| """Unittests for heapq.""" | |
| import random | |
| import unittest | |
| import doctest | |
| from test.support import import_helper | |
| from unittest import TestCase, skipUnless | |
| from operator import itemgetter | |
| py_heapq = import_helper.import_fresh_module('heapq', blocked=['_heapq']) | |
| c_heapq = import_helper.import_fresh_module('heapq', fresh=['_heapq']) | |
| # _heapq.nlargest/nsmallest are saved in heapq._nlargest/_smallest when | |
| # _heapq is imported, so check them there | |
| func_names = ['heapify', 'heappop', 'heappush', 'heappushpop', 'heapreplace'] | |
| # Add max-heap variants | |
| func_names += [func + '_max' for func in func_names] | |
| class TestModules(TestCase): | |
| def test_py_functions(self): | |
| for fname in func_names: | |
| self.assertEqual(getattr(py_heapq, fname).__module__, 'heapq') | |
| @skipUnless(c_heapq, 'requires _heapq') | |
| def test_c_functions(self): | |
| for fname in func_names: | |
| self.assertEqual(getattr(c_heapq, fname).__module__, '_heapq', fname) | |
| def load_tests(loader, tests, ignore): | |
| # The 'merge' function has examples in its docstring which we should test | |
| # with 'doctest'. | |
| # | |
| # However, doctest can't easily find all docstrings in the module (loading | |
| # it through import_fresh_module seems to confuse it), so we specifically | |
| # create a finder which returns the doctests from the merge method. | |
| class HeapqMergeDocTestFinder: | |
| def find(self, *args, **kwargs): | |
| dtf = doctest.DocTestFinder() | |
| return dtf.find(py_heapq.merge) | |
| tests.addTests(doctest.DocTestSuite(py_heapq, | |
| test_finder=HeapqMergeDocTestFinder())) | |
| return tests | |
| class TestHeap: | |
| def test_push_pop(self): | |
| # 1) Push 256 random numbers and pop them off, verifying all's OK. | |
| heap = [] | |
| data = [] | |
| self.check_invariant(heap) | |
| for i in range(256): | |
| item = random.random() | |
| data.append(item) | |
| self.module.heappush(heap, item) | |
| self.check_invariant(heap) | |
| results = [] | |
| while heap: | |
| item = self.module.heappop(heap) | |
| self.check_invariant(heap) | |
| results.append(item) | |
| data_sorted = data[:] | |
| data_sorted.sort() | |
| self.assertEqual(data_sorted, results) | |
| # 2) Check that the invariant holds for a sorted array | |
| self.check_invariant(results) | |
| self.assertRaises(TypeError, self.module.heappush, []) | |
| try: | |
| self.assertRaises(TypeError, self.module.heappush, None, None) | |
| self.assertRaises(TypeError, self.module.heappop, None) | |
| except AttributeError: | |
| pass | |
| def test_max_push_pop(self): | |
| # 1) Push 256 random numbers and pop them off, verifying all's OK. | |
| heap = [] | |
| data = [] | |
| self.check_max_invariant(heap) | |
| for i in range(256): | |
| item = random.random() | |
| data.append(item) | |
| self.module.heappush_max(heap, item) | |
| self.check_max_invariant(heap) | |
| results = [] | |
| while heap: | |
| item = self.module.heappop_max(heap) | |
| self.check_max_invariant(heap) | |
| results.append(item) | |
| data_sorted = data[:] | |
| data_sorted.sort(reverse=True) | |
| self.assertEqual(data_sorted, results) | |
| # 2) Check that the invariant holds for a sorted array | |
| self.check_max_invariant(results) | |
| self.assertRaises(TypeError, self.module.heappush_max, []) | |
| exc_types = (AttributeError, TypeError) | |
| self.assertRaises(exc_types, self.module.heappush_max, None, None) | |
| self.assertRaises(exc_types, self.module.heappop_max, None) | |
| def check_invariant(self, heap): | |
| # Check the heap invariant. | |
