File size: 3,199 Bytes
de99ac3 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 | import networkx as nx
from pyvis.network import Network
import pickle
import os
import random
# --- CONFIGURATION ---
CACHE_FILE = "mastodon_network.pkl"
OUTPUT_FILE = "user_explorer.html"
# --- 1. Load Cache ---
if not os.path.exists(CACHE_FILE):
print("Please run 'build_graph_cache.py' first!")
exit()
print("Loading graph cache...")
with open(CACHE_FILE, 'rb') as f:
G = pickle.load(f)
print(f"Graph loaded! ({G.number_of_nodes()} nodes)")
# --- 2. Select User ---
while True:
print("\n--- Options ---")
print("1. Enter a User ID")
print("2. Pick a Random User")
print("q. Quit")
choice = input("Choice: ").strip()
if choice == 'q': break
target_user_node = ""
if choice == '2':
# Find all nodes that start with "User_"
user_nodes = [n for n in G.nodes if n.startswith("User_")]
target_user_node = random.choice(user_nodes)
print(f"Selected random user: {target_user_node}")
elif choice == '1':
uid = input("Enter User ID (e.g. 13179): ").strip()
target_user_node = f"User_{uid}"
if target_user_node not in G:
print("❌ User not found in graph!")
continue
# --- 3. Extract Subgraph (The Ego Graph) ---
# Radius 1 = User + Connected Topics
# Radius 2 = User + Connected Topics + OTHER Users in those topics (Careful, this can be huge!)
radius = input("Enter exploration depth (1=Topics only, 2=Topics+Neighbors): ").strip()
radius = int(radius) if radius in ['1', '2'] else 1
print(f"Extracting subgraph for {target_user_node}...")
# Get the "Ego Graph" (The node and its neighbors)
subgraph = nx.ego_graph(G, target_user_node, radius=radius)
# If radius is 2, the graph might be huge if they posted in a popular topic.
# Let's limit the "Other Users" to avoid browser freeze
if radius == 2 and subgraph.number_of_nodes() > 500:
print(f"⚠️ Graph is large ({subgraph.number_of_nodes()} nodes). trimming...")
# Keep the main user, all topics, and a random sample of other users
nodes_to_keep = {target_user_node}
topics = [n for n in subgraph.neighbors(target_user_node)]
nodes_to_keep.update(topics)
for t in topics:
# Get neighbors of this topic (other users)
other_users = list(G.neighbors(t))
# Take only 20 random other users per topic
nodes_to_keep.update(random.sample(other_users, min(len(other_users), 20)))
subgraph = G.subgraph(list(nodes_to_keep))
# --- 4. Visualize ---
nt = Network(height="750px", width="100%", bgcolor="#222222", font_color="white")
nt.from_nx(subgraph)
# Highlight the main user in Green so you can find them
if target_user_node in nt.get_nodes():
# PyVis logic to update a specific node
for node in nt.nodes:
if node['id'] == target_user_node:
node['color'] = "#00FF00" # Bright Green
node['size'] = 25
break
nt.barnes_hut()
nt.save_graph(OUTPUT_FILE)
print(f"✅ Visualization saved to '{OUTPUT_FILE}'") |