[GitHub] [arrow] chairmank commented on issue #19157: [Python] Implement pa.array() with type=union type

["chairmank (via GitHub)" <gi...@apache.org>]

chairmank commented on issue #19157:
URL: https://github.com/apache/arrow/issues/19157#issuecomment-1528037394

   I would also like `pyarrow.array` to automatically convert Python values when a sparse union or dense union type is explicitly specified. I frequently use dense union types to represent data that originated in protocol buffers with `oneof` fields. It is inconvenient to have to implement special handling of this case when the target Arrow schema is known.
   
   Also, I would like to politely observe that example code snippets in previous comments are misleading, because they do not distinguish between child fields that happen to have the same data type.
   
   > [Antoine Pitrou](https://issues.apache.org/jira/browse/ARROW-2774?focusedCommentId=17392943) / @pitrou: I'm still not convinced this is a good idea. Consider `pa.array([1, 2.3])`. Should it return a `union<int64, float64>`?
   > 
   > cc @amol- for advice.
   
   > [Joris Van den Bossche](https://issues.apache.org/jira/browse/ARROW-2774?focusedCommentId=17393143) / @jorisvandenbossche: Agreed that we shouldn't do that by default, but we can keep this issue about actually supporting it? Because now construction of a union array from a python sequence is not even supported when explicitly mentioning the type.
   > 
   > ```java
   > In [52]: typ = pa.union([pa.field("int", "int64"), pa.field("float", "float64")], mode="sparse")
   > 
   > In [53]: pa.array([1, 2.3], type=typ)
   > ...
   > ArrowNotImplementedError: sparse_union
   > ../src/arrow/util/converter.h:265  VisitTypeInline(*visitor.type, &visitor)
   > ../src/arrow/python/python_to_arrow.cc:1015  (MakeConverter<PyConverter, PyConverterTrait>( options.type, options, pool))
   > ```
   
   As an example, consider the following union type:
   ```
   >>> string_predicate_type = pa.dense_union([
   ...     pa.field("regexp", pa.string(), False),
   ...     pa.field("regexp", pa.string(), False),
   ...     pa.field("is_null", pa.null()),
   ... ])
   >>> string_predicate_type
   DenseUnionType(dense_union<regexp: string not null=0, regexp: string not null=1, is_null: null=2>)
   ```
   
   Both `equals` and `regexp` are string, but they are semantically distinct. For `pyarrow.array` to convert Python values to the correct child field type, the values ought to be tagged:
   ```
   pa.array([{"equals": "foo"}, {"regexp": "[0-9a-f]{16}"}, {"is_null": None}], type=string_predicate_type)
   ```
   
   
   
   
   
   
   
   
   


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