osm module

The module contains functions for downloading OpenStreetMap data. It wraps the geometries module of the osmnx package (see https://osmnx.readthedocs.io/en/stable/osmnx.html#module-osmnx.geometries). Credits to Geoff Boeing, the developer of the osmnx package. Most functions for downloading OpenStreetMap data require tags of map features. The list of commonly used tags can be found at https://wiki.openstreetmap.org/wiki/Map_features

osm_gdf_from_address(address, tags, dist=1000)

Create GeoDataFrame of OSM entities within some distance N, S, E, W of address.

Parameters:

Name	Type	Description	Default
address	str	The address to geocode and use as the central point around which to get the geometries.	required
tags	dict	Dict of tags used for finding objects in the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one given tag. The dict keys should be OSM tags, (e.g., building, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘building’: True} would return all building footprints in the area. tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop.	required
dist	int	Distance in meters. Defaults to 1000.	1000

Returns:

Name	Type	Description
GeoDataFrame		A GeoDataFrame of OSM entities.

Source code in leafmap/osm.py

def osm_gdf_from_address(address: str, tags: Dict, dist: Optional[int] = 1000):
    """Create GeoDataFrame of OSM entities within some distance N, S, E, W of address.

    Args:
        address (str): The address to geocode and use as the central point around which to get the geometries.
        tags (dict): Dict of tags used for finding objects in the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one given tag. The dict keys should be OSM tags, (e.g., building, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘building’: True} would return all building footprints in the area. tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop.
        dist (int, optional): Distance in meters. Defaults to 1000.

    Returns:
        GeoDataFrame: A GeoDataFrame of OSM entities.
    """
    check_package("osmnx", "https://osmnx.readthedocs.io/en/stable/#installation")

    try:
        import osmnx as ox
    except ImportError:
        raise ImportError(
            "osmnx package is required. Please install it using 'pip install osmnx'"
        )

    gdf = ox.features_from_address(address, tags, dist)
    return gdf

osm_gdf_from_bbox(north, south, east, west, tags)

Create a GeoDataFrame of OSM entities within a N, S, E, W bounding box.

Parameters:

Name	Type	Description	Default
north	float	Northern latitude of bounding box.	required
south	float	Southern latitude of bounding box.	required
east	float	Eastern longitude of bounding box.	required
west	float	Western longitude of bounding box.	required
tags	dict	Dict of tags used for finding objects in the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one given tag. The dict keys should be OSM tags, (e.g., building, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘building’: True} would return all building footprints in the area. tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop.	required

Returns:

Name	Type	Description
GeoDataFrame		A GeoDataFrame of OSM entities.

Source code in leafmap/osm.py

def osm_gdf_from_bbox(north: float, south: float, east: float, west: float, tags: Dict):
    """Create a GeoDataFrame of OSM entities within a N, S, E, W bounding box.

    Args:
        north (float): Northern latitude of bounding box.
        south (float): Southern latitude of bounding box.
        east (float): Eastern longitude of bounding box.
        west (float): Western longitude of bounding box.
        tags (dict): Dict of tags used for finding objects in the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one given tag. The dict keys should be OSM tags, (e.g., building, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘building’: True} would return all building footprints in the area. tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop.

    Returns:
        GeoDataFrame: A GeoDataFrame of OSM entities.
    """
    check_package("osmnx", "https://osmnx.readthedocs.io/en/stable/#installation")
    try:
        import osmnx as ox
    except ImportError:
        raise ImportError(
            "osmnx package is required. Please install it using 'pip install osmnx'"
        )

    gdf = ox.features_from_bbox(north, south, east, west, tags)
    return gdf

osm_gdf_from_geocode(query, which_result=None, by_osmid=False, buffer_dist=None)

Retrieves place(s) by name or ID from the Nominatim API as a GeoDataFrame.

