jorisvandenbossche commented on code in PR #39813:
URL: https://github.com/apache/arrow/pull/39813#discussion_r1481539129
##########
python/pyarrow/array.pxi:
##########
@@ -2570,23 +2588,18 @@ cdef class ListViewArray(Array):
The values include null elements from sub-lists:
>>> import pyarrow as pa
- >>> values = [[1, 2], [3, 4, None, 6]]
- >>> offsets = [0, None, 2]
+ >>> values = [1, 2, None, 3, 4]
+ >>> offsets = [0, 0, 1]
>>> sizes = [2, 0, 4]
>>> array = pa.ListViewArray.from_arrays(offsets, sizes, values)
>>> array.values
Review Comment:
Maybe also show `array` itself first (so you can compare with that output)?
##########
python/pyarrow/array.pxi:
##########
@@ -2557,9 +2572,12 @@ cdef class ListViewArray(Array):
Return the underlying array of values which backs the ListViewArray
ignoring the array's offset and sizes.
- If any of the list elements are null, but are backed by a
- non-empty sub-list, those elements will be included in the
- output.
+ The values array may be out of order and/or contain additional values
+ that are not found in the logical representation of the array. The only
+ guarantee is that each non-null value in the ListView Array is
contiguous.
+
+ Compare with :meth:`flatten`, which returns only the non-null
+ values taking into consideration the array's offset.
Review Comment:
```suggestion
values taking into consideration the array's order and offset.
```
##########
python/pyarrow/array.pxi:
##########
@@ -2842,20 +2910,65 @@ cdef class LargeListViewArray(Array):
--------
>>> import pyarrow as pa
- >>> values = [[1, 2], [3, 4, None, 6]]
- >>> offsets = [0, None, 2]
+ >>> values = [1, 2, None, 3, 4]
+ >>> offsets = [0, 0, 1]
>>> sizes = [2, 0, 4]
>>> array = pa.LargeListViewArray.from_arrays(offsets, sizes, values)
- >>> array.offsets
+ >>> array.sizes
<pyarrow.lib.Int64Array object at ...>
[
+ 2,
0,
- 0,
- 2
+ 4
]
"""
return pyarrow_wrap_array((<CLargeListViewArray*> self.ap).sizes())
+ def flatten(self, pool=None):
Review Comment:
```suggestion
def flatten(self, memory_pool=None):
```
##########
python/pyarrow/array.pxi:
##########
@@ -2638,20 +2651,66 @@ cdef class ListViewArray(Array):
Examples
--------
>>> import pyarrow as pa
- >>> values = [[1, 2], [3, 4, None, 6]]
- >>> offsets = [0, None, 2]
+ >>> values = [1, 2, None, 3, 4]
+ >>> offsets = [0, 0, 1]
>>> sizes = [2, 0, 4]
>>> array = pa.ListViewArray.from_arrays(offsets, sizes, values)
- >>> array.offsets
+ >>> array.sizes
<pyarrow.lib.Int32Array object at ...>
[
+ 2,
0,
- 0,
- 2
+ 4
]
"""
return pyarrow_wrap_array((<CListViewArray*> self.ap).sizes())
+ def flatten(self, pool=None):
Review Comment:
```suggestion
def flatten(self, memory_pool=None):
```
We are not very consistent about it, but at least in this file we use
`memory_pool` more than `pool` .. (something to clean up at some point)
##########
python/pyarrow/array.pxi:
##########
@@ -2638,20 +2651,66 @@ cdef class ListViewArray(Array):
Examples
--------
>>> import pyarrow as pa
- >>> values = [[1, 2], [3, 4, None, 6]]
- >>> offsets = [0, None, 2]
+ >>> values = [1, 2, None, 3, 4]
+ >>> offsets = [0, 0, 1]
>>> sizes = [2, 0, 4]
>>> array = pa.ListViewArray.from_arrays(offsets, sizes, values)
- >>> array.offsets
+ >>> array.sizes
<pyarrow.lib.Int32Array object at ...>
[
+ 2,
0,
- 0,
- 2
+ 4
]
"""
return pyarrow_wrap_array((<CListViewArray*> self.ap).sizes())
+ def flatten(self, pool=None):
+ """
+ Unnest this ListViewArray by one level.
+
+ The returned Array is logically a concatenation of all the sub-lists
+ in this Array.
+
+ Note that this method is different from ``self.values`` in that
+ it takes care of the slicing offset as well as null elements backed
+ by non-empty sub-lists.
+
+ Parameters
+ ----------
+ pool : MemoryPool, optional
+
+ Returns
+ -------
+ result : Array
+
+ Examples
+ --------
+
+ >>> import pyarrow as pa
+ >>> values = [1, 2, 3, 4]
+ >>> offsets = [2, 1, 0]
+ >>> sizes = [2, 2, 2]
+ >>> array = pa.ListViewArray.from_arrays(offsets, sizes, values)
+ >>> array.flatten()
Review Comment:
Maybe here show both `array` and `array.values` outputs as well so it's
easier to compare the different ones?
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