[I] [python] `.slice` methods should accept Arrow scalar types [arrow]

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

ivirshup opened a new issue, #51145:
URL: https://github.com/apache/arrow/issues/51145

   ### Describe the enhancement requested
   
   The `.slice` methods take two integers as arguments, but cannot take arrow integer types.
   
   ```python
   import pyarrow as pa
   
   a = pa.array([0, 1, 2, 3, 4, 5])
   
   a.slice(0, 4)
   # <pyarrow.lib.Int64Array object at 0x798d8fec2ce0>
   # [
   #   1,
   #   2,
   #   3,
   #   4
   # ]
   
   a.slice(a[0], a[4])
   # ---------------------------------------------------------------------------
   # TypeError                                 Traceback (most recent call last)
   # Cell In[12], line 1
   # ----> 1 a.slice(a[0], a[4])
   #
   # File pyarrow/array.pxi:1639, in pyarrow.lib.Array.slice()
   # -> 1639 'Could not get source, probably due dynamically evaluated source code.'
   #
   # TypeError: '<' not supported between instances of 'pyarrow.lib.Int64Scalar' and 'int'
   ```
   
   The same is true for tables:
   
   ```python
   t = pa.Table.from_pydict({"a": a})
   
   t.slice(a[0], a[4])
   # ---------------------------------------------------------------------------
   # TypeError                                 Traceback (most recent call last)
   # Cell In[13], line 1
   # ----> 1 t.slice(a[0], a[4])
   
   # File pyarrow/table.pxi:4299, in pyarrow.lib.Table.slice()
   # -> 4299 'Could not get source, probably due dynamically evaluated source code.'
   
   # TypeError: '<' not supported between instances of 'pyarrow.lib.Int64Scalar' and 'int'
   ```
   
   This is not generally true of other methods. For example, `.take` is fine with getting an arrow array. I can even do `a[slice(a[0], a[0] + a[4])]`, where that `slice` contains pyarrow scalars.
   
   I think it is kinda silly that if I have offsets for an arrow table in another arrow table I am having to convert those offsets to python integers (e.g. `t.slice(a[0].as_py(), a[4].as_py())`) or converting to indexing with a `slice` object.
   
   ### Component(s)
   
   Python


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Re: [I] [Python] `.slice` methods should accept Arrow scalar types [arrow]

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

AlenkaF closed issue #51145: [Python] `.slice` methods should accept Arrow scalar types
URL: https://github.com/apache/arrow/issues/51145


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Re: [I] [Python] `.slice` methods should accept Arrow scalar types [arrow]

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

YusefSyed commented on issue #51145:
URL: https://github.com/apache/arrow/issues/51145#issuecomment-5535944392

   take


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Re: [I] [Python] `.slice` methods should accept Arrow scalar types [arrow]

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

AlenkaF commented on issue #51145:
URL: https://github.com/apache/arrow/issues/51145#issuecomment-5829384609

   Issue resolved by pull request 51160
   https://github.com/apache/arrow/pull/51160


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Re: [I] [Python] `.slice` methods should accept Arrow scalar types [arrow]

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

AlenkaF commented on issue #51145:
URL: https://github.com/apache/arrow/issues/51145#issuecomment-5617017198

   Thanks for the issue @ivirshup 
   The difference between `.take` and `.slice` is that they take two different code paths. `.take` goes through the compute module code path, where [`_pack_compute_args`](https://github.com/apache/arrow/blob/926885f1b1ede73badd24c2e6f63c9429441e99a/python/pyarrow/_compute.pyx#L494) does the type mapping, then C++ compute functions are all called with `arrow::Datum` arguments. Whereas the `.slice` code path goes to the C++ `Array::Slice` which expects `int64_t offset` and `int64_t length`.
   
   I agree, `.slice` behavior could be improved on the Python side. Will look at the PR now.


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