# # Licensed to the Apache Software Foundation (ASF) under one or more # contributor license agreements. See the NOTICE file distributed with # this work for additional information regarding copyright ownership. # The ASF 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. # import functools import shutil import tempfile import unittest import warnings from contextlib import contextmanager from distutils.version import LooseVersion import pandas as pd from pandas.api.types import is_list_like from pandas.testing import assert_frame_equal, assert_index_equal, assert_series_equal from pyspark import pandas as ps from pyspark.pandas.frame import DataFrame from pyspark.pandas.indexes import Index from pyspark.pandas.series import Series from pyspark.pandas.utils import default_session, SPARK_CONF_ARROW_ENABLED from pyspark.testing.sqlutils import SQLTestUtils tabulate_requirement_message = None try: from tabulate import tabulate # noqa: F401 except ImportError as e: # If tabulate requirement is not satisfied, skip related tests. tabulate_requirement_message = str(e) have_tabulate = tabulate_requirement_message is None matplotlib_requirement_message = None try: import matplotlib # type: ignore # noqa: F401 except ImportError as e: # If matplotlib requirement is not satisfied, skip related tests. matplotlib_requirement_message = str(e) have_matplotlib = matplotlib_requirement_message is None plotly_requirement_message = None try: import plotly # type: ignore # noqa: F401 except ImportError as e: # If plotly requirement is not satisfied, skip related tests. plotly_requirement_message = str(e) have_plotly = plotly_requirement_message is None class PandasOnSparkTestCase(unittest.TestCase, SQLTestUtils): @classmethod def setUpClass(cls): cls.spark = default_session() cls.spark.conf.set(SPARK_CONF_ARROW_ENABLED, True) @classmethod def tearDownClass(cls): # We don't stop Spark session to reuse across all tests. # The Spark session will be started and stopped at PyTest session level. # Please see databricks/koalas/conftest.py. pass def assertPandasEqual(self, left, right, check_exact=True): if isinstance(left, pd.DataFrame) and isinstance(right, pd.DataFrame): try: if LooseVersion(pd.__version__) >= LooseVersion("1.1"): kwargs = dict(check_freq=False) else: kwargs = dict() assert_frame_equal( left, right, check_index_type=("equiv" if len(left.index) > 0 else False), check_column_type=("equiv" if len(left.columns) > 0 else False), check_exact=check_exact, **kwargs ) except AssertionError as e: msg = ( str(e) + "\n\nLeft:\n%s\n%s" % (left, left.dtypes) + "\n\nRight:\n%s\n%s" % (right, right.dtypes) ) raise AssertionError(msg) from e elif isinstance(left, pd.Series) and isinstance(right, pd.Series): try: if LooseVersion(pd.__version__) >= LooseVersion("1.1"): kwargs = dict(check_freq=False) else: kwargs = dict() assert_series_equal( left, right, check_index_type=("equiv" if len(left.index) > 0 else False), check_exact=check_exact, **kwargs ) except AssertionError as e: msg = ( str(e) + "\n\nLeft:\n%s\n%s" % (left, left.dtype) + "\n\nRight:\n%s\n%s" % (right, right.dtype) ) raise AssertionError(msg) from e elif isinstance(left, pd.Index) and isinstance(right, pd.Index): try: assert_index_equal(left, right, check_exact=check_exact) except AssertionError as e: msg = ( str(e) + "\n\nLeft:\n%s\n%s" % (left, left.dtype) + "\n\nRight:\n%s\n%s" % (right, right.dtype) ) raise AssertionError(msg) from e else: raise ValueError("Unexpected values: (%s, %s)" % (left, right)) def assertPandasAlmostEqual(self, left, right): """ This function checks if given pandas objects approximately same, which means the conditions below: - Both objects are nullable - Compare floats rounding to the number of decimal places, 7 after dropping missing values (NaN, NaT, None) """ if isinstance(left, pd.DataFrame) and isinstance(right, pd.DataFrame): msg = ( "DataFrames are not almost equal: " + "\n\nLeft:\n%s\n%s" % (left, left.dtypes) + "\n\nRight:\n%s\n%s" % (right, right.dtypes) ) self.assertEqual(left.shape, right.shape, msg=msg) for lcol, rcol in zip(left.columns, right.columns): self.assertEqual(lcol, rcol, msg=msg) for lnull, rnull in zip(left[lcol].isnull(), right[rcol].isnull()): self.assertEqual(lnull, rnull, msg=msg) for lval, rval in zip(left[lcol].dropna(), right[rcol].dropna()): self.assertAlmostEqual(lval, rval, msg=msg) self.assertEqual(left.columns.names, right.columns.names, msg=msg) elif isinstance(left, pd.Series) and isinstance(right, pd.Series): msg = ( "Series are not almost equal: " + "\n\nLeft:\n%s\n%s" % (left, left.dtype) + "\n\nRight:\n%s\n%s" % (right, right.dtype) ) self.assertEqual(left.name, right.name, msg=msg) self.assertEqual(len(left), len(right), msg=msg) for lnull, rnull in zip(left.isnull(), right.isnull()): self.assertEqual(lnull, rnull, msg=msg) for lval, rval in zip(left.dropna(), right.dropna()): self.assertAlmostEqual(lval, rval, msg=msg) elif isinstance(left, pd.MultiIndex) and isinstance(right, pd.MultiIndex): msg = ( "MultiIndices are not almost equal: " + "\n\nLeft:\n%s\n%s" % (left, left.dtype) + "\n\nRight:\n%s\n%s" % (right, right.dtype) ) self.assertEqual(len(left), len(right), msg=msg) for lval, rval in zip(left, right): self.assertAlmostEqual(lval, rval, msg=msg) elif isinstance(left, pd.Index) and isinstance(right, pd.Index): msg = ( "Indices are not almost equal: " + "\n\nLeft:\n%s\n%s" % (left, left.dtype) + "\n\nRight:\n%s\n%s" % (right, right.dtype) ) self.assertEqual(len(left), len(right), msg=msg) for lnull, rnull in