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3059 lines (2489 loc) · 112 KB
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# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
import datetime
from functools import lru_cache, partial
import inspect
import itertools
import os
import pickle
import pytest
import random
import sys
import textwrap
import numpy as np
try:
import pandas as pd
except ImportError:
pd = None
import pyarrow as pa
import pyarrow.compute as pc
all_array_types = [
('bool', [True, False, False, True, True]),
('uint8', np.arange(5)),
('int8', np.arange(5)),
('uint16', np.arange(5)),
('int16', np.arange(5)),
('uint32', np.arange(5)),
('int32', np.arange(5)),
('uint64', np.arange(5, 10)),
('int64', np.arange(5, 10)),
('float', np.arange(0, 0.5, 0.1)),
('double', np.arange(0, 0.5, 0.1)),
('string', ['a', 'b', None, 'ddd', 'ee']),
('binary', [b'a', b'b', b'c', b'ddd', b'ee']),
(pa.binary(3), [b'abc', b'bcd', b'cde', b'def', b'efg']),
(pa.list_(pa.int8()), [[1, 2], [3, 4], [5, 6], None, [9, 16]]),
(pa.large_list(pa.int16()), [[1], [2, 3, 4], [5, 6], None, [9, 16]]),
(pa.struct([('a', pa.int8()), ('b', pa.int8())]), [
{'a': 1, 'b': 2}, None, {'a': 3, 'b': 4}, None, {'a': 5, 'b': 6}]),
]
exported_functions = [
func for (name, func) in sorted(pc.__dict__.items())
if hasattr(func, '__arrow_compute_function__')]
exported_option_classes = [
cls for (name, cls) in sorted(pc.__dict__.items())
if (isinstance(cls, type) and
cls is not pc.FunctionOptions and
issubclass(cls, pc.FunctionOptions))]
numerical_arrow_types = [
pa.int8(),
pa.int16(),
pa.int64(),
pa.uint8(),
pa.uint16(),
pa.uint64(),
pa.float32(),
pa.float64()
]
def test_exported_functions():
# Check that all exported concrete functions can be called with
# the right number of arguments.
# Note that unregistered functions (e.g. with a mismatching name)
# will raise KeyError.
functions = exported_functions
assert len(functions) >= 10
for func in functions:
desc = func.__arrow_compute_function__
if desc['options_required']:
# Skip this function as it will fail with a different error
# message if we don't pass an options instance.
continue
arity = desc['arity']
if arity == 0:
continue
if arity is Ellipsis:
args = [object()] * 3
else:
args = [object()] * arity
with pytest.raises(TypeError,
match="Got unexpected argument type "
"<class 'object'> for compute function"):
func(*args)
def test_hash_aggregate_not_exported():
# Ensure we are not leaking hash aggregate functions
# which are not callable by themselves.
for func in exported_functions:
arrow_f = pc.get_function(func.__arrow_compute_function__["name"])
assert arrow_f.kind != "hash_aggregate"
def test_exported_option_classes():
classes = exported_option_classes
assert len(classes) >= 10
for cls in classes:
# Option classes must have an introspectable constructor signature,
# and that signature should not have any *args or **kwargs.
sig = inspect.signature(cls)
for param in sig.parameters.values():
assert param.kind not in (param.VAR_POSITIONAL,
param.VAR_KEYWORD)
def test_option_class_equality():
options = [
pc.ArraySortOptions(),
pc.AssumeTimezoneOptions("UTC"),
pc.CastOptions.safe(pa.int8()),
pc.CountOptions(),
pc.DayOfWeekOptions(count_from_zero=False, week_start=0),
pc.DictionaryEncodeOptions(),
pc.ElementWiseAggregateOptions(skip_nulls=True),
pc.ExtractRegexOptions("pattern"),
pc.FilterOptions(),
pc.IndexOptions(pa.scalar(1)),
pc.JoinOptions(),
pc.ListSliceOptions(0, -1, 1, True),
pc.MakeStructOptions(["field", "names"],
field_nullability=[True, True],
field_metadata=[pa.KeyValueMetadata({"a": "1"}),
pa.KeyValueMetadata({"b": "2"})]),
pc.MapLookupOptions(pa.scalar(1), "first"),
pc.MatchSubstringOptions("pattern"),
pc.ModeOptions(),
pc.NullOptions(),
pc.PadOptions(5),
pc.PartitionNthOptions(1, null_placement="at_start"),
pc.CumulativeSumOptions(start=0, skip_nulls=False),
pc.QuantileOptions(),
pc.RandomOptions(),
pc.RankOptions(sort_keys="ascending",
null_placement="at_start", tiebreaker="max"),
pc.ReplaceSliceOptions(0, 1, "a"),
pc.ReplaceSubstringOptions("a", "b"),
pc.RoundOptions(2, "towards_infinity"),
pc.RoundTemporalOptions(1, "second", week_starts_monday=True),
pc.RoundToMultipleOptions(100, "towards_infinity"),
pc.ScalarAggregateOptions(),
pc.SelectKOptions(0, sort_keys=[("b", "ascending")]),
pc.SetLookupOptions(pa.array([1])),
pc.SliceOptions(0, 1, 1),
pc.SortOptions([("dummy", "descending")], null_placement="at_start"),
pc.SplitOptions(),
pc.SplitPatternOptions("pattern"),
pc.StrftimeOptions(),
pc.StrptimeOptions("%Y", "s", True),
pc.StructFieldOptions(indices=[]),
pc.TakeOptions(),
pc.TDigestOptions(),
pc.TrimOptions(" "),
pc.Utf8NormalizeOptions("NFKC"),
pc.VarianceOptions(),
pc.WeekOptions(week_starts_monday=True, count_from_zero=False,
first_week_is_fully_in_year=False),
]
