import collections from functools import partial import string import numpy as np import pytest import pandas as pd from pandas import Series import pandas._testing as tm from pandas.core import ops import pandas.core.common as com from pandas.util.version import Version def test_get_callable_name(): getname = com.get_callable_name def fn(x): return x lambda_ = lambda x: x part1 = partial(fn) part2 = partial(part1) class somecall: def __call__(self): # This shouldn't actually get called below; somecall.__init__ # should. raise NotImplementedError assert getname(fn) == "fn" assert getname(lambda_) assert getname(part1) == "fn" assert getname(part2) == "fn" assert getname(somecall()) == "somecall" assert getname(1) is None def test_any_none(): assert com.any_none(1, 2, 3, None) assert not com.any_none(1, 2, 3, 4) def test_all_not_none(): assert com.all_not_none(1, 2, 3, 4) assert not com.all_not_none(1, 2, 3, None) assert not com.all_not_none(None, None, None, None) def test_random_state(): import numpy.random as npr # Check with seed state = com.random_state(5) assert state.uniform() == npr.RandomState(5).uniform() # Check with random state object state2 = npr.RandomState(10) assert com.random_state(state2).uniform() == npr.RandomState(10).uniform() # check with no arg random state assert com.random_state() is np.random # check array-like # GH32503 state_arr_like = npr.randint(0, 2**31, size=624, dtype="uint32") assert ( com.random_state(state_arr_like).uniform() == npr.RandomState(state_arr_like).uniform() ) # Check BitGenerators # GH32503 assert ( com.random_state(npr.MT19937(3)).uniform() == npr.RandomState(npr.MT19937(3)).uniform() ) assert ( com.random_state(npr.PCG64(11)).uniform() == npr.RandomState(npr.PCG64(11)).uniform() ) # Error for floats or strings msg = ( "random_state must be an integer, array-like, a BitGenerator, Generator, " "a numpy RandomState, or None" ) with pytest.raises(ValueError, match=msg): com.random_state("test") with pytest.raises(ValueError, match=msg): com.random_state(5.5) @pytest.mark.parametrize( "left, right, expected", [ (Series([1], name="x"), Series([2], name="x"), "x"), (Series([1], name="x"), Series([2], name="y"), None), (Series([1]), Series([2], name="x"), None), (Series([1], name="x"), Series([2]), None), (Series([1], name="x"), [2], "x"), ([1], Series([2], name="y"), "y"), # matching NAs (Series([1], name=np.nan), pd.Index([], name=np.nan), np.nan), (Series([1], name=np.nan), pd.Index([], name=pd.NaT), None), (Series([1], name=pd.NA), pd.Index([], name=pd.NA), pd.NA), # tuple name GH#39757 ( Series([1], name=np.int64(1)), pd.Index([], name=(np.int64(1), np.int64(2))), None, ), ( Series([1], name=(np.int64(1), np.int64(2))), pd.Index([], name=(np.int64(1), np.int64(2))), (np.int64(1), np.int64(2)), ), pytest.param( Series([1], name=(np.float64("nan"), np.int64(2))), pd.Index([], name=(np.float64("nan"), np.int64(2))), (np.float64("nan"), np.int64(2)), marks=pytest.mark.xfail( reason="Not checking for matching NAs inside tuples." ), ), ], ) def test_maybe_match_name(left, right, expected): res = ops.common._maybe_match_name(left, right) assert res is expected or res == expected def test_standardize_mapping(): # No uninitialized defaultdicts msg = r"to_dict\(\) only accepts initialized defaultdicts" with pytest.raises(TypeError, match=msg): com.standardize_mapping(collections.defaultdict) # No non-mapping subtypes, instance msg = "unsupported type: " with pytest.raises(TypeError, match=msg): com.standardize_mapping([]) # No non-mapping subtypes, class with pytest.raises(TypeError, match=msg): com.standardize_mapping(list) fill = {"bad": "data"} assert com.standardize_mapping(fill) == dict # Convert instance to type assert com.standardize_mapping({}) == dict dd = collections.defaultdict(list) assert isinstance(com.standardize_mapping(dd), partial) def test_git_version(): # GH 21295 git_version = pd.__git_version__ assert len(git_version) == 40 assert all(c in string.hexdigits for c in git_version) def test_version_tag(): version = Version(pd.__version__) try: version > Version("0.0.1") except TypeError: raise ValueError( "No git tags exist, please sync tags between upstream and your repo" ) @pytest.mark.parametrize( "obj", [(obj,) for obj in pd.__dict__.values() if callable(obj)] ) def test_serializable(obj): # GH 35611 unpickled = tm.round_trip_pickle(obj) assert type(obj) == type(unpickled) class TestIsBoolIndexer: def test_non_bool_array_with_na(self): # in particular, this should not raise arr = np.array(["A", "B", np.nan], dtype=object) assert not com.is_bool_indexer(arr) def test_list_subclass(self): # GH#42433 class MyList(list): pass val = MyList(["a"]) assert not com.is_bool_indexer(val) val = MyList([True]) assert com.is_bool_indexer(val) def test_frozenlist(self): # GH#42461 data = {"col1": [1, 2], "col2": [3, 4]} df = pd.DataFrame(data=data) frozen = df.index.names[1:] assert not com.is_bool_indexer(frozen) result = df[frozen] expected = df[[]] tm.assert_frame_equal(result, expected) @pytest.mark.parametrize("with_exception", [True, False]) def test_temp_setattr(with_exception): # GH#45954 ser = Series(dtype=object) ser.name = "first" # Raise a ValueError in either case to satisfy pytest.raises match = "Inside exception raised" if with_exception else "Outside exception raised" with pytest.raises(ValueError, match=match): with com.temp_setattr(ser, "name", "second"): assert ser.name == "second" if with_exception: raise ValueError("Inside exception raised") raise ValueError("Outside exception raised") assert ser.name == "first"