mvashishtha
commented
2 years ago Failures if we treat all default to pandas warnings as errors:
============================================= FAILURES ==============================================
__________________________ test_math_functions[pow-columns-series_or_list] __________________________
[gw3] darwin -- Python 3.7.10 /Users/maheshvashishtha/omnisci-datascience/bin/python3.7
other = <function <lambda> at 0x7ff391657710>, axis = 'columns', op = 'pow'
@pytest.mark.parametrize(
"other",
[
lambda df: 4,
lambda df, axis: df.iloc[0] if axis == "columns" else list(df[df.columns[0]]),
],
ids=["scalar", "series_or_list"],
)
@pytest.mark.parametrize("axis", ["rows", "columns"])
@pytest.mark.parametrize(
"op",
[
*("add", "radd", "sub", "rsub", "mod", "rmod", "pow", "rpow"),
*("truediv", "rtruediv", "mul", "rmul", "floordiv", "rfloordiv"),
],
)
def test_math_functions(other, axis, op):
data = test_data["float_nan_data"]
if (op == "floordiv" or op == "rfloordiv") and axis == "rows":
# lambda == "series_or_list"
pytest.xfail(reason="different behaviour")
if op == "rmod" and axis == "rows":
# lambda == "series_or_list"
pytest.xfail(reason="different behaviour")
eval_general(
> *create_test_dfs(data), lambda df: getattr(df, op)(other(df, axis), axis=axis)
)
modin/pandas/test/dataframe/test_binary.py:69:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
modin/pandas/test/utils.py:741: in eval_general
operation, md_kwargs=md_kwargs, pd_kwargs=pd_kwargs, inplace=__inplace__
modin/pandas/test/utils.py:719: in execute_callable
md_result = fn(modin_df, **md_kwargs)
modin/pandas/test/dataframe/test_binary.py:69: in <lambda>
*create_test_dfs(data), lambda df: getattr(df, op)(other(df, axis), axis=axis)
modin/pandas/dataframe.py:1620: in pow
"pow", other, axis=axis, level=level, fill_value=fill_value
modin/pandas/base.py:454: in _default_to_pandas
empty_self_str,
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
cls = <class 'modin.error_message.ErrorMessage'>
message = '`DataFrame.pow` defaulting to pandas implementation.\nTo request implementation, send an email to feature_requests@modin.org.'
@classmethod
def default_to_pandas(cls, message=""):
if message != "":
message = "{} defaulting to pandas implementation.".format(message)
else:
message = "Defaulting to pandas implementation."
if not cls.printed_request_implementation:
message = (
"{}\n".format(message)
+ "To request implementation, send an email to "
+ "feature_requests@modin.org."
)
cls.printed_request_implementation = True
> warnings.warn(message)
E UserWarning: `DataFrame.pow` defaulting to pandas implementation.
E To request implementation, send an email to feature_requests@modin.org.
modin/error_message.py:55: UserWarning
__________________ test_math_functions_fill_value[pow-None-check_different_index] ___________________
[gw0] darwin -- Python 3.7.10 /Users/maheshvashishtha/omnisci-datascience/bin/python3.7
other = <function <lambda> at 0x7fbfe6336560>, fill_value = None, op = 'pow'
@pytest.mark.parametrize(
"other",
[lambda df: df[: -(2 ** 4)], lambda df: df[df.columns[0]].reset_index(drop=True)],
ids=["check_missing_value", "check_different_index"],
)
@pytest.mark.parametrize("fill_value", [None, 3.0])
@pytest.mark.parametrize(
"op",
[
*("add", "radd", "sub", "rsub", "mod", "rmod", "pow", "rpow"),
*("truediv", "rtruediv", "mul", "rmul", "floordiv", "rfloordiv"),
],
)
def test_math_functions_fill_value(other, fill_value, op):
data = test_data["int_data"]
modin_df, pandas_df = pd.DataFrame(data), pandas.DataFrame(data)
eval_general(
modin_df,
pandas_df,
> lambda df: getattr(df, op)(other(df), axis=0, fill_value=fill_value),
)
modin/pandas/test/dataframe/test_binary.py:93:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
modin/pandas/test/utils.py:741: in eval_general
operation, md_kwargs=md_kwargs, pd_kwargs=pd_kwargs, inplace=__inplace__
modin/pandas/test/utils.py:719: in execute_callable
md_result = fn(modin_df, **md_kwargs)
modin/pandas/test/dataframe/test_binary.py:93: in <lambda>
lambda df: getattr(df, op)(other(df), axis=0, fill_value=fill_value),
modin/pandas/dataframe.py:1620: in pow
"pow", other, axis=axis, level=level, fill_value=fill_value
modin/pandas/base.py:454: in _default_to_pandas
empty_self_str,
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
cls = <class 'modin.error_message.ErrorMessage'>
message = '`DataFrame.pow` defaulting to pandas implementation.\nTo request implementation, send an email to feature_requests@modin.org.'