# TODO: We should test on windows once ARROW-13168 is resolved.
# Timezone database is not available on Windows yet
if sys.platform != 'win32':
options.append(pc.AssumeTimezoneOptions("Europe/Ljubljana"))
classes = {type(option) for option in options}
for cls in exported_option_classes:
# Timezone database is not available on Windows yet
if cls not in classes and sys.platform != 'win32' and \
cls != pc.AssumeTimezoneOptions:
try:
options.append(cls())
except TypeError:
pytest.fail(f"Options class is not tested: {cls}")
for option in options:
assert option == option
assert repr(option).startswith(option.__class__.__name__)
buf = option.serialize()
deserialized = pc.FunctionOptions.deserialize(buf)
assert option == deserialized
assert repr(option) == repr(deserialized)
for option1, option2 in zip(options, options[1:]):
assert option1 != option2
assert repr(pc.IndexOptions(pa.scalar(1))) == "IndexOptions(value=int64:1)"
assert repr(pc.ArraySortOptions()) == \
"ArraySortOptions(order=Ascending, null_placement=AtEnd)"
def test_list_functions():
assert len(pc.list_functions()) > 10
assert "add" in pc.list_functions()
def _check_get_function(name, expected_func_cls, expected_ker_cls,
min_num_kernels=1):
func = pc.get_function(name)
assert isinstance(func, expected_func_cls)
n = func.num_kernels
assert n >= min_num_kernels
assert n == len(func.kernels)
assert all(isinstance(ker, expected_ker_cls) for ker in func.kernels)
def test_get_function_scalar():
_check_get_function("add", pc.ScalarFunction, pc.ScalarKernel, 8)
def test_get_function_vector():
_check_get_function("unique", pc.VectorFunction, pc.VectorKernel, 8)
def test_get_function_scalar_aggregate():
_check_get_function("mean", pc.ScalarAggregateFunction,
pc.ScalarAggregateKernel, 8)
def test_get_function_hash_aggregate():
_check_get_function("hash_sum", pc.HashAggregateFunction,
pc.HashAggregateKernel, 1)
def test_call_function_with_memory_pool():
arr = pa.array(["foo", "bar", "baz"])
indices = np.array([2, 2, 1])
result1 = arr.take(indices)
result2 = pc.call_function('take', [arr, indices],
memory_pool=pa.default_memory_pool())
expected = pa.array(["baz", "baz", "bar"])
assert result1.equals(expected)
assert result2.equals(expected)
result3 = pc.take(arr, indices, memory_pool=pa.default_memory_pool())
assert result3.equals(expected)
def test_pickle_functions():
# Pickle registered functions
for name in pc.list_functions():
func = pc.get_function(name)
reconstructed = pickle.loads(pickle.dumps(func))
assert type(reconstructed) is type(func)
assert reconstructed.name == func.name
assert reconstructed.arity == func.arity
assert reconstructed.num_kernels == func.num_kernels
def test_pickle_global_functions():
# Pickle global wrappers (manual or automatic) of registered functions
for name in pc.list_functions():
try:
func = getattr(pc, name)
except AttributeError:
