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