eland/tests/series/test_arithmetics_pytest.py
2023-09-26 07:34:52 +02:00

359 lines
13 KiB
Python

# Licensed to Elasticsearch B.V. under one or more contributor
# license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright
# ownership. Elasticsearch B.V. 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.
from datetime import datetime
# File called _pytest for PyCharm compatability
import numpy as np
import pytest
from eland import Series
from tests.common import TestData, assert_pandas_eland_series_equal
class TestSeriesArithmetics(TestData):
def test_ecommerce_datetime_comparisons(self):
pd_df = self.pd_ecommerce()
ed_df = self.ed_ecommerce()
ops = ["__le__", "__lt__", "__gt__", "__ge__", "__eq__", "__ne__"]
# this datetime object is timezone naive
datetime_obj = datetime(2016, 12, 18)
# FIXME: the following timezone conversions are just a temporary fix
# to run the datetime comparison tests
#
# The problem:
# - the datetime objects of the pandas DataFrame are timezone aware and
# can't be compared with timezone naive datetime objects
# - the datetime objects of the eland DataFrame are timezone naive (which
# should be fixed)
# - however if the eland DataFrame is converted to a pandas DataFrame
# (using the `to_pandas` function) the datetime objects become timezone aware
#
# This tests converts the datetime objects of the pandas Series to
# timezone naive ones and utilizes a class to make the datetime objects of the
# eland Series timezone naive before the result of `to_pandas` is returned.
# The `to_pandas` function is executed by the `assert_pandas_eland_series_equal`
# function, which compares the eland and pandas Series
# convert to timezone naive datetime object
pd_df["order_date"] = pd_df["order_date"].dt.tz_localize(None)
class ModifiedElandSeries(Series):
def to_pandas(self):
"""remove timezone awareness before returning the pandas dataframe"""
series = super().to_pandas()
series = series.dt.tz_localize(None)
return series
for op in ops:
pd_series = pd_df[getattr(pd_df["order_date"], op)(datetime_obj)][
"order_date"
]
ed_series = ed_df[getattr(ed_df["order_date"], op)(datetime_obj)][
"order_date"
]
# "type cast" to modified class (inherits from ed.Series) that overrides the `to_pandas` function
ed_series.__class__ = ModifiedElandSeries
assert_pandas_eland_series_equal(
pd_series,
ed_series,
check_exact=False,
rtol=1e-3, # previously known as check_less_precise
)
def test_ecommerce_series_invalid_div(self):
pd_df = self.pd_ecommerce()
ed_df = self.ed_ecommerce()
# eland / pandas == error
with pytest.raises(TypeError):
_ = ed_df["total_quantity"] / pd_df["taxful_total_price"]
def test_ecommerce_series_simple_arithmetics(self):
pd_df = self.pd_ecommerce().head(100)
ed_df = self.ed_ecommerce().head(100)
pd_series = (
pd_df["taxful_total_price"]
+ 5
+ pd_df["total_quantity"] / pd_df["taxless_total_price"]
- pd_df["total_unique_products"] * 10.0
+ pd_df["total_quantity"]
)
ed_series = (
ed_df["taxful_total_price"]
+ 5
+ ed_df["total_quantity"] / ed_df["taxless_total_price"]
- ed_df["total_unique_products"] * 10.0
+ ed_df["total_quantity"]
)
assert_pandas_eland_series_equal(pd_series, ed_series, rtol=True)
def test_ecommerce_series_simple_integer_addition(self):
pd_df = self.pd_ecommerce().head(100)
