feat: finalize root api.py with X-Auth-Secret auth security and clean pure sales cohort

scripts/enrich_cohort_images.py

@@ -0,0 +1,113 @@
+"""
+scripts/enrich_cohort_images.py
+Fetches high-resolution artist avatar images via YouTube Data API v3 in batches of 50
+strictly for the 500 cohort, updating image_url and image_verified_flag in SQLite.
+"""
+import os
+import sys
+from pathlib import Path
+import pandas as pd
+import requests
+from dotenv import load_dotenv
+
+ROOT_DIR = Path(__file__).resolve().parent.parent
+if str(ROOT_DIR) not in sys.path:
+    sys.path.insert(0, str(ROOT_DIR))
+
+load_dotenv(ROOT_DIR / ".env")
+from core.database import get_connection
+
+YOUTUBE_API_KEY = os.getenv("YOUTUBE_API_KEY")
+
+def chunk_list(lst, size=50):
+    for i in range(0, len(lst), size):
+        yield lst[i:i + size]
+
+def main():
+    print("=" * 65)
+    print("HIFFI INTELLIGENCE: COHORT PROFILE IMAGE ENRICHMENT")
+    print("=" * 65)
+
+    if not YOUTUBE_API_KEY:
+        print("ERROR: YOUTUBE_API_KEY is missing from .env")
+        sys.exit(1)
+
+    csv_path = ROOT_DIR / "data" / "hiffi_multiplatform_500.csv"
+    if not csv_path.exists():
+        csv_path = ROOT_DIR / "cleaned_artists_inventory.csv"
+
+    df_csv = pd.read_csv(csv_path)
+    name_col = "name" if "name" in df_csv.columns else "artist_name"
+    cohort_names = [str(n).strip() for n in df_csv[name_col].dropna()]
+
+    conn = get_connection()
+    cur = conn.cursor()
+
+    placeholders = ",".join(["?"] * len(cohort_names))
+    cur.execute(f"""
+        SELECT a.artist_id, a.artist_name, a.youtube_url
+        FROM artists a
+        WHERE a.artist_name IN ({placeholders})
+          AND a.youtube_url LIKE 'https://www.youtube.com/channel/%'
+    """, cohort_names)
+    rows = cur.fetchall()
+
+    channel_to_artist = {}
+    for artist_id, name, yt_url in rows:
+        ch_id = yt_url.split("/channel/")[-1].strip("/")
+        if ch_id:
+            channel_to_artist[ch_id] = (artist_id, name)
+
+    all_channels = list(channel_to_artist.keys())
+    print(f"Targeting {len(all_channels)} cohort channel IDs (10 batches of 50)...\n")
+
+    updated_count = 0
+
+    for batch_num, batch in enumerate(chunk_list(all_channels, 50), start=1):
+        ids_str = ",".join(batch)
+        url = "https://www.googleapis.com/youtube/v3/channels"
+        params = {
+            "part": "snippet",
+            "id": ids_str,
+            "key": YOUTUBE_API_KEY,
+            "maxResults": 50,
+        }
+
+        try:
+            resp = requests.get(url, params=params, timeout=15)
+            if resp.status_code == 200:
+                data = resp.json()
+                items = data.get("items", [])
+                for item in items:
+                    ch_id = item["id"]
+                    thumbs = item.get("snippet", {}).get("thumbnails", {})
+                    img_url = (
+                        thumbs.get("high", {}).get("url")
+                        or thumbs.get("medium", {}).get("url")
+                        or thumbs.get("default", {}).get("url")
+                    )
+
+                    if img_url and ch_id in channel_to_artist:
+                        artist_id, artist_name = channel_to_artist[ch_id]
+                        cur.execute("""
+                            UPDATE artists
+                            SET image_url = ?,
+                                image_verified_flag = 1
+                            WHERE artist_id = ?
+                        """, (img_url, artist_id))
+                        updated_count += 1
+                conn.commit()
+                print(f"Batch {batch_num:>2}: Saved {len(items)} official avatars.")
+            else:
+                print(f"Batch {batch_num:>2} error {resp.status_code}: {resp.text[:100]}")
+        except Exception as e:
+            print(f"Batch {batch_num:>2} failed: {e}")
+
+    conn.close()
+
+    print("\n" + "=" * 65)
+    print(f"Completed! Saved verified profile images for {updated_count} artists.")
+    print("=" * 65)
+
+if __name__ == "__main__":
+    main()