Full Code of Acrotrend/awesome-dash for AI

Repository: Acrotrend/awesome-dash
Branch: master
Commit: 506ef0c006bb
Files: 7
Total size: 24.4 KB

Directory structure:
gitextract_fxfd5wbs/

├── LICENSE
├── PULL_REQUEST_TEMPLATE.md
├── README.md
├── contributing.md
├── link_validator.py
├── query_github
└── query_pypi

================================================
FILE CONTENTS
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================================================
FILE: LICENSE
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================================================
FILE: PULL_REQUEST_TEMPLATE.md
================================================
For adding tutorials, packages, or apps
===========================================
<!-- If you are making a pull request on the master branch, please resubmit your pull request using the dev-master branch. -->


##### What did you add to the README.md file?
<!-- Make a detailed list of what awesomeness you have added to the readme -->


Have you ensured your contribution adheres to the pull request guidelines of [awesome](https://github.com/sindresorhus/awesome/edit/master/pull_request_template.md)? In particular:

- Not a duplicate.
- Only has awesome items. Awesome lists are curations of the best, not everything.
- Has consistent formatting and proper spelling/grammar.
	- The link and description are separated by a dash. <br>Example: `- [AVA](…) - JavaScript test runner.`
	- The description starts with an uppercase character and ends with a period.
	- Drop all the `A` / `An` prefixes in the descriptions.
	- Consistent and correct naming. For example, `Node.js`, not `NodeJS` or `node.js`.

----------

### For first time contributors...

##### Do you want to be added to the contributors list on the README.md file?  
<!-- Check yes or no. If yes respond to the next 2 questions. If no, submit the pull request. -->
- [ ] Yes
- [ ] No

##### What name would you like?
<!-- Add a name and link to your name to the README if you checked yes above.-->


##### What website would you like your name linked to?

  


================================================
FILE: README.md
================================================
# Awesome Dash [![Awesome](https://awesome.re/badge-flat.svg)](https://github.com/sindresorhus/awesome)

[<img src="logo.webp" align="right" width="250">](https://plot.ly/products/dash/)

A curated list of awesome Dash (plotly) resources

> [Dash](https://plot.ly/products/dash/) is a productive Python framework for building web applications.
> Written on top of Flask, Plotly.js, and React.js, Dash is ideal for building data visualization apps with highly custom user interfaces in pure Python. It's particularly suited for anyone who works with data in Python.

## Contents
- [Deployment](#deployment)
- [Tutorials](#tutorials)
- [Component Libraries](#component-libraries)
- [App Examples](#app-examples)
- [Idiomatic examples](#idiomatic-examples)
- [Galleries](#galleries)
- [Cheat sheets](#cheat-sheets)
- [Talks](#talks)
- [Books](#books)
- [Community](#community)
- [Contributors](#contributors)

## Deployment

- [Ploomber Cloud](https://ploomber.io) - The community plan allows free deployments

