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David Adams
2024-09-28 22:56:00 -07:00
parent 64d9b78b3a
commit 1973934e95
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from __future__ import annotations
import os
import urllib.request
import warnings
from io import IOBase
from packaging.version import Version
from pathlib import Path
# Adapted from pandas.io.common
from urllib.parse import urlparse as parse_url
from urllib.parse import uses_netloc, uses_params, uses_relative
import numpy as np
import pandas as pd
from pandas.api.types import is_integer_dtype
import shapely
from shapely.geometry import mapping
from shapely.geometry.base import BaseGeometry
from geopandas import GeoDataFrame, GeoSeries
from geopandas._compat import HAS_PYPROJ, PANDAS_GE_20
from geopandas.io.util import vsi_path
_VALID_URLS = set(uses_relative + uses_netloc + uses_params)
_VALID_URLS.discard("")
# file:// URIs are supported by fiona/pyogrio -> don't already open + read the file here
_VALID_URLS.discard("file")
fiona = None
fiona_env = None
fiona_import_error = None
FIONA_GE_19 = False
def _import_fiona():
global fiona
global fiona_env
global fiona_import_error
global FIONA_GE_19
if fiona is None:
try:
import fiona
# only try to import fiona.Env if the main fiona import succeeded
# (otherwise you can get confusing "AttributeError: module 'fiona'
# has no attribute '_loading'" / partially initialized module errors)
try:
from fiona import Env as fiona_env
except ImportError:
try:
from fiona import drivers as fiona_env
except ImportError:
fiona_env = None
FIONA_GE_19 = Version(Version(fiona.__version__).base_version) >= Version(
"1.9.0"
)
except ImportError as err:
fiona = False
fiona_import_error = str(err)
pyogrio = None
pyogrio_import_error = None
def _import_pyogrio():
global pyogrio
global pyogrio_import_error
if pyogrio is None:
try:
import pyogrio
except ImportError as err:
pyogrio = False
pyogrio_import_error = str(err)
def _check_fiona(func):
if not fiona:
raise ImportError(
f"the {func} requires the 'fiona' package, but it is not installed or does "
f"not import correctly.\nImporting fiona resulted in: {fiona_import_error}"
)
def _check_pyogrio(func):
if not pyogrio:
raise ImportError(
f"the {func} requires the 'pyogrio' package, but it is not installed "
"or does not import correctly."
"\nImporting pyogrio resulted in: {pyogrio_import_error}"
)
def _check_metadata_supported(metadata: str | None, engine: str, driver: str) -> None:
if metadata is None:
return
if driver != "GPKG":
raise NotImplementedError(
"The 'metadata' keyword is only supported for the GPKG driver."
)
if engine == "fiona" and not FIONA_GE_19:
raise NotImplementedError(
"The 'metadata' keyword is only supported for Fiona >= 1.9."
)
def _check_engine(engine, func):
# if not specified through keyword or option, then default to "pyogrio" if
# installed, otherwise try fiona
if engine is None:
import geopandas
engine = geopandas.options.io_engine
if engine is None:
_import_pyogrio()
if pyogrio:
engine = "pyogrio"
else:
_import_fiona()
if fiona:
engine = "fiona"
if engine == "pyogrio":
_import_pyogrio()
_check_pyogrio(func)
elif engine == "fiona":
_import_fiona()
_check_fiona(func)
elif engine is None:
raise ImportError(
f"The {func} requires the 'pyogrio' or 'fiona' package, "
"but neither is installed or imports correctly."
f"\nImporting pyogrio resulted in: {pyogrio_import_error}"
f"\nImporting fiona resulted in: {fiona_import_error}"
)
return engine
_EXTENSION_TO_DRIVER = {
".bna": "BNA",
".dxf": "DXF",
".csv": "CSV",
".shp": "ESRI Shapefile",
".dbf": "ESRI Shapefile",
".json": "GeoJSON",
".geojson": "GeoJSON",
".geojsonl": "GeoJSONSeq",
".geojsons": "GeoJSONSeq",
".gpkg": "GPKG",
".gml": "GML",
".xml": "GML",
".gpx": "GPX",
".gtm": "GPSTrackMaker",
".gtz": "GPSTrackMaker",
".tab": "MapInfo File",
".mif": "MapInfo File",
".mid": "MapInfo File",
".dgn": "DGN",
".fgb": "FlatGeobuf",
}
def _expand_user(path):
"""Expand paths that use ~."""
if isinstance(path, str):
path = os.path.expanduser(path)
elif isinstance(path, Path):
path = path.expanduser()
return path
def _is_url(url):
"""Check to see if *url* has a valid protocol."""
try:
return parse_url(url).scheme in _VALID_URLS
except Exception:
return False
def _read_file(
filename, bbox=None, mask=None, columns=None, rows=None, engine=None, **kwargs
):
"""
Returns a GeoDataFrame from a file or URL.