# hash_aggregate functions are not exported as callables.
continue
reconstructed = pickle.loads(pickle.dumps(func))
assert reconstructed is func
def test_function_attributes():
# Sanity check attributes of registered functions
for name in pc.list_functions():
func = pc.get_function(name)
assert isinstance(func, pc.Function)
assert func.name == name
kernels = func.kernels
assert func.num_kernels == len(kernels)
assert all(isinstance(ker, pc.Kernel) for ker in kernels)
repr(func)
for ker in kernels:
repr(ker)
def test_input_type_conversion():
# Automatic array conversion from Python
arr = pc.add([1, 2], [4, None])
assert arr.to_pylist() == [5, None]
# Automatic scalar conversion from Python
arr = pc.add([1, 2], 4)
assert arr.to_pylist() == [5, 6]
# Other scalar type
assert pc.equal(["foo", "bar", None],
"foo").to_pylist() == [True, False, None]
@pytest.mark.parametrize('arrow_type', numerical_arrow_types)
def test_sum_array(arrow_type):
arr = pa.array([1, 2, 3, 4], type=arrow_type)
assert arr.sum().as_py() == 10
assert pc.sum(arr).as_py() == 10
arr = pa.array([1, 2, 3, 4, None], type=arrow_type)
assert arr.sum().as_py() == 10
assert pc.sum(arr).as_py() == 10
arr = pa.array([None], type=arrow_type)
assert arr.sum().as_py() is None # noqa: E711
assert pc.sum(arr).as_py() is None # noqa: E711
assert arr.sum(min_count=0).as_py() == 0
assert pc.sum(arr, min_count=0).as_py() == 0
arr = pa.array([], type=arrow_type)
assert arr.sum().as_py() is None # noqa: E711
assert arr.sum(min_count=0).as_py() == 0
assert pc.sum(arr, min_count=0).as_py() == 0
@pytest.mark.parametrize('arrow_type', numerical_arrow_types)
def test_sum_chunked_array(arrow_type):
arr = pa.chunked_array([pa.array([1, 2, 3, 4], type=arrow_type)])
assert pc.sum(arr).as_py() == 10
arr = pa.chunked_array([
pa.array([1, 2], type=arrow_type), pa.array([3, 4], type=arrow_type)
])
assert pc.sum(arr).as_py() == 10
arr = pa.chunked_array([
pa.array([1, 2], type=arrow_type),
pa.array([], type=arrow_type),
pa.array([3, 4], type=arrow_type)
])
assert pc.sum(arr).as_py() == 10
arr = pa.chunked_array((), type=arrow_type)
assert arr.num_chunks == 0
assert pc.sum(arr).as_py() is None # noqa: E711
assert pc.sum(arr, min_count=0).as_py() == 0
def test_mode_array():
# ARROW-9917
arr = pa.array([1, 1, 3, 4, 3, 5], type='int64')
mode = pc.mode(arr)
assert len(mode) == 1
assert mode[0].as_py() == {"mode": 1, "count": 2}
mode = pc.mode(arr, n=2)
assert len(mode) == 2
assert mode[0].as_py() == {"mode": 1, "count": 2}
assert mode[1].as_py() == {"mode": 3, "count": 2}
arr = pa.array([], type='int64')
assert len(pc.mode(arr)) == 0
arr = pa.array([1, 1, 3, 4, 3, None], type='int64')
mode = pc.mode(arr, skip_nulls=False)
assert len(mode) == 0
mode = pc.mode(arr, min_count=6)
assert len(mode) == 0
mode = pc.mode(arr, skip_nulls=False, min_count=5)
assert len(mode) == 0
arr = pa.array([True, False])
mode = pc.mode(arr, n=2)
assert len(mode) == 2
assert mode[0].as_py() == {"mode": False, "count": 1}
assert mode[1].as_py() == {"mode": True, "count": 1}
def test_mode_chunked_array():
# ARROW-9917
arr = pa.chunked_array([pa.array([1, 1, 3, 4, 3, 5], type='int64')])
mode = pc.mode(arr)
assert len(mode) == 1
assert mode[0].as_py() == {"mode": 1, "count": 2}
mode = pc.mode(arr, n=2)
assert len(mode) == 2
assert mode[0].as_py() == {"mode": 1, "count": 2}
assert mode[1].as_py() == {"mode": 3, "count": 2}
arr = pa.chunked_array((), type='int64')
assert arr.num_chunks == 0
assert len(pc.mode(arr)) == 0
def test_empty_chunked_array():
msg = "cannot construct ChunkedArray from empty vector and omitted type"
with pytest.raises(pa.ArrowInvalid, match=msg):
pa.chunked_array([])
pa.chunked_array([], type=pa.int8())
def test_variance():
data = [1, 2, 3, 4, 5, 6, 7, 8]
assert pc.variance(data).as_py() == 5.25
assert pc.variance(data, ddof=0).as_py() == 5.25
assert pc.variance(data, ddof=1).as_py() == 6.0
def test_count_substring():
for (ty, offset) in [(pa.string(), pa.int32()),
(pa.large_string(), pa.int64())]:
arr = pa.array(["ab", "cab", "abcab", "ba", "AB", None], type=ty)
result = pc.count_substring(arr, "ab")
expected = pa.array([1, 1, 2, 0, 0, None], type=offset)
assert expected == result
result = pc.count_substring(arr, "ab", ignore_case=True)
expected = pa.array([1, 1, 2, 0, 1, None], type=offset)
assert expected == result
def test_count_substring_regex():
for (ty, offset) in [(pa.string(), pa.int32()),
(pa.large_string(), pa.int64())]:
