def test_filter_performance(self):
total = 1000000
items = [ (x, float(x)) for x in range(0, total) ]
dictionary = dict(items)
start = time.time()
dicttools.filter(lambda x, y: x < total/2, dictionary)
dictionary_elapsed = time.time() - start
start = time.time()
filter(lambda (x, y): x < total/2, items)
list_elapsed = time.time() - start
print('\n dict filter is %2.2fx slower than list filter' % \
(dictionary_elapsed/list_elapsed))
start = time.time()
dicttools.filter(lambda x, y: x < total/2, dictionary, recursive=False)
dictionary_elapsed = time.time() - start
print(' dict filter(recursive=False) is %2.2fx slower than list filter' % \
(dictionary_elapsed/list_elapsed))
def test_filter_odd_keys(self):
"""
simple test to filter keys that are odd from the elements in the
specified dictionary
"""
dictionary = {
0: { 1: {}, 2: {} },
1: { 2: {}, 3: {}, 5: {} },
}
expected = {
1: { 3: {}, 5: {} },
}
# filter out the odd elements
actual = dicttools.filter(lambda key, _: key % 2 != 0,dictionary)
self.assertEquals(expected, actual, msg="%s != %s" % (expected, actual))
def test_filter_values_with_multiple_keys(self):
"""
simple test to filter keys that at least 2 underlying elements associated
with that key
"""
dictionary = {
0: { 1: {}, 2: {} },
1: { 3: {}, 5: {} },
2: { 5: {} },
3: { 7: { 8: {}, 9: {}} },
}
expected = {
0: { },
1: { },
}
# filter out the values that only have 1 underlying set of values
actual = dicttools.filter(lambda _, value: len(value) > 1,
dictionary)
self.assertEquals(expected, actual, msg="%s != %s" % (expected, actual))