Parameters
----------
filename : str, path object or file-like object
Either the absolute or relative path to the file or URL to
be opened, or any object with a read() method (such as an open file
or StringIO)
bbox : tuple | GeoDataFrame or GeoSeries | shapely Geometry, default None
Filter features by given bounding box, GeoSeries, GeoDataFrame or a shapely
geometry. With engine="fiona", CRS mis-matches are resolved if given a GeoSeries
or GeoDataFrame. With engine="pyogrio", bbox must be in the same CRS as the
dataset. Tuple is (minx, miny, maxx, maxy) to match the bounds property of
shapely geometry objects. Cannot be used with mask.
mask : dict | GeoDataFrame or GeoSeries | shapely Geometry, default None
Filter for features that intersect with the given dict-like geojson
geometry, GeoSeries, GeoDataFrame or shapely geometry.
CRS mis-matches are resolved if given a GeoSeries or GeoDataFrame.
Cannot be used with bbox. If multiple geometries are passed, this will
first union all geometries, which may be computationally expensive.
columns : list, optional
List of column names to import from the data source. Column names
must exactly match the names in the data source. To avoid reading
any columns (besides the geometry column), pass an empty list-like.
By default reads all columns.
rows : int or slice, default None
Load in specific rows by passing an integer (first `n` rows) or a
slice() object.
engine : str, "pyogrio" or "fiona"
The underlying library that is used to read the file. Currently, the
supported options are "pyogrio" and "fiona". Defaults to "pyogrio" if
installed, otherwise tries "fiona". Engine can also be set globally
with the ``geopandas.options.io_engine`` option.
**kwargs :
Keyword args to be passed to the engine, and can be used to write
to multi-layer data, store data within archives (zip files), etc.
In case of the "pyogrio" engine, the keyword arguments are passed to
`pyogrio.write_dataframe`. In case of the "fiona" engine, the keyword
arguments are passed to fiona.open`. For more information on possible
keywords, type: ``import pyogrio; help(pyogrio.write_dataframe)``.
Examples
--------
>>> df = geopandas.read_file("nybb.shp") # doctest: +SKIP
Specifying layer of GPKG:
>>> df = geopandas.read_file("file.gpkg", layer='cities') # doctest: +SKIP
Reading only first 10 rows:
>>> df = geopandas.read_file("nybb.shp", rows=10) # doctest: +SKIP
Reading only geometries intersecting ``mask``:
>>> df = geopandas.read_file("nybb.shp", mask=polygon) # doctest: +SKIP
Reading only geometries intersecting ``bbox``:
>>> df = geopandas.read_file("nybb.shp", bbox=(0, 0, 10, 20)) # doctest: +SKIP
Returns
-------
:obj:`geopandas.GeoDataFrame` or :obj:`pandas.DataFrame` :
If `ignore_geometry=True` a :obj:`pandas.DataFrame` will be returned.
Notes
-----
The format drivers will attempt to detect the encoding of your data, but
may fail. In this case, the proper encoding can be specified explicitly
by using the encoding keyword parameter, e.g. ``encoding='utf-8'``.
When specifying a URL, geopandas will check if the server supports reading
partial data and in that case pass the URL as is to the underlying engine,
which will then use the network file system handler of GDAL to read from
the URL. Otherwise geopandas will download the data from the URL and pass
all data in-memory to the underlying engine.
If you need more control over how the URL is read, you can specify the
GDAL virtual filesystem manually (e.g. ``/vsicurl/https://...``). See the
GDAL documentation on filesystems for more details
(https://gdal.org/user/virtual_file_systems.html#vsicurl-http-https-ftp-files-random-access).
