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Antoine Pitrou commented on ARROW-2040: --------------------------------------- The existence of the "base" parameter in various public serialization APIs is a bit weird. Normally pyarrow would infer the base object (i.e. the object owning the memory buffer) for deserialized Numpy arrays by itself... Is there a use case for it? [~xhochy] > [Python] pyarrow.read_serialized returns bogus data > --------------------------------------------------- > > Key: ARROW-2040 > URL: https://issues.apache.org/jira/browse/ARROW-2040 > Project: Apache Arrow > Issue Type: Bug > Affects Versions: 0.8.0 > Reporter: Richard Shin > Assignee: Antoine Pitrou > Priority: Major > Fix For: 0.9.0 > > > pyarrow.deserialize works fine, however. > {code:python} > Python 2.7.12 (default, Nov 20 2017, 18:23:56) > [GCC 5.4.0 20160609] on linux2 > Type "help", "copyright", "credits" or "license" for more information. > >>> import pyarrow as pa, numpy as np > >>> with open('test.pyarrow', 'w') as f: > ... f.write(pa.serialize(np.arange(10, > dtype=np.int32)).to_buffer().to_pybytes()) > ... > >>> pa.read_serialized(pa.OSFile('test.pyarrow')).deserialize() > array([54846320, 0, 45484448, 0, 4, 5, 6, 7, 8, 9], dtype=int32) > >>> pa.deserialize(pa.frombuffer(open('test.pyarrow').read())) > array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9], dtype=int32) > {code} -- This message was sent by Atlassian JIRA (v7.6.3#76005)