semvec/pypi-packages huggingface dataset:
dash-table 5.0.0
Dash table
License: MIT

# Notice

As of Dash 2, the development of Dash Table has been moved to the [main Dash repo](https://github.com/plotly/dash)

This package exists for backward compatibility

---

# Dash Table

An interactive `DataTable` for [Dash](https://dash.plotly.com/).

:point_right: [Documentation](https://dash.plotly.com/datatable)

## Quickstart

```
pip install dash-table
```

```python
import dash
import dash_table
import pandas as pd

df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/solar.csv')

app = dash.Dash(__name__)

app.layout = dash_table.DataTable(
    id='table',
    columns=[{"name": i, "id": i} for i in df.columns],
    data=df.to_dict('records'),
)

if __name__ == '__main__':
    app.run_server(debug=True)
```

![Interactive Dash DataTable](https://user-images.githubusercontent.com/1280389/47935912-67187080-deb2-11e8-8936-34b0c99b518f.png)

## Background

Dash DataTable is an interactive table component designed for viewing, editing, and exploring large datasets.

DataTable is rendered with standard, semantic HTML `<table/>` markup, which makes it accessible, responsive, and easy to style.

This component was written from scratch in React.js and Typescript specifically for the Dash community. Its API was designed to be ergonomic and its behavior is completely customizable through its properties.

DataTable was designed with a featureset that allows that Dash users to create complex, spreadsheet driven applications with no compromises. We're excited to continue to work with users and companies that [invest in DataTable's future](https://plotly.com/products/consulting-and-oem/).

Please subscribe to [dash-table#207](https://github.com/plotly/dash-table/issues/207) and the [CHANGELOG.md](https://github.com/plotly/dash-table/blob/master/CHANGELOG.md) to stay up-to-date with any breaking changes. Note: DataTable is currently supported in Chrome, Firefox, Safari, Edge (version 15+), and Internet Explorer 11. 

Share your DataTable Dash apps on the [community forum](https://community.plotly.com/t/show-and-tell-community-thread/7554)!

## Contributing

See [CONTRIBUTING.md](https://github.com/plotly/dash-table/blob/master/CONTRIBUTING.md)
dash-core-components 2.0.0
Core component suite for Dash
License: MIT

# Notice

As of Dash 2, the development of dash-core-components has been moved to the [main Dash repo](https://github.com/plotly/dash)

This package exists for backward compatibility

---

# Dash Core Components

This package provides the core React component suite for [Dash][].

[![CircleCI](https://circleci.com/gh/plotly/dash-core-components.svg?style=svg)](https://circleci.com/gh/plotly/dash-core-components)

## Development

The `dash` package contains some tools to build components and drive the bundles build process.
To avoid the circular dependency situation, we don't add `dash` as a required install in the `dash-core-components` setup.
But, in order to do development locally, you need to install `dash` before everything.

1. Install the dependencies with:

```bash
# it's recommended to install your python packages in a virtualenv
# python 2
$ pip install virtualenv --user && virtualenv venv && . venv/bin/activate
# python 3
$ python -m venv venv && . venv/bin/activate

# make sure dash is installed with dev and testing dependencies
$ pip install dash[dev,testing]  # in some shells you need \ to escape []

# run the build process
$ npm i --ignore-scripts && npm run build

# install dcc in editable mode
$ pip install -e .
```

### Code quality and tests

### To run integration tests (test_integration.py)
You can run the Selenium integration tests with the
```sh
npm test
```

### Testing your components in Dash
1. Run the build watcher by running
        $ npm run build:watch

2. Run the dash layout you want to test

        # Import dash_core_components to your layout, then run it:
        $ python my_dash_layout.py

## Uninstalling python package locally

```sh
$ npm run uninstall-local
```

## Publishing

There's an npm script that will handle publish, provided you have the right credentials. You can run it by running

```sh
$ npm run publish-all
```

See the [Publishing New Components/Features](CONTRIBUTING.md#publishing-new-componentsfeatures) section of the Contributing guide for step-by-step instructions on publishing new components.

## Dash Component Boilerplate

See the [dash-component-boilerplate](https://github.com/plotly/dash-component-boilerplate) repo for more information.

[Dash]: https://plotly.com/dash
[Dash Component Boilerplate]: (https://github.com/plotly/dash-component-boilerplate)
[NPM package authors]: https://www.npmjs.com/package/dash-core-components/access
[PyPi]: https://pypi.python.org/pypi


## Big Thanks
Cross-browser Testing Powered by [![image](https://user-images.githubusercontent.com/1394467/64290307-e4c66600-cf33-11e9-85a1-12c82230a597.png)](https://saucelabs.com)