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# Transportation and Traffic Layers
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Display real-time and static transportation information including traffic conditions, public transit routes, and bicycling paths. These layers provide contextual information about transportation infrastructure and current conditions.
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## Capabilities
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### Traffic Layer
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Display real-time traffic information with automatic updates and current road conditions.
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```python { .api }
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def traffic_layer(auto_refresh=True):
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    """
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    Create a traffic information layer.
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    Parameters:
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    - auto_refresh (bool): Whether layer auto-updates traffic data
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    Returns:
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    Traffic: Traffic layer instance
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    """
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```
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### Traffic Widget
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Widget for displaying current traffic conditions on roads.
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```python { .api }
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class Traffic:
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    """
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    Traffic layer widget showing current traffic conditions.
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    Attributes:
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    - auto_refresh (bool): Whether layer auto-updates
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    """
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```
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### Transit Layer
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Display public transportation routes and stops including buses, trains, and subway systems.
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```python { .api }
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def transit_layer():
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    """
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    Create a public transit layer.
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    Returns:
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    Transit: Transit layer instance
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    """
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```
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### Transit Widget
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Widget for showing public transportation infrastructure.
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```python { .api }
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class Transit:
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    """
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    Transit layer widget showing public transport routes and stops.
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    """
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```
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### Bicycling Layer
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Display bicycle-friendly routes and cycling infrastructure.
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```python { .api }
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def bicycling_layer():
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    """
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    Create a bicycling routes layer.
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    Returns:
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    Bicycling: Bicycling layer instance
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    """
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```
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### Bicycling Widget
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Widget for showing bicycle routes and cycling infrastructure.
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```python { .api }
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class Bicycling:
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    """
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    Bicycling layer widget showing bike routes and cycling infrastructure.
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    """
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```
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## Usage Examples
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### Basic Traffic Layer
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```python
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import gmaps
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gmaps.configure(api_key="YOUR_API_KEY")
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# Create figure with traffic layer
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fig = gmaps.figure(center=(37.7749, -122.4194), zoom_level=12)
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traffic_layer = gmaps.traffic_layer()
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fig.add_layer(traffic_layer)
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# Traffic conditions will be displayed in real-time
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fig
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```
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### Traffic with Auto-refresh Disabled
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```python
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import gmaps
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gmaps.configure(api_key="YOUR_API_KEY")
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# Static traffic snapshot
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fig = gmaps.figure()
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traffic_layer = gmaps.traffic_layer(auto_refresh=False)
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fig.add_layer(traffic_layer)
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fig
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```
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### Public Transit Layer
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```python
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import gmaps
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gmaps.configure(api_key="YOUR_API_KEY")
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# Show public transportation routes
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fig = gmaps.figure(center=(37.7749, -122.4194), zoom_level=12)
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transit_layer = gmaps.transit_layer()
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fig.add_layer(transit_layer)
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# Bus routes, train lines, and subway systems will be displayed
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fig
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```
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### Bicycling Routes
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```python
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import gmaps
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gmaps.configure(api_key="YOUR_API_KEY")
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# Show bicycle-friendly routes
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fig = gmaps.figure(center=(37.7749, -122.4194), zoom_level=13)
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bicycling_layer = gmaps.bicycling_layer()
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fig.add_layer(bicycling_layer)
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# Bike lanes, trails, and cycling routes will be displayed
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fig
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```
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### Combined Transportation Layers
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```python
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import gmaps
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gmaps.configure(api_key="YOUR_API_KEY")
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# Create figure focused on urban area
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fig = gmaps.figure(
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    center=(37.7749, -122.4194),  # San Francisco
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    zoom_level=12
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)
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# Add traffic information
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traffic = gmaps.traffic_layer()
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fig.add_layer(traffic)
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# Add public transit routes
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transit = gmaps.transit_layer()
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fig.add_layer(transit)
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# Add bicycling routes
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bicycling = gmaps.bicycling_layer()
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fig.add_layer(bicycling)
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# All transportation modes are now visible
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fig
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```
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### Transportation with Points of Interest
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```python
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import gmaps
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gmaps.configure(api_key="YOUR_API_KEY")
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fig = gmaps.figure(center=(37.7749, -122.4194), zoom_level=13)
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# Add transportation layers
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traffic = gmaps.traffic_layer()
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transit = gmaps.transit_layer()
