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Basic functions

overturemaestro.functions

Functions.

This module contains helper functions to simplify the usage.

convert_bounding_box_to_geodataframe 

convert_bounding_box_to_geodataframe(
    theme: str,
    type: str,
    bbox: tuple[float, float, float, float],
    release: Optional[str] = None,
    *,
    pyarrow_filter: Optional[PYARROW_FILTER] = None,
    columns_to_download: Optional[list[str]] = None,
    ignore_cache: bool = False,
    working_directory: Union[str, Path] = "files",
    verbosity_mode: VERBOSITY_MODE = "transient",
    max_workers: Optional[int] = None
) -> gpd.GeoDataFrame

Get a GeoDataFrame with Overture Maps data within given bounding box.

Automatically downloads Overture Maps dataset for a given release and theme/type in a concurrent manner and returns a single GeoDataFrame as a result.

PARAMETER DESCRIPTION
theme

Theme of the dataset.

TYPE: str

type

Type of the dataset.

TYPE: str

bbox

Bounding box used to filter data. Order of values: xmin, ymin, xmax, ymax.

TYPE: tuple[float, float, float, float]

release

Release version. If not provided, will automatically load newest available release version. Defaults to None.

TYPE: Optional[str] DEFAULT: None

pyarrow_filter

Filters to apply on a pyarrow dataset. Can be pyarrow.compute.Expression or List[Tuple] or List[List[Tuple]]. Defaults to None.

TYPE: Optional[PYARROW_FILTER] DEFAULT: None

columns_to_download

List of columns to download. Automatically adds geometry column to the list. If None, will download all columns. Defaults to None.

TYPE: Optional[list[str]] DEFAULT: None

ignore_cache

Whether to ignore precalculated geoparquet files or not. Defaults to False.

TYPE: bool DEFAULT: False

working_directory

Directory where to save the downloaded *.parquet files. Defaults to "files".

TYPE: Union[str, Path] DEFAULT: 'files'

verbosity_mode

Set progress verbosity mode. Can be one of: silent, transient and verbose. Silent disables output completely. Transient tracks progress, but removes output after finished. Verbose leaves all progress outputs in the stdout. Defaults to "transient".

TYPE: Literal[silent, transient, verbose] DEFAULT: 'transient'

max_workers

Max number of multiprocessing workers used to process the dataset. Defaults to None.

TYPE: Optional[int] DEFAULT: None

RETURNS DESCRIPTION
GeoDataFrame

gpd.GeoDataFrame: GeoDataFrame with Overture Maps features.

Examples:

Get buildings in the center of London.

>>> import overturemaestro as om
>>> london_bbox = (-0.120077, 51.498164, -0.090809, 51.508849)
>>> gdf = om.convert_bounding_box_to_geodataframe(
...     release="2024-08-20.0",
...     theme="buildings",
...     type="building",
...     bbox=london_bbox,
... )
>>> gdf[['names', 'subtype']].sort_index()
                                                               names       subtype
id
08b194ad14804fff0200fea269f9879c  {'primary': 'Park Plaza London ...          None
08b194ad14812fff02006b5f7b4749e1                                None          None
08b194ad14814fff02002e44dac80f43  {'primary': 'The Barn', 'common...  agricultural
08b194ad14814fff0200c77856a66cd7                                None          None
08b194ad14814fff0200dbc14b9a6d57                                None          None
...                                                              ...           ...
08b194ad33db2fff02006a3ce00700f9  {'primary': 'citizenM hotel Lon...          None
08b194ad33db3fff02008b05d22745ed  {'primary': 'Metal Box Factory'...          None
08b194ad33db4fff0200cb2043a25c3c                                None    commercial
08b194ad33db4fff0200f2ead15d53ac                                None   residential
08b194ad33db5fff02005eaafd2ff033  {'primary': 'Cooper & Southwark...    commercial

[1863 rows x 2 columns]

Download museums in the same area from places dataset with a filter.

>>> gdf = om.convert_bounding_box_to_geodataframe(
...     release="2024-08-20.0",
...     theme="places",
...     type="place",
...     bbox=london_bbox,
...     pyarrow_filter=[[
...         (("categories", "primary"), "=", "museum"),
...         ("confidence", ">", 0.95),
...     ]],
... )
>>> gdf[["names", "confidence"]].sort_values(by='confidence', ascending=False)
                                                               names  confidence
id
08f194ad32a0d494030fdddc1b405fb1  {'primary': 'Shakespeare's Glob...    0.991993
08f194ad1499c8b1038ff3e213d81456  {'primary': 'Florence Nightinga...    0.982253
08f194ad30690a42034312e00c0254a2  {'primary': 'The Clink Prison M...    0.982253
08f194ad149044c6037575af3681766f  {'primary': 'Philip Simpson Des...    0.969941
08f194ad30695784036410e184708927  {'primary': 'Clink Street Londo...    0.965185
Source code in overturemaestro/functions.py 
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def convert_bounding_box_to_geodataframe(
    theme: str,
    type: str,
    bbox: tuple[float, float, float, float],
    release: Optional[str] = None,
    *,
    pyarrow_filter: Optional[PYARROW_FILTER] = None,
    columns_to_download: Optional[list[str]] = None,
    ignore_cache: bool = False,
    working_directory: Union[str, Path] = "files",
    verbosity_mode: VERBOSITY_MODE = "transient",
    max_workers: Optional[int] = None,
) -> gpd.GeoDataFrame:
    """
    Get a GeoDataFrame with Overture Maps data within given bounding box.

    Automatically downloads Overture Maps dataset for a given release and theme/type
    in a concurrent manner and returns a single GeoDataFrame as a result.

    Args:
        theme (str): Theme of the dataset.
        type (str): Type of the dataset.
        bbox (tuple[float, float, float, float]): Bounding box used to filter data.
            Order of values: xmin, ymin, xmax, ymax.
        release (Optional[str], optional): Release version. If not provided, will automatically load
            newest available release version. Defaults to None.
        pyarrow_filter (Optional[PYARROW_FILTER], optional): Filters to apply on a pyarrow dataset.
            Can be pyarrow.compute.Expression or List[Tuple] or List[List[Tuple]]. Defaults to None.
        columns_to_download (Optional[list[str]], optional): List of columns to download.
            Automatically adds geometry column to the list. If None, will download all columns.
            Defaults to None.
        ignore_cache (bool, optional): Whether to ignore precalculated geoparquet files or not.
            Defaults to False.
        working_directory (Union[str, Path], optional): Directory where to save
            the downloaded `*.parquet` files. Defaults to "files".
        verbosity_mode (Literal["silent", "transient", "verbose"], optional): Set progress
            verbosity mode. Can be one of: silent, transient and verbose. Silent disables
            output completely. Transient tracks progress, but removes output after finished.
            Verbose leaves all progress outputs in the stdout. Defaults to "transient".
        max_workers (Optional[int], optional): Max number of multiprocessing workers used to
            process the dataset. Defaults to None.

    Returns:
        gpd.GeoDataFrame: GeoDataFrame with Overture Maps features.

    Examples:
        Get buildings in the center of London.

