1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
|
import doctest
import unittest
doctests = """
########### Tests borrowed from or inspired by test_genexps.py ############
Test simple loop with conditional
>>> sum([i*i for i in range(100) if i&1 == 1])
166650
Test simple nesting
>>> [(i,j) for i in range(3) for j in range(4)]
[(0, 0), (0, 1), (0, 2), (0, 3), (1, 0), (1, 1), (1, 2), (1, 3), (2, 0), (2, 1), (2, 2), (2, 3)]
Test nesting with the inner expression dependent on the outer
>>> [(i,j) for i in range(4) for j in range(i)]
[(1, 0), (2, 0), (2, 1), (3, 0), (3, 1), (3, 2)]
Test the idiom for temporary variable assignment in comprehensions.
>>> [j*j for i in range(4) for j in [i+1]]
[1, 4, 9, 16]
>>> [j*k for i in range(4) for j in [i+1] for k in [j+1]]
[2, 6, 12, 20]
>>> [j*k for i in range(4) for j, k in [(i+1, i+2)]]
[2, 6, 12, 20]
Not assignment
>>> [i*i for i in [*range(4)]]
[0, 1, 4, 9]
>>> [i*i for i in (*range(4),)]
[0, 1, 4, 9]
Make sure the induction variable is not exposed
>>> i = 20
>>> sum([i*i for i in range(100)])
328350
>>> i
20
Verify that syntax error's are raised for listcomps used as lvalues
>>> [y for y in (1,2)] = 10 # doctest: +IGNORE_EXCEPTION_DETAIL
Traceback (most recent call last):
...
SyntaxError: ...
>>> [y for y in (1,2)] += 10 # doctest: +IGNORE_EXCEPTION_DETAIL
Traceback (most recent call last):
...
SyntaxError: ...
########### Tests borrowed from or inspired by test_generators.py ############
Make a nested list comprehension that acts like range()
>>> def frange(n):
... return [i for i in range(n)]
>>> frange(10)
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
Same again, only as a lambda expression instead of a function definition
>>> lrange = lambda n: [i for i in range(n)]
>>> lrange(10)
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
Generators can call other generators:
>>> def grange(n):
... for x in [i for i in range(n)]:
... yield x
>>> list(grange(5))
[0, 1, 2, 3, 4]
Make sure that None is a valid return value
>>> [None for i in range(10)]
[None, None, None, None, None, None, None, None, None, None]
########### Tests for various scoping corner cases ############
Return lambdas that use the iteration variable as a default argument
>>> items = [(lambda i=i: i) for i in range(5)]
>>> [x() for x in items]
[0, 1, 2, 3, 4]
Same again, only this time as a closure variable
>>> items = [(lambda: i) for i in range(5)]
>>> [x() for x in items]
[4, 4, 4, 4, 4]
Another way to test that the iteration variable is local to the list comp
>>> items = [(lambda: i) for i in range(5)]
>>> i = 20
>>> [x() for x in items]
[4, 4, 4, 4, 4]
And confirm that a closure can jump over the list comp scope
>>> items = [(lambda: y) for i in range(5)]
>>> y = 2
>>> [x() for x in items]
[2, 2, 2, 2, 2]
We also repeat each of the above scoping tests inside a function
>>> def test_func():
... items = [(lambda i=i: i) for i in range(5)]
... return [x() for x in items]
>>> test_func()
[0, 1, 2, 3, 4]
>>> def test_func():
... items = [(lambda: i) for i in range(5)]
... return [x() for x in items]
>>> test_func()
[4, 4, 4, 4, 4]
>>> def test_func():
... items = [(lambda: i) for i in range(5)]
... i = 20
... return [x() for x in items]
>>> test_func()
[4, 4, 4, 4, 4]
>>> def test_func():
... items = [(lambda: y) for i in range(5)]
... y = 2
... return [x() for x in items]
>>> test_func()
[2, 2, 2, 2, 2]
"""
__test__ = {'doctests' : doctests}
def load_tests(loader, tests, pattern):
tests.addTest(doctest.DocTestSuite())
return tests
if __name__ == "__main__":
unittest.main()
|