arr = pa.array(["ab", "cab", "baAacaa", "ba", "AB", None], type=ty)
result = pc.count_substring_regex(arr, "a+")
expected = pa.array([1, 1, 3, 1, 0, None], type=offset)
assert expected.equals(result)
result = pc.count_substring_regex(arr, "a+", ignore_case=True)
expected = pa.array([1, 1, 2, 1, 1, None], type=offset)
assert expected.equals(result)
def test_find_substring():
for ty in [pa.string(), pa.binary(), pa.large_string(), pa.large_binary()]:
arr = pa.array(["ab", "cab", "ba", None], type=ty)
result = pc.find_substring(arr, "ab")
assert result.to_pylist() == [0, 1, -1, None]
result = pc.find_substring_regex(arr, "a?b")
assert result.to_pylist() == [0, 1, 0, None]
arr = pa.array(["ab*", "cAB*", "ba", "aB?"], type=ty)
result = pc.find_substring(arr, "aB*", ignore_case=True)
assert result.to_pylist() == [0, 1, -1, -1]
result = pc.find_substring_regex(arr, "a?b", ignore_case=True)
assert result.to_pylist() == [0, 1, 0, 0]
def test_match_like():
arr = pa.array(["ab", "ba%", "ba", "ca%d", None])
result = pc.match_like(arr, r"_a\%%")
expected = pa.array([False, True, False, True, None])
assert expected.equals(result)
arr = pa.array(["aB", "bA%", "ba", "ca%d", None])
result = pc.match_like(arr, r"_a\%%", ignore_case=True)
expected = pa.array([False, True, False, True, None])
assert expected.equals(result)
result = pc.match_like(arr, r"_a\%%", ignore_case=False)
expected = pa.array([False, False, False, True, None])
assert expected.equals(result)
def test_match_substring():
arr = pa.array(["ab", "abc", "ba", None])
result = pc.match_substring(arr, "ab")
expected = pa.array([True, True, False, None])
assert expected.equals(result)
arr = pa.array(["áB", "Ábc", "ba", None])
result = pc.match_substring(arr, "áb", ignore_case=True)
expected = pa.array([True, True, False, None])
assert expected.equals(result)
result = pc.match_substring(arr, "áb", ignore_case=False)
expected = pa.array([False, False, False, None])
assert expected.equals(result)
def test_match_substring_regex():
arr = pa.array(["ab", "abc", "ba", "c", None])
result = pc.match_substring_regex(arr, "^a?b")
expected = pa.array([True, True, True, False, None])
assert expected.equals(result)
arr = pa.array(["aB", "Abc", "BA", "c", None])
result = pc.match_substring_regex(arr, "^a?b", ignore_case=True)
expected = pa.array([True, True, True, False, None])
assert expected.equals(result)
result = pc.match_substring_regex(arr, "^a?b", ignore_case=False)
expected = pa.array([False, False, False, False, None])
assert expected.equals(result)
def test_trim():
# \u3000 is unicode whitespace
arr = pa.array([" foo", None, " \u3000foo bar \t"])
result = pc.utf8_trim_whitespace(arr)
expected = pa.array(["foo", None, "foo bar"])
assert expected.equals(result)
arr = pa.array([" foo", None, " \u3000foo bar \t"])
result = pc.ascii_trim_whitespace(arr)
expected = pa.array(["foo", None, "\u3000foo bar"])
assert expected.equals(result)
arr = pa.array([" foo", None, " \u3000foo bar \t"])
result = pc.utf8_trim(arr, characters=' f\u3000')
expected = pa.array(["oo", None, "oo bar \t"])
assert expected.equals(result)
# Positional option
result = pc.utf8_trim(arr, ' f\u3000')
expected = pa.array(["oo", None, "oo bar \t"])
assert expected.equals(result)
def test_slice_compatibility():
arr = pa.array(["", "𝑓", "𝑓ö", "𝑓öõ", "𝑓öõḍ", "𝑓öõḍš"])
for start in range(-6, 6):
for stop in range(-6, 6):
for step in [-3, -2, -1, 1, 2, 3]:
expected = pa.array([k.as_py()[start:stop:step]
for k in arr])
result = pc.utf8_slice_codeunits(
arr, start=start, stop=stop, step=step)
assert expected.equals(result)
# Positional options
assert pc.utf8_slice_codeunits(arr,
start, stop, step) == result
def test_binary_slice_compatibility():
arr = pa.array([b"", b"a", b"a\xff", b"ab\x00", b"abc\xfb", b"ab\xf2de"])
for start, stop, step in itertools.product(range(-6, 6),
range(-6, 6),
range(-3, 4)):
if step == 0:
continue
expected = pa.array([k.as_py()[start:stop:step]
for k in arr])
result = pc.binary_slice(
arr, start=start, stop=stop, step=step)
assert expected.equals(result)
# Positional options
assert pc.binary_slice(arr, start, stop, step) == result
def test_split_pattern():
arr = pa.array(["-foo---bar--", "---foo---b"])
result = pc.split_pattern(arr, pattern="---")
expected = pa.array([["-foo", "bar--"], ["", "foo", "b"]])
assert expected.equals(result)
result = pc.split_pattern(arr, "---", max_splits=1)
expected = pa.array([["-foo", "bar--"], ["", "foo---b"]])
assert expected.equals(result)
