我有一个数据结构，本质上相当于一个嵌套的字典。假设它是这样的:
{'new jersey': {'mercer county': {'plumbers': 3,
'programmers': 81},
'middlesex county': {'programmers': 81,
'salesmen': 62}},
'new york': {'queens county': {'plumbers': 9,
'salesmen': 36}}}
现在，维护和创造这个是相当痛苦的;每次我有一个新的州/县/职业，我都必须通过讨厌的try/catch块创建下层字典。此外，如果我想遍历所有值，就必须创建恼人的嵌套迭代器。
我也可以使用元组作为键，像这样:
{('new jersey', 'mercer county', 'plumbers'): 3,
('new jersey', 'mercer county', 'programmers'): 81,
('new jersey', 'middlesex county', 'programmers'): 81,
('new jersey', 'middlesex county', 'salesmen'): 62,
('new york', 'queens county', 'plumbers'): 9,
('new york', 'queens county', 'salesmen'): 36}
这使得遍历值非常简单和自然，但在语法上更痛苦的事情，如聚合和查看字典的子集(例如，如果我只想逐个状态查看)。
基本上，有时我想把一个嵌套字典看作一个平面字典，有时我想把它看作一个复杂的层次结构。我可以把这些都打包到一个类中，但似乎有人已经这样做了。或者，似乎有一些非常优雅的语法结构可以做到这一点。
我怎样才能做得更好呢?
附录:我知道setdefault()，但它并不是真正的干净语法。此外，您创建的每个子字典仍然需要手动设置setdefault()。
我发现setdefault非常有用;它检查一个键是否存在，如果不存在就添加它:
d = {}
d.setdefault('new jersey', {}).setdefault('mercer county', {})['plumbers'] = 3
Setdefault总是返回相关的键，所以你实际上是在原地更新'd'的值。
说到迭代，我相信你可以很容易地编写一个生成器，如果Python中还没有这样的生成器:
def iterateStates(d):
# Let's count up the total number of "plumbers" / "dentists" / etc.
# across all counties and states
job_totals = {}
# I guess this is the annoying nested stuff you were talking about?
for (state, counties) in d.iteritems():
for (county, jobs) in counties.iteritems():
for (job, num) in jobs.iteritems():
# If job isn't already in job_totals, default it to zero
job_totals[job] = job_totals.get(job, 0) + num
# Now return an iterator of (job, number) tuples
return job_totals.iteritems()
# Display all jobs
for (job, num) in iterateStates(d):
print "There are %d %s in total" % (job, num)
可以对Collections.defaultdict进行子类化以生成嵌套的dict。然后向该类添加任何有用的迭代方法。
>>> from collections import defaultdict
>>> class nesteddict(defaultdict):
def __init__(self):
defaultdict.__init__(self, nesteddict)
def walk(self):
for key, value in self.iteritems():
if isinstance(value, nesteddict):
for tup in value.walk():
yield (key,) + tup
else:
yield key, value
>>> nd = nesteddict()
>>> nd['new jersey']['mercer county']['plumbers'] = 3
>>> nd['new jersey']['mercer county']['programmers'] = 81
>>> nd['new jersey']['middlesex county']['programmers'] = 81
>>> nd['new jersey']['middlesex county']['salesmen'] = 62
>>> nd['new york']['queens county']['plumbers'] = 9
>>> nd['new york']['queens county']['salesmen'] = 36
>>> for tup in nd.walk():
print tup
('new jersey', 'mercer county', 'programmers', 81)
('new jersey', 'mercer county', 'plumbers', 3)
('new jersey', 'middlesex county', 'programmers', 81)
('new jersey', 'middlesex county', 'salesmen', 62)
('new york', 'queens county', 'salesmen', 36)
('new york', 'queens county', 'plumbers', 9)
