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plotly-dash custom component. Adds Plotly.extendTraces() support to dash_core_components.Graph()

Project description

dash-extendable-graph

PyPI PyPI - Python Version PyPI - License

dash-extendable-graph is a Dash component library. This library contains a single component: ExtendableGraph. The component is a fork of the Graph() component of dash-core-components, with an extra property (extendData) that allows Graph traces to be drawn through Plotly.extendTraces() instead of Plotly.react().

Installation

$ pip install dash-extendable-graph

Usage

import dash_extendable_graph as deg
import dash
from dash.dependencies import Input, Output, State
import dash_html_components as html
import dash_core_components as dcc
import random

app = dash.Dash(__name__)

app.scripts.config.serve_locally = True
app.css.config.serve_locally = True

app.layout = html.Div([
    deg.ExtendableGraph(
        id='extendablegraph_example',
        config={'showAxisDragHandles': True,
                'showAxisRangeEntryBoxes': True,
                'modeBarButtonsToRemove': [
                    'sendDataToCloud',
                    'lasso2d',
                    'autoScale2d',
                    'hoverClosestCartesian',
                    'hoverCompareCartesian',
                    'toggleSpikelines'],
                'displaylogo': False,
                },
        figure=dict(
            data=[{'x': [0],
                   'y': [0],
                   'mode':'lines+markers'
                   }],
        )
    ),
    dcc.Interval(
        id='interval_extendablegraph_update',
        interval=1000,
        n_intervals=0,
        max_intervals=-1),
    html.Div(id='output')
])


@app.callback(Output('extendablegraph_example', 'extendData'),
              [Input('interval_extendablegraph_update', 'n_intervals')],
              [State('extendablegraph_example', 'figure'),
               State('extendablegraph_example', 'extendData')])
def update_extendData(n_intervals, existing, info):
    x_new = existing['data'][0]['x'][-1] + 1
    y_new = random.random()
    return [dict(x=[x_new], y=[y_new])]


if __name__ == '__main__':
    app.run_server(debug=True)

dash-component-boilerplate

Get started with:

  1. Install Dash and its dependencies: https://dash.plot.ly/installation
  2. Install dash-extendable-graph
  3. Run python usage.py
  4. Visit http://localhost:8050 in your web browser

Contributing

See CONTRIBUTING.md

Install dependencies

If you have selected install_dependencies during the prompt, you can skip this part.

  1. Install npm packages

    $ npm install
    
  2. Create a virtual env and activate.

    $ virtualenv venv
    $ . venv/bin/activate
    

    Note: venv\Scripts\activate for windows

  3. Install python packages required to build components.

    $ pip install -r requirements.txt
    
  4. Install the python packages for testing (optional)

    $ pip install -r tests/requirements.txt
    

Write your component code in src/lib/components/ExtendableGraph.react.js.

  • The demo app is in src/demo and you will import your example component code into your demo app.
  • Test your code in a Python environment:
    1. Build your code
      $ npm run build:all
      
    2. Run and modify the usage.py sample dash app:
      $ python usage.py
      
  • Write tests for your component.
    • A sample test is available in tests/test_usage.py, it will load usage.py and you can then automate interactions with selenium.
    • Run the tests with $ pytest tests.
    • The Dash team uses these types of integration tests extensively. Browse the Dash component code on GitHub for more examples of testing (e.g. https://github.com/plotly/dash-core-components)
  • Add custom styles to your component by putting your custom CSS files into your distribution folder (dash_extendable_graph).
    • Make sure that they are referenced in MANIFEST.in so that they get properly included when you're ready to publish your component.
    • Make sure the stylesheets are added to the _css_dist dict in dash_extendable_graph/__init__.py so dash will serve them automatically when the component suite is requested.
  • Review your code

Create a production build and publish:

  1. Build your code:

    $ npm run build:all
    
  2. Create a Python tarball

    $ python setup.py sdist bdist_wheel
    

    This distribution tarball will get generated in the dist/ folder

  3. Test your tarball by copying it into a new environment and installing it locally:

    $ pip install dash_extendable_graph-0.0.1.tar.gz
    
  4. If it works, then you can publish the component to NPM and PyPI:

    1. Cleanup the dist folder (optional)
      $ rm -rf dist
      
    2. Publish on PyPI
      $ twine upload dist/*
      
    3. Publish on NPM (Optional if chosen False in publish_on_npm)
      $ npm publish
      
      Publishing your component to NPM will make the JavaScript bundles available on the unpkg CDN. By default, Dash servers the component library's CSS and JS from the remote unpkg CDN, so if you haven't published the component package to NPM you'll need to set the serve_locally flags to True (unless you choose False on publish_on_npm). We will eventually make serve_locally=True the default, follow our progress in this issue.
  5. Share your component with the community! https://community.plot.ly/c/dash

    1. Publish this repository to GitHub
    2. Tag your GitHub repository with the plotly-dash tag so that it appears here: https://github.com/topics/plotly-dash
    3. Create a post in the Dash community forum: https://community.plot.ly/c/dash

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