        >>> import overturemaestro as om
        >>> london_bbox = (-0.120077, 51.498164, -0.090809, 51.508849)
        >>> gdf = om.convert_bounding_box_to_geodataframe(
        ...     release="2024-08-20.0",
        ...     theme="buildings",
        ...     type="building",
        ...     bbox=london_bbox,
        ... ) # doctest: +IGNORE_RESULT
        >>> gdf[['names', 'subtype']].sort_index()
                                                                       names       subtype
        id
        08b194ad14804fff0200fea269f9879c  {'primary': 'Park Plaza London ...          None
        08b194ad14812fff02006b5f7b4749e1                                None          None
        08b194ad14814fff02002e44dac80f43  {'primary': 'The Barn', 'common...  agricultural
        08b194ad14814fff0200c77856a66cd7                                None          None
        08b194ad14814fff0200dbc14b9a6d57                                None          None
        ...                                                              ...           ...
        08b194ad33db2fff02006a3ce00700f9  {'primary': 'citizenM hotel Lon...          None
        08b194ad33db3fff02008b05d22745ed  {'primary': 'Metal Box Factory'...          None
        08b194ad33db4fff0200cb2043a25c3c                                None    commercial
        08b194ad33db4fff0200f2ead15d53ac                                None   residential
        08b194ad33db5fff02005eaafd2ff033  {'primary': 'Cooper & Southwark...    commercial
        <BLANKLINE>
        [1863 rows x 2 columns]

        Download museums in the same area from places dataset with a filter.

        >>> gdf = om.convert_bounding_box_to_geodataframe(
        ...     release="2024-08-20.0",
        ...     theme="places",
        ...     type="place",
        ...     bbox=london_bbox,
        ...     pyarrow_filter=[[
        ...         (("categories", "primary"), "=", "museum"),
        ...         ("confidence", ">", 0.95),
        ...     ]],
        ... ) # doctest: +IGNORE_RESULT
        >>> gdf[["names", "confidence"]].sort_values(by='confidence', ascending=False)
                                                                       names  confidence
        id
        08f194ad32a0d494030fdddc1b405fb1  {'primary': 'Shakespeare's Glob...    0.991993
        08f194ad1499c8b1038ff3e213d81456  {'primary': 'Florence Nightinga...    0.982253
        08f194ad30690a42034312e00c0254a2  {'primary': 'The Clink Prison M...    0.982253
        08f194ad149044c6037575af3681766f  {'primary': 'Philip Simpson Des...    0.969941
        08f194ad30695784036410e184708927  {'primary': 'Clink Street Londo...    0.965185
    """
    return convert_geometry_to_geodataframe(
        theme=theme,
        type=type,
        geometry_filter=box(*bbox),
        release=release,
        pyarrow_filter=pyarrow_filter,
        columns_to_download=columns_to_download,
        ignore_cache=ignore_cache,
        working_directory=working_directory,
        verbosity_mode=verbosity_mode,
        max_workers=max_workers,
    )

convert_bounding_box_to_geodataframe_for_multiple_types 

convert_bounding_box_to_geodataframe_for_multiple_types(
    theme_type_pairs: list[tuple[str, str]],
    bbox: tuple[float, float, float, float],
    release: Optional[str] = None,
    *,
    pyarrow_filters: Optional[list[Optional[PYARROW_FILTER]]] = None,
    columns_to_download: Optional[list[Optional[list[str]]]] = None,
    ignore_cache: bool = False,
    working_directory: Union[str, Path] = "files",
    verbosity_mode: VERBOSITY_MODE = "transient",
    max_workers: Optional[int] = None
) -> list[gpd.GeoDataFrame]

Get GeoDataFrames list with Overture Maps data within given bounding box for multiple types.

Automatically downloads Overture Maps dataset for a given release and theme/type pairs in a concurrent manner and returns a list of GeoDataFrames as a result.

Order of GeoDataFrames is the same as the input theme_type_pairs list.

PARAMETER DESCRIPTION
theme_type_pairs

Pairs of themes and types of the dataset.

TYPE: list[tuple[str, str]]

bbox

Bounding box used to filter data. Order of values: xmin, ymin, xmax, ymax.

TYPE: tuple[float, float, float, float]

release

Release version. If not provided, will automatically load newest available release version. Defaults to None.

TYPE: Optional[str] DEFAULT: None

pyarrow_filters

A list of pyarrow expressions used to filter specific theme type pair. Must be the same length as the list of theme type pairs. Defaults to None.

TYPE: Optional[list[Optional[PYARROW_FILTER]]] DEFAULT: None

columns_to_download

A list of pyarrow expressions used to filter specific theme type pair. Must be the same length as the list of theme type pairs. Defaults to None.

TYPE: Optional[list[Optional[list[str]]]] DEFAULT: None

ignore_cache

Whether to ignore precalculated geoparquet files or not. Defaults to False.

TYPE: bool DEFAULT: False

working_directory

Directory where to save the downloaded *.parquet files. Defaults to "files".

TYPE: Union[str, Path] DEFAULT: 'files'

verbosity_mode

Set progress verbosity mode. Can be one of: silent, transient and verbose. Silent disables output completely. Transient tracks progress, but removes output after finished. Verbose leaves all progress outputs in the stdout. Defaults to "transient".

TYPE: Literal[silent, transient, verbose] DEFAULT: 'transient'

max_workers

Max number of multiprocessing workers used to process the dataset. Defaults to None.

TYPE: Optional[int] DEFAULT: None

RETURNS DESCRIPTION
list[GeoDataFrame]

list[gpd.GeoDataFrame]: List of GeoDataFrames with Overture Maps features.
Source code in overturemaestro/functions.py 
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def convert_bounding_box_to_geodataframe_for_multiple_types(
    theme_type_pairs: list[tuple[str, str]],
    bbox: tuple[float, float, float, float],
    release: Optional[str] = None,
    *,
    pyarrow_filters: Optional[list[Optional[PYARROW_FILTER]]] = None,
    columns_to_download: Optional[list[Optional[list[str]]]] = None,
    ignore_cache: bool = False,
    working_directory: Union[str, Path] = "files",
    verbosity_mode: VERBOSITY_MODE = "transient",
    max_workers: Optional[int] = None,
) -> list[gpd.GeoDataFrame]:
    """
    Get GeoDataFrames list with Overture Maps data within given bounding box for multiple types.

    Automatically downloads Overture Maps dataset for a given release and theme/type pairs
    in a concurrent manner and returns a list of GeoDataFrames as a result.

    Order of GeoDataFrames is the same as the input theme_type_pairs list.

    Args:
        theme_type_pairs (list[tuple[str, str]]): Pairs of themes and types of the dataset.
        bbox (tuple[float, float, float, float]): Bounding box used to filter data.
            Order of values: xmin, ymin, xmax, ymax.
        release (Optional[str], optional): Release version. If not provided, will automatically load
            newest available release version. Defaults to None.
        pyarrow_filters (Optional[list[Optional[PYARROW_FILTER]]], optional): A list of pyarrow
            expressions used to filter specific theme type pair. Must be the same length as the list
            of theme type pairs. Defaults to None.
        columns_to_download (Optional[list[Optional[list[str]]]], optional): A list of pyarrow
            expressions used to filter specific theme type pair. Must be the same length as the list
            of theme type pairs. Defaults to None.
        ignore_cache (bool, optional): Whether to ignore precalculated geoparquet files or not.
            Defaults to False.
        working_directory (Union[str, Path], optional): Directory where to save
            the downloaded `*.parquet` files. Defaults to "files".
        verbosity_mode (Literal["silent", "transient", "verbose"], optional): Set progress
            verbosity mode. Can be one of: silent, transient and verbose. Silent disables
            output completely. Transient tracks progress, but removes output after finished.
            Verbose leaves all progress outputs in the stdout. Defaults to "transient".
        max_workers (Optional[int], optional): Max number of multiprocessing workers used to
            process the dataset. Defaults to None.

