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OSMOnlineLoader

srai.loaders.OSMOnlineLoader 

OSMOnlineLoader()

Bases: OSMLoader

OSMOnlineLoader.

OSM(OpenStreetMap)[1] online loader is a loader capable of downloading objects from a given area from OSM. It filters features based on OSM tags[2] in form of key:value pairs, that are used by OSM users to give meaning to geometries.

This loader is a wrapper around the osmnx library. It uses osmnx.geometries_from_polygon to make individual queries.

References
  1. https://www.openstreetmap.org/
  2. https://wiki.openstreetmap.org/wiki/Tags
Source code in srai/loaders/osm_loaders/osm_online_loader.py 
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def __init__(self) -> None:
    """Initialize OSMOnlineLoader."""
    import_optional_dependencies(dependency_group="osm", modules=["osmnx"])

    import osmnx

    osmnx_new_api = version.parse(osmnx.__version__) >= version.parse("2.0.0")

    if osmnx_new_api:
        self._ELEMENT_TYPE_INDEX_NAME = "element"
        self._OSMID_INDEX_NAME = "id"

    else:
        self._ELEMENT_TYPE_INDEX_NAME = "element_type"
        self._OSMID_INDEX_NAME = "osmid"

    self._RESULT_INDEX_NAMES = [
        self._ELEMENT_TYPE_INDEX_NAME,
        self._OSMID_INDEX_NAME,
    ]

load 

load(
    area: Union[
        BaseGeometry, Iterable[BaseGeometry], gpd.GeoSeries, gpd.GeoDataFrame
    ],
    tags: Union[OsmTagsFilter, GroupedOsmTagsFilter],
) -> gpd.GeoDataFrame

Download OSM features with specified tags for a given area.

The loader first downloads all objects with tags. It returns a GeoDataFrame containing the geometry column and columns for tag keys.

Some key/value pairs might be missing from the resulting GeoDataFrame,

simply because there are no such objects in the given area.

PARAMETER DESCRIPTION
area

Area for which to download objects.

TYPE: Union[BaseGeometry, Iterable[BaseGeometry], GeoSeries, GeoDataFrame]

tags

A dictionary specifying which tags to download. The keys should be OSM tags (e.g. building, amenity). The values should either be True for retrieving all objects with the tag, string for retrieving a single tag-value pair or list of strings for retrieving all values specified in the list. tags={'leisure': 'park} would return parks from the area. tags={'leisure': 'park, 'amenity': True, 'shop': ['bakery', 'bicycle']} would return parks, all amenity types, bakeries and bicycle shops.

TYPE: Union[OsmTagsFilter, GroupedOsmTagsFilter]

RETURNS DESCRIPTION
GeoDataFrame

gpd.GeoDataFrame: Downloaded features as a GeoDataFrame.
Source code in srai/loaders/osm_loaders/osm_online_loader.py 
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def load(
    self,
    area: Union[BaseGeometry, Iterable[BaseGeometry], gpd.GeoSeries, gpd.GeoDataFrame],
    tags: Union[OsmTagsFilter, GroupedOsmTagsFilter],
) -> gpd.GeoDataFrame:
    """
    Download OSM features with specified tags for a given area.

    The loader first downloads all objects with `tags`. It returns a GeoDataFrame containing
    the `geometry` column and columns for tag keys.

    Note: Some key/value pairs might be missing from the resulting GeoDataFrame,
        simply because there are no such objects in the given area.

    Args:
        area (Union[BaseGeometry, Iterable[BaseGeometry], gpd.GeoSeries, gpd.GeoDataFrame]):
            Area for which to download objects.
        tags (Union[OsmTagsFilter, GroupedOsmTagsFilter]): A dictionary
            specifying which tags to download.
            The keys should be OSM tags (e.g. `building`, `amenity`).
            The values should either be `True` for retrieving all objects with the tag,
            string for retrieving a single tag-value pair
            or list of strings for retrieving all values specified in the list.
            `tags={'leisure': 'park}` would return parks from the area.
            `tags={'leisure': 'park, 'amenity': True, 'shop': ['bakery', 'bicycle']}`
            would return parks, all amenity types, bakeries and bicycle shops.

    Returns:
        gpd.GeoDataFrame: Downloaded features as a GeoDataFrame.
    """
    import osmnx as ox

    area_wgs84 = self._prepare_area_gdf(area)

    merged_tags = merge_osm_tags_filter(tags)

    _tags = self._flatten_tags(merged_tags)

    total_tags_num = len(_tags)
    total_queries = len(area_wgs84) * total_tags_num

    key_value_name_max_len = self._get_max_key_value_name_len(_tags)
    desc_max_len = key_value_name_max_len + len(self._PBAR_FORMAT.format("", ""))

    results = []

    osmnx_new_api = version.parse(ox.__version__) >= version.parse("1.5.0")
    osmnx_download_function = (
        ox.features_from_polygon if osmnx_new_api else ox.geometries_from_polygon
    )

    osmnx_new_exception_api = version.parse(ox.__version__) >= version.parse("1.6.0")
    if osmnx_new_exception_api:
        from osmnx._errors import InsufficientResponseError

        response_error = InsufficientResponseError
    else:
        from osmnx._errors import EmptyOverpassResponse

        response_error = EmptyOverpassResponse

    pbar = tqdm(
        product(area_wgs84[GEOMETRY_COLUMN], _tags), total=total_queries, disable=FORCE_TERMINAL
    )
    for polygon, (key, value) in pbar:
        pbar.set_description(self._get_pbar_desc(key, value, desc_max_len))
        with suppress(response_error):
            geometries = osmnx_download_function(polygon, {key: value})
            if not geometries.empty:
                results.append(geometries[[GEOMETRY_COLUMN, key]])

    result_gdf = self._group_gdfs(results).set_crs(WGS84_CRS)
    result_gdf = self._flatten_index(result_gdf)

    return self._parse_features_gdf_to_groups(result_gdf, tags)