Parameters:

Name	Type	Description	Default
query	str | dict | list	Query string(s) or structured dict(s) to geocode.	required
which_result	INT	Which geocoding result to use. if None, auto-select the first (Multi)Polygon or raise an error if OSM doesn't return one. to get the top match regardless of geometry type, set which_result=1. Defaults to None.	None
by_osmid	bool	If True, handle query as an OSM ID for lookup rather than text search. Defaults to False.	False
buffer_dist	float	Distance to buffer around the place geometry, in meters. Defaults to None.	None

Returns:

Name	Type	Description
GeoDataFrame		A GeoPandas GeoDataFrame.

Source code in leafmap/osm.py

def osm_gdf_from_geocode(
    query: Union[str, Dict, List],
    which_result: Optional[int] = None,
    by_osmid: Optional[bool] = False,
    buffer_dist: Optional[float] = None,
):
    """Retrieves place(s) by name or ID from the Nominatim API as a GeoDataFrame.

    Args:
        query (str | dict | list): Query string(s) or structured dict(s) to geocode.
        which_result (INT, optional): Which geocoding result to use. if None, auto-select the first (Multi)Polygon or raise an error if OSM doesn't return one. to get the top match regardless of geometry type, set which_result=1. Defaults to None.
        by_osmid (bool, optional): If True, handle query as an OSM ID for lookup rather than text search. Defaults to False.
        buffer_dist (float, optional): Distance to buffer around the place geometry, in meters. Defaults to None.

    Returns:
        GeoDataFrame: A GeoPandas GeoDataFrame.
    """

    check_package("osmnx", "https://osmnx.readthedocs.io/en/stable/")

    import osmnx as ox

    gdf = ox.geocode_to_gdf(query, which_result, by_osmid, buffer_dist)
    return gdf

osm_gdf_from_place(query, tags, which_result=None, buffer_dist=None)

Create GeoDataFrame of OSM entities within boundaries of geocodable place(s).

Parameters:

Name	Type	Description	Default
query	str | dict | list	Query string(s) or structured dict(s) to geocode.	required
tags	dict	Dict of tags used for finding objects in the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one given tag. The dict keys should be OSM tags, (e.g., building, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘building’: True} would return all building footprints in the area. tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop.	required
which_result	int	Which geocoding result to use. if None, auto-select the first (Multi)Polygon or raise an error if OSM doesn't return one. to get the top match regardless of geometry type, set which_result=1. Defaults to None.	None
buffer_dist	float	Distance to buffer around the place geometry, in meters. Defaults to None.	None

Returns:

Name	Type	Description
GeoDataFrame		A GeoDataFrame of OSM entities.

Source code in leafmap/osm.py

def osm_gdf_from_place(
    query: Union[str, Dict, List],
    tags: Dict,
    which_result: Optional[int] = None,
    buffer_dist: Optional[float] = None,
):
    """Create GeoDataFrame of OSM entities within boundaries of geocodable place(s).

    Args:
        query (str | dict | list): Query string(s) or structured dict(s) to geocode.
        tags (dict): Dict of tags used for finding objects in the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one given tag. The dict keys should be OSM tags, (e.g., building, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘building’: True} would return all building footprints in the area. tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop.
        which_result (int, optional): Which geocoding result to use. if None, auto-select the first (Multi)Polygon or raise an error if OSM doesn't return one. to get the top match regardless of geometry type, set which_result=1. Defaults to None.
        buffer_dist (float, optional): Distance to buffer around the place geometry, in meters. Defaults to None.

    Returns:
        GeoDataFrame: A GeoDataFrame of OSM entities.
    """
    check_package("osmnx", "https://osmnx.readthedocs.io/en/stable/#installation")
    try:
        import osmnx as ox
    except ImportError:
        raise ImportError(
            "osmnx package is required. Please install it using 'pip install osmnx'"
        )

    ox.settings.use_cache = True
    ox.settings.log_console = False

    gdf = ox.features_from_place(query, tags, which_result, buffer_dist)
    return gdf

osm_gdf_from_point(center_point, tags, dist=1000)

Create GeoDataFrame of OSM entities within some distance N, S, E, W of a point.

