Python:循环遍历由 xmltodict 创建的所有嵌套键值对 [英] Python: Loop through all nested key-value pairs created by xmltodict
问题描述
根据 xml 文件的布局获取特定值非常简单.(请参阅:StackOverflow)
Getting a specific value based on the layout of an xml-file is pretty straight forward. (See: StackOverflow)
但是当我不知道 xml-elements 时，我不能递归它.由于 xmltodoc 将 OrderedDicts 嵌套在 OrderedDicts 中.这些嵌套的 OrderedDict 由 Python 表示为类型:'unicode'.而不是(仍然)作为 OrderedDicts.因此像这样循环，不起作用:
But when I don't know the xml-elements, I can't recurse over it. Since xmltodoc nests OrderedDicts in OrderedDicts. These nested OrderedDicts are typified by Python as type: 'unicode'. And not (still) as OrderedDicts. Therefor looping over like this, doens't work:
def myprint(d):
for k, v in d.iteritems():
if isinstance(v, list):
myprint(v)
else:
print "Key :{0}, Value: {1}".format(k, v)
我基本上想要的是对显示每个键值对的整个 xml 文件进行递归.当一个键的值是另一个键值对列表时，它应该递归到其中.
What I basically want is to recursive over the whole xml-file where every key-value pair is shown. And when a value of a key is another list of key-value pairs, it should recursive into it.
以这个 xml 文件作为输入:
With this xml-file as input:
<?xml version="1.0" encoding="utf-8"?>
<session id="2934" name="Valves" docVersion="5.0.1">
<docInfo>
<field name="Employee" isMandotory="True">Jake Roberts</field>
<field name="Section" isOpen="True" isMandotory="False">5</field>
<field name="Location" isOpen="True" isMandotory="False">Munchen</field>
</docInfo>
</session>
和上面列出的代码一样，会话下的所有数据都作为值添加到关键会话中.
and the above listed code, all data under session is added as a value to the key session.
示例输出:
Key :session, Value: OrderedDict([(u'@id', u'2934'), (u'@name', u'Valves'), (u'@docVersion', u'5.0.1'), (u'docInfo', OrderedDict([(u'field', [OrderedDict([(u'@name', u'Employee'), (u'@isMandotory', u'True'), ('#text', u'Jake Roberts')]), OrderedDict([(u'@name', u'Section'), (u'@isOpen', u'True'), (u'@isMandotory', u'False'), ('#text', u'5')]), OrderedDict([(u'@name', u'Location'), (u'@isOpen', u'True'), (u'@isMandotory', u'False'), ('#text', u'Munchen')])])]))])
这显然不是我想要的.
推荐答案
如果你在数据中遇到一个列表，那么你只需要在列表的每个元素上调用 myprint :
If you come across a list in the data then you just need to call myprint on every element of the list:
def myprint(d):
if isinstance(d,dict): #check if it's a dict before using .iteritems()
for k, v in d.iteritems():
if isinstance(v, (list,dict)): #check for either list or dict
myprint(v)
else:
print "Key :{0}, Value: {1}".format(k, v)
elif isinstance(d,list): #allow for list input too
for item in d:
myprint(item)
然后你会得到类似的输出:
then you will get an output something like:
...
Key :@name, Value: Employee
Key :@isMandotory, Value: True
Key :#text, Value: Jake Roberts
Key :@name, Value: Section
Key :@isOpen, Value: True
Key :@isMandotory, Value: False
Key :#text, Value: 5
...
虽然我不确定这有多大用处，因为你有很多重复的键，比如 @name，但我想提供一个我之前创建的函数来遍历嵌套的 lists的>json数据:
Although I'm not sure how useful this is since you have a lot of duplicate keys like @name, I'd like to offer a function I created a while ago to traverse nested json data of nested dicts and lists:
def traverse(obj, prev_path = "obj", path_repr = "{}[{!r}]".format):
if isinstance(obj,dict):
it = obj.items()
elif isinstance(obj,list):
it = enumerate(obj)
else:
yield prev_path,obj
return
for k,v in it:
for data in traverse(v, path_repr(prev_path,k), path_repr):
yield data
然后你可以遍历数据:
for path,value in traverse(doc):
print("{} = {}".format(path,value))
使用 prev_path 和 path_repr 的默认值，它给出如下输出:
with the default values for prev_path and path_repr it gives output like this:
obj[u'session'][u'@id'] = 2934
obj[u'session'][u'@name'] = Valves
obj[u'session'][u'@docVersion'] = 5.0.1
obj[u'session'][u'docInfo'][u'field'][0][u'@name'] = Employee
obj[u'session'][u'docInfo'][u'field'][0][u'@isMandotory'] = True
obj[u'session'][u'docInfo'][u'field'][0]['#text'] = Jake Roberts
obj[u'session'][u'docInfo'][u'field'][1][u'@name'] = Section
obj[u'session'][u'docInfo'][u'field'][1][u'@isOpen'] = True
obj[u'session'][u'docInfo'][u'field'][1][u'@isMandotory'] = False
obj[u'session'][u'docInfo'][u'field'][1]['#text'] = 5
obj[u'session'][u'docInfo'][u'field'][2][u'@name'] = Location
obj[u'session'][u'docInfo'][u'field'][2][u'@isOpen'] = True
obj[u'session'][u'docInfo'][u'field'][2][u'@isMandotory'] = False
obj[u'session'][u'docInfo'][u'field'][2]['#text'] = Munchen
虽然你可以为path_repr编写一个函数来获取prev_path的值(通过递归调用path_repr确定)和新的key，例如，一个函数接受一个元组并在最后添加另一个元素意味着我们可以获得一个(索引元组:elem)格式，它非常适合传递给 dict 构造函数
although you can write a function for path_repr to take the value of prev_path (determined by recursively calling path_repr) and the new key, for example a function to take a tuple and add another element on the end means we can get a (tuple of indices : elem) format which is perfect to pass to the dict constructor
def _tuple_concat(tup, idx):
return (*tup, idx)
def flatten_data(obj):
"""converts nested dict and list structure into a flat dictionary with tuple keys
corresponding to the sequence of indices to reach particular element"""
return dict(traverse(obj, (), _tuple_concat))
new_data = flatten_data(obj)
import pprint
pprint.pprint(new_data)
它以这种字典格式为您提供数据:
which gives you the data in this dictionary format:
{('session', '@docVersion'): '5.0.1',
('session', '@id'): 2934,
('session', '@name'): 'Valves',
('session', 'docInfo', 'field', 0, '#text'): 'Jake Roberts',
('session', 'docInfo', 'field', 0, '@isMandotory'): True,
('session', 'docInfo', 'field', 0, '@name'): 'Employee',
('session', 'docInfo', 'field', 1, '#text'): 5,
('session', 'docInfo', 'field', 1, '@isMandotory'): False,
('session', 'docInfo', 'field', 1, '@isOpen'): True,
('session', 'docInfo', 'field', 1, '@name'): 'Section',
('session', 'docInfo', 'field', 2, '#text'): 'Munchen',
('session', 'docInfo', 'field', 2, '@isMandotory'): False,
('session', 'docInfo', 'field', 2, '@isOpen'): True,
('session', 'docInfo', 'field', 2, '@name'): 'Location'}
我发现这在处理我的 json 数据时特别有用，但我不确定您想对 xml 做什么.
I found this particularly useful when dealing with my json data but I'm not really sure what you want to do with your xml.
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