amol- commented on a change in pull request #10101:
URL: https://github.com/apache/arrow/pull/10101#discussion_r618381447
##########
File path: python/pyarrow/tests/test_array.py
##########
@@ -688,6 +688,69 @@ def test_dictionary_from_numpy():
assert d2[i].as_py() == dictionary[indices[i]]
+def test_dictionary_to_numpy():
+ expected = pa.array(
+ ["foo", "bar", None, "foo"]
+ ).to_numpy(zero_copy_only=False)
+ a = pa.DictionaryArray.from_arrays(
+ pa.array([0, 1, None, 0]),
+ pa.array(['foo', 'bar'])
+ )
+ assert (a.to_numpy(zero_copy_only=False) == expected).all()
+
+ with pytest.raises(pa.ArrowInvalid):
+ # to_numpy takes for granted that when zero_copy_only=True
+ # there will be no nulls.
+ # If that changes, nulls handling will have to be updated in to_numpy
+ # as we won't be able to rely anymore on decoding the DictionaryArray
+ # to handle nulls.
+ a.to_numpy(zero_copy_only=True)
+
+ anonulls = pa.DictionaryArray.from_arrays(
+ pa.array([0, 1, 1, 0]),
+ pa.array(['foo', 'bar'])
+ )
+ expected = pa.array(
+ ["foo", "bar", "bar", "foo"]
+ ).to_numpy(zero_copy_only=False)
Review comment:
My goal was mostly to test that "wathever decoding a normal `Array`
leads to, decoding a `DictionaryArray` leads to the same exact result". I felt
it was more future proof than testing for the actual value. But if you feel
it's better to test for the actual resulting numpy array I'll gladly change
that.
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