## Tutorials

- [Introducing Plotly Dash](https://medium.com/@plotlygraphs/introducing-dash-5ecf7191b503) - A high level introduction to Dash by Chris Parmer, the author of Dash. This essay was released as part of Dash's official launch (June 21, 2017).
- [Plotly's tutorials - Part 1: App Layout](https://dash.plotly.com/layout)
- [Plotly's tutorials - Part 2: Interactivity](https://dash.plotly.com/basic-callbacks)
- [Plotly's tutorials - Part 3: Interactive Graphing](https://dash.plotly.com/interactive-graphing)
- [Plotly's tutorials - Part 4: Callbacks With State](https://dash.plotly.com/sharing-data-between-callbacks)
- [Charming Data YouTube channel](https://www.youtube.com/charmingdata) - A channel dedicated to teaching Dash and Plotly with over 25k subscribers.
- [Interactive Web-Based Dashboards in Python](https://alysivji.github.io/reactive-dashboards-with-dash.html) - How the MVC model pertains to Dash and a walkthrough of building an app.
- [Using Plotly's Dash to deliver public sector decision support dashboards](https://medium.com/a-r-g-o/using-plotlys-dash-to-deliver-public-sector-decision-support-dashboards-ac863fa829fb) - Building a complex dashboard step-by-step.
- [OPS CodeDay: Dash Plotly Map + Graph](https://radumas.info/blog/tutorial/2017/08/10/codeday.html) - How to use Jupyter notebooks in tandom with Dash to create mapping viz.
- [Creating Interactive Visualizations with Plotly's Dash Framework](http://pbpython.com/plotly-dash-intro.html) - High level overview of how to get started with Dash.
- [ARGO Labs - Plotly Dash Tutorial (Video)](https://www.youtube.com/watch?v=yfWJXkySfe0) - Detailed introduction to creating interactive dashboards.
- [Data Visualization GUIs with Dash and Python (Video playlist)](https://www.youtube.com/watch?v=J_Cy_QjG6NE&list=PLQVvvaa0QuDfsGImWNt1eUEveHOepkjqt) - Five-part series exploring Dash features.
- [Interactive Visualization of Machine Learning and Computer Vision with Dash](https://www.youtube.com/watch?v=3F5AR-uUqJc) - Official introduction video.
- [Webinar: Converting React components to Dash components](https://www.youtube.com/watch?v=wifoPPRgG_I) - Official tutorial about how to convert React components to Dash components.
- [Interactive Image Processing with Dash-Canvas](https://www.youtube.com/watch?v=LKXSFBB5ccI) - Official introduction video to the Dash Canvas components.
- [Dash Cytoscape Component](https://www.youtube.com/watch?v=snXcIsCMQgk) - Official introduction video to the Dash Cytoscape components.
- [An introduction to Dash DataTable](https://www.youtube.com/watch?v=dueejcyrYh8) - Official introduction video to the Dash DataTable components.
- [Tutorial on creating custom Dash components with React.js.](https://dash.plotly.com/plugins)

## Component Libraries

- [Dash PDF](https://github.com/ploomber/dash-pdf) - Display inline PDFs
- [Dash MUI](https://github.com/ploomber/dash-mui) - Material UI components
- [Dash React Simple Maps](https://github.com/ploomber/dash-react-simple-maps) - Create interactive maps
- [Dash Mosaic](https://github.com/ploomber/mosaic-python#dash-mosaic) - Display [Mosaic](https://github.com/uwdata/mosaic) plots
- [Dash Tabler Icons](https://github.com/ploomber/dash-tabler-icons) - Beautiful icons for your Dash apps
- [Dash React Syntax Highlighter](https://github.com/ploomber/dash-react-syntax-highlighter) - Display code snippets with a copy button
- [Dash Canvas Components](https://dash.plotly.com/canvas) - Module for image annotation and image processing using 
Dash.
- [Awesome React Components](https://github.com/brillout/awesome-react-components) - Catalog of React.js components potentially interesting to be wrapped into Dash components.
- [Awesome React](https://github.com/enaqx/awesome-react) - Helpful resources for developing React.js components.
- [Dash Core Components](https://github.com/plotly/dash-core-components)
- [Dash Cytoscape Component](https://dash.plotly.com/cytoscape) - Graph visualization component for creating easily
customizable, high-performance, interactive, and web-based networks.
- [Dash DataTable Component](https://dash.plotly.com/datatable) - Interactive table that supports rich styling,
conditional formatting, editing, sorting, filtering, and more.
- [Dash DAQ Components](https://dash.plotly.com/dash-daq) - Set of controls that make it simpler to integrate data
acquisition and controls into your Dash applications.
- [Dash HTML Components](https://github.com/plotly/dash-html-components)
- [mydcc](https://github.com/jimmybow/mydcc) - Extension of Dash Core Components.
- [sd-material-ui](https://github.com/StratoDem/sd-material-ui) - StratoDem Analytics implementations of material-ui components for Dash.
- [sd-range-slider](https://github.com/StratoDem/sd-range-slider) - Range Slider Dash component.
- [dj-plotly-dash](https://github.com/pikhovkin/dj-plotly-dash) - Plotly Dash fork for Django.
- [dash-flexbox-grid](https://github.com/pikhovkin/dash-flexbox-grid) - Wrapper around react-flexbox-grid for Plotly Dash.
- [dash-color-picker](https://github.com/vivekvs1/dash-color-picker) - Wrapper around react-color.
- [dash-dual-listbox](https://github.com/vivekvs1/dash-dual-listbox) - Wrapper around react-duallist.
- [dash-bootstrap-components](https://dash-bootstrap-components.opensource.faculty.ai/) - Bootstrap components for Dash.
- [dash-uploader](https://github.com/np-8/dash-uploader) - Upload component for Dash. Supports large data files.
- [Dash Mantine Components](https://github.com/snehilvj/dash-mantine-components) - Collection of 40+ Dash components based on Mantine React Components library.
- [plotly-resampler](https://github.com/predict-idlab/plotly-resampler) - Wrapper for plotly figures that adds data downsampling (aggregating) functionality, enabling the visualization of large datasets.
- [dash-vega-components](https://github.com/altair-viz/dash-vega-components) - Dash component for Vega-Altair, Vega-Lite, and Vega charts.

