dash_extendable_graph
v1.2.0
Published
A Dash Graph component modified to support use of figure.data-structured input to extend and/or add traces.
Readme
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 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',
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')])
def update_extendData(n_intervals, existing):
x_new = existing['data'][0]['x'][-1] + 1
y_new = random.random()
return [dict(x=[x_new], y=[y_new])], [0], 100
if __name__ == '__main__':
app.run_server(debug=True)
Contributing
See CONTRIBUTING.md
Local Installation
- Dependencies
$ npm install
$ virtualenv venv
$ . venv/bin/activate
$ pip install -r requirements.txtFor developers:
$ pip install -r tests/requirements.txt- Build
$ npm run build- Check out the component via component-playground
$ npm run startThe demo app is in `src/demo`- Check out the sample Dash application using the component
$ python setup.py install
$ python usage.pyTests
Run locally
Run linting + integration tests in one command:
$ npm run testOr run tests individually:
Code style
Uses flake8, eslint, and prettier. Check package.json, .eslintrc, .eslintignore for configuration settings.
$ npm run lintAlso you can apply formatting settings.
$ npm run formatIntegration
Integration tests for the component can be found in tests/
$ pytestSelenium 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.pyContinuous 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 publishTest your tarball by copying it into a new environment and installing it locally:
$ pip install dash_extendable_graph-X.X.X.tar.gz