zip(left.isnull(), right.isnull()): self.assertEqual(lnull, rnull, msg=msg) for lval, rval in zip(left.dropna(), right.dropna()): self.assertAlmostEqual(lval, rval, msg=msg) else: raise ValueError("Unexpected values: (%s, %s)" % (left, right)) def assert_eq(self, left, right, check_exact=True, almost=False): """ Asserts if two arbitrary objects are equal or not. If given objects are Koalas DataFrame or Series, they are converted into pandas' and compared. :param left: object to compare :param right: object to compare :param check_exact: if this is False, the comparison is done less precisely. :param almost: if this is enabled, the comparison is delegated to `unittest`'s `assertAlmostEqual`. See its documentation for more details. """ lobj = self._to_pandas(left) robj = self._to_pandas(right) if isinstance(lobj, (pd.DataFrame, pd.Series, pd.Index)): if almost: self.assertPandasAlmostEqual(lobj, robj) else: self.assertPandasEqual(lobj, robj, check_exact=check_exact) elif is_list_like(lobj) and is_list_like(robj): self.assertTrue(len(left) == len(right)) for litem, ritem in zip(left, right): self.assert_eq(litem, ritem, check_exact=check_exact, almost=almost) elif (lobj is not None and pd.isna(lobj)) and (robj is not None and pd.isna(robj)): pass else: if almost: self.assertAlmostEqual(lobj, robj) else: self.assertEqual(lobj, robj) @staticmethod def _to_pandas(obj): if isinstance(obj, (DataFrame, Series, Index)): return obj.to_pandas() else: return obj class TestUtils(object): @contextmanager def temp_dir(self): tmp = tempfile.mkdtemp() try: yield tmp finally: shutil.rmtree(tmp) @contextmanager def temp_file(self): with self.temp_dir() as tmp: yield tempfile.mktemp(dir=tmp) class ComparisonTestBase(PandasOnSparkTestCase): @property def kdf(self): return ps.from_pandas(self.pdf) @property def pdf(self): return self.kdf.to_pandas() def compare_both(f=None, almost=True): if f is None: return functools.partial(compare_both, almost=almost) elif isinstance(f, bool): return functools.partial(compare_both, almost=f) @functools.wraps(f) def wrapped(self): if almost: compare = self.assertPandasAlmostEqual else: compare = self.assertPandasEqual for result_pandas, result_spark in zip(f(self, self.pdf), f(self, self.kdf)): compare(result_pandas, result_spark.to_pandas()) return wrapped @contextmanager def assert_produces_warning( expected_warning=Warning, filter_level="always", check_stacklevel=True, raise_on_extra_warnings=True, ): """ Context manager for running code expected to either raise a specific warning, or not raise any warnings. Verifies that the code raises the expected warning, and that it does not raise any other unexpected warnings. It is basically a wrapper around ``warnings.catch_warnings``. Notes ----- Replicated from pandas/_testing/_warnings.py. Parameters ---------- expected_warning : {Warning, False, None}, default Warning The type of Exception raised. ``exception.Warning`` is the base class for all warnings. To check that no warning is returned, specify ``False`` or ``None``. filter_level : str or None, default "always" Specifies whether warnings are ignored, displayed, or turned into errors. Valid values are: * "error" - turns matching warnings into exceptions * "ignore" - discard the warning * "always" - always emit a warning * "default" - print the warning the first time it is generated from each location * "module" - print the warning the first time it is generated from each module * "once" - print the warning the first time it is generated check_stacklevel : bool, default True If True, displays the line that called the function containing the warning to show were the function is called. Otherwise, the line that implements the function is displayed. raise_on_extra_warnings : bool, default True Whether extra warnings not of the type `expected_warning` should cause the test to fail. Examples -------- >>> import warnings >>> with assert_produces_warning(): ... warnings.warn(UserWarning()) ... >>> with assert_produces_warning(False): # doctest: +SKIP ... warnings.warn(RuntimeWarning()) ... Traceback (most recent call last): ... AssertionError: Caused unexpected warning(s): ['RuntimeWarning']. >>> with assert_produces_warning(UserWarning): # doctest: +SKIP ... warnings.warn(RuntimeWarning()) Traceback (most recent call last): ... AssertionError: Did not see expected warning of class 'UserWarning' ..warn:: This is *not* thread-safe. """ __tracebackhide__ = True with warnings.catch_warnings(record=True) as w: saw_warning = False warnings.simplefilter(filter_level) yield w extra_warnings = [] for actual_warning in w: if expected_warning and issubclass(actual_warning.category, expected_warning): saw_warning = True if check_stacklevel and issubclass( actual_warning.category, (FutureWarning, DeprecationWarning) ): from inspect import getframeinfo, stack caller = getframeinfo(stack()[2][0]) msg = ( "Warning not set with correct stacklevel. ", "File where warning is raised: {} != ".format(actual_warning.filename), "{}. Warning message: {}".format(caller.filename, actual_warning.message), ) assert actual_warning.filename == caller.filename, msg else: extra_warnings.append( ( actual_warning.category.__name__, actual_warning.message, actual_warning.filename, actual_warning.lineno, ) ) if expected_warning: msg = "Did not see expected warning of class {}".format(repr(expected_warning.__name__)) assert saw_warning, msg if raise_on_extra_warnings and extra_warnings: raise AssertionError("Caused unexpected warning(s): {}".format(repr(extra_warnings)))