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REF/TST: remove overriding tm.assert_foo pattern #54355

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Merged
merged 5 commits into from
Aug 1, 2023
Merged

REF/TST: remove overriding tm.assert_foo pattern #54355

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32d15f4
REF: remove overriding assert_extension_array_equal
jbrockmendel Jul 31, 2023
daa5440
REF/TST: remove overriding tm.assert_foo pattern
jbrockmendel Aug 1, 2023
b2a09c2
remove the methods
jbrockmendel Aug 1, 2023
f1ce02e
Merge branch 'main' into ref-tst-asserts
jbrockmendel Aug 1, 2023
292d297
update usage
jbrockmendel Aug 1, 2023
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9 changes: 0 additions & 9 deletions .pre-commit-config.yaml
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Expand Up @@ -256,15 +256,6 @@ repos:
|default_rng\(\)
files: ^pandas/tests/
types_or: [python, cython, rst]
- id: unwanted-patterns-in-ea-tests
name: Unwanted patterns in EA tests
language: pygrep
entry: |
(?x)
tm.assert_(series|frame)_equal
files: ^pandas/tests/extension/base/
exclude: ^pandas/tests/extension/base/base\.py$
types_or: [python, cython, rst]
- id: unwanted-patterns-in-cython
name: Unwanted patterns in Cython code
language: pygrep
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3 changes: 2 additions & 1 deletion pandas/tests/arrays/integer/test_comparison.py
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@@ -1,6 +1,7 @@
import pytest

import pandas as pd
import pandas._testing as tm
from pandas.tests.arrays.masked_shared import (
ComparisonOps,
NumericOps,
Expand All @@ -25,7 +26,7 @@ def test_compare_to_int(self, dtype, comparison_op):
expected = method(2).astype("boolean")
expected[s2.isna()] = pd.NA

self.assert_series_equal(result, expected)
tm.assert_series_equal(result, expected)


def test_equals():
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2 changes: 1 addition & 1 deletion pandas/tests/arrays/masked_shared.py
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Expand Up @@ -110,7 +110,7 @@ def test_compare_to_string(self, dtype):
result = ser == "a"
expected = pd.Series([False, pd.NA], dtype="boolean")

self.assert_series_equal(result, expected)
tm.assert_series_equal(result, expected)

def test_ufunc_with_out(self, dtype):
arr = pd.array([1, 2, 3], dtype=dtype)
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7 changes: 0 additions & 7 deletions pandas/tests/extension/base/__init__.py
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Expand Up @@ -33,13 +33,6 @@ class TestMyDtype(BaseDtypeTests):
``BaseDtypeTests``. pytest's fixture discover will supply your ``dtype``
wherever the test requires it. You're free to implement additional tests.

All the tests in these modules use ``self.assert_frame_equal`` or
``self.assert_series_equal`` for dataframe or series comparisons. By default,
they use the usual ``pandas.testing.assert_frame_equal`` and
``pandas.testing.assert_series_equal``. You can override the checks used
by defining the staticmethods ``assert_frame_equal`` and
``assert_series_equal`` on your base test class.

"""
from pandas.tests.extension.base.accumulate import BaseAccumulateTests # noqa: F401
from pandas.tests.extension.base.casting import BaseCastingTests # noqa: F401
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3 changes: 2 additions & 1 deletion pandas/tests/extension/base/accumulate.py
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@@ -1,6 +1,7 @@
import pytest

import pandas as pd
import pandas._testing as tm
from pandas.tests.extension.base.base import BaseExtensionTests


Expand All @@ -20,7 +21,7 @@ def check_accumulate(self, s, op_name, skipna):
)

expected = getattr(s.astype("float64"), op_name)(skipna=skipna)
self.assert_series_equal(result, expected, check_dtype=False)
tm.assert_series_equal(result, expected, check_dtype=False)

