[jira] [Commented] (ARROW-17834) [Python] Allow creating ExtensionArray through pa.array(..) constructor

["Chang She (Jira)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/ARROW-17834?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17613071#comment-17613071 ] 

Chang She commented on ARROW-17834:
-----------------------------------

w00t

> [Python] Allow creating ExtensionArray through pa.array(..) constructor
> -----------------------------------------------------------------------
>
>                 Key: ARROW-17834
>                 URL: https://issues.apache.org/jira/browse/ARROW-17834
>             Project: Apache Arrow
>          Issue Type: Improvement
>          Components: Python
>            Reporter: Joris Van den Bossche
>            Assignee: Joris Van den Bossche
>            Priority: Major
>             Fix For: 10.0.0
>
>
> Currently, creating an ExtensionArray from a python sequence (or numpy array, ..) requires the following:
> {code:python}
> from pyarrow.tests.test_extension_type import IntegerType
> storage_array = pa.array([1, 2, 3])
> ext_arr = pa.ExtensionArray.from_storage(IntegerType(), storage_array)
> {code}
> While doing this directly in {{pa.array(..)}} doesn't work:
> {code:python}
> >>> pa.array([1, 2, 3], type=IntegerType())
> ArrowNotImplementedError: extension
> {code}
> I think it should be possible to basically to the ExtensionArray.from_storage under the hood in {{pa.array(..)}} when the specified type is an extension type?
> I think this should also enable converting from a pandas DataFrame (with a column with matching storage values) to a Table with a specified schema that includes an extension type. Like:
> {code}
> df = pd.DataFrame({'a': [1, 2, 3]})
> pa.table(df, schema=pa.schema([('a', IntegerType())]))
> {code}



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