    Returns:
        list[gpd.GeoDataFrame]: List of GeoDataFrames with Overture Maps features.
    """
    return convert_geometry_to_geodataframe_for_multiple_types(
        theme_type_pairs=theme_type_pairs,
        geometry_filter=box(*bbox),
        release=release,
        pyarrow_filters=pyarrow_filters,
        columns_to_download=columns_to_download,
        ignore_cache=ignore_cache,
        working_directory=working_directory,
        verbosity_mode=verbosity_mode,
        max_workers=max_workers,
    )

convert_bounding_box_to_parquet 

convert_bounding_box_to_parquet(
    theme: str,
    type: str,
    bbox: tuple[float, float, float, float],
    release: Optional[str] = None,
    *,
    pyarrow_filter: Optional[PYARROW_FILTER] = None,
    columns_to_download: Optional[list[str]] = None,
    result_file_path: Optional[Union[str, Path]] = None,
    ignore_cache: bool = False,
    working_directory: Union[str, Path] = "files",
    verbosity_mode: VERBOSITY_MODE = "transient",
    max_workers: Optional[int] = None
) -> Path

Get a GeoParquet file with Overture Maps data within given bounding box.

Automatically downloads Overture Maps dataset for a given release and theme/type in a concurrent manner and returns a single file as a result.

PARAMETER DESCRIPTION
theme

Theme of the dataset.

TYPE: str

type

Type of the dataset.

TYPE: str

bbox

Bounding box used to filter data. Order of values: xmin, ymin, xmax, ymax.

TYPE: tuple[float, float, float, float]

release

Release version. If not provided, will automatically load newest available release version. Defaults to None.

TYPE: Optional[str] DEFAULT: None

pyarrow_filter

Filters to apply on a pyarrow dataset. Can be pyarrow.compute.Expression or List[Tuple] or List[List[Tuple]]. Defaults to None.

TYPE: Optional[PYARROW_FILTER] DEFAULT: None

columns_to_download

List of columns to download. Automatically adds geometry column to the list. If None, will download all columns. Defaults to None.

TYPE: Optional[list[str]] DEFAULT: None

result_file_path

Where to save the geoparquet file. If not provided, will be generated based on hashes from filters. Defaults to None.

TYPE: Union[str, Path] DEFAULT: None

ignore_cache

Whether to ignore precalculated geoparquet files or not. Defaults to False.

TYPE: bool DEFAULT: False

working_directory

Directory where to save the downloaded *.parquet files. Defaults to "files".

TYPE: Union[str, Path] DEFAULT: 'files'

verbosity_mode

Set progress verbosity mode. Can be one of: silent, transient and verbose. Silent disables output completely. Transient tracks progress, but removes output after finished. Verbose leaves all progress outputs in the stdout. Defaults to "transient".

TYPE: Literal[silent, transient, verbose] DEFAULT: 'transient'

max_workers

Max number of multiprocessing workers used to process the dataset. Defaults to None.

TYPE: Optional[int] DEFAULT: None

RETURNS DESCRIPTION
Path

Path to the generated GeoParquet file.

TYPE: Path

Examples:

Get buildings in the center of London.

>>> import overturemaestro as om
>>> london_bbox = (-0.120077, 51.498164, -0.090809, 51.508849)
>>> gpq_path = om.convert_bounding_box_to_parquet(
...     release="2024-08-20.0",
...     theme="buildings",
...     type="building",
...     bbox=london_bbox,
... )
>>> gpq_path.as_posix()
'files/2024-08-20.0/theme=buildings/type=building/7ed11f0d_nofilter.parquet'

Inspect the content

>>> import geopandas as gpd
>>> gdf = gpd.read_parquet(gpq_path)
>>> len(gdf)
1863
>>> list(gdf.columns)
['id', 'geometry', 'bbox', 'version', 'sources', 'subtype', 'class', 'names', 'level',
'has_parts', 'height', 'is_underground', 'num_floors', 'num_floors_underground',
'min_height', 'min_floor', 'facade_color', 'facade_material', 'roof_material', 'roof_shape',
'roof_direction', 'roof_orientation', 'roof_color', 'roof_height', 'theme', 'type']

Download museums in the same area from places dataset with a filter.

>>> gpq_path = om.convert_bounding_box_to_parquet(
...     release="2024-08-20.0",
...     theme="places",
...     type="place",
...     bbox=london_bbox,
...     pyarrow_filter=[[
...         (("categories", "primary"), "=", "museum"),
...         ("confidence", ">", 0.95),
...     ]],
... )
>>> gdf = gpd.read_parquet(gpq_path)
>>> len(gdf)
5
>>> gdf[["id", "names", "confidence"]]
                                 id                               names  confidence
0  08f194ad1499c8b1038ff3e213d81456  {'primary': 'Florence Nightinga...    0.982253
1  08f194ad149044c6037575af3681766f  {'primary': 'Philip Simpson Des...    0.969941
2  08f194ad32a0d494030fdddc1b405fb1  {'primary': 'Shakespeare's Glob...    0.991993
3  08f194ad30695784036410e184708927  {'primary': 'Clink Street Londo...    0.965185
4  08f194ad30690a42034312e00c0254a2  {'primary': 'The Clink Prison M...    0.982253
Source code in overturemaestro/functions.py 
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def convert_bounding_box_to_parquet(
    theme: str,
    type: str,
    bbox: tuple[float, float, float, float],
    release: Optional[str] = None,
    *,
    pyarrow_filter: Optional[PYARROW_FILTER] = None,
    columns_to_download: Optional[list[str]] = None,
    result_file_path: Optional[Union[str, Path]] = None,
    ignore_cache: bool = False,
    working_directory: Union[str, Path] = "files",
    verbosity_mode: VERBOSITY_MODE = "transient",
    max_workers: Optional[int] = None,
) -> Path:
    """
    Get a GeoParquet file with Overture Maps data within given bounding box.

    Automatically downloads Overture Maps dataset for a given release and theme/type
    in a concurrent manner and returns a single file as a result.

    Args:
        theme (str): Theme of the dataset.
        type (str): Type of the dataset.
        bbox (tuple[float, float, float, float]): Bounding box used to filter data.
            Order of values: xmin, ymin, xmax, ymax.
        release (Optional[str], optional): Release version. If not provided, will automatically load
            newest available release version. Defaults to None.
        pyarrow_filter (Optional[PYARROW_FILTER], optional): Filters to apply on a pyarrow dataset.
            Can be pyarrow.compute.Expression or List[Tuple] or List[List[Tuple]]. Defaults to None.
        columns_to_download (Optional[list[str]], optional): List of columns to download.
            Automatically adds geometry column to the list. If None, will download all columns.
            Defaults to None.
        result_file_path (Union[str, Path], optional): Where to save
            the geoparquet file. If not provided, will be generated based on hashes
            from filters. Defaults to None.
        ignore_cache (bool, optional): Whether to ignore precalculated geoparquet files or not.
            Defaults to False.
        working_directory (Union[str, Path], optional): Directory where to save
            the downloaded `*.parquet` files. Defaults to "files".
        verbosity_mode (Literal["silent", "transient", "verbose"], optional): Set progress
            verbosity mode. Can be one of: silent, transient and verbose. Silent disables
            output completely. Transient tracks progress, but removes output after finished.
            Verbose leaves all progress outputs in the stdout. Defaults to "transient".
        max_workers (Optional[int], optional): Max number of multiprocessing workers used to
            process the dataset. Defaults to None.

    Returns:
        Path: Path to the generated GeoParquet file.

    Examples:
        Get buildings in the center of London.

