怎么使用python字典生成树状图

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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 numLeafdef 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

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