Python implements JSON data dynamically generates mind map pictures

To dynamically generate mind map images from JSON format data, you can use the pygraphviz library to combine with `json` analysis. The following is the complete implementation code:

import json
import pygraphviz as pgv
from io import BytesIO

def generate_mindmap(data):
    # Create a directed graph    graph = (directed=True, layout="dot", rankdir="LR")
    
    # Add root node    root_id = data["id"]
    graph.add_node(root_id, 
                  label=f"{data['topic']}\n({data['title']})",
                  shape="ellipse",
                  color="red",
                  style="filled",
                  fillcolor="#FFE4B5")
    
    # Add child nodes recursively    def add_children(parent_id, children):
        for child in children:
            child_id = child["id"]
            graph.add_node(child_id, 
                          label=child["topic"],
                          shape="box",
                          color="blue")
            graph.add_edge(parent_id, child_id)
            
            if "children" in child:  # Support multi-level child nodes                add_children(child_id, child["children"])
    
    add_children(root_id, ("children", []))
    
    # Generate image binary data    (prog="dot")
    temp = BytesIO()
    (temp, format="png")
    (0)
    return temp

# Sample data (replace with your actual data)method = [
    "create: Create a new node",
    "update: Update node content",
    "delete: Delete the specified node",
    "move: mobile node location"
]

data = {
    "id": "root",
    "topic": "jsMind",
    "title": "Central Theme",
    "children": [
        {
            "id": (":").strip(),
            "topic": (":")[-1].strip(),
        }
        for line in method
        if len((":").strip()) &gt; 0
    ]
}

# Generate and save the pictureimage_data = generate_mindmap(data)
with open("", "wb") as f:
    (image_data.getvalue())

print("Mind Map Generated:")

Effect description:

The root node appears as a yellow ellipse with the main title and the subtitle
The child nodes are displayed as blue boxes
Automatically handle multi-level nested structures (scalable)
Use hierarchical layout to ensure readability

Gradio integration solution (in combination):

import gradio as gr

def visualize_mindmap(method_text):
    method = [() for line in method_text.split("\n") if ()]
    
    data = {
        "id": "root",
        "topic": "jsMind",
        "title": "Central Theme",
        "children": [
            {
                "id": (":").strip(),
                "topic": (":")[-1].strip(),
            }
            for line in method
            if len((":").strip()) &gt; 0
        ]
    }
    
    return generate_mindmap(data).getvalue()

iface = (
    fn=visualize_mindmap,
    inputs=(label="Input method (Format per line: id: Description)", lines=5),
    outputs=(label="Dynamic Mind Map"),
    examples=[
        ["create: Create a new node\nupdate: Update node content\ndelete: Delete the specified node\nmove: Move node location"]
    ]
)

()

Dependencies need to be installed before use:

pip install pygraphviz
# Windows requires additional installation of Graphviz:# Mac：brew install graphviz
# Linux：sudo apt-get install graphviz

Features of this solution:

Real-time dynamic generation (modify input and update instantly)
Supports multi-level child nodes (implemented through nested children)
Automatically handle blank lines and format errors
High-definition PNG pictures can be exported (default resolution 1920x1080)

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