Parameters:

Name	Type	Description	Default
center_point	tuple	The (lat, lng) center point around which to get the geometries.	required
tags	dict	Dict of tags used for finding objects in the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one given tag. The dict keys should be OSM tags, (e.g., building, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘building’: True} would return all building footprints in the area. tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop.	required
dist	int	Distance in meters. Defaults to 1000.	1000

Returns:

Name	Type	Description
GeoDataFrame		A GeoDataFrame of OSM entities.

Source code in leafmap/osm.py

def osm_gdf_from_point(
    center_point: Tuple[float, float], tags: Dict, dist: Optional[int] = 1000
):
    """Create GeoDataFrame of OSM entities within some distance N, S, E, W of a point.

    Args:
        center_point (tuple): The (lat, lng) center point around which to get the geometries.
        tags (dict): Dict of tags used for finding objects in the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one given tag. The dict keys should be OSM tags, (e.g., building, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘building’: True} would return all building footprints in the area. tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop.
        dist (int, optional): Distance in meters. Defaults to 1000.

    Returns:
        GeoDataFrame: A GeoDataFrame of OSM entities.
    """
    check_package("osmnx", "https://osmnx.readthedocs.io/en/stable/#installation")
    try:
        import osmnx as ox
    except ImportError:
        raise ImportError(
            "osmnx package is required. Please install it using 'pip install osmnx'"
        )

    gdf = ox.features_from_point(center_point, tags, dist)
    return gdf

osm_gdf_from_polygon(polygon, tags)

Create GeoDataFrame of OSM entities within boundaries of a (multi)polygon.

Parameters:

Name	Type	Description	Default
polygon	Polygon | MultiPolygon	Geographic boundaries to fetch geometries within	required
tags	dict	Dict of tags used for finding objects in the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one given tag. The dict keys should be OSM tags, (e.g., building, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘building’: True} would return all building footprints in the area. tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop.	required

Returns:

Name	Type	Description
GeoDataFrame		A GeoDataFrame of OSM entities.

Source code in leafmap/osm.py

def osm_gdf_from_polygon(polygon, tags: Dict):
    """Create GeoDataFrame of OSM entities within boundaries of a (multi)polygon.

    Args:
        polygon (shapely.geometry.Polygon | shapely.geometry.MultiPolygon): Geographic boundaries to fetch geometries within
        tags (dict): Dict of tags used for finding objects in the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one given tag. The dict keys should be OSM tags, (e.g., building, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘building’: True} would return all building footprints in the area. tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop.

    Returns:
        GeoDataFrame: A GeoDataFrame of OSM entities.
    """
    check_package("osmnx", "https://osmnx.readthedocs.io/en/stable/#installation")
    try:
        import osmnx as ox
    except ImportError:
        raise ImportError(
            "osmnx package is required. Please install it using 'pip install osmnx'"
        )

    gdf = ox.features_from_polygon(polygon, tags)
    return gdf

osm_gdf_from_xml(filepath, polygon=None, tags=None)

Create a GeoDataFrame of OSM entities in an OSM-formatted XML file.

Parameters:

Name	Type	Description	Default
filepath	str	File path to file containing OSM XML data	required
polygon	Polygon	Optional geographic boundary to filter objects. Defaults to None.	None
tags	dict	Dict of tags used for finding objects in the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one given tag. The dict keys should be OSM tags, (e.g., building, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘building’: True} would return all building footprints in the area. tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop.	None

Returns:

Name	Type	Description
GeoDataFrame		A GeoDataFrame of OSM entities.

Source code in leafmap/osm.py

def osm_gdf_from_xml(filepath: str, polygon=None, tags: Dict = None):
    """Create a GeoDataFrame of OSM entities in an OSM-formatted XML file.

    Args:
        filepath (str): File path to file containing OSM XML data
        polygon (shapely.geometry.Polygon, optional): Optional geographic boundary to filter objects. Defaults to None.
        tags (dict): Dict of tags used for finding objects in the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one given tag. The dict keys should be OSM tags, (e.g., building, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘building’: True} would return all building footprints in the area. tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop.

