175 lines
5.0 KiB
Python
175 lines
5.0 KiB
Python
from datetime import datetime
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import sys
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import numpy as np
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import pytest
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from pandas.compat import PYPY
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import pandas as pd
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from pandas import (
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DataFrame,
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Index,
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Series,
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)
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import pandas._testing as tm
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from pandas.core.accessor import PandasDelegate
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from pandas.core.base import (
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NoNewAttributesMixin,
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PandasObject,
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)
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def series_via_frame_from_dict(x, **kwargs):
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return DataFrame({"a": x}, **kwargs)["a"]
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def series_via_frame_from_scalar(x, **kwargs):
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return DataFrame(x, **kwargs)[0]
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@pytest.fixture(
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params=[
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Series,
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series_via_frame_from_dict,
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series_via_frame_from_scalar,
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Index,
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],
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ids=["Series", "DataFrame-dict", "DataFrame-array", "Index"],
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)
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def constructor(request):
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return request.param
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class TestPandasDelegate:
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class Delegator:
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_properties = ["prop"]
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_methods = ["test_method"]
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def _set_prop(self, value):
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self.prop = value
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def _get_prop(self):
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return self.prop
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prop = property(_get_prop, _set_prop, doc="foo property")
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def test_method(self, *args, **kwargs):
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"""a test method"""
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class Delegate(PandasDelegate, PandasObject):
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def __init__(self, obj) -> None:
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self.obj = obj
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def test_invalid_delegation(self):
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# these show that in order for the delegation to work
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# the _delegate_* methods need to be overridden to not raise
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# a TypeError
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self.Delegate._add_delegate_accessors(
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delegate=self.Delegator,
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accessors=self.Delegator._properties,
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typ="property",
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)
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self.Delegate._add_delegate_accessors(
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delegate=self.Delegator, accessors=self.Delegator._methods, typ="method"
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)
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delegate = self.Delegate(self.Delegator())
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msg = "You cannot access the property prop"
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with pytest.raises(TypeError, match=msg):
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delegate.prop
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msg = "The property prop cannot be set"
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with pytest.raises(TypeError, match=msg):
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delegate.prop = 5
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msg = "You cannot access the property prop"
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with pytest.raises(TypeError, match=msg):
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delegate.prop
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@pytest.mark.skipif(PYPY, reason="not relevant for PyPy")
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def test_memory_usage(self):
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# Delegate does not implement memory_usage.
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# Check that we fall back to in-built `__sizeof__`
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# GH 12924
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delegate = self.Delegate(self.Delegator())
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sys.getsizeof(delegate)
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class TestNoNewAttributesMixin:
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def test_mixin(self):
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class T(NoNewAttributesMixin):
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pass
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t = T()
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assert not hasattr(t, "__frozen")
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t.a = "test"
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assert t.a == "test"
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t._freeze()
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assert "__frozen" in dir(t)
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assert getattr(t, "__frozen")
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msg = "You cannot add any new attribute"
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with pytest.raises(AttributeError, match=msg):
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t.b = "test"
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assert not hasattr(t, "b")
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class TestConstruction:
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# test certain constructor behaviours on dtype inference across Series,
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# Index and DataFrame
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@pytest.mark.parametrize(
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"a",
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[
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np.array(["2263-01-01"], dtype="datetime64[D]"),
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np.array([datetime(2263, 1, 1)], dtype=object),
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np.array([np.datetime64("2263-01-01", "D")], dtype=object),
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np.array(["2263-01-01"], dtype=object),
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],
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ids=[
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"datetime64[D]",
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"object-datetime.datetime",
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"object-numpy-scalar",
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"object-string",
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],
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)
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def test_constructor_datetime_outofbound(self, a, constructor):
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# GH-26853 (+ bug GH-26206 out of bound non-ns unit)
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# No dtype specified (dtype inference)
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# datetime64[non-ns] raise error, other cases result in object dtype
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# and preserve original data
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if a.dtype.kind == "M":
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# Can't fit in nanosecond bounds -> get the nearest supported unit
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result = constructor(a)
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assert result.dtype == "M8[s]"
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else:
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result = constructor(a)
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assert result.dtype == "object"
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tm.assert_numpy_array_equal(result.to_numpy(), a)
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# Explicit dtype specified
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# Forced conversion fails for all -> all cases raise error
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msg = "Out of bounds|Out of bounds .* present at position 0"
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with pytest.raises(pd.errors.OutOfBoundsDatetime, match=msg):
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constructor(a, dtype="datetime64[ns]")
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def test_constructor_datetime_nonns(self, constructor):
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arr = np.array(["2020-01-01T00:00:00.000000"], dtype="datetime64[us]")
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dta = pd.core.arrays.DatetimeArray._simple_new(arr, dtype=arr.dtype)
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expected = constructor(dta)
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assert expected.dtype == arr.dtype
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result = constructor(arr)
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tm.assert_equal(result, expected)
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# https://github.com/pandas-dev/pandas/issues/34843
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arr.flags.writeable = False
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result = constructor(arr)
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tm.assert_equal(result, expected)
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