ed_df = self.ed_ecommerce().head(100)
pd_series = pd_df["taxful_total_price"] + 5
ed_series = ed_df["taxful_total_price"] + 5
assert_pandas_eland_series_equal(pd_series, ed_series, rtol=True)
def test_ecommerce_series_simple_series_addition(self):
pd_df = self.pd_ecommerce().head(100)
ed_df = self.ed_ecommerce().head(100)
pd_series = pd_df["taxful_total_price"] + pd_df["total_quantity"]
ed_series = ed_df["taxful_total_price"] + ed_df["total_quantity"]
assert_pandas_eland_series_equal(pd_series, ed_series, rtol=True)
def test_ecommerce_series_basic_arithmetics(self):
pd_df = self.pd_ecommerce().head(100)
ed_df = self.ed_ecommerce().head(100)
ops = [
"__add__",
"__truediv__",
"__floordiv__",
"__pow__",
"__mod__",
"__mul__",
"__sub__",
"add",
"truediv",
"floordiv",
"pow",
"mod",
"mul",
"sub",
]
for op in ops:
pd_series = getattr(pd_df["taxful_total_price"], op)(
pd_df["total_quantity"]
)
ed_series = getattr(ed_df["taxful_total_price"], op)(
ed_df["total_quantity"]
)
assert_pandas_eland_series_equal(pd_series, ed_series, rtol=True)
pd_series = getattr(pd_df["taxful_total_price"], op)(10.56)
ed_series = getattr(ed_df["taxful_total_price"], op)(10.56)
assert_pandas_eland_series_equal(pd_series, ed_series, rtol=True)
pd_series = getattr(pd_df["taxful_total_price"], op)(np.float32(1.879))
ed_series = getattr(ed_df["taxful_total_price"], op)(np.float32(1.879))
assert_pandas_eland_series_equal(pd_series, ed_series, rtol=True)
pd_series = getattr(pd_df["taxful_total_price"], op)(int(8))
ed_series = getattr(ed_df["taxful_total_price"], op)(int(8))
assert_pandas_eland_series_equal(pd_series, ed_series, rtol=True)
def test_supported_series_dtypes_ops(self):
pd_df = self.pd_ecommerce().head(100)
ed_df = self.ed_ecommerce().head(100)
# Test some specific operations that are and aren't supported
numeric_ops = [
"__add__",
"__truediv__",
"__floordiv__",
"__pow__",
"__mod__",
"__mul__",
"__sub__",
]
non_string_numeric_ops = [
"__add__",
"__truediv__",
"__floordiv__",
"__pow__",
"__mod__",
"__sub__",
]
# __mul__ is supported for int * str in pandas
# float op float
for op in numeric_ops:
pd_series = getattr(pd_df["taxful_total_price"], op)(
pd_df["taxless_total_price"]
)
ed_series = getattr(ed_df["taxful_total_price"], op)(
ed_df["taxless_total_price"]
)
assert_pandas_eland_series_equal(pd_series, ed_series, rtol=True)
# int op float
for op in numeric_ops:
pd_series = getattr(pd_df["total_quantity"], op)(
pd_df["taxless_total_price"]
)
ed_series = getattr(ed_df["total_quantity"], op)(
ed_df["taxless_total_price"]
)
assert_pandas_eland_series_equal(pd_series, ed_series, rtol=True)
# float op int
for op in numeric_ops:
pd_series = getattr(pd_df["taxful_total_price"], op)(
pd_df["total_quantity"]
)
ed_series = getattr(ed_df["taxful_total_price"], op)(
ed_df["total_quantity"]
)
assert_pandas_eland_series_equal(pd_series, ed_series, rtol=True)
# str op int (throws)
for op in non_string_numeric_ops:
with pytest.raises(TypeError):
pd_series = getattr(pd_df["currency"], op)(pd_df["total_quantity"])
with pytest.raises(TypeError):
ed_series = getattr(ed_df["currency"], op)(ed_df["total_quantity"])
with pytest.raises(TypeError):
pd_series = getattr(pd_df["currency"], op)(1)
with pytest.raises(TypeError):
ed_series = getattr(ed_df["currency"], op)(1)