    Returns:
        GeoDataFrame: A GeoDataFrame of OSM entities.
    """
    check_package("osmnx", "https://osmnx.readthedocs.io/en/stable/#installation")
    try:
        import osmnx as ox
    except ImportError:
        raise ImportError(
            "osmnx package is required. Please install it using 'pip install osmnx'"
        )

    gdf = ox.features_from_xml(filepath, polygon, tags)
    return gdf

osm_geojson_from_address(address, tags, filepath=None, dist=1000)

Download OSM entities within some distance N, S, E, W of address as a GeoJSON.

Parameters:

Name	Type	Description	Default
address	str	The address to geocode and use as the central point around which to get the geometries.	required
tags	dict	Dict of tags used for finding objects in the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one given tag. The dict keys should be OSM tags, (e.g., building, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘building’: True} would return all building footprints in the area. tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop.	required
filepath	str	File path to the output GeoJSON. Defaults to None.	None
dist	int	Distance in meters. Defaults to 1000.	1000

Returns:

Name	Type	Description
dict	Dict	A GeoJSON dictionary of OSM entities.

Source code in leafmap/osm.py

def osm_geojson_from_address(
    address: str, tags: Dict, filepath: str = None, dist: Optional[int] = 1000
) -> Dict:
    """Download OSM entities within some distance N, S, E, W of address as a GeoJSON.

    Args:
        address (str): The address to geocode and use as the central point around which to get the geometries.
        tags (dict): Dict of tags used for finding objects in the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one given tag. The dict keys should be OSM tags, (e.g., building, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘building’: True} would return all building footprints in the area. tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop.
        filepath (str, optional): File path to the output GeoJSON. Defaults to None.
        dist (int, optional): Distance in meters. Defaults to 1000.

    Returns:
        dict: A GeoJSON dictionary of OSM entities.
    """
    gdf = osm_gdf_from_address(address, tags, dist)
    if filepath is not None:
        gdf.to_file(filepath, driver="GeoJSON")
    else:
        return gdf.__geo_interface__

osm_geojson_from_bbox(north, south, east, west, tags, filepath=None)

Download OSM entities within a N, S, E, W bounding box as a GeoJSON.

Parameters:

Name	Type	Description	Default
north	float	Northern latitude of bounding box.	required
south	float	Southern latitude of bounding box.	required
east	float	Eastern longitude of bounding box.	required
west	float	Western longitude of bounding box.	required
tags	dict	Dict of tags used for finding objects in the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one given tag. The dict keys should be OSM tags, (e.g., building, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘building’: True} would return all building footprints in the area. tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop.	required
filepath	str	File path to the output GeoJSON.	None

Returns:

Name	Type	Description
dict		A GeoJSON dictionary of OSM entities.

Source code in leafmap/osm.py

def osm_geojson_from_bbox(
    north: float,
    south: float,
    east: float,
    west: float,
    tags: Dict,
    filepath: Optional[str] = None,
):
    """Download OSM entities within a N, S, E, W bounding box as a GeoJSON.

    Args:
        north (float): Northern latitude of bounding box.
        south (float): Southern latitude of bounding box.
        east (float): Eastern longitude of bounding box.
        west (float): Western longitude of bounding box.
        tags (dict): Dict of tags used for finding objects in the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one given tag. The dict keys should be OSM tags, (e.g., building, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘building’: True} would return all building footprints in the area. tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop.
        filepath (str, optional): File path to the output GeoJSON.

    Returns:
        dict: A GeoJSON dictionary of OSM entities.
    """
    gdf = osm_gdf_from_bbox(north, south, east, west, tags)
    if filepath is not None:
        gdf.to_file(filepath, driver="GeoJSON")
    else:
        return gdf.__geo_interface__

osm_geojson_from_geocode(query, filepath, which_result=None, by_osmid=False, buffer_dist=None)

Download place(s) by name or ID from the Nominatim API as a GeoJSON.

