Tom*_*cat 10 python parsing dictionary nested data-structures
基本上,我想迭代一个文件并将每行的内容放入一个深度嵌套的dict中,其结构由每行开头的空白量定义.
基本上我们的目标是采取这样的方式:
a
b
c
d
e
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把它变成这样的东西:
{"a":{"b":"c","d":"e"}}
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或这个:
apple
colours
red
yellow
green
type
granny smith
price
0.10
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进入这个:
{"apple":{"colours":["red","yellow","green"],"type":"granny smith","price":0.10}
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这样我就可以将它发送到Python的JSON模块并制作一些JSON.
目前我正试图按照这样的步骤制作一个字典和一个列表:
{"a":""} ["a"]{"a":"b"} ["a"]{"a":{"b":"c"}} ["a","b"]{"a":{"b":{"c":"d"}}}} ["a","b","c"]{"a":{"b":{"c":"d"},"e":""}} ["a","e"]{"a":{"b":{"c":"d"},"e":"f"}} ["a","e"]{"a":{"b":{"c":"d"},"e":{"f":"g"}}} ["a","e","f"]等等
该列表的行为类似于"breadcrumbs",显示了我最后输入dict的位置.
要做到这一点,我需要一种方法来遍历列表并生成类似于dict["a"]["e"]["f"]获取最后一个字典的内容.我已经看过有人制作的AutoVivification类看起来非常有用但是我真的不确定:
我提出了以下功能,但它不起作用:
def get_nested(dict,array,i):
if i != None:
i += 1
if array[i] in dict:
return get_nested(dict[array[i]],array)
else:
return dict
else:
i = 0
return get_nested(dict[array[i]],array)
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非常感谢帮助!
(其余的非常不完整的代码在这里:)
#Import relevant libraries
import codecs
import sys
#Functions
def stripped(str):
if tab_spaced:
return str.lstrip('\t').rstrip('\n\r')
else:
return str.lstrip().rstrip('\n\r')
def current_ws():
if whitespacing == 0 or not tab_spaced:
return len(line) - len(line.lstrip())
if tab_spaced:
return len(line) - len(line.lstrip('\t\n\r'))
def get_nested(adict,anarray,i):
if i != None:
i += 1
if anarray[i] in adict:
return get_nested(adict[anarray[i]],anarray)
else:
return adict
else:
i = 0
return get_nested(adict[anarray[i]],anarray)
#initialise variables
jsondict = {}
unclosed_tags = []
debug = []
vividfilename = 'simple.vivid'
# vividfilename = sys.argv[1]
if len(sys.argv)>2:
jsfilename = sys.argv[2]
else:
jsfilename = vividfilename.split('.')[0] + '.json'
whitespacing = 0
whitespace_array = [0,0]
tab_spaced = False
#open the file
with codecs.open(vividfilename,'rU', "utf-8-sig") as vividfile:
for line in vividfile:
#work out how many whitespaces at start
whitespace_array.append(current_ws())
#For first line with whitespace, work out the whitespacing (eg tab vs 4-space)
if whitespacing == 0 and whitespace_array[-1] > 0:
whitespacing = whitespace_array[-1]
if line[0] == '\t':
tab_spaced = True
#strip out whitespace at start and end
stripped_line = stripped(line)
if whitespace_array[-1] == 0:
jsondict[stripped_line] = ""
unclosed_tags.append(stripped_line)
if whitespace_array[-2] < whitespace_array[-1]:
oldnested = get_nested(jsondict,whitespace_array,None)
print oldnested
# jsondict.pop(unclosed_tags[-1])
# jsondict[unclosed_tags[-1]]={stripped_line:""}
# unclosed_tags.append(stripped_line)
print jsondict
print unclosed_tags
print jsondict
print unclosed_tags
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这是一种基于嵌套Node对象复合结构的面向对象方法。
输入:
indented_text = \
"""
apple
colours
red
yellow
green
type
granny smith
price
0.10
"""
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一个节点类
class Node:
def __init__(self, indented_line):
self.children = []
self.level = len(indented_line) - len(indented_line.lstrip())
self.text = indented_line.strip()
def add_children(self, nodes):
childlevel = nodes[0].level
while nodes:
node = nodes.pop(0)
if node.level == childlevel: # add node as a child
self.children.append(node)
elif node.level > childlevel: # add nodes as grandchildren of the last child
nodes.insert(0,node)
self.children[-1].add_children(nodes)
elif node.level <= self.level: # this node is a sibling, no more children
nodes.insert(0,node)
return
def as_dict(self):
if len(self.children) > 1:
return {self.text: [node.as_dict() for node in self.children]}
elif len(self.children) == 1:
return {self.text: self.children[0].as_dict()}
else:
return self.text
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要解析文本,首先创建一个根节点。然后,从文本中删除空行,并Node为每一行创建一个实例,将其传递给add_children根节点的方法。
root = Node('root')
root.add_children([Node(line) for line in indented_text.splitlines() if line.strip()])
d = root.as_dict()['root']
print(d)
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结果:
{'apple': [
{'colours': ['red', 'yellow', 'green']},
{'type': 'granny smith'},
{'price': '0.10'}]
}
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我认为应该可以一步完成,您只需调用Node一次的构造函数,并将缩进的文本作为参数。
这是一个递归解决方案.首先,按以下方式转换输入.
输入:
person:
address:
street1: 123 Bar St
street2:
city: Madison
state: WI
zip: 55555
web:
email: boo@baz.com
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第一步输出:
[{'name':'person','value':'','level':0},
{'name':'address','value':'','level':1},
{'name':'street1','value':'123 Bar St','level':2},
{'name':'street2','value':'','level':2},
{'name':'city','value':'Madison','level':2},
{'name':'state','value':'WI','level':2},
{'name':'zip','value':55555,'level':2},
{'name':'web','value':'','level':1},
{'name':'email','value':'boo@baz.com','level':2}]
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使用split(':')和计算前导标签的数量很容易实现:
def tab_level(astr):
"""Count number of leading tabs in a string
"""
return len(astr)- len(astr.lstrip('\t'))
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然后将第一步输出提供给以下函数:
def ttree_to_json(ttree,level=0):
result = {}
for i in range(0,len(ttree)):
cn = ttree[i]
try:
nn = ttree[i+1]
except:
nn = {'level':-1}
# Edge cases
if cn['level']>level:
continue
if cn['level']<level:
return result
# Recursion
if nn['level']==level:
dict_insert_or_append(result,cn['name'],cn['value'])
elif nn['level']>level:
rr = ttree_to_json(ttree[i+1:], level=nn['level'])
dict_insert_or_append(result,cn['name'],rr)
else:
dict_insert_or_append(result,cn['name'],cn['value'])
return result
return result
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哪里:
def dict_insert_or_append(adict,key,val):
"""Insert a value in dict at key if one does not exist
Otherwise, convert value to list and append
"""
if key in adict:
if type(adict[key]) != list:
adict[key] = [adict[key]]
adict[key].append(val)
else:
adict[key] = val
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