| for pos, item in enumerate(heap): | |
| if pos: # pos 0 has no parent | |
| parentpos = (pos-1) >> 1 | |
| self.assertTrue(heap[parentpos] <= item) | |
| def check_max_invariant(self, heap): | |
| for pos, item in enumerate(heap[1:], start=1): | |
| parentpos = (pos - 1) >> 1 | |
| self.assertGreaterEqual(heap[parentpos], item) | |
| def test_heapify(self): | |
| for size in list(range(30)) + [20000]: | |
| heap = [random.random() for dummy in range(size)] | |
| self.module.heapify(heap) | |
| self.check_invariant(heap) | |
| self.assertRaises(TypeError, self.module.heapify, None) | |
| def test_heapify_max(self): | |
| for size in list(range(30)) + [20000]: | |
| heap = [random.random() for dummy in range(size)] | |
| self.module.heapify_max(heap) | |
| self.check_max_invariant(heap) | |
| self.assertRaises(TypeError, self.module.heapify_max, None) | |
| def test_naive_nbest(self): | |
| data = [random.randrange(2000) for i in range(1000)] | |
| heap = [] | |
| for item in data: | |
| self.module.heappush(heap, item) | |
| if len(heap) > 10: | |
| self.module.heappop(heap) | |
| heap.sort() | |
| self.assertEqual(heap, sorted(data)[-10:]) | |
| def heapiter(self, heap): | |
| # An iterator returning a heap's elements, smallest-first. | |
| try: | |
| while 1: | |
| yield self.module.heappop(heap) | |
| except IndexError: | |
| pass | |
| def test_nbest(self): | |
| # Less-naive "N-best" algorithm, much faster (if len(data) is big | |
| # enough <wink>) than sorting all of data. | |
| data = [random.randrange(2000) for i in range(1000)] | |
| heap = data[:10] | |
| self.module.heapify(heap) | |
| for item in data[10:]: | |
| if item > heap[0]: # this gets rarer the longer we run | |
| self.module.heapreplace(heap, item) | |
| self.assertEqual(list(self.heapiter(heap)), sorted(data)[-10:]) | |
| self.assertRaises(TypeError, self.module.heapreplace, None) | |
| self.assertRaises(TypeError, self.module.heapreplace, None, None) | |
| self.assertRaises(IndexError, self.module.heapreplace, [], None) | |
| def test_nbest_maxheap(self): | |
| # With a max heap instead of a min heap, the "N-best" algorithm can | |
| # go even faster still via heapify'ing all of data (linear time), then | |
| # doing 10 heappops (10 log-time steps). | |
| data = [random.randrange(2000) for i in range(1000)] | |
| heap = data[:] | |
| self.module.heapify_max(heap) | |
| result = [self.module.heappop_max(heap) for _ in range(10)] | |
| result.reverse() | |
| self.assertEqual(result, sorted(data)[-10:]) | |
| def test_nbest_with_pushpop(self): | |
| data = [random.randrange(2000) for i in range(1000)] | |
| heap = data[:10] | |
| self.module.heapify(heap) | |
| for item in data[10:]: | |
| self.module.heappushpop(heap, item) | |
| self.assertEqual(list(self.heapiter(heap)), sorted(data)[-10:]) | |
| self.assertEqual(self.module.heappushpop([], 'x'), 'x') | |
| def test_naive_nworst(self): | |
| # Max-heap variant of "test_naive_nbest" | |
| data = [random.randrange(2000) for i in range(1000)] | |
| heap = [] | |
| for item in data: | |
| self.module.heappush_max(heap, item) | |
| if len(heap) > 10: | |
| self.module.heappop_max(heap) | |
| heap.sort() | |
| expected = sorted(data)[:10] | |
| self.assertEqual(heap, expected) | |
| def heapiter_max(self, heap): | |
| # An iterator returning a max-heap's elements, largest-first. | |
| try: | |
| while 1: | |
| yield self.module.heappop_max(heap) | |
| except IndexError: | |
| pass | |
| def test_nworst(self): | |
| # Max-heap variant of "test_nbest" | |
| data = [random.randrange(2000) for i in range(1000)] | |
| heap = data[:10] | |
| self.module.heapify_max(heap) | |
