基于Python实现父子关系数据转树形结构及编码分配的需求

Alright, let's work through converting your parent-child data into a structured tree with hierarchical codes in Python. First off, I spotted a duplicate id:5 in your sample data (used for both C2 and C4) — I’ll fix that to id:7 for C4 in my example to avoid key conflicts, since duplicate IDs would break our mapping later. Here's a step-by-step solution:

First, we’ll create a dictionary to map each item’s id to its full data. This lets us quickly look up parent nodes when building the tree. We’ll also convert id and fa_id to integers (since they’re strings in your sample) and initialize an empty children list for every item.

# Fixed sample data (resolved duplicate id issue)
data = [
    {'id': 1, 'fa_id': '0', 'name': 'A1'},
    {'id': 2, 'fa_id': '1', 'name': 'B1'},
    {'id': 3, 'fa_id': '1', 'name': 'B2'},
    {'id': 4, 'fa_id': '2', 'name': 'C1'},
    {'id': 5, 'fa_id': '2', 'name': 'C2'},
    {'id': 6, 'fa_id': '3', 'name': 'C3'},
    {'id': 7, 'fa_id': '3', 'name': 'C4'}
]

# Create a map from id to item, and set up children lists
item_map = {}
for item in data:
    # Convert ID fields to integers for consistent comparison
    item['id'] = int(item['id'])
    item['fa_id'] = int(item['fa_id'])
    item['children'] = []
    item_map[item['id']] = item

Next, we’ll loop through each item and attach it to its parent’s children list. Root nodes (those with fa_id:0) go directly into our top-level tree list.

tree = []
for item in data:
    parent_id = item['fa_id']
    if parent_id == 0:
        # Add root nodes to the main tree
        tree.append(item)
    else:
        # Attach child to its parent's children list (if parent exists)
        if parent_id in item_map:
            item_map[parent_id]['children'].append(item)

We’ll use a recursive function to traverse the tree and assign codes like 1, 1.1, 1.1.1 — these codes reflect the node’s level and position within its parent’s children.

def assign_hierarchical_codes(node, parent_code="", child_index=1):
    # Generate code for current node
    if parent_code == "":
        node['code'] = str(child_index)
    else:
        node['code'] = f"{parent_code}.{child_index}"
    
    # Recursively assign codes to all children
    for idx, child in enumerate(node['children'], start=1):
        assign_hierarchical_codes(child, node['code'], idx)

# Apply code assignment to root nodes
for idx, root_node in enumerate(tree, start=1):
    assign_hierarchical_codes(root_node, "", idx)

If you don’t need the original id and fa_id fields in the final tree, you can remove them with another recursive function:

def clean_unwanted_fields(node):
    # Remove id and fa_id if present
    node.pop('id', None)
    node.pop('fa_id', None)
    # Recursively clean children
    for child in node['children']:
        clean_unwanted_fields(child)

# Clean all nodes in the tree
for root in tree:
    clean_unwanted_fields(root)

To view the formatted tree, you can print it with json.dumps for readability:

import json
print(json.dumps(tree, indent=2))

This will output exactly the structure you’re looking for, plus the hierarchical codes:

[
  {
    "name": "A1",
    "children": [
      {
        "name": "B1",
        "children": [
          {
            "name": "C1",
            "children": [],
            "code": "1.1.1"
          },
          {
            "name": "C2",
            "children": [],
            "code": "1.1.2"
          }
        ],
        "code": "1.1"
      },
      {
        "name": "B2",
        "children": [
          {
            "name": "C3",
            "children": [],
            "code": "1.2.1"
          },
          {
            "name": "C4",
            "children": [],
            "code": "1.2.2"
          }
        ],
        "code": "1.2"
      }
    ],
    "code": "1"
  }
]

内容的提问来源于stack exchange，提问作者haidong zhang