        >>> import overturemaestro as om
        >>> london_bbox = (-0.120077, 51.498164, -0.090809, 51.508849)
        >>> gpq_path = om.convert_bounding_box_to_parquet(
        ...     release="2024-08-20.0",
        ...     theme="buildings",
        ...     type="building",
        ...     bbox=london_bbox,
        ... ) # doctest: +IGNORE_RESULT
        >>> gpq_path.as_posix()
        'files/2024-08-20.0/theme=buildings/type=building/7ed11f0d_nofilter.parquet'

        Inspect the content
        >>> import geopandas as gpd
        >>> gdf = gpd.read_parquet(gpq_path)
        >>> len(gdf)
        1863
        >>> list(gdf.columns) # doctest: +IGNORE_RESULT
        ['id', 'geometry', 'bbox', 'version', 'sources', 'subtype', 'class', 'names', 'level',
        'has_parts', 'height', 'is_underground', 'num_floors', 'num_floors_underground',
        'min_height', 'min_floor', 'facade_color', 'facade_material', 'roof_material', 'roof_shape',
        'roof_direction', 'roof_orientation', 'roof_color', 'roof_height', 'theme', 'type']

        Download museums in the same area from places dataset with a filter.

        >>> gpq_path = om.convert_bounding_box_to_parquet(
        ...     release="2024-08-20.0",
        ...     theme="places",
        ...     type="place",
        ...     bbox=london_bbox,
        ...     pyarrow_filter=[[
        ...         (("categories", "primary"), "=", "museum"),
        ...         ("confidence", ">", 0.95),
        ...     ]],
        ... ) # doctest: +IGNORE_RESULT
        >>> gdf = gpd.read_parquet(gpq_path)
        >>> len(gdf)
        5
        >>> gdf[["id", "names", "confidence"]] # doctest: +IGNORE_RESULT
                                         id                               names  confidence
        0  08f194ad1499c8b1038ff3e213d81456  {'primary': 'Florence Nightinga...    0.982253
        1  08f194ad149044c6037575af3681766f  {'primary': 'Philip Simpson Des...    0.969941
        2  08f194ad32a0d494030fdddc1b405fb1  {'primary': 'Shakespeare's Glob...    0.991993
        3  08f194ad30695784036410e184708927  {'primary': 'Clink Street Londo...    0.965185
        4  08f194ad30690a42034312e00c0254a2  {'primary': 'The Clink Prison M...    0.982253
    """
    return convert_geometry_to_parquet(
        theme=theme,
        type=type,
        geometry_filter=box(*bbox),
        release=release,
        pyarrow_filter=pyarrow_filter,
        columns_to_download=columns_to_download,
        result_file_path=result_file_path,
        ignore_cache=ignore_cache,
        working_directory=working_directory,
        verbosity_mode=verbosity_mode,
        max_workers=max_workers,
    )

convert_bounding_box_to_parquet_for_multiple_types 

convert_bounding_box_to_parquet_for_multiple_types(
    theme_type_pairs: list[tuple[str, str]],
    bbox: tuple[float, float, float, float],
    release: Optional[str] = None,
    *,
    pyarrow_filters: Optional[list[Optional[PYARROW_FILTER]]] = None,
    columns_to_download: Optional[list[Optional[list[str]]]] = None,
    ignore_cache: bool = False,
    working_directory: Union[str, Path] = "files",
    verbosity_mode: VERBOSITY_MODE = "transient",
    max_workers: Optional[int] = None
) -> list[Path]

Get GeoParquet files with Overture Maps data within given bounding box for multiple types.

Automatically downloads Overture Maps dataset for a given release and theme/type pairs in a concurrent manner and returns a list of files as a result.

Order of paths is the same as the input theme_type_pairs list.

PARAMETER DESCRIPTION
theme_type_pairs

Pairs of themes and types of the dataset.

TYPE: list[tuple[str, str]]

bbox

Bounding box used to filter data. Order of values: xmin, ymin, xmax, ymax.

TYPE: tuple[float, float, float, float]

release

Release version. If not provided, will automatically load newest available release version. Defaults to None.

TYPE: Optional[str] DEFAULT: None

pyarrow_filters

A list of pyarrow expressions used to filter specific theme type pair. Must be the same length as the list of theme type pairs. Defaults to None.

TYPE: Optional[list[Optional[PYARROW_FILTER]]] DEFAULT: None

columns_to_download

A list of pyarrow expressions used to filter specific theme type pair. Must be the same length as the list of theme type pairs. Defaults to None.

TYPE: Optional[list[Optional[list[str]]]] DEFAULT: None

ignore_cache

Whether to ignore precalculated geoparquet files or not. Defaults to False.

TYPE: bool DEFAULT: False

working_directory

Directory where to save the downloaded *.parquet files. Defaults to "files".

TYPE: Union[str, Path] DEFAULT: 'files'

verbosity_mode

Set progress verbosity mode. Can be one of: silent, transient and verbose. Silent disables output completely. Transient tracks progress, but removes output after finished. Verbose leaves all progress outputs in the stdout. Defaults to "transient".

TYPE: Literal[silent, transient, verbose] DEFAULT: 'transient'

max_workers

Max number of multiprocessing workers used to process the dataset. Defaults to None.

TYPE: Optional[int] DEFAULT: None

RETURNS DESCRIPTION
list[Path]

list[Path]: List of paths to the generated GeoParquet files.
Source code in overturemaestro/functions.py 
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def convert_bounding_box_to_parquet_for_multiple_types(
    theme_type_pairs: list[tuple[str, str]],
    bbox: tuple[float, float, float, float],
    release: Optional[str] = None,
    *,
    pyarrow_filters: Optional[list[Optional[PYARROW_FILTER]]] = None,
    columns_to_download: Optional[list[Optional[list[str]]]] = None,
    ignore_cache: bool = False,
    working_directory: Union[str, Path] = "files",
    verbosity_mode: VERBOSITY_MODE = "transient",
    max_workers: Optional[int] = None,
) -> list[Path]:
    """
    Get GeoParquet files with Overture Maps data within given bounding box for multiple types.

    Automatically downloads Overture Maps dataset for a given release and theme/type pairs
    in a concurrent manner and returns a list of files as a result.

    Order of paths is the same as the input theme_type_pairs list.

    Args:
        theme_type_pairs (list[tuple[str, str]]): Pairs of themes and types of the dataset.
        bbox (tuple[float, float, float, float]): Bounding box used to filter data.
            Order of values: xmin, ymin, xmax, ymax.
        release (Optional[str], optional): Release version. If not provided, will automatically load
            newest available release version. Defaults to None.
        pyarrow_filters (Optional[list[Optional[PYARROW_FILTER]]], optional): A list of pyarrow
            expressions used to filter specific theme type pair. Must be the same length as the list
            of theme type pairs. Defaults to None.
        columns_to_download (Optional[list[Optional[list[str]]]], optional): A list of pyarrow
            expressions used to filter specific theme type pair. Must be the same length as the list
            of theme type pairs. Defaults to None.
        ignore_cache (bool, optional): Whether to ignore precalculated geoparquet files or not.
            Defaults to False.
        working_directory (Union[str, Path], optional): Directory where to save
            the downloaded `*.parquet` files. Defaults to "files".
        verbosity_mode (Literal["silent", "transient", "verbose"], optional): Set progress
            verbosity mode. Can be one of: silent, transient and verbose. Silent disables
            output completely. Transient tracks progress, but removes output after finished.
            Verbose leaves all progress outputs in the stdout. Defaults to "transient".
        max_workers (Optional[int], optional): Max number of multiprocessing workers used to
            process the dataset. Defaults to None.