result = pc.split_pattern(arr, "---", max_splits=1, reverse=True)
expected = pa.array([["-foo", "bar--"], ["---foo", "b"]])
assert expected.equals(result)
def test_split_whitespace_utf8():
arr = pa.array(["foo bar", " foo \u3000\tb"])
result = pc.utf8_split_whitespace(arr)
expected = pa.array([["foo", "bar"], ["", "foo", "b"]])
assert expected.equals(result)
result = pc.utf8_split_whitespace(arr, max_splits=1)
expected = pa.array([["foo", "bar"], ["", "foo \u3000\tb"]])
assert expected.equals(result)
result = pc.utf8_split_whitespace(arr, max_splits=1, reverse=True)
expected = pa.array([["foo", "bar"], [" foo", "b"]])
assert expected.equals(result)
def test_split_whitespace_ascii():
arr = pa.array(["foo bar", " foo \u3000\tb"])
result = pc.ascii_split_whitespace(arr)
expected = pa.array([["foo", "bar"], ["", "foo", "\u3000", "b"]])
assert expected.equals(result)
result = pc.ascii_split_whitespace(arr, max_splits=1)
expected = pa.array([["foo", "bar"], ["", "foo \u3000\tb"]])
assert expected.equals(result)
result = pc.ascii_split_whitespace(arr, max_splits=1, reverse=True)
expected = pa.array([["foo", "bar"], [" foo \u3000", "b"]])
assert expected.equals(result)
def test_split_pattern_regex():
arr = pa.array(["-foo---bar--", "---foo---b"])
result = pc.split_pattern_regex(arr, pattern="-+")
expected = pa.array([["", "foo", "bar", ""], ["", "foo", "b"]])
assert expected.equals(result)
result = pc.split_pattern_regex(arr, "-+", max_splits=1)
expected = pa.array([["", "foo---bar--"], ["", "foo---b"]])
assert expected.equals(result)
with pytest.raises(NotImplementedError,
match="Cannot split in reverse with regex"):
result = pc.split_pattern_regex(
arr, pattern="---", max_splits=1, reverse=True)
def test_min_max():
# An example generated function wrapper with possible options
data = [4, 5, 6, None, 1]
s = pc.min_max(data)
assert s.as_py() == {'min': 1, 'max': 6}
s = pc.min_max(data, options=pc.ScalarAggregateOptions())
assert s.as_py() == {'min': 1, 'max': 6}
s = pc.min_max(data, options=pc.ScalarAggregateOptions(skip_nulls=True))
assert s.as_py() == {'min': 1, 'max': 6}
s = pc.min_max(data, options=pc.ScalarAggregateOptions(skip_nulls=False))
assert s.as_py() == {'min': None, 'max': None}
# Options as dict of kwargs
s = pc.min_max(data, options={'skip_nulls': False})
assert s.as_py() == {'min': None, 'max': None}
# Options as named functions arguments
s = pc.min_max(data, skip_nulls=False)
assert s.as_py() == {'min': None, 'max': None}
# Both options and named arguments
with pytest.raises(TypeError):
s = pc.min_max(
data, options=pc.ScalarAggregateOptions(), skip_nulls=False)
# Wrong options type
options = pc.TakeOptions()
with pytest.raises(TypeError):
s = pc.min_max(data, options=options)
# Missing argument
with pytest.raises(TypeError, match="min_max takes 1 positional"):
s = pc.min_max()
def test_any():
# ARROW-1846
options = pc.ScalarAggregateOptions(skip_nulls=False, min_count=0)
a = pa.array([], type='bool')
assert pc.any(a).as_py() is None
assert pc.any(a, min_count=0).as_py() is False
assert pc.any(a, options=options).as_py() is False
a = pa.array([False, None, True])
assert pc.any(a).as_py() is True
assert pc.any(a, options=options).as_py() is True
a = pa.array([False, None, False])
assert pc.any(a).as_py() is False
assert pc.any(a, options=options).as_py() is None
def test_all():
# ARROW-10301
options = pc.ScalarAggregateOptions(skip_nulls=False, min_count=0)
a = pa.array([], type='bool')
assert pc.all(a).as_py() is None
assert pc.all(a, min_count=0).as_py() is True
assert pc.all(a, options=options).as_py() is True
a = pa.array([False, True])
assert pc.all(a).as_py() is False
assert pc.all(a, options=options).as_py() is False
a = pa.array([True, None])
assert pc.all(a).as_py() is True
assert pc.all(a, options=options).as_py() is None
a = pa.chunked_array([[True], [True, None]])
assert pc.all(a).as_py() is True
assert pc.all(a, options=options).as_py() is None
a = pa.chunked_array([[True], [False]])
assert pc.all(a).as_py() is False
assert pc.all(a, options=options).as_py() is False
def test_is_valid():
# An example generated function wrapper without options
data = [4, 5, None]
assert pc.is_valid(data).to_pylist() == [True, True, False]
with pytest.raises(TypeError):
pc.is_valid(data, options=None)
def test_generated_docstrings():
# With options
assert pc.min_max.__doc__ == textwrap.dedent("""\
Compute the minimum and maximum values of a numeric array.
Null values are ignored by default.
