如何首先从父级递归对数据进行排序，然后使用 python 对其子级进行排序？

Question

我有一个名为 Topics 的模型，其数据如下：

id	has_sub_topic	parent_id	subject_module_level_id	order
27	1	NULL	25	1
31	1	NULL	25	2
34	0	NULL	25	3
28	0	27	25	1
29	0	27	25	2
40	1	27	25	3
32	0	31	25	1
33	0	31	25	2
41	1	40	25	1
43	0	40	25	2
44	1	40	25	3
42	0	41	25	1
45	0	44	25	1
47	1	44	25	2
48	0	47	25	1

我想先按父级排序，然后像深度优先处理一样进行子级处理，只获取没有has_sub_topic的数据。因此，数据将按如下顺序排序：https://upload.wikimedia.org/wikipedia/commons/7/7f/Depth-First-Search.gif 并仅获取数据 4、7、8、10

之前我尝试过使用 sorted 函数，但是对于很多孩子来说效果并不好。所以，我必须使用递归函数。我使用递归的代码是这样的：

# Example data for topics
import pandas as pd
topics = pd.DataFrame({
    'id': [27, 31, 34, 28, 29, 40, 32, 33, 41, 43, 44, 42, 45, 47, 48], 
    'has_sub_topic': [1, 1, 0, 0, 0, 1, 0, 0, 1, 0, 1, 0, 0, 1, 0],
    'parent_id': [None, None, None, 27, 27, 27, 31, 31, 40, 40, 40, 41, 44, 44, 47],
    'subject_module_level_id': [25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25],
    'order': [1, 2, 3, 1, 2, 3, 1, 2, 1, 2, 3, 1, 1, 2, 1]
    })

def topic_child_order(topic, list_topics=None):
    if list_topics is None: list_topics = []

    if topic.has_sub_topic:
        topics = Topics.objects.filter(parent=topic).order_by('order')
        for child in topics:
            result = topic_child_order(child, list_topics)
    else:
        result = topic

    list_topics.append(result)

    return list_topics
    

topics = Topics.objects.filter(
    subject_module_level_id=25,
    parent=None
).order_by('order')

topics_order = []

for topic in topics:
    topics_order.append(topic_child_order(topic))

结果是这样的：

[
  [
    <Topics: Topicsobject(28)>,
    <Topics: Topicsobject(29)>,
    <Topics: Topicsobject(42)>,
    [
      ...
    ],
    <Topics: Topicsobject(43)>,
    <Topics: Topicsobject(45)>,
    <Topics: Topicsobject(48)>,
    [
      ...
    ],
    [
      ...
    ],
    [
      ...
    ],
    [
      ...
    ]
  ],
  [
    <Topics: Topicsobject(32)>,
    <Topics: Topicsobject(33)>,
    [
      ...
    ]
  ],
  [
    <Topics: Topicsobject(34)>
  ]
]

排序顺序是正确的，但我不知道为什么结果有空列表。有人知道怎么修这个东西吗？或者有谁知道如何以更好的方式做到这一点，以便结果只返回一个列表而不是嵌套列表？

Answer 1

我以嵌套 python dict 的形式显式构建了一棵树，将父 ID 映射到子 ID 列表，使用 .iterrows 将节点添加到树中。孩子按照给定的顺序排序。

然后我在树中执行简单的深度优先搜索，沿途产生叶子的 ID。

最后我使用.loc 来选择数据框中的行。

import pandas as pd

topics = pd.DataFrame({
    'id': [27, 31, 34, 28, 29, 40, 32, 33, 41, 43, 44, 42, 45, 47, 48], 
    'has_sub_topic': [1, 1, 0, 0, 0, 1, 0, 0, 1, 0, 1, 0, 0, 1, 0],
    'parent_id': [0, 0, 0, 27, 27, 27, 31, 31, 40, 40, 40, 41, 44, 44, 47],
    'subject_module_level_id': [25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25],
    'order': [1, 2, 3, 1, 2, 3, 1, 2, 1, 2, 3, 1, 1, 2, 1]
    }).set_index('id')

tree = {}
for i, row in topics.iterrows():
    tree.setdefault(row['parent_id'], []).append(i)

for brotherhood in tree.values():
    brotherhood.sort(key=lambda sibling: topics.at[sibling,'order'])

# print( tree )
# {0: [27, 31, 34], 27: [28, 29, 40], 31: [32, 33], 40: [41, 43, 44], 41: [42], 44: [45, 47], 47: [48]}

def gen_leaves(tree, i=0):
    if i in tree:
        for child in tree[i]:
            yield from gen_leaves(tree, child)
    else:
        yield i

# print( list(gen_leaves(tree)) )
# [28, 29, 42, 43, 45, 48, 32, 33, 34]

leaf_ids = list(gen_leaves(tree))
topics_leaves = topics.loc[leaf_ids]

print(topics_leaves)
#     has_sub_topic  parent_id  subject_module_level_id  order
# id                                                          
# 28              0         27                       25      1
# 29              0         27                       25      2
# 42              0         41                       25      1
# 43              0         40                       25      2
# 45              0         44                       25      1
# 48              0         47                       25      1
# 32              0         31                       25      1
# 33              0         31                       25      2
# 34              0          0                       25      3