"""
engine = _check_engine(engine, "'read_file' function")
filename = _expand_user(filename)
from_bytes = False
if _is_url(filename):
# if it is a url that supports random access -> pass through to
# pyogrio/fiona as is (to support downloading only part of the file)
# otherwise still download manually because pyogrio/fiona don't support
# all types of urls (https://github.com/geopandas/geopandas/issues/2908)
with urllib.request.urlopen(filename) as response:
if not response.headers.get("Accept-Ranges") == "bytes":
filename = response.read()
from_bytes = True
if engine == "pyogrio":
return _read_file_pyogrio(
filename, bbox=bbox, mask=mask, columns=columns, rows=rows, **kwargs
)
elif engine == "fiona":
if pd.api.types.is_file_like(filename):
data = filename.read()
path_or_bytes = data.encode("utf-8") if isinstance(data, str) else data
from_bytes = True
else:
path_or_bytes = filename
return _read_file_fiona(
path_or_bytes,
from_bytes,
bbox=bbox,
mask=mask,
columns=columns,
rows=rows,
**kwargs,
)
else:
raise ValueError(f"unknown engine '{engine}'")
def _read_file_fiona(
path_or_bytes,
from_bytes,
bbox=None,
mask=None,
columns=None,
rows=None,
where=None,
**kwargs,
):
if where is not None and not FIONA_GE_19:
raise NotImplementedError("where requires fiona 1.9+")
if columns is not None:
if "include_fields" in kwargs:
raise ValueError(
"Cannot specify both 'include_fields' and 'columns' keywords"
)
if not FIONA_GE_19:
raise NotImplementedError("'columns' keyword requires fiona 1.9+")
kwargs["include_fields"] = columns
elif "include_fields" in kwargs:
# alias to columns, as this variable is used below to specify column order
# in the dataframe creation
columns = kwargs["include_fields"]
if not from_bytes:
# Opening a file via URL or file-like-object above automatically detects a
# zipped file. In order to match that behavior, attempt to add a zip scheme
# if missing.
path_or_bytes = vsi_path(str(path_or_bytes))
if from_bytes:
reader = fiona.BytesCollection
else:
reader = fiona.open
with fiona_env():
with reader(path_or_bytes, **kwargs) as features:
crs = features.crs_wkt
# attempt to get EPSG code
try:
# fiona 1.9+
epsg = features.crs.to_epsg(confidence_threshold=100)
if epsg is not None:
crs = epsg
except AttributeError:
# fiona <= 1.8
try:
crs = features.crs["init"]
except (TypeError, KeyError):
pass
# handle loading the bounding box
if bbox is not None:
if isinstance(bbox, (GeoDataFrame, GeoSeries)):
bbox = tuple(bbox.to_crs(crs).total_bounds)
elif isinstance(bbox, BaseGeometry):
bbox = bbox.bounds
assert len(bbox) == 4
# handle loading the mask
elif isinstance(mask, (GeoDataFrame, GeoSeries)):
mask = mapping(mask.to_crs(crs).union_all())
elif isinstance(mask, BaseGeometry):
mask = mapping(mask)
filters = {}
if bbox is not None:
filters["bbox"] = bbox
if mask is not None:
filters["mask"] = mask
if where is not None:
filters["where"] = where
# setup the data loading filter
if rows is not None:
if isinstance(rows, int):
rows = slice(rows)
elif not isinstance(rows, slice):
raise TypeError("'rows' must be an integer or a slice.")
f_filt = features.filter(rows.start, rows.stop, rows.step, **filters)
elif filters:
f_filt = features.filter(**filters)
else:
f_filt = features
# get list of columns
columns = columns or list(features.schema["properties"])
datetime_fields = [
k for (k, v) in features.schema["properties"].items() if v == "datetime"
]
if (
kwargs.get("ignore_geometry", False)
or features.schema["geometry"] == "None"
):
df = pd.DataFrame(
[record["properties"] for record in f_filt], columns=columns
)
else:
df = GeoDataFrame.from_features(
f_filt, crs=crs, columns=columns + ["geometry"]
)
for k in datetime_fields:
as_dt = None
# plain try catch for when pandas will raise in the future
# TODO we can tighten the exception type in future when it does
try:
with warnings.catch_warnings():
# pandas 2.x does not yet enforce this behaviour but raises a
# warning -> we want to to suppress this warning for our users,
# and do this by turning it into an error so we take the
# `except` code path to try again with utc=True
warnings.filterwarnings(
"error",
"In a future version of pandas, parsing datetimes with "
"mixed time zones will raise an error",
FutureWarning,
)
as_dt = pd.to_datetime(df[k])
except Exception:
pass
if as_dt is None or as_dt.dtype == "object":
# if to_datetime failed, try again for mixed timezone offsets
# This can still fail if there are invalid datetimes
try:
as_dt = pd.to_datetime(df[k], utc=True)
except Exception:
pass
# if to_datetime succeeded, round datetimes as
# fiona only supports up to ms precision (any microseconds are
# floating point rounding error)
if as_dt is not None and not (as_dt.dtype == "object"):
if PANDAS_GE_20:
df[k] = as_dt.dt.as_unit("ms")
else:
df[k] = as_dt.dt.round(freq="ms")
return df
def _read_file_pyogrio(path_or_bytes, bbox=None, mask=None, rows=None, **kwargs):
import pyogrio
if rows is not None:
if isinstance(rows, int):
kwargs["max_features"] = rows
elif isinstance(rows, slice):
if rows.start is not None:
if rows.start < 0:
raise ValueError(
"Negative slice start not supported with the 'pyogrio' engine."
