### Setup for Contributors

Source: https://github.com/plotly/dash-daq/blob/master/README.md

Steps for contributors to set up a development environment, including installing dependencies and cloning the repository.

```sh
# Clone this repository
git clone https://github.com/plotly/dash-daq.git

# Install dependencies
npm install --also=dev

# Watch source for changes and build to `lib/`
npm start
```

--------------------------------

### Install dash_daq

Source: https://github.com/plotly/dash-daq/blob/master/README.md

Installs the dash_daq library using pip. It also mentions the alternative for Python 3.

```sh
pip install dash_daq
# Or for Python 3, pip3 install dash_daq
```

--------------------------------

### Install Python Package Locally

Source: https://github.com/plotly/dash-daq/blob/master/README.md

Installs the dash-daq module locally into the Python environment's site-packages for testing before publishing.

```sh
yarn run install-local
```

--------------------------------

### Run Demo Server

Source: https://github.com/plotly/dash-daq/blob/master/README.md

Starts a demo development server to view rendered components. Requires maintaining the component list in `demo/Demo.react.js`.

```sh
npm run dash-demo
```

--------------------------------

### Test Components in Dash

Source: https://github.com/plotly/dash-daq/blob/master/README.md

Guides on how to test components locally within a Dash application after development.

```sh
# Build development bundle to `lib/`
npm run start

# Generate metadata, and install the daq pacakage locally for testing
npm run install-local

# Run the Dash demo
npm run dash-demo
```

--------------------------------

### LED Display Example

Source: https://github.com/plotly/dash-daq/blob/master/demo/index.html

Shows how to use the LED display component from Dash DAQ. This component mimics a seven-segment LED display, suitable for showing numerical values or status indicators.

```python
import dash
from dash import html
import dash_daq as daq

app = dash.Dash(__name__)

app.layout = html.Div([
    daq.LEDDisplay(
        id='my-led-display',
        value='12345',
        color="#33FF57",
        size=50
    )
])

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

--------------------------------

### Basic Gauge Example

Source: https://github.com/plotly/dash-daq/blob/master/demo/index.html

Demonstrates how to create a simple Gauge component in Dash DAQ. This component is useful for displaying a single value within a defined range, often used for metrics or sensor readings.

```python
import dash
from dash import html
import dash_daq as daq

app = dash.Dash(__name__)

app.layout = html.Div([
    daq.Gauge(
        id='my-gauge',
        label='Default',
        value=60,
        max=100,
        min=0
    )
])

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

--------------------------------

### Uninstall Python Package Locally

Source: https://github.com/plotly/dash-daq/blob/master/README.md

Removes the locally installed dash-daq module from the Python environment.

```sh
yarn run uninstall-local
```

--------------------------------

### Produce New Release Tarball

Source: https://github.com/plotly/dash-daq/blob/master/README.md

Steps to create a new release tarball for the dash-daq package, including version bumping and building.

```sh
vim dash_daq/version.py # and increase it to X.X.X
rm -rf node_modules dist build lib
yarn install
yarn build-tarball
ls dist/dash_daq-X.X.X.tar.gz # this is your tarball
```

--------------------------------

### Run Lint and Unit Tests

Source: https://github.com/plotly/dash-daq/blob/master/README.md

Executes linting and unit tests for code quality assurance.

```sh
npm run test
```

--------------------------------

### DarkThemeProvider Component

Source: https://github.com/plotly/dash-daq/blob/master/demo/index.html

Shows how to apply a dark theme to Dash DAQ components using the DarkThemeProvider. This component wraps other DAQ components to change their visual appearance.

```python
import dash
from dash import html
import dash_daq as daq

app = dash.Dash(__name__)

app.layout = daq.DarkThemeProvider([
    daq.LEDDisplay(value='DARK'),
    daq.Gauge(value=50)
])

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

--------------------------------

### Color Picker Component

Source: https://github.com/plotly/dash-daq/blob/master/demo/index.html

Demonstrates the ColorPicker component for selecting colors. This component provides a visual interface for users to choose colors, often used for theming or customization.

```python
import dash
from dash import html
import dash_daq as daq

app = dash.Dash(__name__)

app.layout = html.Div([
    daq.ColorPicker(
        id='my-color-picker',
        label='Color Picker',
        value=dict(hex='#111F4B')
    )
])

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

--------------------------------

### Knob Component for Value Selection

Source: https://github.com/plotly/dash-daq/blob/master/demo/index.html

Shows how to use the Knob component, which provides a circular slider for selecting values. It's ideal for settings that require a continuous range of adjustment.

```python
import dash
from dash import html
import dash_daq as daq

app = dash.Dash(__name__)

app.layout = html.Div([
    daq.Knob(
        id='my-knob',
        value=45,
        min=0,
        max=100,
        label='Knob',
        size=150
    )
])

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

--------------------------------

### Power Button Component

Source: https://github.com/plotly/dash-daq/blob/master/demo/index.html

Illustrates the PowerButton component, a toggle switch that can be used to represent on/off states. It's a simple yet effective way to control binary states in an application.

```python
import dash
from dash import html
import dash_daq as daq

app = dash.Dash(__name__)

app.layout = html.Div([
    daq.PowerButton(
        id='my-power-button',
        label='Power',
        checked=True
    )
])

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

--------------------------------

### Tank Component for Level Visualization

Source: https://github.com/plotly/dash-daq/blob/master/demo/index.html

Demonstrates the Tank component, which visually represents a fluid level within a container. This is useful for monitoring quantities or capacities.

```python
import dash
from dash import html
import dash_daq as daq

app = dash.Dash(__name__)

app.layout = html.Div([
    daq.Tank(
        id='my-tank',
        value=75,
        min=0,
        max=100,
        label='Tank Level',
        units='L'
    )
])

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

--------------------------------

### Numeric Input with Stepper

Source: https://github.com/plotly/dash-daq/blob/master/demo/index.html

Illustrates the use of the NumericInput component with stepper buttons. This component allows users to input numerical values and adjust them using increment/decrement buttons.

```python
import dash
from dash import html
import dash_daq as daq

app = dash.Dash(__name__)

app.layout = html.Div([
    daq.NumericInput(
        id='my-numeric-input',
        value=5,
        min=0,
        max=10,
        label='Numeric Input',
        labelPosition='top'
    )
])

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

--------------------------------

### Indicator Component for Status

Source: https://github.com/plotly/dash-daq/blob/master/demo/index.html

Demonstrates the Indicator component, which displays a colored circle to represent status (e.g., online, offline, warning). It's useful for quick visual feedback.

```python
import dash
from dash import html
import dash_daq as daq

app = dash.Dash(__name__)

app.layout = html.Div([
    daq.Indicator(
        id='my-indicator',
        label='Status',
        value=True,  # True for green, False for red
        color='green'
    )
])

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

--------------------------------

### Slider Component for Range Selection

Source: https://github.com/plotly/dash-daq/blob/master/demo/index.html

Illustrates the Slider component for selecting a value within a specified range. It's a common UI element for adjusting parameters or filtering data.

```python
import dash
from dash import html
import dash_daq as daq

app = dash.Dash(__name__)

app.layout = html.Div([
    daq.Slider(
        id='my-slider',
        min=0,
        max=10,
        value=5,
        marks={i: str(i) for i in range(11)},
        step=1,
        tooltip={'always_visible': True}
    )
])

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

=== COMPLETE CONTENT === This response contains all available snippets from this library. No additional content exists. Do not make further requests.