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47b9ff6ba1
*ordering* between objects; there is only a default equality test (defined by an object being equal to itself only). Read the comment in object.c. The current implementation never uses a three-way comparison to compute a rich comparison, but it does use a rich comparison to compute a three-way comparison. I'm not quite done ripping out all the calls to PyObject_Compare/Cmp, or replacing tp_compare implementations with tp_richcompare implementations; but much of that has happened (to make most unit tests pass). The following tests still fail, because I need help deciding or understanding: test_codeop -- depends on comparing code objects test_datetime -- need Tim Peters' opinion test_marshal -- depends on comparing code objects test_mutants -- need help understanding it The problem with test_codeop and test_marshal is this: these tests compare two different code objects and expect them to be equal. Is that still a feature we'd like to support? I've temporarily removed the comparison and hash code from code objects, so they use the default (equality by pointer only) comparison. For the other two tests, run them to see for yourself. (There may be more failing test with "-u all".) A general problem with getting lots of these tests to pass is the reality that for object types that have a natural total ordering, implementing __cmp__ is much more convenient than implementing __eq__, __ne__, __lt__, and so on. Should we go back to allowing __cmp__ to provide a total ordering? Should we provide some other way to implement rich comparison with a single method override? Alex proposed a __key__() method; I've considered a __richcmp__() method. Or perhaps __cmp__() just shouldn't be killed off...
287 lines
9 KiB
Python
287 lines
9 KiB
Python
"""Unittests for heapq."""
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from heapq import heappush, heappop, heapify, heapreplace, nlargest, nsmallest
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import random
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import unittest
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from test import test_support
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import sys
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def heapiter(heap):
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# An iterator returning a heap's elements, smallest-first.
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try:
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while 1:
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yield heappop(heap)
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except IndexError:
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pass
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class TestHeap(unittest.TestCase):
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def test_push_pop(self):
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# 1) Push 256 random numbers and pop them off, verifying all's OK.
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heap = []
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data = []
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self.check_invariant(heap)
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for i in range(256):
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item = random.random()
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data.append(item)
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heappush(heap, item)
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self.check_invariant(heap)
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results = []
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while heap:
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item = heappop(heap)
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self.check_invariant(heap)
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results.append(item)
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data_sorted = data[:]
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data_sorted.sort()
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self.assertEqual(data_sorted, results)
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# 2) Check that the invariant holds for a sorted array
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self.check_invariant(results)
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self.assertRaises(TypeError, heappush, [])
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try:
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self.assertRaises(TypeError, heappush, None, None)
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self.assertRaises(TypeError, heappop, None)
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except AttributeError:
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pass
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def check_invariant(self, heap):
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# Check the heap invariant.
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for pos, item in enumerate(heap):
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if pos: # pos 0 has no parent
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parentpos = (pos-1) >> 1
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self.assert_(heap[parentpos] <= item)
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def test_heapify(self):
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for size in range(30):
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heap = [random.random() for dummy in range(size)]
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heapify(heap)
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self.check_invariant(heap)
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self.assertRaises(TypeError, heapify, None)
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def test_naive_nbest(self):
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data = [random.randrange(2000) for i in range(1000)]
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heap = []
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for item in data:
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heappush(heap, item)
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if len(heap) > 10:
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heappop(heap)
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heap.sort()
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self.assertEqual(heap, sorted(data)[-10:])
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def test_nbest(self):
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# Less-naive "N-best" algorithm, much faster (if len(data) is big
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# enough <wink>) than sorting all of data. However, if we had a max
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# heap instead of a min heap, it could go faster still via
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# heapify'ing all of data (linear time), then doing 10 heappops
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# (10 log-time steps).
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data = [random.randrange(2000) for i in range(1000)]
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heap = data[:10]
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heapify(heap)
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for item in data[10:]:
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if item > heap[0]: # this gets rarer the longer we run
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heapreplace(heap, item)
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self.assertEqual(list(heapiter(heap)), sorted(data)[-10:])
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self.assertRaises(TypeError, heapreplace, None)
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self.assertRaises(TypeError, heapreplace, None, None)
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self.assertRaises(IndexError, heapreplace, [], None)
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def test_heapsort(self):
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# Exercise everything with repeated heapsort checks
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for trial in xrange(100):
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size = random.randrange(50)
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data = [random.randrange(25) for i in range(size)]
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if trial & 1: # Half of the time, use heapify
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heap = data[:]
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heapify(heap)
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else: # The rest of the time, use heappush
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heap = []
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for item in data:
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heappush(heap, item)
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heap_sorted = [heappop(heap) for i in range(size)]
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self.assertEqual(heap_sorted, sorted(data))
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def test_nsmallest(self):
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data = [random.randrange(2000) for i in range(1000)]
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f = lambda x: x * 547 % 2000
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for n in (0, 1, 2, 10, 100, 400, 999, 1000, 1100):
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self.assertEqual(nsmallest(n, data), sorted(data)[:n])
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self.assertEqual(nsmallest(n, data, key=f),
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sorted(data, key=f)[:n])
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def test_nlargest(self):
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data = [random.randrange(2000) for i in range(1000)]
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f = lambda x: x * 547 % 2000
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for n in (0, 1, 2, 10, 100, 400, 999, 1000, 1100):
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self.assertEqual(nlargest(n, data), sorted(data, reverse=True)[:n])
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self.assertEqual(nlargest(n, data, key=f),
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sorted(data, key=f, reverse=True)[:n])
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#==============================================================================
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class LenOnly:
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"Dummy sequence class defining __len__ but not __getitem__."