| for item in data[10:]: | |
| if item < heap[0]: # this gets rarer the longer we run | |
| self.module.heapreplace_max(heap, item) | |
| expected = sorted(data, reverse=True)[-10:] | |
| self.assertEqual(list(self.heapiter_max(heap)), expected) | |
| self.assertRaises(TypeError, self.module.heapreplace_max, None) | |
| self.assertRaises(TypeError, self.module.heapreplace_max, None, None) | |
| self.assertRaises(IndexError, self.module.heapreplace_max, [], None) | |
| def test_nworst_minheap(self): | |
| # Min-heap variant of "test_nbest_maxheap" | |
| data = [random.randrange(2000) for i in range(1000)] | |
| heap = data[:] | |
| self.module.heapify(heap) | |
| result = [self.module.heappop(heap) for _ in range(10)] | |
| result.reverse() | |
| expected = sorted(data, reverse=True)[-10:] | |
| self.assertEqual(result, expected) | |
| def test_nworst_with_pushpop(self): | |
| # Max-heap variant of "test_nbest_with_pushpop" | |
| data = [random.randrange(2000) for i in range(1000)] | |
| heap = data[:10] | |
| self.module.heapify_max(heap) | |
| for item in data[10:]: | |
| self.module.heappushpop_max(heap, item) | |
| expected = sorted(data, reverse=True)[-10:] | |
| self.assertEqual(list(self.heapiter_max(heap)), expected) | |
| self.assertEqual(self.module.heappushpop_max([], 'x'), 'x') | |
| def test_heappushpop(self): | |
| h = [] | |
| x = self.module.heappushpop(h, 10) | |
| self.assertEqual((h, x), ([], 10)) | |
| h = [10] | |
| x = self.module.heappushpop(h, 10.0) | |
| self.assertEqual((h, x), ([10], 10.0)) | |
| self.assertEqual(type(h[0]), int) | |
| self.assertEqual(type(x), float) | |
| h = [10] | |
| x = self.module.heappushpop(h, 9) | |
| self.assertEqual((h, x), ([10], 9)) | |
| h = [10] | |
| x = self.module.heappushpop(h, 11) | |
| self.assertEqual((h, x), ([11], 10)) | |
| def test_heappushpop_max(self): | |
| h = [] | |
| x = self.module.heappushpop_max(h, 10) | |
| self.assertTupleEqual((h, x), ([], 10)) | |
| h = [10] | |
| x = self.module.heappushpop_max(h, 10.0) | |
| self.assertTupleEqual((h, x), ([10], 10.0)) | |
| self.assertIsInstance(h[0], int) | |
| self.assertIsInstance(x, float) | |
| h = [10] | |
| x = self.module.heappushpop_max(h, 11) | |
| self.assertTupleEqual((h, x), ([10], 11)) | |
| h = [10] | |
| x = self.module.heappushpop_max(h, 9) | |
| self.assertTupleEqual((h, x), ([9], 10)) | |
| def test_heappop_max(self): | |
| # heapop_max has an optimization for one-item lists which isn't | |
| # covered in other tests, so test that case explicitly here | |
| h = [3, 2] | |
| self.assertEqual(self.module.heappop_max(h), 3) | |
| self.assertEqual(self.module.heappop_max(h), 2) | |
| def test_heapsort(self): | |
| # Exercise everything with repeated heapsort checks | |
| for trial in range(100): | |
| size = random.randrange(50) | |
| data = [random.randrange(25) for i in range(size)] | |
| if trial & 1: # Half of the time, use heapify | |
| heap = data[:] | |
| self.module.heapify(heap) | |
| else: # The rest of the time, use heappush | |
| heap = [] | |
| for item in data: | |
| self.module.heappush(heap, item) | |
| heap_sorted = [self.module.heappop(heap) for i in range(size)] | |
| self.assertEqual(heap_sorted, sorted(data)) | |
| def test_heapsort_max(self): | |
| for trial in range(100): | |
| size = random.randrange(50) | |
| data = [random.randrange(25) for i in range(size)] | |
| if trial & 1: # Half of the time, use heapify_max | |
| heap = data[:] | |
| self.module.heapify_max(heap) | |
| else: # The rest of the time, use heappush_max | |
| heap = [] | |
| for item in data: | |
| self.module.heappush_max(heap, item) | |
