dash-extendable-graph
dash-extendable-graph is a Dash component library. This library contains a single component: ExtendableGraph
. The component is a fork of the Graph() component from dash-core-components (version 1.3.1). Best efforts will be made to keep in sync with the upstream repository.
The primary differentiation between ExtendableGraph and Graph components is the extendData
callback. This component has been modified to follow an api that matches the format of figure['data']
(as opposed to the api defined Graph.extendData
and Plotly.extendTraces()
).
Note: As of version 1.1.0, dash-extendable-graph
includes PlotlyJS as an internal dependency. Previously, the component assumed it would be used in conjunction with dash-core-components
. As of dash-core-components
version ^1.4.0, PlotlyJS
is only available asynchronously when a Graph component exists on the page.
Installation
Get started with:
- Install Dash and dependencies: https://dash.plot.ly/installation
$ pip install -r requirements.txt
- Install dash-extendable-graph
$ pip install dash-extendable-graph
- Run
python usage.py
- Visit http://localhost:8050 in your web browser
Usage
General examples may be found in usage.py
extendData properties
updateData
[list]: a list of dictionaries, each dictionary representing trace data in a format matchingfigure['data']
(e.gdict(x=[1], y=[1])
)traceIndices
[list, optional]: identify the traces that should be extended. If the specified trace index does not exist, a (new) corresponding trace shall be appended to the figure.maxPoints
[number, optional]: define the maximum number of points to plot in the figure (per trace).
Based on the Plotly.extendTraces()
api. However, the updateData
key has been modified to better match the contents of Plotly.plot()
(e.g. Graph.figure
). Aside from following dash-familiar styling, this component allows the user to extend traces of different types in a single call (Plotly.extendTraces()
takes a map of key:val and assumes all traces will share the same data keys).
Code
Extend a trace once per second, limited to 100 maximum points.
import dash_extendable_graph as degimport dashfrom dash.dependencies import Input, Output, Stateimport dash_html_components as htmlimport dash_core_components as dccimport random app = app.scripts.config.serve_locally = Trueapp.css.config.serve_locally = True app.layout = x_new = + 1 y_new = return , , 100 if __name__ == '__main__':
Contributing
See CONTRIBUTING.md
Local Installation
- Dependencies
$ npm install$ virtualenv venv$ . venv/bin/activate$ pip install -r requirements.txt
For developers:
$ pip install -r tests/requirements.txt
- Build
$ npm run build
- Check out the component via component-playground
$ npm run start
The demo app is in `src/demo`
- Check out the sample Dash application using the component
$ python setup.py install$ python usage.py
Tests
Run locally
Run linting + integration tests in one command:
$ npm run test
Or run tests individually:
Code style
Uses flake8
, eslint
, and prettier
. Check package.json
, .eslintrc
, .eslintignore
for configuration settings.
$ npm run lint
Also you can apply formatting settings.
$ npm run format
Integration
Integration tests for the component can be found in tests/
$ pytest
Selenium test runner configuration options are located in pytest.ini
(e.g. --webdriver
, --headless
). See dash[testing]
documentation for more information on built-ins provided by the dash test fixture.
Run individual integration tests based on the filename.
$ pytest tests/test_extend_maxpoints.py
Continuous Integration via Github Actions
This repository uses github actions to automate testing. CI is triggered for each pull request into the master
branch
Publishing
Create a production build and publish:
$ rm -rf dist$ npm run build$ python setup.py sdist bdist_wheel$ twine upload dist/*$ npm publish
Test your tarball by copying it into a new environment and installing it locally:
$ pip install dash_extendable_graph-X.X.X.tar.gz