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Jython is an implementation of the high-level, dynamic, object-oriented
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the Java platform. It thus allows you to run Python on any Java platform.
"""Unittests for heapq."""
import sys
import random
from test import test_support
from unittest import TestCase, skipUnless
py_heapq = test_support.import_fresh_module('heapq', blocked=['_heapq'])
c_heapq = test_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', '_nlargest', '_nsmallest']
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(TestCase):
module = None
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 range(30):
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 xrange(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 xrange(random.randrange(5)):
row = sorted(random.randrange(1000) for j in range(random.randrange(10)))
inputs.append(row)
self.assertEqual(sorted(chain(*inputs)), list(self.module.merge(*inputs)))
self.assertEqual(list(self.module.merge()), [])
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(self.module.nsmallest(n, data), sorted(data)[:n])
self.assertEqual(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(self.module.nlargest(n, data),
sorted(data, reverse=True)[:n])
self.assertEqual(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__ and __le__
def hsort(data, comp):
data = map(comp, 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.assertEqual(hsort(data, LE), target)
class TestHeapPython(TestHeap):
module = py_heapq
@skipUnless(c_heapq, 'requires _heapq')
class TestHeapC(TestHeap):
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 __cmp__(self, other):
raise ZeroDivisionError
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, imap
def L(seqn):
'Test multiple tiers of iterators'
return chain(imap(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(TestCase):
module = None
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):
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), ('do', 1.2), xrange(2000,2200,5)):
for g in (G, I, Ig, L, R):
with test_support.check_py3k_warnings(
("comparing unequal types not supported",
DeprecationWarning), quiet=True):
self.assertEqual(f(2, g(s)), f(2,s))
self.assertEqual(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):
module = py_heapq
@skipUnless(c_heapq, 'requires _heapq')
class TestErrorHandlingC(TestErrorHandling):
module = c_heapq
#==============================================================================
def test_main(verbose=None):
test_classes = [TestModules, TestHeapPython, TestHeapC,
TestErrorHandlingPython, TestErrorHandlingC]
test_support.run_unittest(*test_classes)
# verify reference counting
if verbose and hasattr(sys, "gettotalrefcount"):
import gc
counts = [None] * 5
for i in xrange(len(counts)):
test_support.run_unittest(*test_classes)
gc.collect()
counts[i] = sys.gettotalrefcount()
print counts
if __name__ == "__main__":
test_main(verbose=True)