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# BSD 3-Clause License; see https://github.com/scikit-hep/awkward/blob/main/LICENSE
# ruff: noqa: E402
from __future__ import annotations
import io
import os
import numpy as np
import pytest
pa = pytest.importorskip("pyarrow")
pq = pytest.importorskip("pyarrow.parquet")
import awkward as ak
from awkward._connect.pyarrow.table_conv import (
AWKWARD_INFO_KEY,
array_with_replacement_type,
awkward_arrow_field_to_native,
collect_ak_arr_type_metadata,
convert_awkward_arrow_table_to_native,
convert_native_arrow_table_to_awkward,
native_arrow_field_to_akarraytype,
)
from awkward.operations import to_list
nested_ints = ak.Array([[[[[1, 2, 3], [], [4, 5]] * 5] * 3] * 2])
struct_array = ak.Array(
[
{"lbl": "item 1", "idx": 11, "ids": [1, 2, 3]},
{"lbl": "item 2", "idx": 12, "ids": [51, 52]},
{"lbl": "item 3", "idx": 13, "ids": [61, 62, 63, 64]},
],
with_name="my_items",
)
with_nulls = ak.Array([[11, None], [23], None])
option_types = ak.Array(
[[1, 2], [[10, 11, None], None, [3, 4, 5], ["one", "two"]], None]
)
(indexed, indexed_tuple) = (
# Unique for this test, contains nested types within the
ak.contents.IndexedArray(
ak.index.Index64(np.array([2, 1, 0], dtype=np.uint64)),
ak.contents.RecordArray(
[
ak.contents.ByteMaskedArray(
ak.index.Index8(np.array([False, True, False]).view(np.int8)),
ak.contents.NumpyArray(np.array([1.1, 2.2, 3.3])),
valid_when=False,
),
ak.contents.UnmaskedArray(
ak.contents.ListOffsetArray(
ak.index.Index32(np.array([0, 3, 3, 5], dtype=np.int32)),
ak.contents.NumpyArray(
np.array([1.1, 2.2, 3.3, 4.4, 5.5]),
),
),
),
],
None if is_tuple else ["x", "y"],
),
parameters={"__array__": "categorical", "foo": "thap"},
)
for is_tuple in (False, True)
)
(records, records_tuple) = (
ak.contents.RecordArray(
[
ak.contents.NumpyArray(
np.array([1.1, 2.2, 3.3]), parameters={"foo": "inner1"}
),
ak.contents.ListOffsetArray(
ak.index.Index32(np.array([0, 3, 3, 5], dtype=np.int32)),
ak.contents.NumpyArray(
np.array([1.1, 2.2, 3.3, 4.4, 5.5]), parameters={"foo": "inner2"}
),
),
],
None if is_tuple else ["x", "y"],
parameters={"foo": "outer"},
)
for is_tuple in (False, True)
)
@pytest.mark.parametrize(
"akarray, as_dict",
[
(nested_ints, False),
(struct_array, False),
(with_nulls, False),
(option_types, False),
(indexed, True),
(indexed_tuple, True),
(records, True),
(records_tuple, True),
(indexed, False),
(indexed_tuple, False),
(records, False),
(records_tuple, False),
],
)
def test_array_conversions(akarray, as_dict):
arrow_natv = ak.to_arrow(
akarray, categorical_as_dictionary=as_dict, extensionarray=False
)
arrow_extn = ak.to_arrow(
akarray, categorical_as_dictionary=as_dict, extensionarray=True
)
extn_field = pa.field("test_field", arrow_extn.type)
# Convert to native pyarrow types:
metadata = collect_ak_arr_type_metadata(extn_field)
conv_natv_field = awkward_arrow_field_to_native(extn_field)
assert conv_natv_field.type == arrow_natv.type
as_natv = array_with_replacement_type(arrow_extn, conv_natv_field.type)
assert as_natv == arrow_natv
# Complete a round-trip, back to AwkwardArrowArray
conv_extn_field = native_arrow_field_to_akarraytype(conv_natv_field, metadata)
assert conv_extn_field.type == arrow_extn.type
assert (
conv_extn_field.type._metadata_as_dict() == arrow_extn.type._metadata_as_dict()
)
conv_metadata = collect_ak_arr_type_metadata(conv_extn_field)
assert conv_metadata == metadata
# assert_equal_arrowextntypes(conv_extn_field.type, arrow_extn.type)
as_extn = array_with_replacement_type(as_natv, conv_extn_field.type)
assert as_extn == arrow_extn
assert as_extn.type._metadata_as_dict() == arrow_extn.type._metadata_as_dict()
# And back to Awkward array
rt_array = ak.from_arrow(as_extn, highlevel=True)
assert to_list(rt_array) == to_list(akarray)
# Deeper test of types
akarray_high = ak.Array(akarray)
if akarray_high.type.content.parameters.get("__categorical__", False) == as_dict:
