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
from pandas.core.accessor import PandasDelegate
from pandas.core.base import NoNewAttributesMixin, PandasObject
import pandas.util.testing as tm


class TestPandasDelegate:
    class Delegator:
        _properties = ["foo"]
        _methods = ["bar"]

        def _set_foo(self, value):
            self.foo = value

        def _get_foo(self):
            return self.foo

        foo = property(_get_foo, _set_foo, doc="foo property")

        def bar(self, *args, **kwargs):
            """ a test bar method """
            pass

    class Delegate(PandasDelegate, PandasObject):
        def __init__(self, obj):
            self.obj = obj

    def setup_method(self, method):
        pass

    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())

        with pytest.raises(TypeError):
            delegate.foo

        with pytest.raises(TypeError):
            delegate.foo = 5

        with pytest.raises(TypeError):
            delegate.foo()

    @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")

        with pytest.raises(AttributeError):
            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(
        "klass",
        [
            Series,
            lambda x, **kwargs: DataFrame({"a": x}, **kwargs)["a"],
            pytest.param(
                lambda x, **kwargs: DataFrame(x, **kwargs)[0], marks=pytest.mark.xfail
            ),
            Index,
        ],
    )
    @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, klass):
        # 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":
            with pytest.raises(pd.errors.OutOfBoundsDatetime):
                klass(a)
        else:
            result = klass(a)
            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
        with pytest.raises(pd.errors.OutOfBoundsDatetime):
            klass(a, dtype="datetime64[ns]")