## App Examples

- [Oil and Gas Explorer](https://dash.gallery/dash-oil-and-gas/) - Explore oil and gas production over time and with linked visualisations. [Source Code.](https://github.com/plotly/dash-oil-and-gas-demo)
- [Uber Rides](https://dash.gallery/dash-uber-rides-demo/) - Displays all of the Uber rides in New York City in 2014. Pandas on the backend filters a 0.5gig datafile. [Source Code.](https://github.com/plotly/dash-sample-apps/tree/main/apps/dash-uber-rides-demo)
- [Drug Discovery](https://dash.gallery/dash-drug-discovery/) - Displays a description of the drug as you hover over points in the graph. [Source Code.](https://github.com/plotly/dash-sample-apps/tree/main/apps/dash-drug-discovery)
- [Live Wind Streaming](https://dash.gallery/dash-wind-streaming/) - Continually queries a SQL database and displays live charts of wind speed and wind direction. [Source Code.](https://github.com/plotly/dash-sample-apps/tree/main/apps/dash-wind-streaming)
- [3D Yield Curve](https://dash.gallery/dash-yield-curve/) - Adapted from NYTimes's excellent [A 3-D View of a Chart That Predicts The Economic Future: The Yield Curve](https://www.nytimes.com/interactive/2015/03/19/upshot/3d-yield-curve-economic-growth.html). [Source Code.](https://github.com/plotly/dash-sample-apps/tree/main/apps/dash-yield-curve)
- [Visualize Earthquakes with Plotly Dash](https://dash-earthquakes-production-45eyyotfta-ey.a.run.app/) - Great UI and usage of geospatial analytics with Dash. Includes [basic unit tests](https://github.com/jackdbd/dash-earthquakes/tree/master/tests). [Source Code.](https://github.com/jackdbd/dash-earthquakes)
- [GutenSearch](https://gutensearch.com/) - Look inside the books of Project Gutenberg. [Source Code.](https://github.com/cordb/gutensearch)

## Idiomatic examples
- [Dash recipes](https://github.com/plotly/dash-recipes) - A collection of scripts and examples created of the plotly team while answering questions from the greater Dash community.

## Galleries
- [Dash Data Dashboards and Apps](https://www.dashboardom.com/) - Collection of data dashboards with real life data, for various topics, as well as a few apps for online marketing built with Dash.
- [Dash Gallery](https://dash.gallery/) - A collection of Dash apps.