)
kwargs["skip_features"] = rows.start
if rows.stop is not None:
kwargs["max_features"] = rows.stop - (rows.start or 0)
if rows.step is not None:
raise ValueError("slice with step is not supported")
else:
raise TypeError("'rows' must be an integer or a slice.")
if bbox is not None and mask is not None:
# match error message from Fiona
raise ValueError("mask and bbox can not be set together")
if bbox is not None:
if isinstance(bbox, (GeoDataFrame, GeoSeries)):
crs = pyogrio.read_info(path_or_bytes).get("crs")
if isinstance(path_or_bytes, IOBase):
path_or_bytes.seek(0)
bbox = tuple(bbox.to_crs(crs).total_bounds)
elif isinstance(bbox, BaseGeometry):
bbox = bbox.bounds
if len(bbox) != 4:
raise ValueError("'bbox' should be a length-4 tuple.")
if mask is not None:
# NOTE: mask cannot be used at same time as bbox keyword
if isinstance(mask, (GeoDataFrame, GeoSeries)):
crs = pyogrio.read_info(path_or_bytes).get("crs")
if isinstance(path_or_bytes, IOBase):
path_or_bytes.seek(0)
mask = shapely.unary_union(mask.to_crs(crs).geometry.values)
elif isinstance(mask, BaseGeometry):
mask = shapely.unary_union(mask)
elif isinstance(mask, dict) or hasattr(mask, "__geo_interface__"):
# convert GeoJSON to shapely geometry
mask = shapely.geometry.shape(mask)
kwargs["mask"] = mask
if kwargs.pop("ignore_geometry", False):
kwargs["read_geometry"] = False
# translate `ignore_fields`/`include_fields` keyword for back compat with fiona
if "ignore_fields" in kwargs and "include_fields" in kwargs:
raise ValueError("Cannot specify both 'ignore_fields' and 'include_fields'")
elif "ignore_fields" in kwargs:
if kwargs.get("columns", None) is not None:
raise ValueError(
"Cannot specify both 'columns' and 'ignore_fields' keywords"
)
warnings.warn(
"The 'include_fields' and 'ignore_fields' keywords are deprecated, and "
"will be removed in a future release. You can use the 'columns' keyword "
"instead to select which columns to read.",
DeprecationWarning,
stacklevel=3,
)
ignore_fields = kwargs.pop("ignore_fields")
fields = pyogrio.read_info(path_or_bytes)["fields"]
include_fields = [col for col in fields if col not in ignore_fields]
kwargs["columns"] = include_fields
elif "include_fields" in kwargs:
# translate `include_fields` keyword for back compat with fiona engine
if kwargs.get("columns", None) is not None:
raise ValueError(
"Cannot specify both 'columns' and 'include_fields' keywords"
)
warnings.warn(
"The 'include_fields' and 'ignore_fields' keywords are deprecated, and "
"will be removed in a future release. You can use the 'columns' keyword "
"instead to select which columns to read.",
DeprecationWarning,
stacklevel=3,
)
kwargs["columns"] = kwargs.pop("include_fields")
return pyogrio.read_dataframe(path_or_bytes, bbox=bbox, **kwargs)
def _detect_driver(path):
"""
Attempt to auto-detect driver based on the extension
"""
try:
# in case the path is a file handle
path = path.name
except AttributeError:
pass
try:
return _EXTENSION_TO_DRIVER[Path(path).suffix.lower()]
except KeyError:
# Assume it is a shapefile folder for now. In the future,
# will likely raise an exception when the expected
# folder writing behavior is more clearly defined.
return "ESRI Shapefile"
def _to_file(
df,
filename,
driver=None,
schema=None,
index=None,
mode="w",
crs=None,
engine=None,
metadata=None,
**kwargs,
):
"""
Write this GeoDataFrame to an OGR data source
A dictionary of supported OGR providers is available via:
>>> import pyogrio
>>> pyogrio.list_drivers() # doctest: +SKIP
Parameters
----------
df : GeoDataFrame to be written
filename : string
File path or file handle to write to. The path may specify a
GDAL VSI scheme.
driver : string, default None
The OGR format driver used to write the vector file.