    Returns:
        list[Path]: List of paths to the generated GeoParquet files.
    """
    return convert_geometry_to_parquet_for_multiple_types(
        theme_type_pairs=theme_type_pairs,
        geometry_filter=box(*bbox),
        release=release,
        pyarrow_filters=pyarrow_filters,
        columns_to_download=columns_to_download,
        ignore_cache=ignore_cache,
        working_directory=working_directory,
        verbosity_mode=verbosity_mode,
        max_workers=max_workers,
    )

convert_geometry_to_geodataframe 

convert_geometry_to_geodataframe(
    theme: str,
    type: str,
    geometry_filter: BaseGeometry,
    release: Optional[str] = None,
    *,
    pyarrow_filter: Optional[PYARROW_FILTER] = None,
    columns_to_download: Optional[list[str]] = None,
    ignore_cache: bool = False,
    working_directory: Union[str, Path] = "files",
    verbosity_mode: VERBOSITY_MODE = "transient",
    max_workers: Optional[int] = None
) -> gpd.GeoDataFrame

Get a GeoDataFrame with Overture Maps data within given geometry.

Automatically downloads Overture Maps dataset for a given release and theme/type in a concurrent manner and returns a single GeoDataFrame as a result.

PARAMETER DESCRIPTION
theme

Theme of the dataset.

TYPE: str

type

Type of the dataset.

TYPE: str

geometry_filter

Geometry used to filter data.

TYPE: BaseGeometry

release

Release version. If not provided, will automatically load newest available release version. Defaults to None.

TYPE: Optional[str] DEFAULT: None

pyarrow_filter

Filters to apply on a pyarrow dataset. Can be pyarrow.compute.Expression or List[Tuple] or List[List[Tuple]]. Defaults to None.

TYPE: Optional[PYARROW_FILTER] DEFAULT: None

columns_to_download

List of columns to download. Automatically adds geometry column to the list. If None, will download all columns. Defaults to None.

TYPE: Optional[list[str]] DEFAULT: None

ignore_cache

Whether to ignore precalculated geoparquet files or not. Defaults to False.

TYPE: bool DEFAULT: False

working_directory

Directory where to save the downloaded *.parquet files. Defaults to "files".

TYPE: Union[str, Path] DEFAULT: 'files'

verbosity_mode

Set progress verbosity mode. Can be one of: silent, transient and verbose. Silent disables output completely. Transient tracks progress, but removes output after finished. Verbose leaves all progress outputs in the stdout. Defaults to "transient".

TYPE: Literal[silent, transient, verbose] DEFAULT: 'transient'

max_workers

Max number of multiprocessing workers used to process the dataset. Defaults to None.

TYPE: Optional[int] DEFAULT: None

RETURNS DESCRIPTION
GeoDataFrame

gpd.GeoDataFrame: GeoDataFrame with Overture Maps features.

Examples:

Get buildings in the center of London.

>>> import overturemaestro as om
>>> from shapely import box
>>> london_bbox = box(-0.120077, 51.498164, -0.090809, 51.508849)
>>> gdf = om.convert_geometry_to_geodataframe(
...     release="2024-08-20.0",
...     theme="buildings",
...     type="building",
...     geometry_filter=london_bbox,
... )
>>> gdf[['names', 'subtype']].sort_index()
                                                               names       subtype
id
08b194ad14804fff0200fea269f9879c  {'primary': 'Park Plaza London ...          None
08b194ad14812fff02006b5f7b4749e1                                None          None
08b194ad14814fff02002e44dac80f43  {'primary': 'The Barn', 'common...  agricultural
08b194ad14814fff0200c77856a66cd7                                None          None
08b194ad14814fff0200dbc14b9a6d57                                None          None
...                                                              ...           ...
08b194ad33db2fff02006a3ce00700f9  {'primary': 'citizenM hotel Lon...          None
08b194ad33db3fff02008b05d22745ed  {'primary': 'Metal Box Factory'...          None
08b194ad33db4fff0200cb2043a25c3c                                None    commercial
08b194ad33db4fff0200f2ead15d53ac                                None   residential
08b194ad33db5fff02005eaafd2ff033  {'primary': 'Cooper & Southwark...    commercial

[1863 rows x 2 columns]

Download museums in the same area from places dataset with a filter.

>>> gdf = om.convert_geometry_to_geodataframe(
...     release="2024-08-20.0",
...     theme="places",
...     type="place",
...     geometry_filter=london_bbox,
...     pyarrow_filter=[[
...         (("categories", "primary"), "=", "museum"),
...         ("confidence", ">", 0.95),
...     ]],
... )
>>> gdf[["names", "confidence"]].sort_values(by='confidence', ascending=False)
                                                               names  confidence
id
08f194ad32a0d494030fdddc1b405fb1  {'primary': 'Shakespeare's Glob...    0.991993
08f194ad1499c8b1038ff3e213d81456  {'primary': 'Florence Nightinga...    0.982253
08f194ad30690a42034312e00c0254a2  {'primary': 'The Clink Prison M...    0.982253
08f194ad149044c6037575af3681766f  {'primary': 'Philip Simpson Des...    0.969941
08f194ad30695784036410e184708927  {'primary': 'Clink Street Londo...    0.965185
Source code in overturemaestro/functions.py 
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def convert_geometry_to_geodataframe(
    theme: str,
    type: str,
    geometry_filter: BaseGeometry,
    release: Optional[str] = None,
    *,
    pyarrow_filter: Optional[PYARROW_FILTER] = None,
    columns_to_download: Optional[list[str]] = None,
    ignore_cache: bool = False,
    working_directory: Union[str, Path] = "files",
    verbosity_mode: VERBOSITY_MODE = "transient",
    max_workers: Optional[int] = None,
) -> gpd.GeoDataFrame:
    """
    Get a GeoDataFrame with Overture Maps data within given geometry.

    Automatically downloads Overture Maps dataset for a given release and theme/type
    in a concurrent manner and returns a single GeoDataFrame as a result.

    Args:
        theme (str): Theme of the dataset.
        type (str): Type of the dataset.
        geometry_filter (BaseGeometry): Geometry used to filter data.
        release (Optional[str], optional): Release version. If not provided, will automatically load
            newest available release version. Defaults to None.
        pyarrow_filter (Optional[PYARROW_FILTER], optional): Filters to apply on a pyarrow dataset.
            Can be pyarrow.compute.Expression or List[Tuple] or List[List[Tuple]]. Defaults to None.
        columns_to_download (Optional[list[str]], optional): List of columns to download.
            Automatically adds geometry column to the list. If None, will download all columns.
            Defaults to None.
        ignore_cache (bool, optional): Whether to ignore precalculated geoparquet files or not.
            Defaults to False.
        working_directory (Union[str, Path], optional): Directory where to save
            the downloaded `*.parquet` files. Defaults to "files".
        verbosity_mode (Literal["silent", "transient", "verbose"], optional): Set progress
            verbosity mode. Can be one of: silent, transient and verbose. Silent disables
            output completely. Transient tracks progress, but removes output after finished.
            Verbose leaves all progress outputs in the stdout. Defaults to "transient".
        max_workers (Optional[int], optional): Max number of multiprocessing workers used to
            process the dataset. Defaults to None.

    Returns:
        gpd.GeoDataFrame: GeoDataFrame with Overture Maps features.

    Examples:
        Get buildings in the center of London.