Parameters:

Name	Type	Description	Default
query	str | dict | list	Query string(s) or structured dict(s) to geocode.	required
filepath	str	File path to the output GeoJSON.	required
which_result	int	Which geocoding result to use. if None, auto-select the first (Multi)Polygon or raise an error if OSM doesn't return one. to get the top match regardless of geometry type, set which_result=1. Defaults to None.	None
by_osmid	bool	If True, handle query as an OSM ID for lookup rather than text search. Defaults to False.	False
buffer_dist	float	Distance to buffer around the place geometry, in meters. Defaults to None.	None

Returns:

Name	Type	Description
dict		A GeoJSON dictionary of OSM entities.

Source code in leafmap/osm.py

def osm_geojson_from_geocode(
    query: Union[str, Dict, List],
    filepath: str,
    which_result: Optional[int] = None,
    by_osmid: Optional[bool] = False,
    buffer_dist: Optional[float] = None,
):
    """Download place(s) by name or ID from the Nominatim API as a GeoJSON.

    Args:
        query (str | dict | list): Query string(s) or structured dict(s) to geocode.
        filepath (str): File path to the output GeoJSON.
        which_result (int, optional): Which geocoding result to use. if None, auto-select the first (Multi)Polygon or raise an error if OSM doesn't return one. to get the top match regardless of geometry type, set which_result=1. Defaults to None.
        by_osmid (bool, optional): If True, handle query as an OSM ID for lookup rather than text search. Defaults to False.
        buffer_dist (float, optional): Distance to buffer around the place geometry, in meters. Defaults to None.

    Returns:
        dict: A GeoJSON dictionary of OSM entities.
    """
    gdf = osm_gdf_from_geocode(query, which_result, by_osmid, buffer_dist)
    if filepath is not None:
        gdf.to_file(filepath, driver="GeoJSON")
    else:
        return gdf.__geo_interface__

osm_geojson_from_place(query, tags, filepath, which_result=None, buffer_dist=None)

Download OSM entities within boundaries of geocodable place(s) as a GeoJSON.

Parameters:

Name	Type	Description	Default
query	str | dict | list	Query string(s) or structured dict(s) to geocode.	required
tags	dict	Dict of tags used for finding objects in the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one given tag. The dict keys should be OSM tags, (e.g., building, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘building’: True} would return all building footprints in the area. tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop.	required
filepath	str	File path to the output shapefile.	required
which_result	int	Which geocoding result to use. if None, auto-select the first (Multi)Polygon or raise an error if OSM doesn't return one. to get the top match regardless of geometry type, set which_result=1. Defaults to None.	None
buffer_dist	float	Distance to buffer around the place geometry, in meters. Defaults to None.	None

Returns:

Name	Type	Description
dict	Dict	A GeoJSON dictionary of OSM entities.

Source code in leafmap/osm.py

def osm_geojson_from_place(
    query: Union[str, Dict, List],
    tags: Dict,
    filepath: str,
    which_result: Optional[int] = None,
    buffer_dist: Optional[float] = None,
) -> Dict:
    """Download OSM entities within boundaries of geocodable place(s) as a GeoJSON.

    Args:
        query (str | dict | list): Query string(s) or structured dict(s) to geocode.
        tags (dict): Dict of tags used for finding objects in the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one given tag. The dict keys should be OSM tags, (e.g., building, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘building’: True} would return all building footprints in the area. tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop.
        filepath (str): File path to the output shapefile.
        which_result (int, optional): Which geocoding result to use. if None, auto-select the first (Multi)Polygon or raise an error if OSM doesn't return one. to get the top match regardless of geometry type, set which_result=1. Defaults to None.
        buffer_dist (float, optional): Distance to buffer around the place geometry, in meters. Defaults to None.

    Returns:
        dict: A GeoJSON dictionary of OSM entities.
    """

    gdf = osm_gdf_from_place(query, tags, which_result, buffer_dist)
    if filepath is not None:
        gdf.to_file(filepath, driver="GeoJSON")
    else:
        return gdf.__geo_interface__

osm_geojson_from_point(center_point, tags, filepath, dist=1000)

Download OSM entities within some distance N, S, E, W of point as a GeoJSON.