If not specified, it attempts to infer it from the file extension.
If no extension is specified, it saves ESRI Shapefile to a folder.
schema : dict, default None
If specified, the schema dictionary is passed to Fiona to
better control how the file is written. If None, GeoPandas
will determine the schema based on each column's dtype.
Not supported for the "pyogrio" engine.
index : bool, default None
If True, write index into one or more columns (for MultiIndex).
Default None writes the index into one or more columns only if
the index is named, is a MultiIndex, or has a non-integer data
type. If False, no index is written.
.. versionadded:: 0.7
Previously the index was not written.
mode : string, default 'w'
The write mode, 'w' to overwrite the existing file and 'a' to append;
when using the pyogrio engine, you can also pass ``append=True``.
Not all drivers support appending. For the fiona engine, the drivers
that support appending are listed in fiona.supported_drivers or
https://github.com/Toblerity/Fiona/blob/master/fiona/drvsupport.py.
For the pyogrio engine, you should be able to use any driver that
is available in your installation of GDAL that supports append
capability; see the specific driver entry at
https://gdal.org/drivers/vector/index.html for more information.
crs : pyproj.CRS, default None
If specified, the CRS is passed to Fiona to
better control how the file is written. If None, GeoPandas
will determine the crs based on crs df attribute.
The value can be anything accepted
by :meth:`pyproj.CRS.from_user_input() <pyproj.crs.CRS.from_user_input>`,
such as an authority string (eg "EPSG:4326") or a WKT string.
engine : str, "pyogrio" or "fiona"
The underlying library that is used to read the file. Currently, the
supported options are "pyogrio" and "fiona". Defaults to "pyogrio" if
installed, otherwise tries "fiona". Engine can also be set globally
with the ``geopandas.options.io_engine`` option.
metadata : dict[str, str], default None
Optional metadata to be stored in the file. Keys and values must be
strings. Only supported for the "GPKG" driver
(requires Fiona >= 1.9 or pyogrio >= 0.6).
**kwargs :
Keyword args to be passed to the engine, and can be used to write
to multi-layer data, store data within archives (zip files), etc.
In case of the "fiona" engine, the keyword arguments are passed to
fiona.open`. For more information on possible keywords, type:
``import fiona; help(fiona.open)``. In case of the "pyogrio" engine,
the keyword arguments are passed to `pyogrio.write_dataframe`.
Notes
-----
The format drivers will attempt to detect the encoding of your data, but
may fail. In this case, the proper encoding can be specified explicitly
by using the encoding keyword parameter, e.g. ``encoding='utf-8'``.
"""
engine = _check_engine(engine, "'to_file' method")
filename = _expand_user(filename)
if index is None:
# Determine if index attribute(s) should be saved to file
# (only if they are named or are non-integer)
index = list(df.index.names) != [None] or not is_integer_dtype(df.index.dtype)
if index:
df = df.reset_index(drop=False)
if driver is None:
driver = _detect_driver(filename)
if driver == "ESRI Shapefile" and any(len(c) > 10 for c in df.columns.tolist()):
warnings.warn(
"Column names longer than 10 characters will be truncated when saved to "
"ESRI Shapefile.",
stacklevel=3,
)
if (df.dtypes == "geometry").sum() > 1:
raise ValueError(
"GeoDataFrame contains multiple geometry columns but GeoDataFrame.to_file "
"supports only a single geometry column. Use a GeoDataFrame.to_parquet or "
"GeoDataFrame.to_feather, drop additional geometry columns or convert them "
"to a supported format like a well-known text (WKT) using "
"`GeoSeries.to_wkt()`.",
)
_check_metadata_supported(metadata, engine, driver)
if mode not in ("w", "a"):
raise ValueError(f"'mode' should be one of 'w' or 'a', got '{mode}' instead")
if engine == "pyogrio":
_to_file_pyogrio(df, filename, driver, schema, crs, mode, metadata, **kwargs)
elif engine == "fiona":
_to_file_fiona(df, filename, driver, schema, crs, mode, metadata, **kwargs)
else:
raise ValueError(f"unknown engine '{engine}'")
def _to_file_fiona(df, filename, driver, schema, crs, mode, metadata, **kwargs):
if not HAS_PYPROJ and crs:
raise ImportError(
"The 'pyproj' package is required to write a file with a CRS, but it is not"
" installed or does not import correctly."
