[jira] [Commented] (ARROW-8004) [Python] Define API for user-defined conversions of array cell values in pyarrow.array

["Joris Van den Bossche (Jira)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/ARROW-8004?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17055776#comment-17055776 ] 

Joris Van den Bossche commented on ARROW-8004:
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For a more limited use case than general objects, i.e. array-like objects, we could also think about checking for {{__array__}} and then convert to ListArray.

For example, now we can infer a list of lists or a list of numpy arrays, but will error on a list of pandas Series

> [Python] Define API for user-defined conversions of array cell values in pyarrow.array
> --------------------------------------------------------------------------------------
>
>                 Key: ARROW-8004
>                 URL: https://issues.apache.org/jira/browse/ARROW-8004
>             Project: Apache Arrow
>          Issue Type: Improvement
>          Components: Python
>            Reporter: Wes McKinney
>            Priority: Major
>
> Consider the statement
> {code}
> pyarrow.array([v0, v1, v2, v3])
> {code}
> or correspondingly
> {code}
> pyarrow.array(pd.Series([v0, v1, v2, v3], dtype=object))
> {code}
> where {{v0, ..., v4}} are instances of types with no built-in conversion-to-Arrow support in pyarrow. An API could be provided to allow user-defined unboxing to a data type that the library _does_ understand (like a NumPy array). One complexity is that if the unboxing is costly, we may need to "keep around" the unboxed value when doing multiple passes over the data (e.g. initially for type inference and then for conversion)



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