@pytest.mark.parametrize("skipna", [True, False])
def test_accumulate_series_raises(self, data, all_numeric_accumulations, skipna):
Expand Down
17 changes: 1 addition & 16 deletions pandas/tests/extension/base/base.py
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@@ -1,17 +1,2 @@
import pandas._testing as tm


class BaseExtensionTests:
# classmethod and different signature is needed
# to make inheritance compliant with mypy
@classmethod
def assert_equal(cls, left, right, **kwargs):
return tm.assert_equal(left, right, **kwargs)

@classmethod
def assert_series_equal(cls, left, right, *args, **kwargs):
return tm.assert_series_equal(left, right, *args, **kwargs)

@classmethod
def assert_frame_equal(cls, left, right, *args, **kwargs):
return tm.assert_frame_equal(left, right, *args, **kwargs)
pass
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This removal is not backward compatible for extensionarrays tests that inherit BaseExtensionTests. IMO this should be deprecated instead?

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Is there a downstream EA that is actually affected or is this just in principal?

If the latter, I'm inclined to be more aggressive with changing the tests than the non-test code. I don't want to get in the business of writing deprecation tests for the tests.

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Every downstream EA that reuses those tests can be affected if they use the same pattern in those classes (eg in a test they override). See the two linked PRs below for two such examples.

Now, I think the question is: is there any downstream EA implementation that actually makes use of those test class methods (i.e. by overriding them, and thus not relying purely on the base tm.assert_.._equal functions). That I don't know (the two examples of affected projects don't do this, and so for them it's an easy fix)

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Looking at some know downstream EAs, there are a few others that will be affected as well in the sense of having to replace self.assert_.. with tm.assert_.., but I didn't see any public one that actually overrides those methods.

10 changes: 5 additions & 5 deletions pandas/tests/extension/base/casting.py
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Expand Up @@ -46,7 +46,7 @@ def test_tolist(self, data):
def test_astype_str(self, data):
result = pd.Series(data[:5]).astype(str)
expected = pd.Series([str(x) for x in data[:5]], dtype=str)
self.assert_series_equal(result, expected)
tm.assert_series_equal(result, expected)

@pytest.mark.parametrize(
"nullable_string_dtype",
Expand All @@ -62,22 +62,22 @@ def test_astype_string(self, data, nullable_string_dtype):
[str(x) if not isinstance(x, bytes) else x.decode() for x in data[:5]],
dtype=nullable_string_dtype,
)
self.assert_series_equal(result, expected)
tm.assert_series_equal(result, expected)

def test_to_numpy(self, data):
expected = np.asarray(data)

result = data.to_numpy()
self.assert_equal(result, expected)
tm.assert_equal(result, expected)

result = pd.Series(data).to_numpy()
self.assert_equal(result, expected)
tm.assert_equal(result, expected)

def test_astype_empty_dataframe(self, dtype):
# https://github.com/pandas-dev/pandas/issues/33113
df = pd.DataFrame()
result = df.astype(dtype)
self.assert_frame_equal(result, df)
tm.assert_frame_equal(result, df)

@pytest.mark.parametrize("copy", [True, False])
def test_astype_own_type(self, data, copy):
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22 changes: 11 additions & 11 deletions pandas/tests/extension/base/constructors.py
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Expand Up @@ -39,27 +39,27 @@ def test_series_constructor(self, data):
def test_series_constructor_no_data_with_index(self, dtype, na_value):
result = pd.Series(index=[1, 2, 3], dtype=dtype)
expected = pd.Series([na_value] * 3, index=[1, 2, 3], dtype=dtype)
self.assert_series_equal(result, expected)
tm.assert_series_equal(result, expected)