Parameters:

Name	Type	Description	Default
center_point	tuple	The (lat, lng) center point around which to get the geometries.	required
tags	dict	Dict of tags used for finding objects in the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one given tag. The dict keys should be OSM tags, (e.g., building, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘building’: True} would return all building footprints in the area. tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop.	required
filepath	str	File path to the output shapefile.	required
dist	int	Distance in meters. Defaults to 1000.	1000

Returns:

Name	Type	Description
dict	Dict	A GeoJSON dictionary of OSM entities.

Source code in leafmap/osm.py

def osm_geojson_from_point(
    center_point: Tuple[float, float],
    tags: Dict,
    filepath: str,
    dist: Optional[int] = 1000,
) -> Dict:
    """Download OSM entities within some distance N, S, E, W of point as a GeoJSON.

    Args:
        center_point (tuple): The (lat, lng) center point around which to get the geometries.
        tags (dict): Dict of tags used for finding objects in the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one given tag. The dict keys should be OSM tags, (e.g., building, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘building’: True} would return all building footprints in the area. tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop.
        filepath (str): File path to the output shapefile.
        dist (int, optional): Distance in meters. Defaults to 1000.

    Returns:
        dict: A GeoJSON dictionary of OSM entities.
    """
    gdf = osm_gdf_from_point(center_point, tags, dist)
    if filepath is not None:
        gdf.to_file(filepath, driver="GeoJSON")
    else:
        return gdf.__geo_interface__

osm_geojson_from_polygon(polygon, tags, filepath=None)

Download OSM entities within boundaries of a (multi)polygon as a GeoJSON.

Parameters:

Name	Type	Description	Default
polygon	Polygon | MultiPolygon	Geographic boundaries to fetch geometries within	required
tags	dict	Dict of tags used for finding objects in the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one given tag. The dict keys should be OSM tags, (e.g., building, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘building’: True} would return all building footprints in the area. tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop.	required
filepath	str	File path to the output GeoJSON.	None

Returns:

Name	Type	Description
dict	Dict	A GeoJSON dictionary of OSM entities.

Source code in leafmap/osm.py

def osm_geojson_from_polygon(
    polygon, tags: Dict, filepath: Optional[str] = None
) -> Dict:
    """Download OSM entities within boundaries of a (multi)polygon as a GeoJSON.

    Args:
        polygon (shapely.geometry.Polygon | shapely.geometry.MultiPolygon): Geographic boundaries to fetch geometries within
        tags (dict): Dict of tags used for finding objects in the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one given tag. The dict keys should be OSM tags, (e.g., building, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘building’: True} would return all building footprints in the area. tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop.
        filepath (str, optional): File path to the output GeoJSON.

    Returns:
        dict: A GeoJSON dictionary of OSM entities.
    """
    gdf = osm_gdf_from_polygon(polygon, tags)
    if filepath is not None:
        gdf.to_file(filepath, driver="GeoJSON")
    else:
        return gdf.__geo_interface__

osm_shp_from_address(address, tags, filepath, dist=1000)

Download OSM entities within some distance N, S, E, W of address as a shapefile.

Parameters:

Name	Type	Description	Default
address	str	The address to geocode and use as the central point around which to get the geometries.	required
tags	dict	Dict of tags used for finding objects in the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one given tag. The dict keys should be OSM tags, (e.g., building, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘building’: True} would return all building footprints in the area. tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop.	required
filepath	str	File path to the output shapefile.	required
dist	int	Distance in meters. Defaults to 1000.	1000

Source code in leafmap/osm.py

def osm_shp_from_address(
    address: str, tags: Dict, filepath: str, dist: Optional[int] = 1000
):
    """Download OSM entities within some distance N, S, E, W of address as a shapefile.

    Args:
        address (str): The address to geocode and use as the central point around which to get the geometries.
        tags (dict): Dict of tags used for finding objects in the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one given tag. The dict keys should be OSM tags, (e.g., building, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘building’: True} would return all building footprints in the area. tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop.
        filepath (str): File path to the output shapefile.
        dist (int, optional): Distance in meters. Defaults to 1000.

    """
    gdf = osm_gdf_from_address(address, tags, dist)
    gdf.to_file(filepath)

osm_shp_from_bbox(north, south, east, west, tags, filepath)

Download OSM entities within a N, S, E, W bounding box as a shapefile.

