我正在尝试从python中的一个简单表构建一个json层次结构。
数据如下所示：
id parent name
1 10 test-name-1
2 10 test-name-2
3 5 test-name-3
4 none test-name-4
5 10 test-name-5
6 none test-name-6
7 1 test-name-7
8 1 test-name-8
9 8 test-name-9
10 4 test-name-10
我正在寻找这样的输出：
{"$4":{"name":"test-name-4","children":{
"$10":{"name":"test-name-10","children":{
"$1":{"name":"test-name-1","children":{
"$7":{"name":"test-name-7","children":{}},
"$8":{"name":"test-name-8","children":{
"$9":{"name":"test-name-9","children":{}}}}}},
"$2":{"name":"test-name-2","children":{}},
"$5":{"name":"test-name-5","children":{
"$3":{"name":"test-name-3","children":{}}}}}}}},
"$6":{"name":"test-name-6","children":"test-name-6"}}
我不知道会有多少“叶子”或“根”，或者来自csv的行的顺序是什么。我的问题是，有没有办法可以递归地构建字典/列表一个子节点直到父节点？如何从python中树的“叶子”片段生成分层树？
感谢您的帮助！
答案 0 :(得分：6)
我有一个基于2个循环的解决方案（1个缓存，1个构建），没有JSON编码器，并且可以提供您所需的输出：
>>> import re
>>> from collections import defaultdict
>>> parents = defaultdict(list)
>>> for i, line in enumerate(file_.split('\n')):
if i != 0 and line.strip():
id_, parent, name = re.findall(r'[\d\w-]+', line)
parents[parent].append((id_, name))
>>> parents
defaultdict(<type 'list'>, {'10': [('1', 'test-name-1'), ('2', 'test-name-2'), ('5', 'test-name-5')], 'none': [('4', 'test-name-4'), ('6', 'test-name-6')], '1': [('7', 'test-name-7'), ('8', 'test-name-8')], '5': [('3', 'test-name-3')], '4': [('10', 'test-name-10')], '8': [('9', 'test-name-9')]})
好的，现在我们有了缓存，递归函数很容易构建我们想要的输出：
>>> def build_tree(d, val):
return {'$' + id_: {'name': name, 'children': build_tree(d, id_)} for id_, name in d[val]}
我们只需要在之前构建的dict上调用它，值为'none'，即树根：
>>> from pprint import pprint
>>> pprint(build_tree(parents, 'none'))
{'$4': {'children': {'$10': {'children': {'$1': {'children': {'$7': {'children': {},
'name': 'test-name-7'},
'$8': {'children': {'$9': {'children': {},
'name': 'test-name-9'}},
'name': 'test-name-8'}},
'name': 'test-name-1'},
'$2': {'children': {},
'name': 'test-name-2'},
'$5': {'children': {'$3': {'children': {},
'name': 'test-name-3'}},
'name': 'test-name-5'}},
'name': 'test-name-10'}},
'name': 'test-name-4'},
'$6': {'children': {}, 'name': 'test-name-6'}}
>>>
答案 1 :(得分：3)
要将所有子节点分配给其父节点，可以对节点列表执行两次传递。第一遍将每个节点添加到UserDict。在第二次传递中，每个节点的父节点都保证在UserDict中，因此节点可以添加到其父节点的children。
要序列化为JSON，可以使用JSONEncoder。
#!/usr/bin/env python
import sys
import json
import UserDict
class Node(object):
def __init__(self, nid, parent, name):
self.nid = nid
self.parent = parent
self.children = []
self.name = name
class NodeDict(UserDict.UserDict):
def addNodes(self, nodes):
""" Add every node as a child to its parent by doing two passes."""
for i in (1, 2):
for node in nodes:
self.data[node.nid] = node
if node.parent in self.data.keys():
if node.parent != "none" and
node not in self.data[node.parent].children:
self.data[node.parent].children.append(node)
class NodeJSONEncoder(json.JSONEncoder):
def default(self, node):
if type(node) == Node:
return {"nid":node.nid, "name":node.name, "children":node.children}
raise TypeError("{} is not an instance of Node".format(node))
if __name__ == "__main__":
nodes = []
with open(sys.argv[1]) as f:
for row in f.readlines()[1:]:
nid, parent, name = row.split()
nodes.append(Node(nid, parent, name))
nodeDict = NodeDict()
nodeDict.addNodes(nodes)
rootNodes = [node for nid, node in nodeDict.items()
if node.parent == "none"]
for rootNode in rootNodes:
print NodeJSONEncoder().encode(rootNode)
结果：
{"name": "test-name-4", "nid": "4", "children":[
{"name": "test-name-10", "nid": "10", "children":[
{"name": "test-name-1", "nid": "1", "children":[
{"name": "test-name-7", "nid": "7", "children": []},
{"name": "test-name-8", "nid": "8", "children":[
{"name": "test-name-9", "nid": "9", "children": []}]}]},
{"name": "test-name-2", "nid": "2", "children": []},
{"name": "test-name-5", "nid": "5", "children":[
{"name": "test-name-3", "nid": "3", "children": []}]}]}]}
{"name": "test-name-6", "nid": "6", "children": []}
答案 2 :(得分：0)
给出的答案在python 3.6中对我不起作用，因为Dict.Dict已被弃用。所以我进行了一些更改以使其工作并通过让用户通过命令行指定child_id，parent_id和子名称的列来稍微概括它。请看下面（我刚刚学习并确信这可以改进，但它适用于我的目的）。
""" Converts a CSV file with Parent/Child Hierarchy to a hierarchical JSON file for front-end processing (javascript/DS)
USAGE: csv2json.py <somefile.csv> a b c (column nrs of a=child_id, b=parent-id, c=name(of child))
ROOT of hierarchy should contain child_id and parent_id = 'none' or blank. name must exist """
import sys
import json
import csv
#import UserDict
from collections import UserDict
class Node(object):
def __init__(self, child_id, parent_id, name):
self.child_id = child_id
self.parent_id = parent_id
self.children = []
self.name = name
class NodeDict(UserDict):
def addNodes(self, nodes):
""" Add every node as a child to its parent_id by doing two passes."""
for i in (1, 2):
for node in nodes:
self.data[node.child_id] = node
if node.parent_id in self.data.keys():
if (node.parent_id != "none" or node.parent_id != "") and node not in self.data[node.parent_id].children:
self.data[node.parent_id].children.append(node)
class NodeJSONEncoder(json.JSONEncoder):
def default(self, node):
if type(node) == Node:
return {"name":node.name, "children":node.children}
raise TypeError("{} is not an instance of Node".format(node))
if __name__ == "__main__":
nodes = []
with open(sys.argv[1], 'r') as f:
reader = csv.reader(f)
for row in reader:
if not row[int(sys.argv[4])] : #skip if no name/label exists
continue
child_id, parent_id, name = row[int(sys.argv[2])] , row[int(sys.argv[3])] , row[int(sys.argv[4])]
nodes.append(Node(child_id, parent_id, name))
nodeDict = NodeDict()
nodeDict.addNodes(nodes)
rootNodes = [node for child_id, node in nodeDict.items()
if (node.parent_id == "none" or node.parent_id == "")]
for rootNode in rootNodes:
print(NodeJSONEncoder().encode(rootNode))