read

Contents

read#

read(vector: str | CloudPath | Path | GeoDataFrame | GeoSeries | None = None, crs: Any | None = None, archive_regex: str | None = None, window: Any | None = None, **kwargs) → GeoDataFrame[source]#

Read any vector:

  • if KML/KMZ: sets correctly the drivers and open layered KML (you may need ogr2ogr to make it work !)

  • if archive (only zip or tar), use a regex to look for the vector inside the archive. You can use this site to build your regex.

  • if GML: manages the empty errors

Handles a lot of exceptions and have fallback mechanisms with ogr2ogr (if in PATH)

Handles both on disk and cloud-stored vectors.

Adds two attributes to your vector:

  • path: File path

  • name: File name

If vector object is passed:

  • in case of geopandas.GeoSeries: A geopandas.GeoDataFrame is created from it

  • in case of geopandas.GeoDataFrame: returned as is

Parameters:

  • vector (AnyVectorType | gpd.GeoSeries) – Path to vector to read or vector itself. In case of archive, path to the archive.

  • crs – Wanted CRS of the vector. If None, using naive or origin CRS.

  • archive_regex (str) – [Archive only] Regex for the wanted vector inside the archive

  • window (Any) – Anything that can be returned as a bbox (i.e. path, gpd.GeoPandas, Iterable, …). In case of an iterable, assumption is made it corresponds to geographic bounds. Mimics rasters.read(..., window=). If given, bbox is ignored.

  • **kwargs – Additional arguments used in gpd.read_file. You can also give file_list, the list of files of the archive to get the vector from, as this operation is expensive when done with large archives stored on the cloud. You can also set compute_sindex=False to avoid computing the spatial index of the vector.

Returns:

Read vector as a GeoDataFrame

Return type:

gpd.GeoDataFrame

Examples

>>> # Usual
>>> path = 'D:/path/to/vector.geojson'
>>> vec = vectors.read(path, crs=WGS84)
                       Name  ...                                           geometry
0  Sentinel-1 Image Overlay  ...  POLYGON ((0.85336 42.24660, -2.32032 42.65493,...
>>>
>>> # Attributes
>>> vec.attrs["path"]
'D:/path/to/vector.geojson'
>>>
>>> vec.attrs["name"]
'vector.geojson'

>>> # Archive
>>> arch_path = 'D:/path/to/zip.zip'
>>> vectors.read(arch_path, archive_regex=r".*map-overlay.kml")
                       Name  ...                                           geometry
0  Sentinel-1 Image Overlay  ...  POLYGON ((0.85336 42.24660, -2.32032 42.65493,...
Contents