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fig.add_layer(traffic)
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fig.add_layer(transit)
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# Add markers for transit stations or important locations
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transit_stations = [
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    (37.7749, -122.4194),  # Downtown station
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    (37.7849, -122.4094),  # Midtown station
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    (37.7949, -122.3994)   # Uptown station
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]
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markers = gmaps.marker_layer(
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    transit_stations,
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    label=['Downtown', 'Midtown', 'Uptown'],
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    hover_text=['Main Transit Hub', 'Shopping District', 'Residential Area']
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)
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fig.add_layer(markers)
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fig
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```
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### Route Planning with Transportation Context
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```python
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import gmaps
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gmaps.configure(api_key="YOUR_API_KEY")
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fig = gmaps.figure(center=(37.7749, -122.4194), zoom_level=12)
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# Add transportation context layers
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traffic = gmaps.traffic_layer()
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bicycling = gmaps.bicycling_layer()
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fig.add_layer(traffic)
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fig.add_layer(bicycling)
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# Add driving route
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start = (37.7749, -122.4194)
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end = (37.7849, -122.4094)
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driving_route = gmaps.directions_layer(
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    start, end,
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    travel_mode='DRIVING',
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    stroke_color='blue',
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    stroke_weight=4.0
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)
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fig.add_layer(driving_route)
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# Add cycling alternative
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cycling_route = gmaps.directions_layer(
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    start, end,
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    travel_mode='BICYCLING',
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    stroke_color='green',
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    stroke_weight=3.0
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)
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fig.add_layer(cycling_route)
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fig
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```
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### Transportation Analysis Map
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```python
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import gmaps
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import gmaps.datasets
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gmaps.configure(api_key="YOUR_API_KEY")
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fig = gmaps.figure(center=(37.7749, -122.4194), zoom_level=11)
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# Add all transportation layers for comprehensive view
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traffic = gmaps.traffic_layer()
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transit = gmaps.transit_layer()
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bicycling = gmaps.bicycling_layer()
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fig.add_layer(traffic)
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fig.add_layer(transit)
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fig.add_layer(bicycling)
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# Add data layer (e.g., taxi pickups to show transportation demand)
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try:
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    taxi_data = gmaps.datasets.load_dataset_as_df('taxi_rides')
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    pickup_locations = taxi_data[['pickup_latitude', 'pickup_longitude']]
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    # Create heatmap of transportation demand
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    demand_heatmap = gmaps.heatmap_layer(
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        pickup_locations,
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        opacity=0.6,
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        max_intensity=10,
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        gradient=['rgba(0,0,255,0)', 'rgba(0,0,255,1)', 'rgba(255,0,0,1)']
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    )
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    fig.add_layer(demand_heatmap)
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except:
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    # Dataset not available, skip
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    pass
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fig
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```
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### Real-time Traffic Monitoring
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```python
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import gmaps
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import time
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gmaps.configure(api_key="YOUR_API_KEY")
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# Create traffic monitoring setup
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fig = gmaps.figure(
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    center=(37.7749, -122.4194),
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    zoom_level=12,
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    map_type='ROADMAP'
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)
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# Traffic layer with auto-refresh enabled
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traffic = gmaps.traffic_layer(auto_refresh=True)
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fig.add_layer(traffic)
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# Add key intersections or highways as markers
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key_locations = [
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    (37.7749, -122.4194),  # Downtown
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    (37.7849, -122.4094),  # Highway entrance
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    (37.7649, -122.4294)   # Bridge approach
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]
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markers = gmaps.marker_layer(
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    key_locations,
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    label=['DT', 'HW', 'BR'],
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    hover_text=['Downtown Core', 'Highway On-ramp', 'Bridge Approach']
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)
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fig.add_layer(markers)
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# Traffic conditions will update automatically
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fig
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```
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### Transportation Accessibility Map
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```python
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import gmaps
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gmaps.configure(api_key="YOUR_API_KEY")
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fig = gmaps.figure(center=(37.7749, -122.4194), zoom_level=12)
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# Show all transportation options
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transit = gmaps.transit_layer()
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bicycling = gmaps.bicycling_layer()
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fig.add_layer(transit)
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fig.add_layer(bicycling)
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# Add accessible locations
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accessible_locations = [
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    (37.7749, -122.4194),  # Wheelchair accessible station
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    (37.7849, -122.4094),  # Bike share station
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    (37.7649, -122.4294)   # Park & ride facility
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]
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accessibility_symbols = gmaps.symbol_layer(
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    accessible_locations,
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    fill_color=['blue', 'green', 'orange'],
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    scale=[5, 4, 4],
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    hover_text=[
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        'Wheelchair Accessible Transit',
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        'Bike Share Station',
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        'Park & Ride Facility'
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    ]
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)
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fig.add_layer(accessibility_symbols)
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fig
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```