        >>> import overturemaestro as om
        >>> from shapely import box
        >>> london_bbox = box(-0.120077, 51.498164, -0.090809, 51.508849)
        >>> gdf = om.convert_geometry_to_geodataframe(
        ...     release="2024-08-20.0",
        ...     theme="buildings",
        ...     type="building",
        ...     geometry_filter=london_bbox,
        ... ) # doctest: +IGNORE_RESULT
        >>> gdf[['names', 'subtype']].sort_index()
                                                                       names       subtype
        id
        08b194ad14804fff0200fea269f9879c  {'primary': 'Park Plaza London ...          None
        08b194ad14812fff02006b5f7b4749e1                                None          None
        08b194ad14814fff02002e44dac80f43  {'primary': 'The Barn', 'common...  agricultural
        08b194ad14814fff0200c77856a66cd7                                None          None
        08b194ad14814fff0200dbc14b9a6d57                                None          None
        ...                                                              ...           ...
        08b194ad33db2fff02006a3ce00700f9  {'primary': 'citizenM hotel Lon...          None
        08b194ad33db3fff02008b05d22745ed  {'primary': 'Metal Box Factory'...          None
        08b194ad33db4fff0200cb2043a25c3c                                None    commercial
        08b194ad33db4fff0200f2ead15d53ac                                None   residential
        08b194ad33db5fff02005eaafd2ff033  {'primary': 'Cooper & Southwark...    commercial
        <BLANKLINE>
        [1863 rows x 2 columns]

        Download museums in the same area from places dataset with a filter.

        >>> gdf = om.convert_geometry_to_geodataframe(
        ...     release="2024-08-20.0",
        ...     theme="places",
        ...     type="place",
        ...     geometry_filter=london_bbox,
        ...     pyarrow_filter=[[
        ...         (("categories", "primary"), "=", "museum"),
        ...         ("confidence", ">", 0.95),
        ...     ]],
        ... ) # doctest: +IGNORE_RESULT
        >>> gdf[["names", "confidence"]].sort_values(by='confidence', ascending=False)
                                                                       names  confidence
        id
        08f194ad32a0d494030fdddc1b405fb1  {'primary': 'Shakespeare's Glob...    0.991993
        08f194ad1499c8b1038ff3e213d81456  {'primary': 'Florence Nightinga...    0.982253
        08f194ad30690a42034312e00c0254a2  {'primary': 'The Clink Prison M...    0.982253
        08f194ad149044c6037575af3681766f  {'primary': 'Philip Simpson Des...    0.969941
        08f194ad30695784036410e184708927  {'primary': 'Clink Street Londo...    0.965185
    """
    parsed_geoparquet_file = download_data(
        theme=theme,
        type=type,
        geometry_filter=geometry_filter,
        release=release,
        pyarrow_filter=pyarrow_filter,
        columns_to_download=columns_to_download,
        ignore_cache=ignore_cache,
        working_directory=working_directory,
        verbosity_mode=verbosity_mode,
        max_workers=max_workers,
    )
    return geodataframe_from_parquet(parsed_geoparquet_file)

convert_geometry_to_geodataframe_for_multiple_types 

convert_geometry_to_geodataframe_for_multiple_types(
    theme_type_pairs: list[tuple[str, str]],
    geometry_filter: BaseGeometry,
    release: Optional[str] = None,
    *,
    pyarrow_filters: Optional[list[Optional[PYARROW_FILTER]]] = None,
    columns_to_download: Optional[list[Optional[list[str]]]] = None,
    ignore_cache: bool = False,
    working_directory: Union[str, Path] = "files",
    verbosity_mode: VERBOSITY_MODE = "transient",
    max_workers: Optional[int] = None
) -> list[gpd.GeoDataFrame]

Get GeoDataFrames list with Overture Maps data within given geometry for multiple types.

Automatically downloads Overture Maps dataset for a given release and theme/type pairs in a concurrent manner and returns a list of GeoDataFrames as a result.

Order of GeoDataFrames is the same as the input theme_type_pairs list.

PARAMETER DESCRIPTION
theme_type_pairs

Pairs of themes and types of the dataset.

TYPE: list[tuple[str, str]]

geometry_filter

Geometry used to filter data.

TYPE: BaseGeometry

release

Release version. If not provided, will automatically load newest available release version. Defaults to None.

TYPE: Optional[str] DEFAULT: None

pyarrow_filters

A list of pyarrow expressions used to filter specific theme type pair. Must be the same length as the list of theme type pairs. Defaults to None.

TYPE: Optional[list[Optional[PYARROW_FILTER]]] DEFAULT: None

columns_to_download

A list of pyarrow expressions used to filter specific theme type pair. Must be the same length as the list of theme type pairs. Defaults to None.

TYPE: Optional[list[Optional[list[str]]]] DEFAULT: None

ignore_cache

Whether to ignore precalculated geoparquet files or not. Defaults to False.

TYPE: bool DEFAULT: False

working_directory

Directory where to save the downloaded *.parquet files. Defaults to "files".

TYPE: Union[str, Path] DEFAULT: 'files'

verbosity_mode

Set progress verbosity mode. Can be one of: silent, transient and verbose. Silent disables output completely. Transient tracks progress, but removes output after finished. Verbose leaves all progress outputs in the stdout. Defaults to "transient".

TYPE: Literal[silent, transient, verbose] DEFAULT: 'transient'

max_workers

Max number of multiprocessing workers used to process the dataset. Defaults to None.

TYPE: Optional[int] DEFAULT: None

RETURNS DESCRIPTION
list[GeoDataFrame]

list[gpd.GeoDataFrame]: List of GeoDataFrames with Overture Maps features.
Source code in overturemaestro/functions.py 
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def convert_geometry_to_geodataframe_for_multiple_types(
    theme_type_pairs: list[tuple[str, str]],
    geometry_filter: BaseGeometry,
    release: Optional[str] = None,
    *,
    pyarrow_filters: Optional[list[Optional[PYARROW_FILTER]]] = None,
    columns_to_download: Optional[list[Optional[list[str]]]] = None,
    ignore_cache: bool = False,
    working_directory: Union[str, Path] = "files",
    verbosity_mode: VERBOSITY_MODE = "transient",
    max_workers: Optional[int] = None,
) -> list[gpd.GeoDataFrame]:
    """
    Get GeoDataFrames list with Overture Maps data within given geometry for multiple types.

    Automatically downloads Overture Maps dataset for a given release and theme/type pairs
    in a concurrent manner and returns a list of GeoDataFrames as a result.

    Order of GeoDataFrames is the same as the input theme_type_pairs list.

    Args:
        theme_type_pairs (list[tuple[str, str]]): Pairs of themes and types of the dataset.
        geometry_filter (BaseGeometry): Geometry used to filter data.
        release (Optional[str], optional): Release version. If not provided, will automatically load
            newest available release version. Defaults to None.
        pyarrow_filters (Optional[list[Optional[PYARROW_FILTER]]], optional): A list of pyarrow
            expressions used to filter specific theme type pair. Must be the same length as the list
            of theme type pairs. Defaults to None.
        columns_to_download (Optional[list[Optional[list[str]]]], optional): A list of pyarrow
            expressions used to filter specific theme type pair. Must be the same length as the list
            of theme type pairs. Defaults to None.
        ignore_cache (bool, optional): Whether to ignore precalculated geoparquet files or not.
            Defaults to False.
        working_directory (Union[str, Path], optional): Directory where to save
            the downloaded `*.parquet` files. Defaults to "files".
        verbosity_mode (Literal["silent", "transient", "verbose"], optional): Set progress
            verbosity mode. Can be one of: silent, transient and verbose. Silent disables
            output completely. Transient tracks progress, but removes output after finished.
            Verbose leaves all progress outputs in the stdout. Defaults to "transient".
        max_workers (Optional[int], optional): Max number of multiprocessing workers used to
            process the dataset. Defaults to None.