Parameters:

Name	Type	Description	Default
north	float	Northern latitude of bounding box.	required
south	float	Southern latitude of bounding box.	required
east	float	Eastern longitude of bounding box.	required
west	float	Western longitude of bounding box.	required
tags	dict	Dict of tags used for finding objects in the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one given tag. The dict keys should be OSM tags, (e.g., building, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘building’: True} would return all building footprints in the area. tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop.	required
filepath	str	File path to the output shapefile.	required

Source code in leafmap/osm.py

def osm_shp_from_bbox(
    north: float, south: float, east: float, west: float, tags: Dict, filepath: str
):
    """Download OSM entities within a N, S, E, W bounding box as a shapefile.

    Args:
        north (float): Northern latitude of bounding box.
        south (float): Southern latitude of bounding box.
        east (float): Eastern longitude of bounding box.
        west (float): Western longitude of bounding box.
        tags (dict): Dict of tags used for finding objects in the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one given tag. The dict keys should be OSM tags, (e.g., building, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘building’: True} would return all building footprints in the area. tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop.
        filepath (str): File path to the output shapefile.
    """
    gdf = osm_gdf_from_bbox(north, south, east, west, tags)
    gdf.to_file(filepath)

osm_shp_from_geocode(query, filepath, which_result=None, by_osmid=False, buffer_dist=None)

Download place(s) by name or ID from the Nominatim API as a shapefile.

Parameters:

Name	Type	Description	Default
query	str | dict | list	Query string(s) or structured dict(s) to geocode.	required
filepath	str	File path to the output shapefile.	required
which_result	int	Which geocoding result to use. if None, auto-select the first (Multi)Polygon or raise an error if OSM doesn't return one. to get the top match regardless of geometry type, set which_result=1. Defaults to None.	None
by_osmid	bool	If True, handle query as an OSM ID for lookup rather than text search. Defaults to False.	False
buffer_dist	float	Distance to buffer around the place geometry, in meters. Defaults to None.	None

Source code in leafmap/osm.py

def osm_shp_from_geocode(
    query: Union[str, Dict, List],
    filepath: str,
    which_result: Optional[int] = None,
    by_osmid: Optional[bool] = False,
    buffer_dist: Optional[float] = None,
):
    """Download place(s) by name or ID from the Nominatim API as a shapefile.

    Args:
        query (str | dict | list): Query string(s) or structured dict(s) to geocode.
        filepath (str): File path to the output shapefile.
        which_result (int, optional): Which geocoding result to use. if None, auto-select the first (Multi)Polygon or raise an error if OSM doesn't return one. to get the top match regardless of geometry type, set which_result=1. Defaults to None.
        by_osmid (bool, optional): If True, handle query as an OSM ID for lookup rather than text search. Defaults to False.
        buffer_dist (float, optional): Distance to buffer around the place geometry, in meters. Defaults to None.
    """
    gdf = osm_gdf_from_geocode(query, which_result, by_osmid, buffer_dist)
    gdf.to_file(filepath)

osm_shp_from_place(query, tags, filepath, which_result=None, buffer_dist=None)

Download OSM entities within boundaries of geocodable place(s) as a shapefile.

Parameters:

Name	Type	Description	Default
query	str | dict | list	Query string(s) or structured dict(s) to geocode.	required
tags	dict	Dict of tags used for finding objects in the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one given tag. The dict keys should be OSM tags, (e.g., building, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘building’: True} would return all building footprints in the area. tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop.	required
filepath	str	File path to the output shapefile.	required
which_result	int	Which geocoding result to use. if None, auto-select the first (Multi)Polygon or raise an error if OSM doesn't return one. to get the top match regardless of geometry type, set which_result=1. Defaults to None.	None
buffer_dist	float	Distance to buffer around the place geometry, in meters. Defaults to None.	None

Source code in leafmap/osm.py

def osm_shp_from_place(
    query: Union[str, Dict, List],
    tags: Dict,
    filepath: str,
    which_result: Optional[int] = None,
    buffer_dist: Optional[float] = None,
):
    """Download OSM entities within boundaries of geocodable place(s) as a shapefile.

