ak.to_feather#

Defined in awkward.operations.ak_to_feather on line 16.

ak.to_feather(array, destination, *, list_to32=False, string_to32=True, bytestring_to32=True, emptyarray_to=None, categorical_as_dictionary=False, extensionarray=True, count_nulls=True, compression='zstd', compression_level=None, chunksize=None, feather_version=2)#
Parameters:

  • array – Array-like data (anything ak.to_layout recognizes).

  • destination (str) – Local destination path, passed to pyarrow.feather.write_feather.

  • list_to32 (bool) – If True, convert Awkward lists into 32-bit Arrow lists if they’re small enough, even if it means an extra conversion. Otherwise, signed 32-bit ak.types.ListType maps to Arrow ListType, signed 64-bit ak.types.ListType maps to Arrow LargeListType, and unsigned 32-bit ak.types.ListType picks whichever Arrow type its values fit into.

  • string_to32 (bool) – Same as the above for Arrow string and large_string.

  • bytestring_to32 (bool) – Same as the above for Arrow binary and large_binary.

  • emptyarray_to (None or dtype) – If None, ak.types.UnknownType maps to Arrow’s null type; otherwise, it is converted a given numeric dtype.

  • categorical_as_dictionary (bool) – If True, ak.contents.IndexedArray and ak.contents.IndexedOptionArray labeled with __array__ = "categorical" are mapped to Arrow DictionaryArray; otherwise, the projection is evaluated before conversion (always the case without __array__ = "categorical").

  • extensionarray (bool) – If True, this function returns extended Arrow arrays (at all levels of nesting), which preserve metadata so that Awkward → Arrow → Awkward preserves the array’s ak.types.Type (though not the ak.forms.Form). If False, this function returns generic Arrow arrays that might be needed for third-party tools that don’t recognize Arrow’s extensions. Even with extensionarray=False, the values produced by Arrow’s to_pylist method are the same as the values produced by Awkward’s ak.to_list.

  • count_nulls (bool) – If True, count the number of missing values at each level and include these in the resulting Arrow array, which makes some downstream applications faster. If False, skip the up-front cost of counting them.

  • compression (None or str) – Can be one of {“zstd”, “lz4”, “uncompressed”}. The default of None uses LZ4 for feather_version=2 files if it is available, otherwise uncompressed. Passed to pyarrow.feather.write_feather.

  • compression_level (None or int) – Use a compression level particular to the chosen compressor. If None use the default compression level. Passed to pyarrow.feather.write_feather.

  • chunksize (None or int) – For feather_version=2 files, this is the internal maximum size of Arrow RecordBatch chunks when writing the Arrow IPC file format. None means use the default, which is currently 64K. Passed to pyarrow.feather.write_feather.

  • feather_version (int) – Feather file version, passed to pyarrow.feather.write_feather. Version 2 is the current. Version 1 is the more limited legacy format. If not provided, version 2 is used.

Writes an Awkward Array to a Feather file (through pyarrow).

>>> array = ak.Array([[1.1, 2.2, 3.3], [], [4.4, 5.5]])
>>> ak.to_feather(array, "filename.feather")

If the array does not contain records at top-level, the Arrow table will consist of one field whose name is "" iff. extensionarray is False.

If extensionarray is True``, use a custom Arrow extension to store this array. Otherwise, generic Arrow arrays are used, and if the array does not contain records at top-level, the Arrow table will consist of one field whose name is "". See ak.to_arrow_table for more details.

See also ak.from_feather.