## Talks
- [Dash: Data exploration web apps in pure Python](https://www.youtube.com/watch?v=eusglTlW4OA) - Chelsea Douglas, PyData DC 2018.
- [Overview of Dash](https://www.youtube.com/watch?v=sea2K4AuPOk) - Chris Parmer, creator of Dash (SciPy 2017).
- [We're Launching Dash](https://www.youtube.com/watch?v=5BAthiN0htc&t=1s) - Chris Parmer, creator of Dash, speaking about the motivations behind Dash before it was launched (Plotcon NYC 2016).
- [Plotly dash and data visualisation in Python, PyData, Berlin 2017](https://www.slideshare.net/vladimirkazantsev/plotly-dash-and-data-visualisation-in-python) - Volodymyr Kazantsev (slides only).

## Cheat sheets
- [plotly.py Cheat Sheet](https://images.plot.ly/plotly-documentation/images/python_cheat_sheet.pdf)

## Community
- [Plotly hosted Question and Answer community](https://community.plot.ly)
- [Stack Overflow](https://stackoverflow.com/questions/tagged/plotly-dash)

## Contributors
- [Luke Singham](https://lukesingham.com/)
- [Aly Sivji](https://alysivji.github.io/)
- [Chris Parmer](https://github.com/chriddyp)
- [Sergey Pikhovkin](https://github.com/pikhovkin)
- [Pascal Bugnion](https://pascalbugnion.net)
- [Florian Kromer](https://github.com/fkromer)
- [Elias Dabbas](https://www.dashboardom.com)
- [vaexio](https://github.com/vaexio)
- [Fanchao MENG](https://github.com/pingf)
- [Snehil Vijay](https://github.com/snehilvj)
- [Eduardo Blancas](https://github.com/edublancas)

## License
This work is licensed under a Creative Commons Attribution 4.0 International License.


================================================
FILE: contributing.md
================================================
# Contribution Guidelines #

### The pull request should have a useful title. Pull requests with `Update readme.md` as title will be closed right away because I'm so tired of nobody reading this document. Please carefully read everything in `Adding to this list`.

## Table of Contents

- [Adding to this list](#adding-to-this-list)
- [Creating your own awesome list](#creating-your-own-awesome-list)
- [Adding something to an awesome list](#adding-something-to-an-awesome-list)
- [Updating your Pull Request](#updating-your-pull-request)

## Adding to this list

Please ensure your pull request adheres to the following guidelines:

- Search previous suggestions before making a new one, as yours may be a duplicate.
- Make sure the list is useful before submitting. That implies it has enough content and every item has a good succinct description.
- Make an individual pull request for each suggestion.
- Use [title-casing](http://titlecapitalization.com) (AP style).
- Use the following format: `[Resource Name](link)`
- Link additions should be added to the bottom of the relevant category.
- New categories or improvements to the existing categorisation are welcome.
- Check your spelling and grammar.
- Make sure your text editor is set to remove trailing whitespace.
- The pull request and commit should have a useful title.

## Adding something to an awesome list

If you have something awesome to contribute to an awesome list, this is how you do it.

You'll need a [GitHub account](https://github.com/join)!

1. Access the awesome list's GitHub page. For example: https://github.com/sindresorhus/awesome
2. Click on the `readme.md` file: ![Step 2 Click on Readme.md](https://cloud.githubusercontent.com/assets/170270/9402920/53a7e3ea-480c-11e5-9d81-aecf64be55eb.png)
3. Now click on the edit icon. ![Step 3 - Click on Edit](https://cloud.githubusercontent.com/assets/170270/9402927/6506af22-480c-11e5-8c18-7ea823530099.png)
4. You can start editing the text of the file in the in-browser editor. Make sure you follow guidelines above. You can use [GitHub Flavored Markdown](https://help.github.com/articles/github-flavored-markdown/). ![Step 4 - Edit the file](https://cloud.githubusercontent.com/assets/170270/9402932/7301c3a0-480c-11e5-81f5-7e343b71674f.png)
5. Say why you're proposing the changes, and then click on "Propose file change". ![Step 5 - Propose Changes](https://cloud.githubusercontent.com/assets/170270/9402937/7dd0652a-480c-11e5-9138-bd14244593d5.png)
6. Submit the [pull request](https://help.github.com/articles/using-pull-requests/)!

