需要帮助理解for循环的行为

时间:2016-06-27 08:46:20

标签: python for-loop set-comprehension

我正在研究Python 2.7中的集合教程,我遇到了一个使用我不理解的for循环的行为,我试图找出导致差异的原因是什么。输出可能是。

练习的目的是使用for循环从包含由城市对冻结集组成的键的字典中生成一组城市。

数据来自以下字典:

flight_distances = {
    frozenset(['Atlanta', 'Chicago']): 590.0,
    frozenset(['Atlanta', 'Dallas']): 720.0,
    frozenset(['Atlanta', 'Houston']): 700.0,
    frozenset(['Atlanta', 'New York']): 750.0,
    frozenset(['Austin', 'Dallas']): 180.0,
    frozenset(['Austin', 'Houston']): 150.0,
    frozenset(['Boston', 'Chicago']): 850.0,
    frozenset(['Boston', 'Miami']): 1260.0,
    frozenset(['Boston', 'New York']): 190.0,
    frozenset(['Chicago', 'Denver']): 920.0,
    frozenset(['Chicago', 'Houston']): 940.0,
    frozenset(['Chicago', 'Los Angeles']): 1740.0,
    frozenset(['Chicago', 'New York']): 710.0,
    frozenset(['Chicago', 'Seattle']): 1730.0,
    frozenset(['Dallas', 'Denver']): 660.0,
    frozenset(['Dallas', 'Los Angeles']): 1240.0,
    frozenset(['Dallas', 'New York']): 1370.0,
    frozenset(['Denver', 'Los Angeles']): 830.0,
    frozenset(['Denver', 'New York']): 1630.0,
    frozenset(['Denver', 'Seattle']): 1020.0,
    frozenset(['Houston', 'Los Angeles']): 1370.0,
    frozenset(['Houston', 'Miami']): 970.0,
    frozenset(['Houston', 'San Francisco']): 1640.0,
    frozenset(['Los Angeles', 'New York']): 2450.0,
    frozenset(['Los Angeles', 'San Francisco']): 350.0,
    frozenset(['Los Angeles', 'Seattle']): 960.0,
    frozenset(['Miami', 'New York']): 1090.0,
    frozenset(['New York', 'San Francisco']): 2570.0,
    frozenset(['San Francisco', 'Seattle']): 680.0,
}

还有一个测试列表可以创建预期的集合作为检查:

flying_circus_cities = [
    'Houston', 'Chicago', 'Miami', 'Boston', 'Dallas', 'Denver', 
    'New York', 'Los Angeles', 'San Francisco', 'Atlanta', 
    'Seattle', 'Austin'
]

当代码以下面的形式编写时,循环产生预期的结果。

cities = set()
for pair in flight_distances:
    cities = cities.union(pair)
print cities
print "Check:", cities == set(flying_circus_cities)

输出:

set(['Houston', 'Chicago', 'Miami', 'Boston', 'Dallas', 'Denver', 'New York', 'Los Angeles', 'San Francisco', 'Atlanta', 'Seattle', 'Austin'])
Check: True

但是,如果我尝试理解,使用以下任何一种方法,我会得到不同的结果。

cities = set()
cities = {pair for pair in flight_distances}
print cities
print "Check:", cites == set(flying_circus_cities)

cities = set()
cities = cities.union(pair for pair in flight_distances)
print cities
print "Check:", cities == set(flying_circus_cities)