    Returns:
        list[gpd.GeoDataFrame]: List of GeoDataFrames with Overture Maps features.
    """
    parsed_geoparquet_files = download_data_for_multiple_types(
        theme_type_pairs=theme_type_pairs,
        geometry_filter=geometry_filter,
        release=release,
        pyarrow_filters=pyarrow_filters,
        columns_to_download=columns_to_download,
        ignore_cache=ignore_cache,
        working_directory=working_directory,
        verbosity_mode=verbosity_mode,
        max_workers=max_workers,
    )
    return [
        geodataframe_from_parquet(parsed_geoparquet_file)
        for parsed_geoparquet_file in parsed_geoparquet_files
    ]

convert_geometry_to_parquet 

convert_geometry_to_parquet(
    theme: str,
    type: str,
    geometry_filter: BaseGeometry,
    release: Optional[str] = None,
    *,
    pyarrow_filter: Optional[PYARROW_FILTER] = None,
    columns_to_download: Optional[list[str]] = None,
    result_file_path: Optional[Union[str, Path]] = None,
    ignore_cache: bool = False,
    working_directory: Union[str, Path] = "files",
    verbosity_mode: VERBOSITY_MODE = "transient",
    max_workers: Optional[int] = None
) -> Path

Get a GeoParquet file with Overture Maps data within given geometry.

Automatically downloads Overture Maps dataset for a given release and theme/type in a concurrent manner and returns a single file as a result.

PARAMETER DESCRIPTION
theme

Theme of the dataset.

TYPE: str

type

Type of the dataset.

TYPE: str

geometry_filter

Geometry used to filter data.

TYPE: BaseGeometry

release

Release version. If not provided, will automatically load newest available release version. Defaults to None.

TYPE: Optional[str] DEFAULT: None

pyarrow_filter

Filters to apply on a pyarrow dataset. Can be pyarrow.compute.Expression or List[Tuple] or List[List[Tuple]]. Defaults to None.

TYPE: Optional[PYARROW_FILTER] DEFAULT: None

columns_to_download

List of columns to download. Automatically adds geometry column to the list. If None, will download all columns. Defaults to None.

TYPE: Optional[list[str]] DEFAULT: None

result_file_path

Where to save the geoparquet file. If not provided, will be generated based on hashes from filters. Defaults to None.

TYPE: Union[str, Path] DEFAULT: None

ignore_cache

Whether to ignore precalculated geoparquet files or not. Defaults to False.

TYPE: bool DEFAULT: False

working_directory

Directory where to save the downloaded *.parquet files. Defaults to "files".

TYPE: Union[str, Path] DEFAULT: 'files'

verbosity_mode

Set progress verbosity mode. Can be one of: silent, transient and verbose. Silent disables output completely. Transient tracks progress, but removes output after finished. Verbose leaves all progress outputs in the stdout. Defaults to "transient".

TYPE: Literal[silent, transient, verbose] DEFAULT: 'transient'

max_workers

Max number of multiprocessing workers used to process the dataset. Defaults to None.

TYPE: Optional[int] DEFAULT: None

RETURNS DESCRIPTION
Path

Path to the generated GeoParquet file.

TYPE: Path

Examples:

Get buildings in the center of London.

>>> import overturemaestro as om
>>> from shapely import box
>>> london_bbox = box(-0.120077, 51.498164, -0.090809, 51.508849)
>>> gpq_path = om.convert_geometry_to_parquet(
...     release="2024-08-20.0",
...     theme="buildings",
...     type="building",
...     geometry_filter=london_bbox,
... )
>>> gpq_path.as_posix()
'files/2024-08-20.0/theme=buildings/type=building/7ed11f0d_nofilter.parquet'

Inspect the content

>>> import geopandas as gpd
>>> gdf = gpd.read_parquet(gpq_path)
>>> len(gdf)
1863
>>> list(gdf.columns)
['id', 'geometry', 'bbox', 'version', 'sources', 'subtype', 'class', 'names', 'level',
'has_parts', 'height', 'is_underground', 'num_floors', 'num_floors_underground',
'min_height', 'min_floor', 'facade_color', 'facade_material', 'roof_material', 'roof_shape',
'roof_direction', 'roof_orientation', 'roof_color', 'roof_height', 'theme', 'type']

Download museums in the same area from places dataset with a filter.

>>> gpq_path = om.convert_geometry_to_parquet(
...     release="2024-08-20.0",
...     theme="places",
...     type="place",
...     geometry_filter=london_bbox,
...     pyarrow_filter=[[
...         (("categories", "primary"), "=", "museum"),
...         ("confidence", ">", 0.95),
...     ]],
... )
>>> gdf = gpd.read_parquet(gpq_path)
>>> len(gdf)
5
>>> gdf[["id", "names", "confidence"]]
                                 id                               names  confidence
0  08f194ad1499c8b1038ff3e213d81456  {'primary': 'Florence Nightinga...    0.982253
1  08f194ad149044c6037575af3681766f  {'primary': 'Philip Simpson Des...    0.969941
2  08f194ad32a0d494030fdddc1b405fb1  {'primary': 'Shakespeare's Glob...    0.991993
3  08f194ad30695784036410e184708927  {'primary': 'Clink Street Londo...    0.965185
4  08f194ad30690a42034312e00c0254a2  {'primary': 'The Clink Prison M...    0.982253
Source code in overturemaestro/functions.py 
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def convert_geometry_to_parquet(
    theme: str,
    type: str,
    geometry_filter: BaseGeometry,
    release: Optional[str] = None,
    *,
    pyarrow_filter: Optional[PYARROW_FILTER] = None,
    columns_to_download: Optional[list[str]] = None,
    result_file_path: Optional[Union[str, Path]] = None,
    ignore_cache: bool = False,
    working_directory: Union[str, Path] = "files",
    verbosity_mode: VERBOSITY_MODE = "transient",
    max_workers: Optional[int] = None,
) -> Path:
    """
    Get a GeoParquet file with Overture Maps data within given geometry.

    Automatically downloads Overture Maps dataset for a given release and theme/type
    in a concurrent manner and returns a single file as a result.

    Args:
        theme (str): Theme of the dataset.
        type (str): Type of the dataset.
        geometry_filter (BaseGeometry): Geometry used to filter data.
        release (Optional[str], optional): Release version. If not provided, will automatically load
            newest available release version. Defaults to None.
        pyarrow_filter (Optional[PYARROW_FILTER], optional): Filters to apply on a pyarrow dataset.
            Can be pyarrow.compute.Expression or List[Tuple] or List[List[Tuple]]. Defaults to None.
        columns_to_download (Optional[list[str]], optional): List of columns to download.
            Automatically adds geometry column to the list. If None, will download all columns.
            Defaults to None.
        result_file_path (Union[str, Path], optional): Where to save
            the geoparquet file. If not provided, will be generated based on hashes
            from filters. Defaults to None.
        ignore_cache (bool, optional): Whether to ignore precalculated geoparquet files or not.
            Defaults to False.
        working_directory (Union[str, Path], optional): Directory where to save
            the downloaded `*.parquet` files. Defaults to "files".
        verbosity_mode (Literal["silent", "transient", "verbose"], optional): Set progress
            verbosity mode. Can be one of: silent, transient and verbose. Silent disables
            output completely. Transient tracks progress, but removes output after finished.
            Verbose leaves all progress outputs in the stdout. Defaults to "transient".
        max_workers (Optional[int], optional): Max number of multiprocessing workers used to
            process the dataset. Defaults to None.

    Returns:
        Path: Path to the generated GeoParquet file.

    Examples:
        Get buildings in the center of London.

