arva_polar_clock

arva_polar_clock is a Dash component library.

Get started with:
1. Install Dash and its dependencies: https://dash.plotly.com/installation
2. Run python usage.py
3. Visit http://localhost:8050 in your web browser

Contributing

See CONTRIBUTING.md

$3

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`

`$3`

- The demo app is in src/demoand 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`2. Run and modify theusage.pysample dash app:`$ python usage.py`- Write tests for your component. - A sample test is available intests/test_usage.py, it will load usage.pyand 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 (arva_polar_clock). - Make sure that they are referenced inMANIFEST.inso 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 arva_polar_clock/__init__.pyso dash will serve them automatically when the component suite is requested. - Review your code

`$3`

1. Build your code:`$ npm run build`2. Create a Python tarball`$ python setup.py sdist`This distribution tarball will get generated in thedist/ folder

3. Test your tarball by copying it into a new environment and installing it locally:`$ pip install arva_polar_clock-0.0.1.tar.gz`

4. If it works, then you can publish the component to NPM and PyPI: 1. Publish on PyPI`$ twine upload dist/*`2. Cleanup the dist folder (optional)`$ rm -rf dist`3. Publish on NPM (Optional if chosen False inpublish_on_npm)`$ npm publish`_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 setserve_locally to False` and you may see faster load times._

5. Share your component with the community! https://community.plotly.com/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.plotly.com/c/dash

Contributing

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

$3

- 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


    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 (

arva_polar_clock

).
    - 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 arva_polar_clock/__init__.py

 so dash will serve them automatically when the component suite is requested.
- Review your code

$3

1. Build your code:


    $ npm run build


2. Create a Python tarball


    $ python setup.py sdist


    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 arva_polar_clock-0.0.1.tar.gz

4. If it works, then you can publish the component to NPM and PyPI:
    1. Publish on PyPI


        $ twine upload dist/*


    2. Cleanup the dist folder (optional)


        $ rm -rf 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 serves the component library's CSS and JS locally, but if you choose to publish the package to NPM you can set

serve_locally to False` and you may see faster load times._