Dash Heatmap

Dash Heatmap to display Warehouse stock movement frequency

Quickstart

pip install dash-heatmap

import dash
import dash_heatmap
import json

app = dash.Dash(__name__)

# NB: Usually add data via filters and callbacks
with open('./assets/data/lmTest.json') as test_data:
    data = json.load(test_data)

app.layout = dash_heatmap.DashHeatmap(
    id='my-warehouse',
    width='100%',
    svg='../../assets/svg/test.svg', # Path relative to JavaScript imports
    data=data # Optional prop
)

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

Reference

See a list of all of the Heatmap properties.

Development

Install dependencies

Install npm packages
```
$ npm install
```
Create a virtual env and activate.
```
$ virtualenv venv
$ . venv/bin/activate
```
Note: venv\Scripts\activate for windows
Install python packages required to build components.
```
$ pip install -r requirements.txt
```

Install the python packages for testing

$ pip install -r tests/requirements.txt

Running the Demo

The demo app is in src/demo
To run the demo
1. npm run start
Test your code in a Python environment:
1. Activate virtual env
```
$ . venv/bin/activate
```
2. Build your code
```
$ npm run build
```
3. Run and modify the usage.py dash app:
```
$ python usage.py
```
Tests for the Dash Heatmap component.
- Tests are available in tests/test_selenium.py
- You will need to install chromedriver, eg. in Debian:
```
wget https://chromedriver.storage.googleapis.com/<VERSION>/chromedriver_linux64.zip
unzip chromedriver_linux64.zip
sudo mv chromedriver /usr/bin/chromedriver
sudo chown root:root /usr/bin/chromedriver
sudo chmod +x /usr/bin/chromedriver
```
- Build the JavaScript with $ npm run build
- Ensure you have completed Step 4. of the Install dependancies
- Run the tests with $ pytest tests.

Create a production build and publish:

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_heatmap-[VERSION].tar.gz
```
If it works, authorised users can publish the component to PyPI:
1. Publish on PyPI
```
$ twine upload dist/*
```
2. Cleanup the dist folder (optional)
```
$ rm -rf dist
```

Contributing

We welcome contributions to Dash Heatmap. If you find a bug or have ideas for new features please feel free to make a New Issue or submit a pull request.