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https://issues.apache.org/jira/browse/ARROW-12609?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Sergey Mozharov updated ARROW-12609:
------------------------------------
    Description: 
For List-like data types, the scalar corresponding to a missing value has 
'___len___' attribute, but TypeError is raised when it is accessed
{code:java}
import pyarrow as pa

data_type = pa.list_(pa.struct([
    ('a', pa.int64()),
    ('b', pa.bool_())
]))
data = [[{'a': 1, 'b': False}, {'a': 2, 'b': True}], None]
arr = pa.array(data, type=data_type)
missing_scalar = arr[1]  # <pyarrow.ListScalar: None>
assert hasattr(missing_scalar, '__len__')
assert len(missing_scalar) == 0  # --> TypeError: object of type 'NoneType' has 
no len()
{code}
Expected behavior: length is expected to be 0.

This issue causes several pandas unit tests to fail when an ExtensionArray 
backed by arrow array with this data type is built.

This behavior is also inconsistent with a similar example where the data type 
is a struct:
{code:java}
import pyarrow as pa

data_type = pa.struct([
    ('a', pa.int64()),
    ('b', pa.bool_())
])
data = [{'a': 1, 'b': False}, None]
arr = pa.array(data, type=data_type)
missing_scalar = arr[1]  # <pyarrow.StructScalar: None>
assert hasattr(missing_scalar, '__len__')
assert len(missing_scalar) == 0  # Ok
{code}
 In this second example the TypeError is not raised.

  was:
For List-like data types, the scalar type corresponding to a missing value has 
'___len___' attribute, but TypeError is raised when it is accessed
{code:java}
import pyarrow as pa

data_type = pa.list_(pa.struct([
    ('a', pa.int64()),
    ('b', pa.bool_())
]))
data = [[{'a': 1, 'b': False}, {'a': 2, 'b': True}], None]
arr = pa.array(data, type=data_type)
missing_scalar = arr[1]  # <pyarrow.ListScalar: None>
assert hasattr(missing_scalar, '__len__')
assert len(missing_scalar) == 0  # --> TypeError: object of type 'NoneType' has 
no len()
{code}
Expected behavior: length is expected to be 0.

This issue causes several pandas unit tests to fail when an ExtensionArray 
backed by arrow array with this data type is built.

This behavior is also inconsistent with a similar example where the data type 
is a struct:
{code:java}
import pyarrow as pa

data_type = pa.struct([
    ('a', pa.int64()),
    ('b', pa.bool_())
])
data = [{'a': 1, 'b': False}, None]
arr = pa.array(data, type=data_type)
missing_scalar = arr[1]  # <pyarrow.StructScalar: None>
assert hasattr(missing_scalar, '__len__')
assert len(missing_scalar) == 0  # Ok
{code}
 In this second example the TypeError is not raised.


> TypeError when accessing length of an invalid ListScalar
> --------------------------------------------------------
>
>                 Key: ARROW-12609
>                 URL: https://issues.apache.org/jira/browse/ARROW-12609
>             Project: Apache Arrow
>          Issue Type: Bug
>          Components: Python
>    Affects Versions: 3.0.0, 4.0.0
>         Environment: Windows 10
> python=3.9.2
> pyarrow=4.0.0 (3.0.0 has the same behavior)
>            Reporter: Sergey Mozharov
>            Priority: Major
>
> For List-like data types, the scalar corresponding to a missing value has 
> '___len___' attribute, but TypeError is raised when it is accessed
> {code:java}
> import pyarrow as pa
> data_type = pa.list_(pa.struct([
>     ('a', pa.int64()),
>     ('b', pa.bool_())
> ]))
> data = [[{'a': 1, 'b': False}, {'a': 2, 'b': True}], None]
> arr = pa.array(data, type=data_type)
> missing_scalar = arr[1]  # <pyarrow.ListScalar: None>
> assert hasattr(missing_scalar, '__len__')
> assert len(missing_scalar) == 0  # --> TypeError: object of type 'NoneType' 
> has no len()
> {code}
> Expected behavior: length is expected to be 0.
> This issue causes several pandas unit tests to fail when an ExtensionArray 
> backed by arrow array with this data type is built.
> This behavior is also inconsistent with a similar example where the data type 
> is a struct:
> {code:java}
> import pyarrow as pa
> data_type = pa.struct([
>     ('a', pa.int64()),
>     ('b', pa.bool_())
> ])
> data = [{'a': 1, 'b': False}, None]
> arr = pa.array(data, type=data_type)
> missing_scalar = arr[1]  # <pyarrow.StructScalar: None>
> assert hasattr(missing_scalar, '__len__')
> assert len(missing_scalar) == 0  # Ok
> {code}
>  In this second example the TypeError is not raised.



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