# as_dict is supposed to go hand-in-hand with __categorical__: True, and if it
# does not, we do not round-trip perfectly. So only test when this is set correctly.
assert rt_array.type == akarray_high.type
ak_type_str_orig = io.StringIO()
ak_type_str_rtrp = io.StringIO()
akarray_high.type.show(stream=ak_type_str_orig)
rt_array.type.show(stream=ak_type_str_rtrp)
if ak_type_str_orig.getvalue() != ak_type_str_rtrp.getvalue():
print(" Original type:", ak_type_str_orig.getvalue())
print(" Rnd-trip type:", ak_type_str_rtrp.getvalue())
assert ak_type_str_orig.getvalue() == ak_type_str_rtrp.getvalue()
def test_table_conversion():
ak_tbl_like = ak.Array(
{
"struct_array": struct_array,
"with_nulls": with_nulls,
"option_types": option_types,
"indexed": indexed,
}
)
natv_tbl = ak.to_arrow_table(
ak_tbl_like, categorical_as_dictionary=True, extensionarray=False
)
extn_tbl = ak.to_arrow_table(
ak_tbl_like, categorical_as_dictionary=True, extensionarray=True
)
conv_natv_tbl = convert_awkward_arrow_table_to_native(extn_tbl)
assert (
conv_natv_tbl.schema == natv_tbl.schema
) # This comparison does not include metadata
assert conv_natv_tbl == natv_tbl
assert AWKWARD_INFO_KEY in conv_natv_tbl.schema.metadata
assert len(conv_natv_tbl["struct_array"].chunks[0].field(2).buffers()) == 4
# This verifies that our conversions are zero-copy for the table data
assert (
extn_tbl["struct_array"].chunks[0].storage.field(2).buffers()[3].address
== conv_natv_tbl["struct_array"].chunks[0].field(2).buffers()[3].address
)
conv_extn_tbl = convert_native_arrow_table_to_awkward(conv_natv_tbl)
assert conv_extn_tbl.schema == extn_tbl.schema
assert conv_extn_tbl == extn_tbl # Full Round-trip verification
assert AWKWARD_INFO_KEY not in conv_extn_tbl.schema.metadata
assert (
extn_tbl["struct_array"].chunks[0].storage.field(2).buffers()[3].address
== conv_extn_tbl["struct_array"].chunks[0].storage.field(2).buffers()[3].address
)
def test_selective_parquet(tmp_path):
filename = os.path.join(tmp_path, "whatever.parquet")
ak_tbl = ak.Array(
{
"with_nulls": with_nulls,
"struct_array": struct_array,
"indexed": indexed,
}
)
ak.to_parquet(ak_tbl, filename)
tbl_tr = ak.from_parquet(filename, columns=["struct_array", "indexed"])
assert to_list(tbl_tr["struct_array"]) == to_list(ak_tbl["struct_array"])
@pytest.mark.parametrize("doit", [False, True])
def test_empty(tmp_path, doit):
filename = os.path.join(tmp_path, "whatever.parquet")
ak.to_parquet(ak.Array([{"x": 1, "y": 1.1}])[0:0], filename, extensionarray=doit)
assert str(ak.from_parquet(filename).type) == "0 * {x: int64, y: float64}"
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