This can be changed through ScalarAggregateOptions.
Parameters
----------
array : Array-like
Argument to compute function.
skip_nulls : bool, default True
Whether to skip (ignore) nulls in the input.
If False, any null in the input forces the output to null.
min_count : int, default 1
Minimum number of non-null values in the input. If the number
of non-null values is below `min_count`, the output is null.
options : pyarrow.compute.ScalarAggregateOptions, optional
Alternative way of passing options.
memory_pool : pyarrow.MemoryPool, optional
If not passed, will allocate memory from the default memory pool.
""")
# Without options
assert pc.add.__doc__ == textwrap.dedent("""\
Add the arguments element-wise.
Results will wrap around on integer overflow.
Use function "add_checked" if you want overflow
to return an error.
Parameters
----------
x : Array-like or scalar-like
Argument to compute function.
y : Array-like or scalar-like
Argument to compute function.
memory_pool : pyarrow.MemoryPool, optional
If not passed, will allocate memory from the default memory pool.
""")
# Varargs with options
assert pc.min_element_wise.__doc__ == textwrap.dedent("""\
Find the element-wise minimum value.
Nulls are ignored (by default) or propagated.
NaN is preferred over null, but not over any valid value.
Parameters
----------
*args : Array-like or scalar-like
Argument to compute function.
skip_nulls : bool, default True
Whether to skip (ignore) nulls in the input.
If False, any null in the input forces the output to null.
options : pyarrow.compute.ElementWiseAggregateOptions, optional
Alternative way of passing options.
memory_pool : pyarrow.MemoryPool, optional
If not passed, will allocate memory from the default memory pool.
""")
assert pc.filter.__doc__ == textwrap.dedent("""\
Filter with a boolean selection filter.
The output is populated with values from the input at positions
where the selection filter is non-zero. Nulls in the selection filter
are handled based on FilterOptions.
Parameters
----------
input : Array-like or scalar-like
Argument to compute function.
selection_filter : Array-like or scalar-like
Argument to compute function.
null_selection_behavior : str, default "drop"
How to handle nulls in the selection filter.
Accepted values are "drop", "emit_null".
options : pyarrow.compute.FilterOptions, optional
Alternative way of passing options.
memory_pool : pyarrow.MemoryPool, optional
If not passed, will allocate memory from the default memory pool.
Examples
--------
>>> import pyarrow as pa
>>> arr = pa.array(["a", "b", "c", None, "e"])
>>> mask = pa.array([True, False, None, False, True])
>>> arr.filter(mask)
<pyarrow.lib.StringArray object at ...>
[
"a",
"e"
]
>>> arr.filter(mask, null_selection_behavior='emit_null')
<pyarrow.lib.StringArray object at ...>
[
"a",
null,
"e"
]
""")
def test_generated_signatures():
# The self-documentation provided by signatures should show acceptable
# options and their default values.
# Without options
sig = inspect.signature(pc.add)
assert str(sig) == "(x, y, /, *, memory_pool=None)"
# With options
sig = inspect.signature(pc.min_max)
assert str(sig) == ("(array, /, *, skip_nulls=True, min_count=1, "
"options=None, memory_pool=None)")
# With positional options
sig = inspect.signature(pc.quantile)
assert str(sig) == ("(array, /, q=0.5, *, interpolation='linear', "
"skip_nulls=True, min_count=0, "
"options=None, memory_pool=None)")
# Varargs with options
sig = inspect.signature(pc.binary_join_element_wise)
assert str(sig) == ("(*strings, null_handling='emit_null', "
"null_replacement='', options=None, "
"memory_pool=None)")
# Varargs without options
sig = inspect.signature(pc.choose)
assert str(sig) == "(indices, /, *values, memory_pool=None)"
# Nullary with options
sig = inspect.signature(pc.random)
assert str(sig) == ("(n, *, initializer='system', "
"options=None, memory_pool=None)")