        >>> import overturemaestro as om
        >>> from shapely import box
        >>> london_bbox = box(-0.120077, 51.498164, -0.090809, 51.508849)
        >>> gpq_path = om.convert_geometry_to_parquet(
        ...     release="2024-08-20.0",
        ...     theme="buildings",
        ...     type="building",
        ...     geometry_filter=london_bbox,
        ... ) # doctest: +IGNORE_RESULT
        >>> gpq_path.as_posix()
        'files/2024-08-20.0/theme=buildings/type=building/7ed11f0d_nofilter.parquet'

        Inspect the content
        >>> import geopandas as gpd
        >>> gdf = gpd.read_parquet(gpq_path)
        >>> len(gdf)
        1863
        >>> list(gdf.columns) # doctest: +IGNORE_RESULT
        ['id', 'geometry', 'bbox', 'version', 'sources', 'subtype', 'class', 'names', 'level',
        'has_parts', 'height', 'is_underground', 'num_floors', 'num_floors_underground',
        'min_height', 'min_floor', 'facade_color', 'facade_material', 'roof_material', 'roof_shape',
        'roof_direction', 'roof_orientation', 'roof_color', 'roof_height', 'theme', 'type']

        Download museums in the same area from places dataset with a filter.

        >>> gpq_path = om.convert_geometry_to_parquet(
        ...     release="2024-08-20.0",
        ...     theme="places",
        ...     type="place",
        ...     geometry_filter=london_bbox,
        ...     pyarrow_filter=[[
        ...         (("categories", "primary"), "=", "museum"),
        ...         ("confidence", ">", 0.95),
        ...     ]],
        ... ) # doctest: +IGNORE_RESULT
        >>> gdf = gpd.read_parquet(gpq_path)
        >>> len(gdf)
        5
        >>> gdf[["id", "names", "confidence"]] # doctest: +IGNORE_RESULT
                                         id                               names  confidence
        0  08f194ad1499c8b1038ff3e213d81456  {'primary': 'Florence Nightinga...    0.982253
        1  08f194ad149044c6037575af3681766f  {'primary': 'Philip Simpson Des...    0.969941
        2  08f194ad32a0d494030fdddc1b405fb1  {'primary': 'Shakespeare's Glob...    0.991993
        3  08f194ad30695784036410e184708927  {'primary': 'Clink Street Londo...    0.965185
        4  08f194ad30690a42034312e00c0254a2  {'primary': 'The Clink Prison M...    0.982253
    """
    return download_data(
        release=release,
        theme=theme,
        type=type,
        geometry_filter=geometry_filter,
        pyarrow_filter=pyarrow_filter,
        columns_to_download=columns_to_download,
        result_file_path=result_file_path,
        ignore_cache=ignore_cache,
        working_directory=working_directory,
        verbosity_mode=verbosity_mode,
        max_workers=max_workers,
    )

convert_geometry_to_parquet_for_multiple_types 

convert_geometry_to_parquet_for_multiple_types(
    theme_type_pairs: list[tuple[str, str]],
    geometry_filter: BaseGeometry,
    release: Optional[str] = None,
    *,
    pyarrow_filters: Optional[list[Optional[PYARROW_FILTER]]] = None,
    columns_to_download: Optional[list[Optional[list[str]]]] = None,
    ignore_cache: bool = False,
    working_directory: Union[str, Path] = "files",
    verbosity_mode: VERBOSITY_MODE = "transient",
    max_workers: Optional[int] = None
) -> list[Path]

Get GeoParquet files with Overture Maps data within given geometry for multiple types.

Automatically downloads Overture Maps dataset for a given release and theme/type pairs in a concurrent manner and returns a list of files as a result.

Order of paths is the same as the input theme_type_pairs list.

PARAMETER DESCRIPTION
theme_type_pairs

Pairs of themes and types of the dataset.

TYPE: list[tuple[str, str]]

geometry_filter

Geometry used to filter data.

TYPE: BaseGeometry

release

Release version. If not provided, will automatically load newest available release version. Defaults to None.

TYPE: Optional[str] DEFAULT: None

pyarrow_filters

A list of pyarrow expressions used to filter specific theme type pair. Must be the same length as the list of theme type pairs. Defaults to None.

TYPE: Optional[list[Optional[PYARROW_FILTER]]] DEFAULT: None

columns_to_download

A list of pyarrow expressions used to filter specific theme type pair. Must be the same length as the list of theme type pairs. Defaults to None.

TYPE: Optional[list[Optional[list[str]]]] DEFAULT: None

ignore_cache

Whether to ignore precalculated geoparquet files or not. Defaults to False.

TYPE: bool DEFAULT: False

working_directory

Directory where to save the downloaded *.parquet files. Defaults to "files".

TYPE: Union[str, Path] DEFAULT: 'files'

verbosity_mode

Set progress verbosity mode. Can be one of: silent, transient and verbose. Silent disables output completely. Transient tracks progress, but removes output after finished. Verbose leaves all progress outputs in the stdout. Defaults to "transient".

TYPE: Literal[silent, transient, verbose] DEFAULT: 'transient'

max_workers

Max number of multiprocessing workers used to process the dataset. Defaults to None.

TYPE: Optional[int] DEFAULT: None

RETURNS DESCRIPTION
list[Path]

list[Path]: List of paths to the generated GeoParquet files.
Source code in overturemaestro/functions.py 
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def convert_geometry_to_parquet_for_multiple_types(
    theme_type_pairs: list[tuple[str, str]],
    geometry_filter: BaseGeometry,
    release: Optional[str] = None,
    *,
    pyarrow_filters: Optional[list[Optional[PYARROW_FILTER]]] = None,
    columns_to_download: Optional[list[Optional[list[str]]]] = None,
    ignore_cache: bool = False,
    working_directory: Union[str, Path] = "files",
    verbosity_mode: VERBOSITY_MODE = "transient",
    max_workers: Optional[int] = None,
) -> list[Path]:
    """
    Get GeoParquet files with Overture Maps data within given geometry for multiple types.

    Automatically downloads Overture Maps dataset for a given release and theme/type pairs
    in a concurrent manner and returns a list of files as a result.

    Order of paths is the same as the input theme_type_pairs list.

    Args:
        theme_type_pairs (list[tuple[str, str]]): Pairs of themes and types of the dataset.
        geometry_filter (BaseGeometry): Geometry used to filter data.
        release (Optional[str], optional): Release version. If not provided, will automatically load
            newest available release version. Defaults to None.
        pyarrow_filters (Optional[list[Optional[PYARROW_FILTER]]], optional): A list of pyarrow
            expressions used to filter specific theme type pair. Must be the same length as the list
            of theme type pairs. Defaults to None.
        columns_to_download (Optional[list[Optional[list[str]]]], optional): A list of pyarrow
            expressions used to filter specific theme type pair. Must be the same length as the list
            of theme type pairs. Defaults to None.
        ignore_cache (bool, optional): Whether to ignore precalculated geoparquet files or not.
            Defaults to False.
        working_directory (Union[str, Path], optional): Directory where to save
            the downloaded `*.parquet` files. Defaults to "files".
        verbosity_mode (Literal["silent", "transient", "verbose"], optional): Set progress
            verbosity mode. Can be one of: silent, transient and verbose. Silent disables
            output completely. Transient tracks progress, but removes output after finished.
            Verbose leaves all progress outputs in the stdout. Defaults to "transient".
        max_workers (Optional[int], optional): Max number of multiprocessing workers used to
            process the dataset. Defaults to None.

    Returns:
        list[Path]: List of paths to the generated GeoParquet files.
    """
    return download_data_for_multiple_types(
        theme_type_pairs=theme_type_pairs,
        geometry_filter=geometry_filter,
        release=release,
        pyarrow_filters=pyarrow_filters,
        columns_to_download=columns_to_download,
        ignore_cache=ignore_cache,
        working_directory=working_directory,
        verbosity_mode=verbosity_mode,
        max_workers=max_workers,
    )