| heap_sorted = [self.module.heappop_max(heap) for i in range(size)] | |
| self.assertEqual(heap_sorted, sorted(data, reverse=True)) | |
| def test_merge(self): | |
| inputs = [] | |
| for i in range(random.randrange(25)): | |
| row = [] | |
| for j in range(random.randrange(100)): | |
| tup = random.choice('ABC'), random.randrange(-500, 500) | |
| row.append(tup) | |
| inputs.append(row) | |
| for key in [None, itemgetter(0), itemgetter(1), itemgetter(1, 0)]: | |
| for reverse in [False, True]: | |
| seqs = [] | |
| for seq in inputs: | |
| seqs.append(sorted(seq, key=key, reverse=reverse)) | |
| self.assertEqual(sorted(chain(*inputs), key=key, reverse=reverse), | |
| list(self.module.merge(*seqs, key=key, reverse=reverse))) | |
| self.assertEqual(list(self.module.merge()), []) | |
| def test_empty_merges(self): | |
| # Merging two empty lists (with or without a key) should produce | |
| # another empty list. | |
| self.assertEqual(list(self.module.merge([], [])), []) | |
| self.assertEqual(list(self.module.merge([], [], key=lambda: 6)), []) | |
| def test_merge_does_not_suppress_index_error(self): | |
| # Issue 19018: Heapq.merge suppresses IndexError from user generator | |
| def iterable(): | |
| s = list(range(10)) | |
| for i in range(20): | |
| yield s[i] # IndexError when i > 10 | |
| with self.assertRaises(IndexError): | |
| list(self.module.merge(iterable(), iterable())) | |
| def test_merge_stability(self): | |
| class Int(int): | |
| pass | |
| inputs = [[], [], [], []] | |
| for i in range(20000): | |
| stream = random.randrange(4) | |
| x = random.randrange(500) | |
| obj = Int(x) | |
| obj.pair = (x, stream) | |
| inputs[stream].append(obj) | |
| for stream in inputs: | |
| stream.sort() | |
| result = [i.pair for i in self.module.merge(*inputs)] | |
| self.assertEqual(result, sorted(result)) | |
| def test_nsmallest(self): | |
| data = [(random.randrange(2000), i) for i in range(1000)] | |
| for f in (None, lambda x: x[0] * 547 % 2000): | |
| for n in (0, 1, 2, 10, 100, 400, 999, 1000, 1100): | |
| self.assertEqual(list(self.module.nsmallest(n, data)), | |
| sorted(data)[:n]) | |
| self.assertEqual(list(self.module.nsmallest(n, data, key=f)), | |
| sorted(data, key=f)[:n]) | |
| def test_nlargest(self): | |
| data = [(random.randrange(2000), i) for i in range(1000)] | |
| for f in (None, lambda x: x[0] * 547 % 2000): | |
| for n in (0, 1, 2, 10, 100, 400, 999, 1000, 1100): | |
| self.assertEqual(list(self.module.nlargest(n, data)), | |
| sorted(data, reverse=True)[:n]) | |
| self.assertEqual(list(self.module.nlargest(n, data, key=f)), | |
| sorted(data, key=f, reverse=True)[:n]) | |
| def test_comparison_operator(self): | |
| # Issue 3051: Make sure heapq works with both __lt__ | |
| # For python 3.0, __le__ alone is not enough | |
| def hsort(data, comp): | |
| data = [comp(x) for x in data] | |
| self.module.heapify(data) | |
| return [self.module.heappop(data).x for i in range(len(data))] | |
| class LT: | |
| def __init__(self, x): | |
| self.x = x | |
| def __lt__(self, other): | |
| return self.x > other.x | |
| class LE: | |
| def __init__(self, x): | |
| self.x = x | |
| def __le__(self, other): | |
| return self.x >= other.x | |
| data = [random.random() for i in range(100)] | |
| target = sorted(data, reverse=True) | |
| self.assertEqual(hsort(data, LT), target) | |
| self.assertRaises(TypeError, data, LE) | |
| class TestHeapPython(TestHeap, TestCase): | |
| module = py_heapq | |
| @skipUnless(c_heapq, 'requires _heapq') | |
| class TestHeapC(TestHeap, TestCase): | |
| module = c_heapq | |
