File size: 3,885 Bytes
273764c 3a29397 | 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 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 | import os
import networkx as nx
import pickle
from supabase import create_client, Client
# --- CONFIGURATION ---
SUPABASE_URL = os.environ.get("SUPABASE_URL")
SUPABASE_KEY = os.environ.get("SUPABASE_KEY")
CACHE_FILE = "mastodon_network.pkl"
BUCKET = "topic_assets"
PAGE_SIZE = 5000 # Fetch 5k rows at a time (adjust if hitting timeouts)
# --- 1. Connect ---
if not SUPABASE_URL or not SUPABASE_KEY:
raise ValueError("❌ Missing Supabase credentials in environment variables.")
print(f"Connecting to Supabase at {SUPABASE_URL}...")
supabase: Client = create_client(SUPABASE_URL, SUPABASE_KEY)
# --- 2. Build Graph with Weights & Time ---
print("Building weighted temporal graph...")
G = nx.Graph()
topic_counts = {}
offset = 0
total_processed = 0
while True:
# Fetch batch of posts that have a cluster assigned
# We only need 3 columns to build the graph, so we select only those.
print(f" Fetching rows {offset} to {offset + PAGE_SIZE}...")
try:
response = supabase.table("posts") \
.select("author_user_id, cluster_id, post_timestamp") \
.neq("cluster_id", -1) \
.not_.is_("cluster_id", "null") \
.not_.is_("author_user_id", "null") \
.range(offset, offset + PAGE_SIZE - 1) \
.execute()
batch = response.data
if not batch:
break
for row in batch:
user_id = row.get("author_user_id")
topic_id = row.get("cluster_id")
ts = row.get("post_timestamp", 0)
# Create node IDs
u_node = f"User_{user_id}"
t_node = f"Topic_{topic_id}"
# Ensure nodes exist
if u_node not in G:
G.add_node(u_node, label=f"User {user_id}", group="users", color="#97C2FC", size=10)
if t_node not in G:
G.add_node(t_node, label=f"Topic {topic_id}", group="topics", color="#FB7E81", size=20)
# --- Edge Logic: Weight + Time ---
if G.has_edge(u_node, t_node):
# Increment weight
G[u_node][t_node]['weight'] += 1
# Keep the MOST RECENT timestamp
if ts > G[u_node][t_node]['last_timestamp']:
G[u_node][t_node]['last_timestamp'] = ts
else:
# Initialize new connection
G.add_edge(u_node, t_node, weight=1, last_timestamp=ts)
# Track counts for sizing later
topic_counts[topic_id] = topic_counts.get(topic_id, 0) + 1
total_processed += len(batch)
offset += PAGE_SIZE
# Safety break for huge DBs (remove if you want 100% of data)
# if total_processed > 100000:
# print(" Limit reached (100k), stopping fetch.")
# break
except Exception as e:
print(f"❌ Error fetching batch: {e}")
break
print(f"Graph built! Nodes: {len(G.nodes)}, Edges: {len(G.edges)}")
# --- 3. Resize Topics ---
print("Resizing topic nodes...")
for topic_id, count in topic_counts.items():
t_node = f"Topic_{topic_id}"
if t_node in G:
# Scale size: Min 20, Max 60
G.nodes[t_node]['size'] = max(20, min(60, count / 5))
G.nodes[t_node]['title'] = f"Topic {topic_id}: {count} posts"
# --- 4. Save and Upload ---
print(f"Saving graph to '{CACHE_FILE}'...")
with open(CACHE_FILE, 'wb') as f:
pickle.dump(G, f)
print(f"☁️ Uploading {CACHE_FILE} to Supabase Storage...")
try:
with open(CACHE_FILE, 'rb') as f:
supabase.storage.from_(BUCKET).upload(
CACHE_FILE,
f,
file_options={"x-upsert": "true"}
)
print("✅ Done! Graph cached and uploaded.")
except Exception as e:
print(f"❌ Upload failed: {e}") |