Dash renderjson is a Dash component library, it makes use of react-json-tree from redux-devtools and allows you to render a simple dictionary object (currently basic types supported)
Get started with:
- Install Dash and its dependencies: https://dash.plotly.com/installation
- Run
pip install dash-renderjson
Note: This demo useage makes use of
dash_daq
for the ToggleSwitch
import dash_renderjson
import dash
import dash_daq as daq
from dash.dependencies import Input, Output
import dash_html_components as html
app = dash.Dash(__name__)
app.layout = html.Div([daq.ToggleSwitch(id="my-toggle-switch", value=False), html.Div(id="output")])
@app.callback(Output("output", "children"), [Input("my-toggle-switch", "value")])
def display_output(value):
if value:
data = {"a": 1, "b": [1, 2, 3, {"c": 4}]}
theme = {
"scheme": "monokai",
"author": "wimer hazenberg (http://www.monokai.nl)",
"base00": "#272822",
"base01": "#383830",
"base02": "#49483e",
"base03": "#75715e",
"base04": "#a59f85",
"base05": "#f8f8f2",
"base06": "#f5f4f1",
"base07": "#f9f8f5",
"base08": "#f92672",
"base09": "#fd971f",
"base0A": "#f4bf75",
"base0B": "#a6e22e",
"base0C": "#a1efe4",
"base0D": "#66d9ef",
"base0E": "#ae81ff",
"base0F": "#cc6633",
}
return dash_renderjson.DashRenderjson(id="input", data=data, max_depth=-1, theme=theme, invert_theme=True)
if __name__ == "__main__":
app.run_server(debug=True)
id
- Required, the id of the JSONRenderer element to createdata
- Required, the dictionary you want to displaymax_depth
- (-1) shows full JSON, 0 hides all but root, 1 shows one max depth, etctheme
- A theme dictionary, example given aboveinvert_theme
- Whether to invert the colors of the supplied/default theme
See CONTRIBUTING.md
If you have selected install_dependencies during the prompt, you can skip this part.
-
Install npm packages
$ npm install
-
Create a virtual env and activate.
$ virtualenv venv $ . venv/bin/activate
Note: venv\Scripts\activate for windows
-
Install python packages required to build components.
$ pip install -r requirements.txt
-
Install the python packages for testing (optional)
$ pip install -r tests/requirements.txt
- 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:
- Build your code
$ npm run build
- Run and modify the
usage.py
sample dash app:$ python usage.py
- Build your code
- Write tests for your component.
- A sample test is available in
tests/test_usage.py
, it will loadusage.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)
- A sample test is available in
- Add custom styles to your component by putting your custom CSS files into your distribution folder (
dash_renderjson
).- 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 indash_renderjson/__init__.py
so dash will serve them automatically when the component suite is requested.
- Make sure that they are referenced in
- Review your code
-
Build your code:
$ npm run build
-
Create a Python tarball
$ python setup.py sdist
This distribution tarball will get generated in the
dist/
folder -
Test your tarball by copying it into a new environment and installing it locally:
$ pip install dash_renderjson-0.0.1.tar.gz
-
If it works, then you can publish the component to NPM and PyPI:
- Publish on PyPI
$ twine upload dist/*
- Cleanup the dist folder (optional)
$ rm -rf dist
- Publish on NPM (Optional if chosen False in
publish_on_npm
)Publishing your component to NPM will make the JavaScript bundles available on the unpkg CDN. By default, Dash serves the component library's CSS and JS locally, but if you choose to publish the package to NPM you can set$ npm publish
serve_locally
toFalse
and you may see faster load times.
- Publish on PyPI
-
Share your component with the community! https://community.plotly.com/c/dash
- Publish this repository to GitHub
- Tag your GitHub repository with the plotly-dash tag so that it appears here: https://github.com/topics/plotly-dash
- Create a post in the Dash community forum: https://community.plotly.com/c/dash