# GH 33559 - empty index
result = pd.Series(index=[], dtype=dtype)
expected = pd.Series([], index=pd.Index([], dtype="object"), dtype=dtype)
self.assert_series_equal(result, expected)
tm.assert_series_equal(result, expected)

def test_series_constructor_scalar_na_with_index(self, dtype, na_value):
result = pd.Series(na_value, index=[1, 2, 3], dtype=dtype)
expected = pd.Series([na_value] * 3, index=[1, 2, 3], dtype=dtype)
self.assert_series_equal(result, expected)
tm.assert_series_equal(result, expected)

def test_series_constructor_scalar_with_index(self, data, dtype):
scalar = data[0]
result = pd.Series(scalar, index=[1, 2, 3], dtype=dtype)
expected = pd.Series([scalar] * 3, index=[1, 2, 3], dtype=dtype)
self.assert_series_equal(result, expected)
tm.assert_series_equal(result, expected)

result = pd.Series(scalar, index=["foo"], dtype=dtype)
expected = pd.Series([scalar], index=["foo"], dtype=dtype)
self.assert_series_equal(result, expected)
tm.assert_series_equal(result, expected)

@pytest.mark.parametrize("from_series", [True, False])
def test_dataframe_constructor_from_dict(self, data, from_series):
Expand Down Expand Up @@ -91,19 +91,19 @@ def test_from_dtype(self, data):

expected = pd.Series(data)
result = pd.Series(list(data), dtype=dtype)
self.assert_series_equal(result, expected)
tm.assert_series_equal(result, expected)

result = pd.Series(list(data), dtype=str(dtype))
self.assert_series_equal(result, expected)
tm.assert_series_equal(result, expected)

# gh-30280

expected = pd.DataFrame(data).astype(dtype)
result = pd.DataFrame(list(data), dtype=dtype)
self.assert_frame_equal(result, expected)
tm.assert_frame_equal(result, expected)

result = pd.DataFrame(list(data), dtype=str(dtype))
self.assert_frame_equal(result, expected)
tm.assert_frame_equal(result, expected)

def test_pandas_array(self, data):
# pd.array(extension_array) should be idempotent...
Expand All @@ -114,15 +114,15 @@ def test_pandas_array_dtype(self, data):
# ... but specifying dtype will override idempotency
result = pd.array(data, dtype=np.dtype(object))
expected = pd.arrays.NumpyExtensionArray(np.asarray(data, dtype=object))
self.assert_equal(result, expected)
tm.assert_equal(result, expected)

def test_construct_empty_dataframe(self, dtype):
# GH 33623
result = pd.DataFrame(columns=["a"], dtype=dtype)
expected = pd.DataFrame(
{"a": pd.array([], dtype=dtype)}, index=pd.RangeIndex(0)
)
self.assert_frame_equal(result, expected)
tm.assert_frame_equal(result, expected)

def test_empty(self, dtype):
cls = dtype.construct_array_type()
Expand Down
2 changes: 1 addition & 1 deletion pandas/tests/extension/base/dim2.py
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Expand Up @@ -33,7 +33,7 @@ def test_frame_from_2d_array(self, data):

df = pd.DataFrame(arr2d)
expected = pd.DataFrame({0: arr2d[:, 0], 1: arr2d[:, 1]})
self.assert_frame_equal(df, expected)
tm.assert_frame_equal(df, expected)

def test_swapaxes(self, data):
arr2d = data.repeat(2).reshape(-1, 2)
Expand Down
5 changes: 3 additions & 2 deletions pandas/tests/extension/base/dtype.py
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Expand Up @@ -2,6 +2,7 @@
import pytest

import pandas as pd
import pandas._testing as tm
from pandas.api.types import (
infer_dtype,
is_object_dtype,
Expand Down Expand Up @@ -66,11 +67,11 @@ def test_check_dtype(self, data):

expected = pd.Series([True, True, False, False], index=list("ABCD"))

self.assert_series_equal(result, expected)
tm.assert_series_equal(result, expected)

expected = pd.Series([True, True, False, False], index=list("ABCD"))
result = df.dtypes.apply(str) == str(dtype)
self.assert_series_equal(result, expected)
tm.assert_series_equal(result, expected)

def test_hashable(self, dtype):
hash(dtype) # no error
Expand Down
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