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https://issues.apache.org/jira/browse/ARROW-6158?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Antoine Pitrou updated ARROW-6158:
----------------------------------
Fix Version/s: 1.0.0
> [Python] possible to create StructArray with type that conflicts with child
> array's types
> -----------------------------------------------------------------------------------------
>
> Key: ARROW-6158
> URL: https://issues.apache.org/jira/browse/ARROW-6158
> Project: Apache Arrow
> Issue Type: Bug
> Components: Python
> Reporter: Joris Van den Bossche
> Priority: Major
> Fix For: 1.0.0
>
>
> Using the Python interface as example. This creates a {{StructArray}} where
> the field types don't match the child array types:
> {code}
> a = pa.array([1, 2, 3], type=pa.int64())
> b = pa.array(['a', 'b', 'c'], type=pa.string())
> inconsistent_fields = [pa.field('a', pa.int32()), pa.field('b', pa.float64())]
> a = pa.StructArray.from_arrays([a, b], fields=inconsistent_fields)
> {code}
> The above works fine. I didn't find anything that errors (eg conversion to
> pandas, slicing), also validation passes, but the type actually has the
> inconsistent child types:
> {code}
> In [2]: a
> Out[2]:
> <pyarrow.lib.StructArray object at 0x7f450af52eb8>
> -- is_valid: all not null
> -- child 0 type: int64
> [
> 1,
> 2,
> 3
> ]
> -- child 1 type: string
> [
> "a",
> "b",
> "c"
> ]
> In [3]: a.type
> Out[3]: StructType(struct<a: int32, b: double>)
> In [4]: a.to_pandas()
> Out[4]:
> array([{'a': 1, 'b': 'a'}, {'a': 2, 'b': 'b'}, {'a': 3, 'b': 'c'}],
> dtype=object)
> In [5]: a.validate()
> {code}
> Shouldn't this be disallowed somehow? (it could be checked in the Python
> {{from_arrays}} method, but maybe also in {{StructArray::Make}} which already
> checks for the number of fields vs arrays and a consistent array length).
> Similarly to discussion in ARROW-6132, I would also expect that this the
> {{ValidateArray}} catches this.
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