jorisvandenbossche commented on code in PR #40341:
URL: https://github.com/apache/arrow/pull/40341#discussion_r1524478032
##########
python/pyarrow/array.pxi:
##########
@@ -336,11 +338,21 @@ def array(object obj, type=None, mask=None, size=None,
from_pandas=None,
if pandas_api.have_pandas:
values, type = pandas_api.compat.get_datetimetz_type(
values, obj.dtype, type)
- result = _ndarray_to_array(values, mask, type, c_from_pandas, safe,
- pool)
+ if type and type.id == _Type_RUN_END_ENCODED:
+ arr = _ndarray_to_array(
+ values, mask, type.value_type, c_from_pandas, safe, pool)
+ result = run_end_encode(arr, run_end_type=type.run_end_type)
Review Comment:
You can pass the `pool` here as well
##########
python/pyarrow/array.pxi:
##########
@@ -21,6 +21,8 @@ import os
import warnings
from cython import sizeof
+from pyarrow.compute import run_end_encode
Review Comment:
Instead of this import here (which isn't guaranteed to work, as one can
build pyarrow without compute support), you can use `_pc()` to get the compute
module where calling `run_end_encode` (see the other examples of that in this
file)
##########
python/pyarrow/tests/test_array.py:
##########
@@ -3579,6 +3579,42 @@ def test_run_end_encoded_from_buffers():
1, offset, children)
+def test_run_end_encoded_from_array_with_type():
+ run_ends = pa.array([1, 3, 6], type=pa.int32())
+ values = pa.array([1, 2, 3], type=pa.int64())
+
+ ree_type = pa.run_end_encoded(pa.int32(), pa.int64())
+
+ arr = [1, 2, 2, 3, 3, 3]
+ result = pa.array(arr, type=ree_type)
+
+ assert result.run_ends.equals(run_ends)
+ assert result.values.equals(values)
Review Comment:
Instead of each time checking both run ends and values, I think you could
also once created the expected result (`expected =
pa.RunEndEncodedArray.from_arrays(run_ends, values, ree_type)`), and then just
check `assert result.equals(expected)`
##########
python/pyarrow/tests/test_array.py:
##########
@@ -3579,6 +3579,42 @@ def test_run_end_encoded_from_buffers():
1, offset, children)
+def test_run_end_encoded_from_array_with_type():
+ run_ends = pa.array([1, 3, 6], type=pa.int32())
+ values = pa.array([1, 2, 3], type=pa.int64())
+
+ ree_type = pa.run_end_encoded(pa.int32(), pa.int64())
+
+ arr = [1, 2, 2, 3, 3, 3]
+ result = pa.array(arr, type=ree_type)
+
+ assert result.run_ends.equals(run_ends)
+ assert result.values.equals(values)
+
+ result = pa.array(np.array(arr), type=ree_type)
Review Comment:
Can you also do one more version of this with `pa.array(arr)` as input?
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