I encourage you to fork this to create your own version. I also accept pull requests on this, if they are small, atomic, and if they make my own packaging experience better.

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Walking skeleton for Bokeh plots in a Material Design dashboard interacting with Flask.

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