| #============================================================================== | |
| class LenOnly: | |
| "Dummy sequence class defining __len__ but not __getitem__." | |
| def __len__(self): | |
| return 10 | |
| class CmpErr: | |
| "Dummy element that always raises an error during comparison" | |
| def __eq__(self, other): | |
| raise ZeroDivisionError | |
| __ne__ = __lt__ = __le__ = __gt__ = __ge__ = __eq__ | |
| def R(seqn): | |
| 'Regular generator' | |
| for i in seqn: | |
| yield i | |
| class G: | |
| 'Sequence using __getitem__' | |
| def __init__(self, seqn): | |
| self.seqn = seqn | |
| def __getitem__(self, i): | |
| return self.seqn[i] | |
| class I: | |
| 'Sequence using iterator protocol' | |
| def __init__(self, seqn): | |
| self.seqn = seqn | |
| self.i = 0 | |
| def __iter__(self): | |
| return self | |
| def __next__(self): | |
| if self.i >= len(self.seqn): raise StopIteration | |
| v = self.seqn[self.i] | |
| self.i += 1 | |
| return v | |
| class Ig: | |
| 'Sequence using iterator protocol defined with a generator' | |
| def __init__(self, seqn): | |
| self.seqn = seqn | |
| self.i = 0 | |
| def __iter__(self): | |
| for val in self.seqn: | |
| yield val | |
| class X: | |
| 'Missing __getitem__ and __iter__' | |
| def __init__(self, seqn): | |
| self.seqn = seqn | |
| self.i = 0 | |
| def __next__(self): | |
| if self.i >= len(self.seqn): raise StopIteration | |
| v = self.seqn[self.i] | |
| self.i += 1 | |
| return v | |
| class N: | |
| 'Iterator missing __next__()' | |
| def __init__(self, seqn): | |
| self.seqn = seqn | |
| self.i = 0 | |
| def __iter__(self): | |
| return self | |
| class E: | |
| 'Test propagation of exceptions' | |
| def __init__(self, seqn): | |
| self.seqn = seqn | |
| self.i = 0 | |
| def __iter__(self): | |
| return self | |
| def __next__(self): | |
| 3 // 0 | |
| class S: | |
| 'Test immediate stop' | |
| def __init__(self, seqn): | |
| pass | |
| def __iter__(self): | |
| return self | |
| def __next__(self): | |
| raise StopIteration | |
| from itertools import chain | |
| def L(seqn): | |
| 'Test multiple tiers of iterators' | |
| return chain(map(lambda x:x, R(Ig(G(seqn))))) | |
| class SideEffectLT: | |
| def __init__(self, value, heap): | |
| self.value = value | |
| self.heap = heap | |
| def __lt__(self, other): | |
| self.heap[:] = [] | |
| return self.value < other.value | |
| class TestErrorHandling: | |
| def test_non_sequence(self): | |
| for f in (self.module.heapify, self.module.heappop, | |
| self.module.heapify_max, self.module.heappop_max): | |
| self.assertRaises((TypeError, AttributeError), f, 10) | |
| for f in (self.module.heappush, self.module.heapreplace, | |
| self.module.heappush_max, self.module.heapreplace_max, | |
| self.module.nlargest, self.module.nsmallest): | |
| self.assertRaises((TypeError, AttributeError), f, 10, 10) | |
| def test_len_only(self): | |
| for f in (self.module.heapify, self.module.heappop, | |
| self.module.heapify_max, self.module.heappop_max): | |
| self.assertRaises((TypeError, AttributeError), f, LenOnly()) | |
| for f in (self.module.heappush, self.module.heapreplace, | |
| self.module.heappush_max, self.module.heapreplace_max): | |
| self.assertRaises((TypeError, AttributeError), f, LenOnly(), 10) | |
| for f in (self.module.nlargest, self.module.nsmallest): | |
| self.assertRaises(TypeError, f, 2, LenOnly()) | |
| def test_cmp_err(self): | |
| seq = [CmpErr(), CmpErr(), CmpErr()] | |
| for f in (self.module.heapify, self.module.heappop): | |
| self.assertRaises(ZeroDivisionError, f, seq) | |
| for f in (self.module.heappush, self.module.heapreplace, | |
| self.module.heappush_max, self.module.heapreplace_max): | |