@classmethod
def default_to_pandas(cls, message=""):
if message != "":
message = "{} defaulting to pandas implementation.".format(message)
else:
message = "Defaulting to pandas implementation."
if not cls.printed_request_implementation:
message = (
"{}\n".format(message)
+ "To request implementation, send an email to "
+ "feature_requests@modin.org."
)
cls.printed_request_implementation = True
> warnings.warn(message)
E UserWarning: `DataFrame.pow` defaulting to pandas implementation.
E To request implementation, send an email to feature_requests@modin.org.
modin/error_message.py:55: UserWarning
_________________________ test_math_functions[rpow-columns-series_or_list] __________________________
[gw3] darwin -- Python 3.7.10 /Users/maheshvashishtha/omnisci-datascience/bin/python3.7
other = <function <lambda> at 0x7ff391657710>, axis = 'columns', op = 'rpow'
@pytest.mark.parametrize(
"other",
[
lambda df: 4,
lambda df, axis: df.iloc[0] if axis == "columns" else list(df[df.columns[0]]),
],
ids=["scalar", "series_or_list"],
)
@pytest.mark.parametrize("axis", ["rows", "columns"])
@pytest.mark.parametrize(
"op",
[
*("add", "radd", "sub", "rsub", "mod", "rmod", "pow", "rpow"),
*("truediv", "rtruediv", "mul", "rmul", "floordiv", "rfloordiv"),
],
)
def test_math_functions(other, axis, op):
data = test_data["float_nan_data"]
if (op == "floordiv" or op == "rfloordiv") and axis == "rows":
# lambda == "series_or_list"
pytest.xfail(reason="different behaviour")
if op == "rmod" and axis == "rows":
# lambda == "series_or_list"
pytest.xfail(reason="different behaviour")
eval_general(
> *create_test_dfs(data), lambda df: getattr(df, op)(other(df, axis), axis=axis)
)
modin/pandas/test/dataframe/test_binary.py:69:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
modin/pandas/test/utils.py:741: in eval_general
operation, md_kwargs=md_kwargs, pd_kwargs=pd_kwargs, inplace=__inplace__
modin/pandas/test/utils.py:719: in execute_callable
md_result = fn(modin_df, **md_kwargs)
modin/pandas/test/dataframe/test_binary.py:69: in <lambda>
*create_test_dfs(data), lambda df: getattr(df, op)(other(df, axis), axis=axis)
modin/pandas/dataframe.py:1848: in rpow
"rpow", other, axis=axis, level=level, fill_value=fill_value
modin/pandas/base.py:454: in _default_to_pandas
empty_self_str,
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
cls = <class 'modin.error_message.ErrorMessage'>
message = '`DataFrame.rpow` defaulting to pandas implementation.'
@classmethod
def default_to_pandas(cls, message=""):
if message != "":
message = "{} defaulting to pandas implementation.".format(message)
else:
message = "Defaulting to pandas implementation."
if not cls.printed_request_implementation:
message = (
"{}\n".format(message)
+ "To request implementation, send an email to "
+ "feature_requests@modin.org."
)
cls.printed_request_implementation = True
> warnings.warn(message)
E UserWarning: `DataFrame.rpow` defaulting to pandas implementation.
modin/error_message.py:55: UserWarning
___________________ test_math_functions_fill_value[pow-3.0-check_different_index] ___________________
[gw0] darwin -- Python 3.7.10 /Users/maheshvashishtha/omnisci-datascience/bin/python3.7
fn = <function test_math_functions_fill_value.<locals>.<lambda> at 0x7fbfe7d7d8c0>, inplace = False
md_kwargs = {}, pd_kwargs = {}
def execute_callable(fn, inplace=False, md_kwargs={}, pd_kwargs={}):
try:
> pd_result = fn(pandas_df, **pd_kwargs)
modin/pandas/test/utils.py:701:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
df = col33 col34 col35 col36 col37 ... col28 col29 col30 col31 index
0 51 79 61 16 61 ...5 66 2
255 69 93 62 74 37 ... 56 33 55 29 54
[256 rows x 64 columns]
> lambda df: getattr(df, op)(other(df), axis=0, fill_value=fill_value),
)
modin/pandas/test/dataframe/test_binary.py:93:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = col33 col34 col35 col36 col37 ... col28 col29 col30 col31 index
0 51 79 61 16 61 ...5 66 2
255 69 93 62 74 37 ... 56 33 55 29 54
[256 rows x 64 columns]
other = 0 51
1 92
2 14
3 71
4 60
..
251 15
252 96
253 72
254 58
255 69
Name: col33, Length: 256, dtype: int64
axis = 0, level = None, fill_value = 3.0
@Appender(doc)
def f(self, other, axis=default_axis, level=None, fill_value=None):
if should_reindex_frame_op(
self, other, op, axis, default_axis, fill_value, level
):
return frame_arith_method_with_reindex(self, other, op)
if isinstance(other, ABCSeries) and fill_value is not None:
# TODO: We could allow this in cases where we end up going
# through the DataFrame path
> raise NotImplementedError(f"fill_value {fill_value} not supported.")
E NotImplementedError: fill_value 3.0 not supported.
../omnisci-datascience/lib/python3.7/site-packages/pandas/core/ops/__init__.py:428: NotImplementedError
During handling of the above exception, another exception occurred:
other = <function <lambda> at 0x7fbfe6336560>, fill_value = 3.0, op = 'pow'
@pytest.mark.parametrize(
"other",
[lambda df: df[: -(2 ** 4)], lambda df: df[df.columns[0]].reset_index(drop=True)],
ids=["check_missing_value", "check_different_index"],
)
@pytest.mark.parametrize("fill_value", [None, 3.0])
@pytest.mark.parametrize(
"op",
[
*("add", "radd", "sub", "rsub", "mod", "rmod", "pow", "rpow"),
*("truediv", "rtruediv", "mul", "rmul", "floordiv", "rfloordiv"),
],
)
def test_math_functions_fill_value(other, fill_value, op):
data = test_data["int_data"]
modin_df, pandas_df = pd.DataFrame(data), pandas.DataFrame(data)
eval_general(
modin_df,
pandas_df,
> lambda df: getattr(df, op)(other(df), axis=0, fill_value=fill_value),
)
modin/pandas/test/dataframe/test_binary.py:93:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
modin/pandas/test/utils.py:741: in eval_general
operation, md_kwargs=md_kwargs, pd_kwargs=pd_kwargs, inplace=__inplace__
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
fn = <function test_math_functions_fill_value.<locals>.<lambda> at 0x7fbfe7d7d8c0>, inplace = False
md_kwargs = {}, pd_kwargs = {}
def execute_callable(fn, inplace=False, md_kwargs={}, pd_kwargs={}):
try:
pd_result = fn(pandas_df, **pd_kwargs)
except Exception as pd_e:
if check_exception_type is None:
return None
with pytest.raises(Exception) as md_e:
# repr to force materialization
repr(fn(modin_df, **md_kwargs))
if check_exception_type:
assert isinstance(
md_e.value, type(pd_e)
), "Got Modin Exception type {}, but pandas Exception type {} was expected".format(
> type(md_e.value), type(pd_e)
)
E AssertionError: Got Modin Exception type <class 'UserWarning'>, but pandas Exception type <class 'NotImplementedError'> was expected
modin/pandas/test/utils.py:712: AssertionError
__________________ test_math_functions_fill_value[rpow-None-check_different_index] __________________
[gw0] darwin -- Python 3.7.10 /Users/maheshvashishtha/omnisci-datascience/bin/python3.7
other = <function <lambda> at 0x7fbfe6336560>, fill_value = None, op = 'rpow'
@pytest.mark.parametrize(
"other",
[lambda df: df[: -(2 ** 4)], lambda df: df[df.columns[0]].reset_index(drop=True)],
ids=["check_missing_value", "check_different_index"],
)
@pytest.mark.parametrize("fill_value", [None, 3.0])
@pytest.mark.parametrize(
"op",
[
*("add", "radd", "sub", "rsub", "mod", "rmod", "pow", "rpow"),
*("truediv", "rtruediv", "mul", "rmul", "floordiv", "rfloordiv"),
],
)
def test_math_functions_fill_value(other, fill_value, op):
data = test_data["int_data"]
modin_df, pandas_df = pd.DataFrame(data), pandas.DataFrame(data)
eval_general(
modin_df,
pandas_df,
> lambda df: getattr(df, op)(other(df), axis=0, fill_value=fill_value),
)
modin/pandas/test/dataframe/test_binary.py:93:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
modin/pandas/test/utils.py:741: in eval_general
operation, md_kwargs=md_kwargs, pd_kwargs=pd_kwargs, inplace=__inplace__
modin/pandas/test/utils.py:719: in execute_callable
md_result = fn(modin_df, **md_kwargs)
modin/pandas/test/dataframe/test_binary.py:93: in <lambda>
lambda df: getattr(df, op)(other(df), axis=0, fill_value=fill_value),
modin/pandas/dataframe.py:1848: in rpow
"rpow", other, axis=axis, level=level, fill_value=fill_value
modin/pandas/base.py:454: in _default_to_pandas
empty_self_str,
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
cls = <class 'modin.error_message.ErrorMessage'>
message = '`DataFrame.rpow` defaulting to pandas implementation.'
@classmethod
def default_to_pandas(cls, message=""):
if message != "":
message = "{} defaulting to pandas implementation.".format(message)
else:
message = "Defaulting to pandas implementation."
if not cls.printed_request_implementation:
message = (
"{}\n".format(message)
+ "To request implementation, send an email to "
+ "feature_requests@modin.org."
)
cls.printed_request_implementation = True
> warnings.warn(message)
E UserWarning: `DataFrame.rpow` defaulting to pandas implementation.
modin/error_message.py:55: UserWarning
__________________ test_math_functions_fill_value[rpow-3.0-check_different_index] ___________________
[gw0] darwin -- Python 3.7.10 /Users/maheshvashishtha/omnisci-datascience/bin/python3.7
fn = <function test_math_functions_fill_value.<locals>.<lambda> at 0x7fbfe7f4fe60>, inplace = False
md_kwargs = {}, pd_kwargs = {}
def execute_callable(fn, inplace=False, md_kwargs={}, pd_kwargs={}):
try:
> pd_result = fn(pandas_df, **pd_kwargs)
modin/pandas/test/utils.py:701:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
df = col33 col34 col35 col36 col37 ... col28 col29 col30 col31 index
0 51 79 61 16 61 ...5 66 2
255 69 93 62 74 37 ... 56 33 55 29 54
[256 rows x 64 columns]
> lambda df: getattr(df, op)(other(df), axis=0, fill_value=fill_value),
)
modin/pandas/test/dataframe/test_binary.py:93:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = col33 col34 col35 col36 col37 ... col28 col29 col30 col31 index
0 51 79 61 16 61 ...5 66 2
255 69 93 62 74 37 ... 56 33 55 29 54
[256 rows x 64 columns]
other = 0 51
1 92
2 14
3 71
4 60
..
251 15
252 96
253 72
254 58
255 69
Name: col33, Length: 256, dtype: int64
axis = 0, level = None, fill_value = 3.0
@Appender(doc)
def f(self, other, axis=default_axis, level=None, fill_value=None):
if should_reindex_frame_op(
self, other, op, axis, default_axis, fill_value, level
):
return frame_arith_method_with_reindex(self, other, op)
if isinstance(other, ABCSeries) and fill_value is not None:
# TODO: We could allow this in cases where we end up going
# through the DataFrame path
> raise NotImplementedError(f"fill_value {fill_value} not supported.")
E NotImplementedError: fill_value 3.0 not supported.
../omnisci-datascience/lib/python3.7/site-packages/pandas/core/ops/__init__.py:428: NotImplementedError
During handling of the above exception, another exception occurred:
other = <function <lambda> at 0x7fbfe6336560>, fill_value = 3.0, op = 'rpow'
@pytest.mark.parametrize(
"other",
[lambda df: df[: -(2 ** 4)], lambda df: df[df.columns[0]].reset_index(drop=True)],
ids=["check_missing_value", "check_different_index"],
)
@pytest.mark.parametrize("fill_value", [None, 3.0])
@pytest.mark.parametrize(
"op",
[
*("add", "radd", "sub", "rsub", "mod", "rmod", "pow", "rpow"),
*("truediv", "rtruediv", "mul", "rmul", "floordiv", "rfloordiv"),
],
)
def test_math_functions_fill_value(other, fill_value, op):
data = test_data["int_data"]
modin_df, pandas_df = pd.DataFrame(data), pandas.DataFrame(data)
eval_general(
modin_df,
pandas_df,
> lambda df: getattr(df, op)(other(df), axis=0, fill_value=fill_value),
)
modin/pandas/test/dataframe/test_binary.py:93:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
modin/pandas/test/utils.py:741: in eval_general
operation, md_kwargs=md_kwargs, pd_kwargs=pd_kwargs, inplace=__inplace__
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
fn = <function test_math_functions_fill_value.<locals>.<lambda> at 0x7fbfe7f4fe60>, inplace = False
md_kwargs = {}, pd_kwargs = {}
def execute_callable(fn, inplace=False, md_kwargs={}, pd_kwargs={}):
try:
pd_result = fn(pandas_df, **pd_kwargs)
except Exception as pd_e:
if check_exception_type is None:
return None
with pytest.raises(Exception) as md_e:
# repr to force materialization
repr(fn(modin_df, **md_kwargs))
if check_exception_type:
assert isinstance(
md_e.value, type(pd_e)
), "Got Modin Exception type {}, but pandas Exception type {} was expected".format(
> type(md_e.value), type(pd_e)
)
E AssertionError: Got Modin Exception type <class 'UserWarning'>, but pandas Exception type <class 'NotImplementedError'> was expected
modin/pandas/test/utils.py:712: AssertionError
---------- coverage: platform darwin, python 3.7.10-final-0 ----------
Coverage XML written to file coverage.xml
====================================== short test summary info ======================================
FAILED modin/pandas/test/dataframe/test_binary.py::test_math_functions[pow-columns-series_or_list]
FAILED modin/pandas/test/dataframe/test_binary.py::test_math_functions_fill_value[pow-None-check_different_index]
FAILED modin/pandas/test/dataframe/test_binary.py::test_math_functions[rpow-columns-series_or_list]
FAILED modin/pandas/test/dataframe/test_binary.py::test_math_functions_fill_value[pow-3.0-check_different_index]
FAILED modin/pandas/test/dataframe/test_binary.py::test_math_functions_fill_value[rpow-None-check_different_index]
FAILED modin/pandas/test/dataframe/test_binary.py::test_math_functions_fill_value[rpow-3.0-check_different_index]
We need to ensure that we are validating that the tests that default to pandas are indeed defaulting to pandas.