)
if schema is None:
schema = infer_schema(df)
if crs:
from pyproj import CRS
crs = CRS.from_user_input(crs)
else:
crs = df.crs
with fiona_env():
crs_wkt = None
try:
gdal_version = Version(
fiona.env.get_gdal_release_name().strip("e")
) # GH3147
except (AttributeError, ValueError):
gdal_version = Version("2.0.0") # just assume it is not the latest
if gdal_version >= Version("3.0.0") and crs:
crs_wkt = crs.to_wkt()
elif crs:
crs_wkt = crs.to_wkt("WKT1_GDAL")
with fiona.open(
filename, mode=mode, driver=driver, crs_wkt=crs_wkt, schema=schema, **kwargs
) as colxn:
if metadata is not None:
colxn.update_tags(metadata)
colxn.writerecords(df.iterfeatures())
def _to_file_pyogrio(df, filename, driver, schema, crs, mode, metadata, **kwargs):
import pyogrio
if schema is not None:
raise ValueError(
"The 'schema' argument is not supported with the 'pyogrio' engine."
)
if mode == "a":
kwargs["append"] = True
if crs is not None:
raise ValueError("Passing 'crs' is not supported with the 'pyogrio' engine.")
# for the fiona engine, this check is done in gdf.iterfeatures()
if not df.columns.is_unique:
raise ValueError("GeoDataFrame cannot contain duplicated column names.")
pyogrio.write_dataframe(df, filename, driver=driver, metadata=metadata, **kwargs)
def infer_schema(df):
from collections import OrderedDict
# TODO: test pandas string type and boolean type once released
types = {
"Int32": "int32",
"int32": "int32",
"Int64": "int",
"string": "str",
"boolean": "bool",
}
def convert_type(column, in_type):
if in_type == object:
return "str"
if in_type.name.startswith("datetime64"):
# numpy datetime type regardless of frequency
return "datetime"
if str(in_type) in types:
out_type = types[str(in_type)]
else:
out_type = type(np.zeros(1, in_type).item()).__name__
if out_type == "long":
out_type = "int"
return out_type
properties = OrderedDict(
[
(col, convert_type(col, _type))
for col, _type in zip(df.columns, df.dtypes)
if col != df._geometry_column_name
]
)
if df.empty:
warnings.warn(
"You are attempting to write an empty DataFrame to file. "
"For some drivers, this operation may fail.",
UserWarning,
stacklevel=3,
)
# Since https://github.com/Toblerity/Fiona/issues/446 resolution,
# Fiona allows a list of geometry types
geom_types = _geometry_types(df)
schema = {"geometry": geom_types, "properties": properties}
return schema
def _geometry_types(df):
"""
Determine the geometry types in the GeoDataFrame for the schema.
"""
geom_types_2D = df[~df.geometry.has_z].geometry.geom_type.unique()
geom_types_2D = [gtype for gtype in geom_types_2D if gtype is not None]
geom_types_3D = df[df.geometry.has_z].geometry.geom_type.unique()
geom_types_3D = ["3D " + gtype for gtype in geom_types_3D if gtype is not None]
geom_types = geom_types_3D + geom_types_2D
if len(geom_types) == 0:
# Default geometry type supported by Fiona
# (Since https://github.com/Toblerity/Fiona/issues/446 resolution)
return "Unknown"
if len(geom_types) == 1:
geom_types = geom_types[0]
return geom_types
def _list_layers(filename) -> pd.DataFrame:
"""List layers available in a file.
Provides an overview of layers available in a file or URL together with their
geometry types. When supported by the data source, this includes both spatial and
non-spatial layers. Non-spatial layers are indicated by the ``"geometry_type"``
column being ``None``. GeoPandas will not read such layers but they can be read into
a pd.DataFrame using :func:`pyogrio.read_dataframe`.
Parameters
----------
filename : str, path object or file-like object
Either the absolute or relative path to the file or URL to
be opened, or any object with a read() method (such as an open file
or StringIO)
Returns
-------
pandas.DataFrame
A DataFrame with columns "name" and "geometry_type" and one row per layer.
"""
_import_pyogrio()
_check_pyogrio("list_layers")
import pyogrio
return pd.DataFrame(
pyogrio.list_layers(filename), columns=["name", "geometry_type"]
)