# We use isprintable to find about codepoints that Python doesn't know, but
# utf8proc does (or in a future version of Python the other way around).
# These codepoints cannot be compared between Arrow and the Python
# implementation.
@lru_cache()
def find_new_unicode_codepoints():
new = set()
characters = [chr(c) for c in range(0x80, 0x11000)
if not (0xD800 <= c < 0xE000)]
is_printable = pc.utf8_is_printable(pa.array(characters)).to_pylist()
for i, c in enumerate(characters):
if is_printable[i] != c.isprintable():
new.add(ord(c))
return new
# Python claims there are not alpha, not sure why, they are in
# gc='Other Letter': https://graphemica.com/%E1%B3%B2
unknown_issue_is_alpha = {0x1cf2, 0x1cf3}
# utf8proc does not know if codepoints are lower case
utf8proc_issue_is_lower = {
0xaa, 0xba, 0x2b0, 0x2b1, 0x2b2, 0x2b3, 0x2b4,
0x2b5, 0x2b6, 0x2b7, 0x2b8, 0x2c0, 0x2c1, 0x2e0,
0x2e1, 0x2e2, 0x2e3, 0x2e4, 0x37a, 0x1d2c, 0x1d2d,
0x1d2e, 0x1d2f, 0x1d30, 0x1d31, 0x1d32, 0x1d33,
0x1d34, 0x1d35, 0x1d36, 0x1d37, 0x1d38, 0x1d39,
0x1d3a, 0x1d3b, 0x1d3c, 0x1d3d, 0x1d3e, 0x1d3f,
0x1d40, 0x1d41, 0x1d42, 0x1d43, 0x1d44, 0x1d45,
0x1d46, 0x1d47, 0x1d48, 0x1d49, 0x1d4a, 0x1d4b,
0x1d4c, 0x1d4d, 0x1d4e, 0x1d4f, 0x1d50, 0x1d51,
0x1d52, 0x1d53, 0x1d54, 0x1d55, 0x1d56, 0x1d57,
0x1d58, 0x1d59, 0x1d5a, 0x1d5b, 0x1d5c, 0x1d5d,
0x1d5e, 0x1d5f, 0x1d60, 0x1d61, 0x1d62, 0x1d63,
0x1d64, 0x1d65, 0x1d66, 0x1d67, 0x1d68, 0x1d69,
0x1d6a, 0x1d78, 0x1d9b, 0x1d9c, 0x1d9d, 0x1d9e,
0x1d9f, 0x1da0, 0x1da1, 0x1da2, 0x1da3, 0x1da4,
0x1da5, 0x1da6, 0x1da7, 0x1da8, 0x1da9, 0x1daa,
0x1dab, 0x1dac, 0x1dad, 0x1dae, 0x1daf, 0x1db0,
0x1db1, 0x1db2, 0x1db3, 0x1db4, 0x1db5, 0x1db6,
0x1db7, 0x1db8, 0x1db9, 0x1dba, 0x1dbb, 0x1dbc,
0x1dbd, 0x1dbe, 0x1dbf, 0x2071, 0x207f, 0x2090,
0x2091, 0x2092, 0x2093, 0x2094, 0x2095, 0x2096,
0x2097, 0x2098, 0x2099, 0x209a, 0x209b, 0x209c,
0x2c7c, 0x2c7d, 0xa69c, 0xa69d, 0xa770, 0xa7f8,
0xa7f9, 0xab5c, 0xab5d, 0xab5e, 0xab5f, }
# utf8proc does not store if a codepoint is numeric
numeric_info_missing = {
0x3405, 0x3483, 0x382a, 0x3b4d, 0x4e00, 0x4e03,
0x4e07, 0x4e09, 0x4e5d, 0x4e8c, 0x4e94, 0x4e96,
0x4ebf, 0x4ec0, 0x4edf, 0x4ee8, 0x4f0d, 0x4f70,
0x5104, 0x5146, 0x5169, 0x516b, 0x516d, 0x5341,
0x5343, 0x5344, 0x5345, 0x534c, 0x53c1, 0x53c2,
0x53c3, 0x53c4, 0x56db, 0x58f1, 0x58f9, 0x5e7a,
0x5efe, 0x5eff, 0x5f0c, 0x5f0d, 0x5f0e, 0x5f10,
0x62fe, 0x634c, 0x67d2, 0x6f06, 0x7396, 0x767e,
0x8086, 0x842c, 0x8cae, 0x8cb3, 0x8d30, 0x9621,
0x9646, 0x964c, 0x9678, 0x96f6, 0xf96b, 0xf973,
0xf978, 0xf9b2, 0xf9d1, 0xf9d3, 0xf9fd, 0x10fc5,
0x10fc6, 0x10fc7, 0x10fc8, 0x10fc9, 0x10fca,
0x10fcb, }
# utf8proc has no no digit/numeric information
digit_info_missing = {
0xb2, 0xb3, 0xb9, 0x1369, 0x136a, 0x136b, 0x136c,
0x136d, 0x136e, 0x136f, 0x1370, 0x1371, 0x19da, 0x2070,
0x2074, 0x2075, 0x2076, 0x2077, 0x2078, 0x2079, 0x2080,
0x2081, 0x2082, 0x2083, 0x2084, 0x2085, 0x2086, 0x2087,
0x2088, 0x2089, 0x2460, 0x2461, 0x2462, 0x2463, 0x2464,
0x2465, 0x2466, 0x2467, 0x2468, 0x2474, 0x2475, 0x2476,
0x2477, 0x2478, 0x2479, 0x247a, 0x247b, 0x247c, 0x2488,
0x2489, 0x248a, 0x248b, 0x248c, 0x248d, 0x248e, 0x248f,
0x2490, 0x24ea, 0x24f5, 0x24f6, 0x24f7, 0x24f8, 0x24f9,
0x24fa, 0x24fb, 0x24fc, 0x24fd, 0x24ff, 0x2776, 0x2777,
0x2778, 0x2779, 0x277a, 0x277b, 0x277c, 0x277d, 0x277e,
0x2780, 0x2781, 0x2782, 0x2783, 0x2784, 0x2785, 0x2786,
0x2787, 0x2788, 0x278a, 0x278b, 0x278c, 0x278d, 0x278e,
