关于列表：Python RuntimeError：cmp中超出了最大递归深度

Python RuntimeError: maximum recursion depth exceeded in cmp

我试图处理一个复杂的数据结构。

数据结构说明：我有一本类字典。密钥是一个名称。该值是类引用。该类包含两个字典列表。

下面是我的数据结构的一个简单示例：

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import scipy.stats

class employee_salaries(object):
def __init__(self,management, players, disparity):
self.management = management
self.players = players
self.disparity = disparity

# the coach's salary was 12 his 1st year and 11 his 2nd year
mgmt1 = [{'Coach':12, 'Owner':15, 'Team Manager': 13}, {'Coach':11, 'Owner':14, 'Team Manager':15}]
plyrs1 = [{'Point Guard': 14, 'Power Forward':16,},{'Point Guard':16, 'Power Forward':18}]

NBA = {}

mgmt2 = [{'Coach':10, 'Owner':12}, {'Coach':13,'Owner':15}]
plyrs2 = [{'Point Guard':17, 'Power Forward':14}, {'Point Guard': 22, 'Power Forward':16}]

NBA['cavs'] = employee_salaries(mgmt1,plyrs1,0)
NBA['celtics'] = employee_salaries(mgmt2,plyrs2,0)

比如说，我想确定这两年控球后卫的工资和老板的工资之间的差距。

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for key, value in NBA.iteritems():
x1=[]; x2=[]
num = len(NBA[key].players)
for i in range(0,num):
x1.append(NBA[key].players[i]['Point Guard'])
x2.append(NBA[key].management[i]['Owner'])
tau, p_value = scipy.stats.kendalltau(x1, x2)

NBA[key].disparity = tau
print NBA['cavs'].disparity

记住这不是我的真实数据。在我的实际数据结构中，有150多个键。字典列表中还有更多的元素。当我在真实数据上运行上面的代码时，会得到一个运行时错误。

RuntimeError: maximum recursion depth exceeded in cmp error.

如何更改上面的代码，使它不会给我一个最大的递归深度错误？我想进行这种类型的比较，并能够保存该值。

相关讨论

这是一个错误。

固定在0.15

您传入的是空数组，函数处理错误。或者更新scipy，或者在数组为空的情况下跳过(不过，请检查您的数据是否正确，以及在其中使用空数组是否有意义)。

为您的代码提供一些建议。

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for team in NBA.itervalues():
#Or `for name, team in NBA.iteritems()` if you use the name.
x1, x2 = [], []
# Not `x1 = x2 = []`, since that would be two names for one list

for player, manager in izip(team.players, team.management):
x1.append(player['Point Guard'])
x2.append(manager['Owner'])
# Or lose the `for` loop and say:
# `x1 = [player['Point Guard'] for player in team.players]`
# `x2 = [manager['Owner'] for manager in team.management]`
# (This can be more efficient.)

tau, p_value = scipy.stats.kendalltau(x1, x2)

team.disparity = tau

print NBA['cavs'].disparity