由于您有一个星型模式设计，您可能希望它的结构更像一个关系表，而不是字典。

import collections

class Jobs( object ):
    def __init__( self, state, county, title, count ):
        self.state= state
        self.count= county
        self.title= title
        self.count= count

facts = [
    Jobs( 'new jersey', 'mercer county', 'plumbers', 3 ),
    ...

def groupBy( facts, name ):
    total= collections.defaultdict( int )
    for f in facts:
        key= getattr( f, name )
        total[key] += f.count

这类事情对于创建一个没有SQL开销的类似数据仓库的设计大有帮助。

您可以创建一个YAML文件，并使用PyYaml读取它。

第一步:创建一个YAML文件"employment.yml":

new jersey:
  mercer county:
    pumbers: 3
    programmers: 81
  middlesex county:
    salesmen: 62
    programmers: 81
new york:
  queens county:
    plumbers: 9
    salesmen: 36

第二步:用Python阅读

import yaml
file_handle = open("employment.yml")
my_shnazzy_dictionary = yaml.safe_load(file_handle)
file_handle.close()

现在my_shnazzy_dictionary有你所有的值。如果需要动态执行此操作，可以将YAML创建为字符串，并将其提供给YAML .safe_load(…)。

除非您的数据集将保持相当小，否则您可能会考虑使用关系数据库。它将完全满足您的需要:方便添加计数、选择计数子集，甚至按州、县、职业或这些的任何组合进行汇总计数。

由于您有一个星型模式设计，您可能希望它的结构更像一个关系表，而不是字典。

import collections

class Jobs( object ):
    def __init__( self, state, county, title, count ):
        self.state= state
        self.count= county
        self.title= title
        self.count= count

facts = [
    Jobs( 'new jersey', 'mercer county', 'plumbers', 3 ),
    ...

def groupBy( facts, name ):
    total= collections.defaultdict( int )
    for f in facts:
        key= getattr( f, name )
        total[key] += f.count

这类事情对于创建一个没有SQL开销的类似数据仓库的设计大有帮助。

对于下面(从上面复制)，是否有一种方法来实现append函数。我试图使用嵌套字典存储值作为数组。

class Vividict(dict):
    def __missing__(self, key):
        value = self[key] = type(self)() # retain local pointer to value
    return value  

我目前的实现如下:

totalGeneHash=Vividict()
        
for keys in GenHash:
    for second in GenHash[keys]:
        if keys in sampleHash:
            total_val = GenHash[keys][second]
                totalGeneHash[gene][keys].append(total_val)
This is the error I get: AttributeError: 'Vividict' object has no attribute 'append'

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)