"""Unittests for heapq.""" import random import unittest from test import support from unittest import TestCase, skipUnless from operator import itemgetter py_heapq = support.import_fresh_module('heapq', blocked=['_heapq']) c_heapq = support.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', '_heappop_max', '_heapreplace_max', '_heapify_max'] 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') 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 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 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_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 ) than sorting all of data. However, if we had a max # heap instead of a min heap, it could go 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[: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_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_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_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_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_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 GetOnly: "Dummy sequence class defining __getitem__ but not __len__." def __getitem__(self, ndx): 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.assertRaises((TypeError, AttributeError), f, 10) for f in (self.module.heappush, self.module.heapreplace, 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.assertRaises((TypeError, AttributeError), f, LenOnly()) for f in (self.module.heappush, self.module.heapreplace): self.assertRaises((TypeError, AttributeError), f, LenOnly(), 10) for f in (self.module.nlargest, self.module.nsmallest): self.assertRaises(TypeError, f, 2, LenOnly()) def test_get_only(self): for f in (self.module.heapify, self.module.heappop): self.assertRaises(TypeError, f, GetOnly()) for f in (self.module.heappush, self.module.heapreplace): self.assertRaises(TypeError, f, GetOnly(), 10) for f in (self.module.nlargest, self.module.nsmallest): self.assertRaises(TypeError, f, 2, GetOnly()) def test_get_only(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.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.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)) 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) class TestErrorHandlingPython(TestErrorHandling, TestCase): module = py_heapq @skipUnless(c_heapq, 'requires _heapq') class TestErrorHandlingC(TestErrorHandling, TestCase): module = c_heapq if __name__ == "__main__": unittest.main()