python 字典生成树状图的实例

目录

• python字典生成树状图
• python生成树结构

python字典生成树状图

from graphviz import Digraph

# 获取所有节点中最多子节点的叶节点
def getMaxLeafs(myTree):
    numLeaf = len(myTree.keys())
    for key, value in myTree.items():
        if isinstance(value, dict):
            sum_numLeaf = getMaxLeafs(value)
            if sum_numLeaf > numLeaf:
                numLeaf = sum_numLeaf
    return numLeaf

def plot_model(tree, name):
    g = Digraph("G", filename=name, format='png', strict=False)
    first_label = list(tree.keys())[0]
    g.node("0", first_label)
    _sub_plot(g, tree, "0")
    leafs = str(getMaxLeafs(tree) // 10)
    g.attr(rankdir='LR', ranksep=leafs)
    g.view()

root = "0"

def _sub_plot(g, tree, inc):
    global root

    first_label = list(tree.keys())[0]
    ts = tree[first_label]
    for i in ts.keys():
        if isinstance(tree[first_label][i], dict):
            root = str(int(root) + 1)
            g.node(root, list(tree[first_label][i].keys())[0])
            g.edge(inc, root, str(i))
            _sub_plot(g, tree[first_label][i], root)
        else:
            root = str(int(root) + 1)
            g.node(root, tree[first_label][i])
            g.edge(inc, root, str(i))

tree = {
        "tearRate": {
            "reduced": "no lenses",
            "normal": {
                "astigmatic": {
                    "yes": {
                        "prescript": {
                            "myope": "hard",
                            "hyper": {
                                "age": {
                                    "young": "hard",
                                    "presbyopic": "no lenses",
                                    "pre": "no lenses"
                                }
                            }
                        }
                    },
                    "no": {
                        "age": {
                            "young": "soft",
                            "presbyopic": {
                                "prescript": {
                                    "myope": "no lenses",
                                    "hyper": "soft"
                                }
                            },
                            "pre": "soft"
                        }
                    }
                }
            }
        }
    }
plot_model(tree, "tree.gv")

效果如下：

python生成树结构

# 生成树结构
def get_trees(data,
              key_column='elementId',
              parent_column='parentId',
              child_column='children'):
    """
    :param data: 数据列表
    :param key_column: 主键字段，默认id
    :param parent_column: 父ID字段名，父ID默认从0开始
    :param child_column: 子列表字典名称
    :return: 树结构
    """
    data_dic = {}
    for d in data:
        data_dic[d.get(key_column)] = d  # 以自己的权限主键为键,以新构建的字典为值,构造新的字典

    data_tree_list = []  # 整个数据大列表
    for d_id, d_dic in data_dic.items():
        pid = d_dic.get(parent_column)  # 取每一个字典中的父id
        if not pid:  # 父id=0，就直接加入数据大列表
            data_tree_list.append(d_dic)
        else:  # 父id>0 就加入父id队对应的那个的节点列表
            try:  # 判断异常代表有子节点，增加子节点列表=[]
                data_dic[pid][child_column].append(d_dic)
            except KeyError:
                data_dic[pid][child_column] = []
                data_dic[pid][child_column].append(d_dic)
    return data_tree_list

def recursion(data, l=None):
    if l is None:
        l = []
    for i in data:
        if 'children' in i:
            children=i.pop('children')
            l.append(i)
            recursion(children,l)
        else:
            l.append(i)
    return l

以上为个人经验，希望能给大家一个参考，也希望大家多多支持我们。