pitrou commented on a change in pull request #8805:
URL: https://github.com/apache/arrow/pull/8805#discussion_r542441007
##########
File path: python/pyarrow/tests/test_compute.py
##########
@@ -1017,3 +1017,51 @@ def test_partition_nth():
for i in range(pivot))
assert all(data[indices[i]] >= data[indices[pivot]]
for i in range(pivot, len(data)))
+
+
+def test_array_sort_indices():
+ arr = pa.array([1, 2, None, 0])
+ result = pc.array_sort_indices(arr)
+ assert result.to_pylist() == [3, 0, 1, 2]
+ result = pc.array_sort_indices(arr, order="ascending")
+ assert result.to_pylist() == [3, 0, 1, 2]
+ result = pc.array_sort_indices(arr, order="descending")
+ assert result.to_pylist() == [1, 0, 3, 2]
+
+ with pytest.raises(ValueError, match="not a valid order"):
+ pc.array_sort_indices(arr, order="nonscending")
+
+
+def test_sort_indices_array():
+ arr = pa.array([1, 2, None, 0])
+ result = pc.sort_indices(arr)
+ assert result.to_pylist() == [3, 0, 1, 2]
+ result = pc.sort_indices(arr, sort_keys=[("dummy", "ascending")])
Review comment:
Just thinking out loud, but another possibility would be
`sort_keys=["a", "-b"]` for `[("a", "ascending"), ("b", "descending")]`. Not
sure how that feels...
cc @xhochy for opinions.
##########
File path: python/pyarrow/includes/libarrow.pxd
##########
@@ -1788,6 +1788,25 @@ cdef extern from "arrow/compute/api.h" namespace
"arrow::compute" nogil:
CPartitionNthOptions(int64_t pivot)
int64_t pivot
+ enum CSortOrder" arrow::compute::SortOrder":
Review comment:
I think this should be `ctypedef enum` because
`arrow::compute::SortOrder` is a scoped num (it's declared as `enum class
SortOrder`.
Hopefully that'd fix the compile error on CI.
##########
File path: python/pyarrow/tests/test_compute.py
##########
@@ -1017,3 +1017,51 @@ def test_partition_nth():
for i in range(pivot))
assert all(data[indices[i]] >= data[indices[pivot]]
for i in range(pivot, len(data)))
+
+
+def test_array_sort_indices():
+ arr = pa.array([1, 2, None, 0])
+ result = pc.array_sort_indices(arr)
+ assert result.to_pylist() == [3, 0, 1, 2]
+ result = pc.array_sort_indices(arr, order="ascending")
+ assert result.to_pylist() == [3, 0, 1, 2]
+ result = pc.array_sort_indices(arr, order="descending")
+ assert result.to_pylist() == [1, 0, 3, 2]
+
+ with pytest.raises(ValueError, match="not a valid order"):
+ pc.array_sort_indices(arr, order="nonscending")
+
+
+def test_sort_indices_array():
+ arr = pa.array([1, 2, None, 0])
+ result = pc.sort_indices(arr)
+ assert result.to_pylist() == [3, 0, 1, 2]
+ result = pc.sort_indices(arr, sort_keys=[("dummy", "ascending")])
Review comment:
It's a bit of a pity to have such a verbose convention (having to type
"ascending" for every sort key). Apparently
[pandas](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.sort_values.html)
uses a separate `ascending` argument with is a list of bools, though that's
not very pretty either...
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