# int op str (throws)
for op in non_string_numeric_ops:
with pytest.raises(TypeError):
pd_series = getattr(pd_df["total_quantity"], op)(pd_df["currency"])
with pytest.raises(TypeError):
ed_series = getattr(ed_df["total_quantity"], op)(ed_df["currency"])
def test_ecommerce_series_basic_rarithmetics(self):
pd_df = self.pd_ecommerce().head(10)
ed_df = self.ed_ecommerce().head(10)
ops = [
"__radd__",
"__rtruediv__",
"__rfloordiv__",
"__rpow__",
"__rmod__",
"__rmul__",
"__rsub__",
"radd",
"rtruediv",
"rfloordiv",
"rpow",
"rmod",
"rmul",
"rsub",
]
for op in ops:
pd_series = getattr(pd_df["taxful_total_price"], op)(
pd_df["total_quantity"]
)
ed_series = getattr(ed_df["taxful_total_price"], op)(
ed_df["total_quantity"]
)
assert_pandas_eland_series_equal(pd_series, ed_series, rtol=True)
pd_series = getattr(pd_df["taxful_total_price"], op)(3.141)
ed_series = getattr(ed_df["taxful_total_price"], op)(3.141)
assert_pandas_eland_series_equal(pd_series, ed_series, rtol=True)
pd_series = getattr(pd_df["taxful_total_price"], op)(np.float32(2.879))
ed_series = getattr(ed_df["taxful_total_price"], op)(np.float32(2.879))
assert_pandas_eland_series_equal(pd_series, ed_series, rtol=True)
pd_series = getattr(pd_df["taxful_total_price"], op)(int(6))
ed_series = getattr(ed_df["taxful_total_price"], op)(int(6))
assert_pandas_eland_series_equal(pd_series, ed_series, rtol=True)
def test_supported_series_dtypes_rops(self):
pd_df = self.pd_ecommerce().head(100)
ed_df = self.ed_ecommerce().head(100)
# Test some specific operations that are and aren't supported
numeric_ops = [
"__radd__",
"__rtruediv__",
"__rfloordiv__",
"__rpow__",
"__rmod__",
"__rmul__",
"__rsub__",
]
non_string_numeric_ops = [
"__radd__",
"__rtruediv__",
"__rfloordiv__",
"__rpow__",
"__rmod__",
"__rsub__",
]
# __rmul__ is supported for int * str in pandas
# float op float
for op in numeric_ops:
pd_series = getattr(pd_df["taxful_total_price"], op)(
pd_df["taxless_total_price"]
)
ed_series = getattr(ed_df["taxful_total_price"], op)(
ed_df["taxless_total_price"]
)
assert_pandas_eland_series_equal(pd_series, ed_series, rtol=True)
# int op float
for op in numeric_ops:
pd_series = getattr(pd_df["total_quantity"], op)(
pd_df["taxless_total_price"]
)
ed_series = getattr(ed_df["total_quantity"], op)(
ed_df["taxless_total_price"]
)
assert_pandas_eland_series_equal(pd_series, ed_series, rtol=True)
# float op int
for op in numeric_ops:
pd_series = getattr(pd_df["taxful_total_price"], op)(
pd_df["total_quantity"]
)
ed_series = getattr(ed_df["taxful_total_price"], op)(
ed_df["total_quantity"]
)
assert_pandas_eland_series_equal(pd_series, ed_series, rtol=True)
# str op int (throws)
for op in non_string_numeric_ops:
with pytest.raises(TypeError):
pd_series = getattr(pd_df["currency"], op)(pd_df["total_quantity"])
with pytest.raises(TypeError):
ed_series = getattr(ed_df["currency"], op)(ed_df["total_quantity"])
with pytest.raises(TypeError):
pd_series = getattr(pd_df["currency"], op)(10.0)
with pytest.raises(TypeError):
ed_series = getattr(ed_df["currency"], op)(10.0)
# int op str (throws)
for op in non_string_numeric_ops:
with pytest.raises(TypeError):
pd_series = getattr(pd_df["total_quantity"], op)(pd_df["currency"])
with pytest.raises(TypeError):
ed_series = getattr(ed_df["total_quantity"], op)(ed_df["currency"])