    Args:
        query (str | dict | list): Query string(s) or structured dict(s) to geocode.
        tags (dict): Dict of tags used for finding objects in the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one given tag. The dict keys should be OSM tags, (e.g., building, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘building’: True} would return all building footprints in the area. tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop.
        filepath (str): File path to the output shapefile.
        which_result (int, optional): Which geocoding result to use. if None, auto-select the first (Multi)Polygon or raise an error if OSM doesn't return one. to get the top match regardless of geometry type, set which_result=1. Defaults to None.
        buffer_dist (float, optional): Distance to buffer around the place geometry, in meters. Defaults to None.
    """
    gdf = osm_gdf_from_place(query, tags, which_result, buffer_dist)
    gdf.to_file(filepath)

osm_shp_from_point(center_point, tags, filepath, dist=1000)

Download OSM entities within some distance N, S, E, W of point as a shapefile.

Parameters:

Name	Type	Description	Default
center_point	tuple	The (lat, lng) center point around which to get the geometries.	required
tags	dict	Dict of tags used for finding objects in the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one given tag. The dict keys should be OSM tags, (e.g., building, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘building’: True} would return all building footprints in the area. tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop.	required
filepath	str	File path to the output shapefile.	required
dist	int	Distance in meters. Defaults to 1000.	1000

Source code in leafmap/osm.py

def osm_shp_from_point(
    center_point: Tuple[float, float],
    tags: Dict,
    filepath: str,
    dist: Optional[int] = 1000,
):
    """Download OSM entities within some distance N, S, E, W of point as a shapefile.

    Args:
        center_point (tuple): The (lat, lng) center point around which to get the geometries.
        tags (dict): Dict of tags used for finding objects in the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one given tag. The dict keys should be OSM tags, (e.g., building, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘building’: True} would return all building footprints in the area. tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop.
        filepath (str): File path to the output shapefile.
        dist (int, optional): Distance in meters. Defaults to 1000.
    """
    gdf = osm_gdf_from_point(center_point, tags, dist)
    gdf.to_file(filepath)

osm_shp_from_polygon(polygon, tags, filepath)

Download OSM entities within boundaries of a (multi)polygon as a shapefile.

Parameters:

Name	Type	Description	Default
polygon	Polygon | MultiPolygon	Geographic boundaries to fetch geometries within	required
tags	dict	Dict of tags used for finding objects in the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one given tag. The dict keys should be OSM tags, (e.g., building, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘building’: True} would return all building footprints in the area. tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop.	required
filepath	str	File path to the output shapefile.	required

Source code in leafmap/osm.py

def osm_shp_from_polygon(polygon, tags: Dict, filepath: str):
    """Download OSM entities within boundaries of a (multi)polygon as a shapefile.

    Args:
        polygon (shapely.geometry.Polygon | shapely.geometry.MultiPolygon): Geographic boundaries to fetch geometries within
        tags (dict): Dict of tags used for finding objects in the selected area. Results returned are the union, not intersection of each individual tag. Each result matches at least one given tag. The dict keys should be OSM tags, (e.g., building, landuse, highway, etc) and the dict values should be either True to retrieve all items with the given tag, or a string to get a single tag-value combination, or a list of strings to get multiple values for the given tag. For example, tags = {‘building’: True} would return all building footprints in the area. tags = {‘amenity’:True, ‘landuse’:[‘retail’,’commercial’], ‘highway’:’bus_stop’} would return all amenities, landuse=retail, landuse=commercial, and highway=bus_stop.
        filepath (str): File path to the output shapefile.
    """
    gdf = osm_gdf_from_polygon(polygon, tags)
    gdf.to_file(filepath)

osm_tags_list()

Open a browser to see all tags of OSM features.

Source code in leafmap/osm.py

def osm_tags_list():
    """Open a browser to see all tags of OSM features."""
    import webbrowser

    webbrowser.open_new_tab("https://wiki.openstreetmap.org/wiki/Map_features")