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69 lines
2.0 KiB
Python
69 lines
2.0 KiB
Python
"""Converters used in the table data fetching methods."""
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from collections.abc import Iterator
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from typing import Any, Optional, Union
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class TableConverter:
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"""Base class for table data converters."""
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def do_conversion(self, features: Iterator[Any]) -> Any:
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raise NotImplementedError()
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class PandasConverter(TableConverter):
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"""Converter from a feature generator to a `pandas.DataFrame`."""
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def do_conversion(self, features: Iterator[Any]) -> Any:
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try:
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import pandas # pylint: disable=g-import-not-at-top
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except ImportError as exc:
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raise ImportError(
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'Using format PANDAS_DATAFRAME requires pandas.'
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) from exc
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return pandas.DataFrame.from_records(self._convert_to_records(features))
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def _convert_to_records(
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self, features: Iterator[Any]
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) -> Iterator[dict[str, Any]]:
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for feature in features:
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yield {
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'geo': feature.get('geometry'),
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**(feature.get('properties', {}) or {}),
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}
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class GeoPandasConverter(TableConverter):
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"""Converter from a feature generator to a `geopandas.GeoDataFrame`."""
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def do_conversion(self, features: Iterator[Any]) -> Any:
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try:
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import geopandas # pylint: disable=g-import-not-at-top
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except ImportError as exc:
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raise ImportError(
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'Using format GEOPANDAS_GEODATAFRAME requires geopandas.'
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) from exc
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return geopandas.GeoDataFrame.from_features(
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self._materialize_features(features)
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)
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def _materialize_features(self, features: Iterator[Any]) -> list[Any]:
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"""Materializes the features, making several requests if necessary."""
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return list(features)
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_TABLE_DATA_CONVERTERS: dict[str, type[TableConverter]] = {
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'PANDAS_DATAFRAME': PandasConverter,
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'GEOPANDAS_GEODATAFRAME': GeoPandasConverter,
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}
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def from_file_format(
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file_format: Union[str, TableConverter]
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) -> Optional[TableConverter]:
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if isinstance(file_format, TableConverter):
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return file_format
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if file_format in _TABLE_DATA_CONVERTERS:
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return _TABLE_DATA_CONVERTERS[file_format.upper()]()
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return None
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