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110 lines
3.2 KiB
Python
110 lines
3.2 KiB
Python
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""" feather-format compat """
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from pandas.compat._optional import import_optional_dependency
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from pandas import DataFrame, Int64Index, RangeIndex
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from pandas.io.common import get_filepath_or_buffer, stringify_path
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def to_feather(df: DataFrame, path, **kwargs):
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"""
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Write a DataFrame to the binary Feather format.
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Parameters
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----------
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df : DataFrame
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path : string file path, or file-like object
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**kwargs :
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Additional keywords passed to `pyarrow.feather.write_feather`.
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.. versionadded:: 1.1.0
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"""
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import_optional_dependency("pyarrow")
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from pyarrow import feather
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path = stringify_path(path)
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if not isinstance(df, DataFrame):
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raise ValueError("feather only support IO with DataFrames")
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valid_types = {"string", "unicode"}
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# validate index
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# --------------
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# validate that we have only a default index
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# raise on anything else as we don't serialize the index
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if not isinstance(df.index, Int64Index):
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typ = type(df.index)
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raise ValueError(
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f"feather does not support serializing {typ} "
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"for the index; you can .reset_index() to make the index into column(s)"
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)
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if not df.index.equals(RangeIndex.from_range(range(len(df)))):
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raise ValueError(
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"feather does not support serializing a non-default index for the index; "
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"you can .reset_index() to make the index into column(s)"
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)
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if df.index.name is not None:
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raise ValueError(
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"feather does not serialize index meta-data on a default index"
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)
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# validate columns
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# ----------------
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# must have value column names (strings only)
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if df.columns.inferred_type not in valid_types:
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raise ValueError("feather must have string column names")
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feather.write_feather(df, path, **kwargs)
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def read_feather(path, columns=None, use_threads: bool = True):
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"""
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Load a feather-format object from the file path.
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Parameters
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----------
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path : str, path object or file-like object
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Any valid string path is acceptable. The string could be a URL. Valid
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URL schemes include http, ftp, s3, and file. For file URLs, a host is
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expected. A local file could be:
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``file://localhost/path/to/table.feather``.
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If you want to pass in a path object, pandas accepts any
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``os.PathLike``.
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By file-like object, we refer to objects with a ``read()`` method,
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such as a file handler (e.g. via builtin ``open`` function)
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or ``StringIO``.
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columns : sequence, default None
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If not provided, all columns are read.
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.. versionadded:: 0.24.0
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use_threads : bool, default True
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Whether to parallelize reading using multiple threads.
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.. versionadded:: 0.24.0
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Returns
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-------
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type of object stored in file
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"""
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import_optional_dependency("pyarrow")
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from pyarrow import feather
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path, _, _, should_close = get_filepath_or_buffer(path)
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df = feather.read_feather(path, columns=columns, use_threads=bool(use_threads))
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# s3fs only validates the credentials when the file is closed.
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if should_close:
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path.close()
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return df
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