npm package discovery and stats viewer.

Discover Tips

  • General search

    [free text search, go nuts!]

  • Package details

    pkg:[package-name]

  • User packages

    @[username]

Sponsor

Optimize Toolset

I’ve always been into building performant and accessible sites, but lately I’ve been taking it extremely seriously. So much so that I’ve been building a tool to help me optimize and monitor the sites that I build to make sure that I’m making an attempt to offer the best experience to those who visit them. If you’re into performant, accessible and SEO friendly sites, you might like it too! You can check it out at Optimize Toolset.

About

Hi, 👋, I’m Ryan Hefner  and I built this site for me, and you! The goal of this site was to provide an easy way for me to check the stats on my npm packages, both for prioritizing issues and updates, and to give me a little kick in the pants to keep up on stuff.

As I was building it, I realized that I was actually using the tool to build the tool, and figured I might as well put this out there and hopefully others will find it to be a fast and useful way to search and browse npm packages as I have.

If you’re interested in other things I’m working on, follow me on Twitter or check out the open source projects I’ve been publishing on GitHub.

I am also working on a Twitter bot for this site to tweet the most popular, newest, random packages from npm. Please follow that account now and it will start sending out packages soon–ish.

Open Software & Tools

This site wouldn’t be possible without the immense generosity and tireless efforts from the people who make contributions to the world and share their work via open source initiatives. Thank you 🙏

© 2024 – Pkg Stats / Ryan Hefner

dash_dataflow_components

v0.0.8

Published

Components that create easy to use editable dataflows.

Downloads

2

Readme

dash_dataflow_components

dash_dataflow_components 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

Install dependencies

If you have selected install_dependencies during the prompt, you can skip this part.

  1. Install npm packages

    $ npm install --legacy-peer-deps
  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

Write your component code in src/lib/components/DashDataflowComponents.react.js.

  • 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 (dash_dataflow_components).
    • 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 dash_dataflow_components/__init__.py so dash will serve them automatically when the component suite is requested.
  • Review your code

Create a production build and publish:

  1. Build your code:

    $ npm run build
  2. Create a Python distribution

    $ python setup.py sdist bdist_wheel

    This will create source and wheel distribution in the generated the dist/ folder. See PyPA for more information.

  3. Test your tarball by copying it into a new environment and installing it locally:

    $ pip install dash_dataflow_components-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.
  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