code: def _read_file_fiona(
      path_or_bytes,
      from_bytes,
      bbox=None,
      mask=None,
      rows=None,
      where=None,
      **kwargs,
  ):
      if where is not None and not FIONA_GE_19:
          raise NotImplementedError("where requires fiona 1.9+")
  
      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.
          if _is_zip(str(path_or_bytes)):
              parsed = fiona.parse_path(str(path_or_bytes))
              if isinstance(parsed, fiona.path.ParsedPath):
                  # If fiona is able to parse the path, we can safely look at the scheme
                  # and update it to have a zip scheme if necessary.
                  schemes = (parsed.scheme or "").split("+")
                  if "zip" not in schemes:
                      parsed.scheme = "+".join(["zip"] + schemes)
                  path_or_bytes = parsed.name
              elif isinstance(
                  parsed, fiona.path.UnparsedPath
              ) and not str(path_or_bytes).startswith("/vsi"):
                  # If fiona is unable to parse the path, it might have a Windows drive
                  # scheme. Try adding zip:// to the front. If the path starts with "/vsi"
                  # it is a legacy GDAL path type, so let it pass unmodified.
                  path_or_bytes = "zip://" + parsed.name
  
      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 = 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 = pd.to_datetime(df[k], errors="ignore")
                  # if to_datetime failed, try again for mixed timezone offsets
                  if as_dt.dtype == "object":
                      # This can still fail if there are invalid datetimes
                      as_dt = pd.to_datetime(
                          df[k], errors="ignore", utc=True
                      )
                  # if to_datetime succeeded, round datetimes as
                  # fiona only supports up to ms precision (any microseconds are
                  # floating point rounding error)
                  if 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
  
imports: import os
  from packaging.version import Version
  from pathlib import Path
  import warnings
  import numpy
  import pandas
  from pandas.api.types import is_integer_dtype
  import pyproj
  from shapely.geometry import mapping
  from shapely.geometry.base import BaseGeometry
  from geopandas import GeoDataFrame, GeoSeries
  from urllib.parse import urlparse
  from urllib.parse import uses_netloc, uses_params, uses_relative
  import urllib.request
  from geopandas._compat import PANDAS_GE_20
label_desc: Use image node_id 10 for calling a global function with example usage: _read_file_fiona(path_or_bytes, from_bytes, bbox, mask, rows, where) and returns: df