## Updating your Pull Request

Sometimes, a maintainer of an awesome list will ask you to edit your Pull Request before it is included. This is normally due to spelling errors or because your PR didn't match the awesome-* list guidelines.

[Here](https://github.com/RichardLitt/docs/blob/master/amending-a-commit-guide.md) is a write up on how to change a Pull Request, and the different ways you can do that.


================================================
FILE: link_validator.py
================================================
# Simple link validator for the README.md file

import asyncio
import re

import httpx


async def validate_link(client: httpx.AsyncClient, url: str) -> tuple[str, bool]:
    url = url.rstrip(")")
    try:
        response = await client.head(url, follow_redirects=True, timeout=5.0)
        is_valid = 200 <= response.status_code < 400
        print(f"URL: {url}, Status Code: {response.status_code}")
        return url, is_valid
    except Exception as e:
        print(f"URL: {url}, Exception: {e}")
        return url, False


def extract_markdown_links(content: str) -> list[str]:
    # Match markdown links [text](url) and direct URLs
    markdown_pattern = r"\[(?:[^\]]*)\]\((https?://[^\s\)]+)\)"
    direct_url_pattern = r"(?<!\])\b(https?://[^\s\)]+)"

    # Find all markdown format links
    markdown_links = re.findall(markdown_pattern, content)
    # Find all direct URLs (not part of markdown syntax)
    direct_urls = re.findall(direct_url_pattern, content)

    return markdown_links + direct_urls


async def check_readme_links(readme_path: str, only_invalid: bool = False) -> None:
    with open(readme_path, "r") as file:
        content = file.read()

    links = extract_markdown_links(content)

    async with httpx.AsyncClient() as client:
        tasks = [validate_link(client, link) for link in links]
        results = await asyncio.gather(*tasks)

        print("Results:")
        for url, is_valid in results:
            if not only_invalid or not is_valid:
                print(f"{url}: {'Valid' if is_valid else 'Invalid'}")


asyncio.run(check_readme_links("README.md", only_invalid=True))


================================================
FILE: query_github
================================================
#!/usr/bin/env python3
# -*- coding: utf-8 -*-

"""Script to get owners and websites of GitHub projects tagged with topics
plotly and dash.

The script has the side effect of depending on environment variables GIT_USER
and GIT_PASSWORD which have to be set to the Github user name and the GitHub
password respectively.

The script has been tested with PyGithub v1.43.8 running under Python 3.6.8.
"""

from os import getenv

from github import Github
from github.GithubException import RateLimitExceededException

USER = getenv("GIT_USER")
PASSWORD = getenv("GIT_PASSWORD")

client = Github(USER, PASSWORD)  # pylint: disable=C0103
try:
    repos = client.search_repositories(query="topic:plotly topic:dash")  # pylint: disable=C0103
    for r in repos:
        name = r.name
        owner = r.owner.login
        url = r.owner.blog
        print(f"Repo: {name}")
        print(f"   Owner: {owner}")
        print(f"   URL:   {url}")
except RateLimitExceededException:
    print("You've triggered your GitHub API rate limit. Try again later.")


================================================
FILE: query_pypi
================================================
#!/usr/bin/env python3
# -*- coding: utf-8 -*-

"""
Prints all PyPi projects which make use of the
PyPi trove classifier avilable for the framework.
The script has been tested running under Python 3.6.8.
"""


import xmlrpc.client as xmlrpclib

client = xmlrpclib.ServerProxy('https://pypi.python.org/pypi')

trove_classifiers = ["Framework :: Dash"]
pypi_projects = []
for tc in trove_classifiers:
    tc_pypi_projects = [p[0] for p in client.browse([tc])]
    pypi_projects += tc_pypi_projects

for p in set(pypi_projects):
    print(p)
~