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def __len__(self):
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return 10
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class GetOnly:
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"Dummy sequence class defining __getitem__ but not __len__."
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def __getitem__(self, ndx):
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return 10
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class CmpErr:
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"Dummy element that always raises an error during comparison"
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def __cmp__(self, other):
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raise ZeroDivisionError
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__eq__ = __ne__ = __lt__ = __le__ = __gt__ = __ge__ = __cmp__
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def R(seqn):
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'Regular generator'
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for i in seqn:
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yield i
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class G:
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'Sequence using __getitem__'
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def __init__(self, seqn):
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self.seqn = seqn
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def __getitem__(self, i):
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return self.seqn[i]
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class I:
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'Sequence using iterator protocol'
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def __init__(self, seqn):
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self.seqn = seqn
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self.i = 0
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def __iter__(self):
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return self
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def next(self):
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if self.i >= len(self.seqn): raise StopIteration
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v = self.seqn[self.i]
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self.i += 1
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return v
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class Ig:
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'Sequence using iterator protocol defined with a generator'
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def __init__(self, seqn):
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self.seqn = seqn
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self.i = 0
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def __iter__(self):
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for val in self.seqn:
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yield val
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class X:
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'Missing __getitem__ and __iter__'
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def __init__(self, seqn):
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self.seqn = seqn
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self.i = 0
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def next(self):
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if self.i >= len(self.seqn): raise StopIteration
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v = self.seqn[self.i]
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self.i += 1
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return v
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class N:
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'Iterator missing next()'
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def __init__(self, seqn):
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self.seqn = seqn
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self.i = 0
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def __iter__(self):
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return self
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class E:
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'Test propagation of exceptions'
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def __init__(self, seqn):
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self.seqn = seqn
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self.i = 0
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def __iter__(self):
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return self
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def next(self):
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3 // 0
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class S:
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'Test immediate stop'
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def __init__(self, seqn):
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pass
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def __iter__(self):
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return self
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def next(self):
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raise StopIteration
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from itertools import chain, imap
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def L(seqn):
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'Test multiple tiers of iterators'
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return chain(imap(lambda x:x, R(Ig(G(seqn)))))
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class TestErrorHandling(unittest.TestCase):
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def test_non_sequence(self):
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for f in (heapify, heappop):
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self.assertRaises(TypeError, f, 10)
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for f in (heappush, heapreplace, nlargest, nsmallest):
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self.assertRaises(TypeError, f, 10, 10)
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def test_len_only(self):
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for f in (heapify, heappop):
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self.assertRaises(TypeError, f, LenOnly())
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for f in (heappush, heapreplace):
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self.assertRaises(TypeError, f, LenOnly(), 10)
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for f in (nlargest, nsmallest):
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self.assertRaises(TypeError, f, 2, LenOnly())
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def test_get_only(self):
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for f in (heapify, heappop):
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self.assertRaises(TypeError, f, GetOnly())
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for f in (heappush, heapreplace):
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self.assertRaises(TypeError, f, GetOnly(), 10)
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for f in (nlargest, nsmallest):
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self.assertRaises(TypeError, f, 2, GetOnly())
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def test_get_only(self):
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seq = [CmpErr(), CmpErr(), CmpErr()]
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for f in (heapify, heappop):
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self.assertRaises(ZeroDivisionError, f, seq)
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for f in (heappush, heapreplace):
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self.assertRaises(ZeroDivisionError, f, seq, 10)
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for f in (nlargest, nsmallest):
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self.assertRaises(ZeroDivisionError, f, 2, seq)
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def test_arg_parsing(self):
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for f in (heapify, heappop, heappush, heapreplace, nlargest, nsmallest):
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self.assertRaises(TypeError, f, 10)
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def test_iterable_args(self):
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for f in (nlargest, nsmallest):
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for s in ("123", "", range(1000), (1, 1.2), xrange(2000,2200,5)):
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for g in (G, I, Ig, L, R):
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self.assertEqual(f(2, g(s)), f(2,s))
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self.assertEqual(f(2, S(s)), [])
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self.assertRaises(TypeError, f, 2, X(s))
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self.assertRaises(TypeError, f, 2, N(s))
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self.assertRaises(ZeroDivisionError, f, 2, E(s))
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#==============================================================================
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def test_main(verbose=None):
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from types import BuiltinFunctionType
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test_classes = [TestHeap]
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if isinstance(heapify, BuiltinFunctionType):
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test_classes.append(TestErrorHandling)
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test_support.run_unittest(*test_classes)
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# verify reference counting
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if verbose and hasattr(sys, "gettotalrefcount"):
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import gc
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counts = [None] * 5
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for i in xrange(len(counts)):
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test_support.run_unittest(*test_classes)
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gc.collect()
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counts[i] = sys.gettotalrefcount()
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print counts
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if __name__ == "__main__":
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test_main(verbose=True)
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