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Jython is an implementation of the high-level, dynamic, object-oriented language Python written in 100% Pure Java, and seamlessly integrated with the Java platform. It thus allows you to run Python on any Java platform.

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import unittest
from test import test_support, seq_tests

class TupleTest(seq_tests.CommonTest):
    type2test = tuple

    def test_constructors(self):
        super(TupleTest, self).test_len()
        # calling built-in types without argument must return empty
        self.assertEqual(tuple(), ())

    def test_truth(self):
        super(TupleTest, self).test_truth()
        self.assert_(not ())
        self.assert_((42, ))

    def test_len(self):
        super(TupleTest, self).test_len()
        self.assertEqual(len(()), 0)
        self.assertEqual(len((0,)), 1)
        self.assertEqual(len((0, 1, 2)), 3)

    def test_iadd(self):
        super(TupleTest, self).test_iadd()
        u = (0, 1)
        u2 = u
        u += (2, 3)
        self.assert_(u is not u2)

    def test_imul(self):
        super(TupleTest, self).test_imul()
        u = (0, 1)
        u2 = u
        u *= 3
        self.assert_(u is not u2)

    def test_tupleresizebug(self):
        # Check that a specific bug in _PyTuple_Resize() is squashed.
        def f():
            for i in range(1000):
                yield i
        self.assertEqual(list(tuple(f())), range(1000))

    def test_hash(self):
        from java.lang import OutOfMemoryError
        try:
            self._test_hash()
        except OutOfMemoryError, oome:
            oome.printStackTrace()
            raise

    def _test_hash(self):
        # See SF bug 942952:  Weakness in tuple hash
        # The hash should:
        #      be non-commutative
        #      should spread-out closely spaced values
        #      should not exhibit cancellation in tuples like (x,(x,y))
        #      should be distinct from element hashes:  hash(x)!=hash((x,))
        # This test exercises those cases.
        # For a pure random hash and N=50, the expected number of occupied
        #      buckets when tossing 252,600 balls into 2**32 buckets
        #      is 252,592.6, or about 7.4 expected collisions.  The
        #      standard deviation is 2.73.  On a box with 64-bit hash
        #      codes, no collisions are expected.  Here we accept no
        #      more than 15 collisions.  Any worse and the hash function
        #      is sorely suspect.

        N=50
        base = range(N)
        xp = [(i, j) for i in base for j in base]
        inps = base + [(i, j) for i in base for j in xp] + \
                     [(i, j) for i in xp for j in base] + xp + zip(base)
        hashes = map(hash, inps)
        unique = set(hashes)
        unique_len = len(unique)
        collisions  = len(inps) - unique_len
        #collisions = len(inps) - len(set(map(hash, inps)))
        self.assert_(collisions <= 15)

    def test_repr(self):
        l0 = tuple()
        l2 = (0, 1, 2)
        a0 = self.type2test(l0)
        a2 = self.type2test(l2)

        self.assertEqual(str(a0), repr(l0))
        self.assertEqual(str(a2), repr(l2))
        self.assertEqual(repr(a0), "()")
        self.assertEqual(repr(a2), "(0, 1, 2)")

    def test_setitem(self):
        #This test is equivalent to (1,2)[0] = 0 which was briefly broken in
        #Jython 2.5b2
        import operator
        self.assertRaises(TypeError, operator.setitem, (1,2), 0, 0)

def test_main():
    test_support.run_unittest(TupleTest)

if __name__=="__main__":
    test_main()