0x278f, 0x2790, 0x2791, 0x2792, 0x10a40, 0x10a41,
0x10a42, 0x10a43, 0x10e60, 0x10e61, 0x10e62, 0x10e63,
0x10e64, 0x10e65, 0x10e66, 0x10e67, 0x10e68, }
numeric_info_missing = {
0x3405, 0x3483, 0x382a, 0x3b4d, 0x4e00, 0x4e03,
0x4e07, 0x4e09, 0x4e5d, 0x4e8c, 0x4e94, 0x4e96,
0x4ebf, 0x4ec0, 0x4edf, 0x4ee8, 0x4f0d, 0x4f70,
0x5104, 0x5146, 0x5169, 0x516b, 0x516d, 0x5341,
0x5343, 0x5344, 0x5345, 0x534c, 0x53c1, 0x53c2,
0x53c3, 0x53c4, 0x56db, 0x58f1, 0x58f9, 0x5e7a,
0x5efe, 0x5eff, 0x5f0c, 0x5f0d, 0x5f0e, 0x5f10,
0x62fe, 0x634c, 0x67d2, 0x6f06, 0x7396, 0x767e,
0x8086, 0x842c, 0x8cae, 0x8cb3, 0x8d30, 0x9621,
0x9646, 0x964c, 0x9678, 0x96f6, 0xf96b, 0xf973,
0xf978, 0xf9b2, 0xf9d1, 0xf9d3, 0xf9fd, }
codepoints_ignore = {
'is_alnum': numeric_info_missing | digit_info_missing |
unknown_issue_is_alpha,
'is_alpha': unknown_issue_is_alpha,
'is_digit': digit_info_missing,
'is_numeric': numeric_info_missing,
'is_lower': utf8proc_issue_is_lower
}
@pytest.mark.parametrize('function_name', ['is_alnum', 'is_alpha',
'is_ascii', 'is_decimal',
'is_digit', 'is_lower',
'is_numeric', 'is_printable',
'is_space', 'is_upper', ])
@pytest.mark.parametrize('variant', ['ascii', 'utf8'])
def test_string_py_compat_boolean(function_name, variant):
arrow_name = variant + "_" + function_name
py_name = function_name.replace('_', '')
ignore = codepoints_ignore.get(function_name, set()) | \
find_new_unicode_codepoints()
for i in range(128 if ascii else 0x11000):
if i in range(0xD800, 0xE000):
continue # bug? pyarrow doesn't allow utf16 surrogates
# the issues we know of, we skip
if i in ignore:
continue
# Compare results with the equivalent Python predicate
# (except "is_space" where functions are known to be incompatible)
c = chr(i)
if hasattr(pc, arrow_name) and function_name != 'is_space':
ar = pa.array([c])
arrow_func = getattr(pc, arrow_name)
assert arrow_func(ar)[0].as_py() == getattr(c, py_name)()
def test_pad():
arr = pa.array([None, 'a', 'abcd'])
assert pc.ascii_center(arr, width=3).tolist() == [None, ' a ', 'abcd']
assert pc.ascii_lpad(arr, width=3).tolist() == [None, ' a', 'abcd']
assert pc.ascii_rpad(arr, width=3).tolist() == [None, 'a ', 'abcd']
assert pc.ascii_center(arr, 3).tolist() == [None, ' a ', 'abcd']
assert pc.ascii_lpad(arr, 3).tolist() == [None, ' a', 'abcd']
assert pc.ascii_rpad(arr, 3).tolist() == [None, 'a ', 'abcd']
arr = pa.array([None, 'á', 'abcd'])
assert pc.utf8_center(arr, width=3).tolist() == [None, ' á ', 'abcd']
assert pc.utf8_lpad(arr, width=3).tolist() == [None, ' á', 'abcd']
assert pc.utf8_rpad(arr, width=3).tolist() == [None, 'á ', 'abcd']
assert pc.utf8_center(arr, 3).tolist() == [None, ' á ', 'abcd']
assert pc.utf8_lpad(arr, 3).tolist() == [None, ' á', 'abcd']
assert pc.utf8_rpad(arr, 3).tolist() == [None, 'á ', 'abcd']
@pytest.mark.pandas
def test_replace_slice():
offsets = range(-3, 4)
arr = pa.array([None, '', 'a', 'ab', 'abc', 'abcd', 'abcde'])
series = arr.to_pandas()
for start in offsets:
for stop in offsets:
expected = series.str.slice_replace(start, stop, 'XX')
actual = pc.binary_replace_slice(
arr, start=start, stop=stop, replacement='XX')
assert actual.tolist() == expected.tolist()
# Positional options
assert pc.binary_replace_slice(arr, start, stop, 'XX') == actual
arr = pa.array([None, '', 'π', 'πb', 'πbθ', 'πbθd', 'πbθde'])
series = arr.to_pandas()
for start in offsets: