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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,108 @@ | ||
| # Licensed to Modin Development Team under one or more contributor license agreements. | ||
| # See the NOTICE file distributed with this work for additional information regarding | ||
| # copyright ownership. The Modin Development Team 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 modin.config import Engine | ||
| from modin.tests.pandas.utils import NoModinException, create_test_dfs, df_equals | ||
| from modin.utils import try_cast_to_pandas | ||
|
|
||
|
|
||
| def eval_general_interop( | ||
| data, | ||
| backend, | ||
| operation, | ||
| df_mode_pair, | ||
| comparator=df_equals, | ||
| __inplace__=False, | ||
| expected_exception=None, | ||
| check_kwargs_callable=True, | ||
| md_extra_kwargs=None, | ||
| comparator_kwargs=None, | ||
| **kwargs, | ||
| ): | ||
| df_mode1, df_mode2 = df_mode_pair | ||
| modin_df1, pandas_df1 = create_test_dfs(data, backend=backend, df_mode=df_mode1) | ||
| modin_df2, pandas_df2 = create_test_dfs(data, backend=backend, df_mode=df_mode2) | ||
| md_kwargs, pd_kwargs = {}, {} | ||
|
|
||
| def execute_callable(fn, inplace=False, md_kwargs={}, pd_kwargs={}): | ||
| try: | ||
| pd_result = fn(pandas_df1, pandas_df2, **pd_kwargs) | ||
| except Exception as pd_e: | ||
| try: | ||
| if inplace: | ||
| _ = fn(modin_df1, modin_df2, **md_kwargs) | ||
| try_cast_to_pandas(modin_df1) # force materialization | ||
| else: | ||
| try_cast_to_pandas( | ||
| fn(modin_df1, modin_df2, **md_kwargs) | ||
| ) # force materialization | ||
| except Exception as md_e: | ||
| assert isinstance( | ||
| md_e, type(pd_e) | ||
| ), "Got Modin Exception type {}, but pandas Exception type {} was expected".format( | ||
| type(md_e), type(pd_e) | ||
| ) | ||
| if expected_exception: | ||
| if Engine.get() == "Ray": | ||
| from ray.exceptions import RayTaskError | ||
|
|
||
| # unwrap ray exceptions from remote worker | ||
| if isinstance(md_e, RayTaskError): | ||
| md_e = md_e.args[0] | ||
| assert ( | ||
| type(md_e) is type(expected_exception) | ||
| and md_e.args == expected_exception.args | ||
| ), f"not acceptable Modin's exception: [{repr(md_e)}]" | ||
| assert ( | ||
| pd_e.args == expected_exception.args | ||
| ), f"not acceptable Pandas' exception: [{repr(pd_e)}]" | ||
| elif expected_exception is False: | ||
| # The only way to disable exception message checking. | ||
| pass | ||
| else: | ||
| # It’s not enough that Modin and pandas have the same types of exceptions; | ||
| # we need to explicitly specify the instance of an exception | ||
| # (using `expected_exception`) in tests so that we can check exception messages. | ||
| # This allows us to eliminate situations where exceptions are thrown | ||
| # that we don't expect, which could hide different bugs. | ||
| raise pd_e | ||
| else: | ||
| raise NoModinException( | ||
| f"Modin doesn't throw an exception, while pandas does: [{repr(pd_e)}]" | ||
| ) | ||
| else: | ||
| md_result = fn(modin_df1, modin_df2, **md_kwargs) | ||
| return (md_result, pd_result) if not inplace else (modin_df1, pandas_df1) | ||
|
|
||
| for key, value in kwargs.items(): | ||
| if check_kwargs_callable and callable(value): | ||
| values = execute_callable(value) | ||
| # that means, that callable raised an exception | ||
| if values is None: | ||
| return | ||
| else: | ||
| md_value, pd_value = values | ||
| else: | ||
| md_value, pd_value = value, value | ||
|
|
||
| md_kwargs[key] = md_value | ||
| pd_kwargs[key] = pd_value | ||
|
|
||
| if md_extra_kwargs: | ||
| assert isinstance(md_extra_kwargs, dict) | ||
| md_kwargs.update(md_extra_kwargs) | ||
|
|
||
| values = execute_callable( | ||
| operation, md_kwargs=md_kwargs, pd_kwargs=pd_kwargs, inplace=__inplace__ | ||
| ) | ||
| if values is not None: | ||
| comparator(*values, **(comparator_kwargs or {})) |
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