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Maps

OpenMap #

Bases: BaseReader

OpenMap Reader.

Get the map Features from the overpass api(osm) for the given location/area

Parameters:

Name Type Description Default
if you not sure about the search_tag and tag_values visit https

//taginfo.openstreetmap.org/tags

 required
Source code in llama-index-integrations/readers/llama-index-readers-maps/llama_index/readers/maps/base.py 
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class OpenMap(BaseReader):
    """OpenMap Reader.

    Get the map Features from the overpass api(osm) for the given location/area


    Args:
        localarea(str) -  Area or location you are searching for
        tag_values(str) -  filter for the give area
        search_tag(str)  - Tag that you are looking for

        if you not sure about the search_tag and tag_values visit https://taginfo.openstreetmap.org/tags

        remove_keys(list) - list of keys that need to be removed from the response
                            by default  following keys will be removed ['nodes','geometry','members']

    """

    def __init__(self) -> None:
        """Initialize with parameters."""
        super().__init__()

    @staticmethod
    def _get_user() -> str:
        # choose from all lowercase letter
        letters = string.ascii_lowercase
        return "".join(random.choice(letters) for i in range(10))

    @staticmethod
    def _get_latlon(locarea: str, user_agent: str) -> tuple:
        try:
            from geopy.geocoders import Nominatim
        except ImportError:
            raise ImportError("install geopy using `pip3 install geopy`")

        geolocator = Nominatim(user_agent=user_agent)
        location = geolocator.geocode(locarea)
        return (location.latitude, location.longitude) if location else (None, None)

    def load_data(
        self,
        localarea: str,
        search_tag: Optional[str] = "amenity",
        remove_keys: Optional[List] = ["nodes", "geometry", "members"],
        tag_only: Optional[bool] = True,
        tag_values: Optional[List] = [""],
        local_area_buffer: Optional[int] = 2000,
    ) -> List[Document]:
        """
        This loader will bring you the all the node values from the open street maps for the given location.

        Args:
        localarea(str) -  Area or location you are searching for
        search_tag(str)  - Tag that you are looking for
        if you not sure about the search_tag and tag_values visit https://taginfo.openstreetmap.org/tags

        remove_keys(list) - list of keys that need to be removed from the response
                            by default it those keys will be removed ['nodes','geometry','members']

        tag_only(bool) - if True it  return the nodes which has tags if False returns all the nodes
        tag_values(str) -  filter for the give area
        local_area_buffer(int) - range that you wish to cover (Default 2000(2km))
        """
        try:
            from osmxtract import location, overpass
            from osmxtract.errors import OverpassBadRequest
        except ImportError:
            raise ImportError("install osmxtract using `pip3 install osmxtract`")

        null_list = ["", "null", "none", None]
        extra_info = {}
        local_area = localarea

        if local_area.lower().strip() in null_list:
            raise Exception("The Area should not be null")

        user = self._get_user()
        lat, lon = self._get_latlon(local_area, user)
        try:
            bounds = location.from_buffer(lat, lon, buffer_size=int(local_area_buffer))
        except TypeError:
            raise TypeError("Please give valid location name or check for spelling")

        # overpass query generation and execution
        tag_values = [str(i).lower().strip() for i in tag_values]
        query = overpass.ql_query(
            bounds, tag=search_tag.lower(), values=tag_values, timeout=500
        )

        extra_info["overpass_query"] = query
        try:
            response = overpass.request(query)

        except OverpassBadRequest:
            raise TypeError(
                f"Error while executing the Query {query} please check the Args"
            )

        res = response["elements"]

        _meta = response.copy()
        del _meta["elements"]
        extra_info["overpass_meta"] = str(_meta)
        extra_info["lat"] = lat
        extra_info["lon"] = lon
        # filtering for only the tag values
        filtered = [i for i in res if "tags" in i] if tag_only else res

        for key in remove_keys:
            [i.pop(key, None) for i in filtered]
        if filtered:
            return Document(text=str(filtered), extra_info=extra_info)
        else:
            return Document(text=str(res), extra_info=extra_info)

load_data #

load_data(localarea: str, search_tag: Optional[str] = 'amenity', remove_keys: Optional[List] = ['nodes', 'geometry', 'members'], tag_only: Optional[bool] = True, tag_values: Optional[List] = [''], local_area_buffer: Optional[int] = 2000) -> List[Document]

This loader will bring you the all the node values from the open street maps for the given location.

Args: localarea(str) - Area or location you are searching for search_tag(str) - Tag that you are looking for if you not sure about the search_tag and tag_values visit https://taginfo.openstreetmap.org/tags

remove_keys(list) - list of keys that need to be removed from the response by default it those keys will be removed ['nodes','geometry','members']

tag_only(bool) - if True it return the nodes which has tags if False returns all the nodes tag_values(str) - filter for the give area local_area_buffer(int) - range that you wish to cover (Default 2000(2km))

Source code in llama-index-integrations/readers/llama-index-readers-maps/llama_index/readers/maps/base.py 
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def load_data(
    self,
    localarea: str,
    search_tag: Optional[str] = "amenity",
    remove_keys: Optional[List] = ["nodes", "geometry", "members"],
    tag_only: Optional[bool] = True,
    tag_values: Optional[List] = [""],
    local_area_buffer: Optional[int] = 2000,
) -> List[Document]:
    """
    This loader will bring you the all the node values from the open street maps for the given location.

    Args:
    localarea(str) -  Area or location you are searching for
    search_tag(str)  - Tag that you are looking for
    if you not sure about the search_tag and tag_values visit https://taginfo.openstreetmap.org/tags

    remove_keys(list) - list of keys that need to be removed from the response
                        by default it those keys will be removed ['nodes','geometry','members']

    tag_only(bool) - if True it  return the nodes which has tags if False returns all the nodes
    tag_values(str) -  filter for the give area
    local_area_buffer(int) - range that you wish to cover (Default 2000(2km))
    """
    try:
        from osmxtract import location, overpass
        from osmxtract.errors import OverpassBadRequest
    except ImportError:
        raise ImportError("install osmxtract using `pip3 install osmxtract`")

    null_list = ["", "null", "none", None]
    extra_info = {}
    local_area = localarea

    if local_area.lower().strip() in null_list:
        raise Exception("The Area should not be null")

    user = self._get_user()
    lat, lon = self._get_latlon(local_area, user)
    try:
        bounds = location.from_buffer(lat, lon, buffer_size=int(local_area_buffer))
    except TypeError:
        raise TypeError("Please give valid location name or check for spelling")

    # overpass query generation and execution
    tag_values = [str(i).lower().strip() for i in tag_values]
    query = overpass.ql_query(
        bounds, tag=search_tag.lower(), values=tag_values, timeout=500
    )

    extra_info["overpass_query"] = query
    try:
        response = overpass.request(query)

    except OverpassBadRequest:
        raise TypeError(
            f"Error while executing the Query {query} please check the Args"
        )

    res = response["elements"]

    _meta = response.copy()
    del _meta["elements"]
    extra_info["overpass_meta"] = str(_meta)
    extra_info["lat"] = lat
    extra_info["lon"] = lon
    # filtering for only the tag values
    filtered = [i for i in res if "tags" in i] if tag_only else res

    for key in remove_keys:
        [i.pop(key, None) for i in filtered]
    if filtered:
        return Document(text=str(filtered), extra_info=extra_info)
    else:
        return Document(text=str(res), extra_info=extra_info)