| self.assertRaises(ZeroDivisionError, f, seq, 10) | |
| for f in (self.module.nlargest, self.module.nsmallest): | |
| self.assertRaises(ZeroDivisionError, f, 2, seq) | |
| def test_arg_parsing(self): | |
| for f in (self.module.heapify, self.module.heappop, | |
| self.module.heappush, self.module.heapreplace, | |
| self.module.heapify_max, self.module.heappop_max, | |
| self.module.heappush_max, self.module.heapreplace_max, | |
| self.module.nlargest, self.module.nsmallest): | |
| self.assertRaises((TypeError, AttributeError), f, 10) | |
| def test_iterable_args(self): | |
| for f in (self.module.nlargest, self.module.nsmallest): | |
| for s in ("123", "", range(1000), (1, 1.2), range(2000,2200,5)): | |
| for g in (G, I, Ig, L, R): | |
| self.assertEqual(list(f(2, g(s))), list(f(2,s))) | |
| self.assertEqual(list(f(2, S(s))), []) | |
| self.assertRaises(TypeError, f, 2, X(s)) | |
| self.assertRaises(TypeError, f, 2, N(s)) | |
| self.assertRaises(ZeroDivisionError, f, 2, E(s)) | |
| # Issue #17278: the heap may change size while it's being walked. | |
| def test_heappush_mutating_heap(self): | |
| heap = [] | |
| heap.extend(SideEffectLT(i, heap) for i in range(200)) | |
| # Python version raises IndexError, C version RuntimeError | |
| with self.assertRaises((IndexError, RuntimeError)): | |
| self.module.heappush(heap, SideEffectLT(5, heap)) | |
| heap = [] | |
| heap.extend(SideEffectLT(i, heap) for i in range(200)) | |
| with self.assertRaises((IndexError, RuntimeError)): | |
| self.module.heappush_max(heap, SideEffectLT(5, heap)) | |
| def test_heappop_mutating_heap(self): | |
| heap = [] | |
| heap.extend(SideEffectLT(i, heap) for i in range(200)) | |
| # Python version raises IndexError, C version RuntimeError | |
| with self.assertRaises((IndexError, RuntimeError)): | |
| self.module.heappop(heap) | |
| heap = [] | |
| heap.extend(SideEffectLT(i, heap) for i in range(200)) | |
| with self.assertRaises((IndexError, RuntimeError)): | |
| self.module.heappop_max(heap) | |
| def test_comparison_operator_modifying_heap(self): | |
| # See bpo-39421: Strong references need to be taken | |
| # when comparing objects as they can alter the heap | |
| class EvilClass(int): | |
| def __lt__(self, o): | |
| heap.clear() | |
| return NotImplemented | |
| heap = [] | |
| self.module.heappush(heap, EvilClass(0)) | |
| self.assertRaises(IndexError, self.module.heappushpop, heap, 1) | |
| def test_comparison_operator_modifying_heap_two_heaps(self): | |
| class h(int): | |
| def __lt__(self, o): | |
| list2.clear() | |
| return NotImplemented | |
| class g(int): | |
| def __lt__(self, o): | |
| list1.clear() | |
| return NotImplemented | |
| list1, list2 = [], [] | |
| self.module.heappush(list1, h(0)) | |
| self.module.heappush(list2, g(0)) | |
| self.assertRaises((IndexError, RuntimeError), self.module.heappush, list1, g(1)) | |
| self.assertRaises((IndexError, RuntimeError), self.module.heappush, list2, h(1)) | |
| list1, list2 = [], [] | |
| self.module.heappush_max(list1, h(0)) | |
| self.module.heappush_max(list2, g(0)) | |
| self.module.heappush_max(list1, g(1)) | |
| self.module.heappush_max(list2, h(1)) | |
| self.assertRaises((IndexError, RuntimeError), self.module.heappush_max, list1, g(1)) | |
| self.assertRaises((IndexError, RuntimeError), self.module.heappush_max, list2, h(1)) | |
| class TestErrorHandlingPython(TestErrorHandling, TestCase): | |
| module = py_heapq | |
| @skipUnless(c_heapq, 'requires _heapq') | |
| class TestErrorHandlingC(TestErrorHandling, TestCase): | |
| module = c_heapq | |
| if __name__ == "__main__": | |
| unittest.main() |