两者的输出:

set([frozenset(['Atlanta', 'Dallas']), frozenset(['San Francisco', 'New York']), frozenset(['Denver', 'Chicago']), frozenset(['Houston', 'San Francisco']), frozenset(['San Francisco', 'Austin']), frozenset(['Seattle', 'Los Angeles']), frozenset(['Boston', 'New York']), frozenset(['Houston', 'Atlanta']), frozenset(['New York', 'Chicago']), frozenset(['San Francisco', 'Seattle']), frozenset(['Austin', 'Dallas']), frozenset(['New York', 'Dallas']), frozenset(['Houston', 'Chicago']), frozenset(['Seattle', 'Denver']), frozenset(['Seattle', 'Chicago']), frozenset(['Miami', 'New York']), frozenset(['Los Angeles', 'Denver']), frozenset(['Miami', 'Houston']), frozenset(['San Francisco', 'Los Angeles']), frozenset(['New York', 'Denver']), frozenset(['Atlanta', 'Chicago']), frozenset(['Boston', 'Chicago']), frozenset(['Houston', 'Austin']), frozenset(['Houston', 'Los Angeles']), frozenset(['New York', 'Los Angeles']), frozenset(['Atlanta', 'New York']), frozenset(['Denver', 'Dallas']), frozenset(['Los Angeles', 'Dallas']), frozenset(['Los Angeles', 'Chicago'])])
Check: False

我无法弄清楚为什么第一个示例中的for循环按预期解包对,以便它生成一个包含每个城市的一个实例的集合,同时尝试编写循环作为理解拉出frozenset([city1, city2])配对并将它们放在集合中。

我不明白为什么pair会在第一个实例中给出城市字符串,但在第二个实例中传递冻结集。

有人可以解释不同的行为吗?

注意:正如Holtdonkopotamus所解释的那样,为什么这种行为方式不同的问题是,在进行单一作业之前,使用理解完全评估了整个字典到cities变量,从而创建一组frozensets,其中标准for循环一次一个地解包对,并分别评估每个对,将它们分配给cities一个每次传递for循环的时间,并允许union函数评估传递给它的对的每个实例。

他们进一步解释说,使用*-operator在理解中解压缩字典以产生所需的行为。

cities = cities.union(*(set(pair) for pair in flight_distances))

2 个答案:

答案 0 :(得分:1)

表达式:

cities = set()
cities = cities.union(pair for pair in flight_distances)

将空集{}与另一集

结合起来
{pair_0, pair_1, pair_2, ..., pair_n}

给你一套套装。

相比之下,以下内容将为您提供所有飞往的城市:

>>> set.union(*(set(pair) for pair in flight_distances))
{'Atlanta',
 'Austin',
 'Boston',
 'Chicago',
 'Dallas',
 'Denver',
 'Houston',
 'Los Angeles',
 'Miami',
 'New York',
 'San Francisco',
 'Seattle'}

这里我们将每个冻结的集合密钥转换为普通集合并找到联合。

答案 1 :(得分:0)

在第一个版本中,pair在每个循环中都是frozenset,因此您可以使用它union,而在您的版本中,您尝试使用{ {1}}的{​​1}}。

第一种情况归结为(在每次迭代时与set联合):

frozenset

所以你有(数学上):

frozenset

在您的(最后一个)案例中,您正在执行以下操作(一个序列为cities = set() cities.union(frozenset(['Atlanta', 'Chicago'])) cities.union(frozenset(['Atlanta', 'Dallas'])) ... 的联合):

cities = {} # Empty set
cities = {} U {'Atlanta', 'Chicago'} = {'Atlanta', 'Chicago'}
cities = {'Atlanta', 'Chicago'} U {'Atlanta', 'Dallas'} = {'Atlanta', 'Chicago', 'Dallas'}
...

所以你有:

frozenset

由于没有两对是相同的,因此您将获得初始字典中所有对的一组,因为您传递的是cities = set() cities.union([frozenset(['Atlanta', 'Chicago']), frozenset(['Atlanta', 'Dallas']), ...]) cities = {} cities = {} U {{'Atlanta', 'Chicago'}, {'Atlanta', 'Dallas'}, ...} = {{'Atlanta', 'Chicago'}, {'Atlanta', 'Dallas'}, ...} # Nothing disappears (对)城市,而不是{{1}城市到set

从更抽象的角度来看,你正试图获得:

set

使用:

set