mirror of
https://github.com/elastic/eland.git
synced 2025-07-24 00:00:39 +08:00
317 lines
11 KiB
Python
317 lines
11 KiB
Python
# Licensed to Elasticsearch B.V under one or more agreements.
|
|
# Elasticsearch B.V licenses this file to you under the Apache 2.0 License.
|
|
# See the LICENSE file in the project root for more information
|
|
|
|
# File called _pytest for PyCharm compatability
|
|
import numpy as np
|
|
import pytest
|
|
|
|
from eland.tests.common import TestData, assert_pandas_eland_series_equal
|
|
|
|
|
|
class TestSeriesArithmetics(TestData):
|
|
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, check_less_precise=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, check_less_precise=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, check_less_precise=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, check_less_precise=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, check_less_precise=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, check_less_precise=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, check_less_precise=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, check_less_precise=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, check_less_precise=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, check_less_precise=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, check_less_precise=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, check_less_precise=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, check_less_precise=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, check_less_precise=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, check_less_precise=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, check_less_precise=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, check_less_precise=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"])
|