This readme is part of the automatically generated README.md file (from the cookiecutter template)
- 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_uploader
).- 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_uploader/__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_uploader-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