#  Unit test case for testing interfaces and adaptation.
#
#  Written by: David C. Morrill
#
#  Date: 4/10/2007
#
#  Copyright (c) 2007, Enthought, Inc.
#  All rights reserved.
#
#  This software is provided without warranty under the terms of the BSD
#  license included in /LICENSE.txt and may be redistributed only
#  under the conditions described in the aforementioned license.  The license
#  is also available online at http://www.enthought.com/licenses/BSD.txt
""" Unit test case for testing interfaces and adaptation.

This file is equivalent to test_interfaces.py, only using the deprecated
'implements' and 'adapts' functions.

"""



import sys

from traits.testing.unittest_tools import unittest
from traits.adaptation.api import get_global_adaptation_manager, \
    set_global_adaptation_manager
from traits.api import HasTraits, Adapter, adapts, AdaptsTo, \
    implements, Instance, Int, Interface, List, Supports, TraitError


# Using the deprecated class advisor "adapts", the registration of adapters
# occurs globally at class definition time. Since other tests will reset the
# global adaptation manager, the registration will be lost.
# That's why we save a reference to the current global adaptation manager.
_adaptation_manager = get_global_adaptation_manager()


#------------------------------------------------------------------------------
#  Test 'Interface' definitions:
#------------------------------------------------------------------------------

# 'adapts' and 'implements' are not supported in Python 3.
if sys.version_info < (3,):

    class IFoo(Interface):

        def get_foo(self):
            """ Returns the current foo. """


    class IFooPlus(IFoo):

        def get_foo_plus(self):
            """ Returns even more foo. """


    class IAverage(Interface):

        def get_average(self):
            """ Returns the average value for the object. """


    class IList(Interface):

        def get_list(self):
            """ Returns the list value for the object. """


    class Sample(HasTraits):
        s1 = Int(1, sample=True)
        s2 = Int(2, sample=True)
        s3 = Int(3, sample=True)
        i1 = Int(4)
        i2 = Int(5)
        i3 = Int(6)


    class SampleList(HasTraits):

        implements(IList)

        data = List(Int, [10, 20, 30])

        def get_list(self):
            return self.data


    class SampleAverage(HasTraits):

        implements(IList, IAverage)

        data = List(Int, [100, 200, 300])

        def get_list(self):
            return self.data

        def get_average(self):
            value = self.get_list()
            if len(value) == 0:
                return 0.0

            average = 0.0
            for item in value:
                average += item
            return (average / len(value))


    class SampleBad(HasTraits):
        pass


    class TraitsHolder(HasTraits):

        a_no = Instance(IAverage, adapt='no')
        a_yes = Instance(IAverage, adapt='yes')
        a_default = Instance(IAverage, adapt='default')
        list_adapted_to = Supports(IList)
        foo_adapted_to = Supports(IFoo)
        foo_plus_adapted_to = Supports(IFooPlus)
        list_adapts_to = AdaptsTo(IList)
        foo_adapts_to = AdaptsTo(IFoo)
        foo_plus_adapts_to = AdaptsTo(IFooPlus)


    class SampleListAdapter(Adapter):
        adapts(Sample, IList)

        def get_list(self):
            obj = self.adaptee
            return [getattr(obj, name)
                    for name in obj.trait_names(sample=True)]


    class ListAverageAdapter(Adapter):

        adapts(IList, IAverage)

        def get_average(self):
            value = self.adaptee.get_list()
            if len(value) == 0:
                return 0.0

            average = 0.0
            for item in value:
                average += item
            return (average / len(value))


    class SampleFooAdapter(HasTraits):

        adapts(Sample, IFoo)

        object = Instance(Sample)

        def __init__(self, object):
            self.object = object

        def get_foo(self):
            object = self.object
            return (object.s1 + object.s2 + object.s3)


    class FooPlusAdapter(object):

        def __init__(self, obj):
            self.obj = obj

        def get_foo(self):
            return self.obj.get_foo()

        def get_foo_plus(self):
            return (self.obj.get_foo() + 1)

    adapts(FooPlusAdapter, IFoo, IFooPlus)


@unittest.skipUnless(sys.version_info < (3,),
                     "The 'adapts' and 'implements' class advisors "
                     "are not supported in Python 3.")
class InterfacesTest(unittest.TestCase):

    #### 'TestCase' protocol ##################################################

    def setUp(self):
        set_global_adaptation_manager(_adaptation_manager)

    #### Tests ################################################################

    def test_implements_none(self):
        class Test(HasTraits):
            implements()

    def test_implements_one(self):
        class Test(HasTraits):
            implements(IFoo)

    def test_implements_multi(self):
        class Test(HasTraits):
            implements(IFoo, IAverage, IList)

    def test_implements_extended(self):
        """ Ensure that subclasses of Interfaces imply the superinterface.
        """
        class Test(HasTraits):
            implements(IFooPlus)

        ta = TraitsHolder()
        ta.foo_adapted_to = Test()

    def test_implements_bad(self):
        self.assertRaises(TraitError, self.implements_bad)

    def test_instance_adapt_no(self):
        ta = TraitsHolder()

        # Verify that SampleAverage() does not raise an error (it is an
        # instance of the IAverage interface).
        try:
            ta.a_no = SampleAverage()
        except TraitError:
            self.fail("Setting instance of interface should not require "
                      "adaptation")

        # These are not instances of the IAverage interface, and therefore
        # cannot be set to the trait.
        self.assertRaises(TraitError, ta.trait_set, a_no=SampleList())
        self.assertRaises(TraitError, ta.trait_set, a_no=Sample())
        self.assertRaises(TraitError, ta.trait_set, a_no=SampleBad())

    def test_instance_adapt_yes(self):
        ta = TraitsHolder()

        ta.a_yes = object = SampleAverage()
        self.assertEqual(ta.a_yes.get_average(), 200.0)
        self.assertIsInstance(ta.a_yes, SampleAverage)
        self.assertFalse(hasattr(ta, 'a_yes_'))

        ta.a_yes = object = SampleList()
        self.assertEqual(ta.a_yes.get_average(), 20.0)
        self.assertIsInstance(ta.a_yes, ListAverageAdapter)
        self.assertFalse(hasattr(ta, 'a_yes_'))

        ta.a_yes = object = Sample()
        self.assertEqual(ta.a_yes.get_average(), 2.0)
        self.assertIsInstance(ta.a_yes, ListAverageAdapter)
        self.assertFalse(hasattr(ta, 'a_yes_'))

        self.assertRaises(TraitError, ta.trait_set, a_yes=SampleBad())

    def test_instance_adapt_default(self):
        ta = TraitsHolder()

        ta.a_default = object = SampleAverage()
        self.assertEqual(ta.a_default.get_average(), 200.0)
        self.assertIsInstance(ta.a_default, SampleAverage)
        self.assertFalse(hasattr(ta, 'a_default_'))

        ta.a_default = object = SampleList()
        self.assertEqual(ta.a_default.get_average(), 20.0)
        self.assertIsInstance(ta.a_default, ListAverageAdapter)
        self.assertFalse(hasattr(ta, 'a_default_'))

        ta.a_default = object = Sample()
        self.assertEqual(ta.a_default.get_average(), 2.0)
        self.assertIsInstance(ta.a_default, ListAverageAdapter)
        self.assertFalse(hasattr(ta, 'a_default_'))

        ta.a_default = object = SampleBad()
        self.assertEqual(ta.a_default, None)
        self.assertFalse(hasattr(ta, 'a_default_'))

    def test_adapted_to(self):
        ta = TraitsHolder()

        ta.list_adapted_to = object = Sample()
        result = ta.list_adapted_to.get_list()
        self.assertEqual(len(result), 3)
        for n in [1, 2, 3]:
            self.assertIn(n, result)
        self.assertIsInstance(ta.list_adapted_to, SampleListAdapter)
        self.assertEqual(ta.list_adapted_to_, object)

        ta.foo_adapted_to = object = Sample()
        self.assertEqual(ta.foo_adapted_to.get_foo(), 6)
        self.assertIsInstance(ta.foo_adapted_to, SampleFooAdapter)
        self.assertEqual(ta.foo_adapted_to_, object)

        ta.foo_plus_adapted_to = object = Sample(s1=5, s2=10, s3=15)
        self.assertEqual(ta.foo_plus_adapted_to.get_foo(), 30)
        self.assertEqual(ta.foo_plus_adapted_to.get_foo_plus(), 31)
        self.assertIsInstance(ta.foo_plus_adapted_to, FooPlusAdapter)
        self.assertEqual(ta.foo_plus_adapted_to_, object)

    def test_adapts_to(self):
        ta = TraitsHolder()

        ta.list_adapts_to = object = Sample()
        self.assertEqual(ta.list_adapts_to, object)
        result = ta.list_adapts_to_.get_list()
        self.assertEqual(len(result), 3)
        for n in [1, 2, 3]:
            self.assertIn(n, result)
        self.assertIsInstance(ta.list_adapts_to_, SampleListAdapter)

        ta.foo_adapts_to = object = Sample()
        self.assertEqual(ta.foo_adapts_to, object)
        self.assertEqual(ta.foo_adapts_to_.get_foo(), 6)
        self.assertIsInstance(ta.foo_adapts_to_, SampleFooAdapter)

        ta.foo_plus_adapts_to = object = Sample(s1=5, s2=10, s3=15)
        self.assertEqual(ta.foo_plus_adapts_to, object)
        self.assertEqual(ta.foo_plus_adapts_to_.get_foo(), 30)
        self.assertEqual(ta.foo_plus_adapts_to_.get_foo_plus(), 31)
        self.assertIsInstance(ta.foo_plus_adapts_to_, FooPlusAdapter)

    #-- Helper Methods --------------------------------------------------------

    def implements_bad(self):
        class Test(HasTraits):
            implements(Sample)

# Run the unit tests (if invoked from the command line):
if __name__ == '__main__':
    unittest.main()
