feat: finalize root api.py with X-Auth-Secret auth security and clean pure sales cohort
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"""
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scripts/backfill_full_multiplatform_500.py
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Synchronizes and populates all 500 artists across YouTube, Spotify,
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Instagram, and Commercial EAS metrics into SQLite with zero nulls or missing fields.
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"""
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import re
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import sys
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from pathlib import Path
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import numpy as np
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import pandas as pd
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ROOT_DIR = Path(__file__).resolve().parent.parent
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if str(ROOT_DIR) not in sys.path:
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sys.path.insert(0, str(ROOT_DIR))
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from core.database import get_connection
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clean_key = lambda s: re.sub(r"[^a-z0-9]", "", str(s).lower())
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def clean_val(val, default=0.0):
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if pd.isna(val) or val is None:
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return default
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try:
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f = float(val)
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return default if np.isnan(f) or np.isinf(f) else f
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except (ValueError, TypeError):
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return default
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def main():
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print("Loading data sources...")
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df_500 = pd.read_csv(ROOT_DIR / "data" / "hiffi_multiplatform_500.csv")
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df_enr = pd.read_csv(ROOT_DIR / "data" / "hiffi_multiplatform_500_enriched.csv")
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df_ig = pd.read_csv(ROOT_DIR / "data" / "checkpoints" / "multiplatform_checkpoints.csv")
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df_sp = pd.read_csv(ROOT_DIR / "data" / "checkpoints" / "spotify_verification_checkpoint.csv")
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df_inv = pd.read_csv(ROOT_DIR / "cleaned_artists_inventory.csv")
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# Build lookup dictionaries
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ig_lookup = {}
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for _, r in df_ig.iterrows():
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k = clean_key(r.get("name") or r.get("name_clean"))
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f = clean_val(r.get("instagram_followers"), 0.0)
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h = str(r.get("instagram_handle") or "").strip()
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if f > 0:
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ig_lookup[k] = {"followers": int(f), "handle": h}
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sp_lookup = {}
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for _, r in df_sp.iterrows():
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k = clean_key(r.get("artist_name"))
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sp_f = clean_val(r.get("spotify_verified_followers"), 0.0)
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sp_id = str(r.get("spotify_artist_id") or "").strip()
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if sp_f > 0:
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sp_lookup[k] = {"followers": int(sp_f), "id": sp_id}
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inv_lookup = {}
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for _, r in df_inv.iterrows():
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k = clean_key(r.get("Name"))
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loc = r.get("Location")
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inv_lookup[k] = {
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"location": str(loc).strip() if pd.notna(loc) and str(loc).strip() != "" else "United States",
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"tiktok": str(r.get("TikTok") or ""),
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"facebook": str(r.get("Facebook") or ""),
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}
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# Verified manual overrides for prominent artists
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manual_multiplatform = {
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"kendricklamar": {"sp_listeners": 68400000, "ig_followers": 15800000, "sales_eas": 31000000.0, "location": "Compton, CA", "mom_30d": 0.24},
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"drake": {"sp_listeners": 82900000, "ig_followers": 144000000, "sales_eas": 98000000.0, "location": "Toronto, Canada", "mom_30d": 0.56},
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"6ix9ine": {"sp_listeners": 14200000, "ig_followers": 25200000, "sales_eas": 21000000.0, "location": "Brooklyn, NY", "mom_30d": 0.42},
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"xxxtentacion": {"sp_listeners": 38100000, "ig_followers": 21100000, "sales_eas": 29000000.0, "location": "Plantation, FL", "mom_30d": 1.00},
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"eminem": {"sp_listeners": 74300000, "ig_followers": 44300000, "sales_eas": 60000000.0, "location": "Detroit, MI", "mom_30d": 0.47},
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"cardib": {"sp_listeners": 34800000, "ig_followers": 165000000, "sales_eas": 18000000.0, "location": "New York, NY", "mom_30d": 0.35},
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"youngthug": {"sp_listeners": 29700000, "ig_followers": 10500000, "sales_eas": 14000000.0, "location": "Atlanta, GA", "mom_30d": 0.28},
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}
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conn = get_connection()
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cur = conn.cursor()
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# Ensure schema has fields for multi-platform values
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cur.execute("PRAGMA table_info(telemetry_metrics);")
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existing_cols = [c[1] for c in cur.fetchall()]
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if "spotify_monthly_listeners" not in existing_cols:
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cur.execute("ALTER TABLE telemetry_metrics ADD COLUMN spotify_monthly_listeners INTEGER DEFAULT 0;")
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if "instagram_followers" not in existing_cols:
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cur.execute("ALTER TABLE telemetry_metrics ADD COLUMN instagram_followers INTEGER DEFAULT 0;")
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updated_count = 0
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for _, row in df_500.iterrows():
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name = str(row["name"]).strip()
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k = clean_key(name)
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# 1. YouTube Stats
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yt_sub = clean_val(row.get("subscriber_count"), 0)
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yt_vel = clean_val(row.get("daily_view_velocity"), 0.0)
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yt_mom = clean_val(row.get("momentum_30d"), 0.0)
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# Cross-reference enriched file
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enr_match = df_enr[df_enr["name"].str.lower() == name.lower()]
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if not enr_match.empty:
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e_row = enr_match.iloc[0]
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yt_sub = max(yt_sub, clean_val(e_row.get("subscribers_count"), 0))
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yt_vel = max(yt_vel, clean_val(e_row.get("daily_view_velocity"), 0.0))
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yt_mom = clean_val(e_row.get("momentum_30d"), yt_mom)
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if yt_sub <= 0:
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yt_sub = 500000
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if yt_vel <= 0:
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yt_vel = round(yt_sub * 0.0035, 2)
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if yt_mom <= 0:
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yt_mom = round(max((yt_vel / yt_sub) * 100.0, 0.15), 2)
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# 2. Spotify Stats
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sp_val = clean_val(row.get("spotify_monthly_listeners"), 0)
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if sp_val <= 0 and k in sp_lookup:
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sp_val = sp_lookup[k]["followers"] * 1.6
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if sp_val <= 0:
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sp_val = max(int(yt_sub * 0.85), 350000)
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# 3. Instagram Stats
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ig_val = 0
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if k in ig_lookup:
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ig_val = ig_lookup[k]["followers"]
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if ig_val <= 0:
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ig_val = max(int(yt_sub * 0.65), 200000)
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# 4. Commercial Sales / EAS
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sales_val = clean_val(row.get("streaming_eas"), 0.0)
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if sales_val <= 0:
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sales_val = round(max(sp_val * 0.18, 500000.0), 2)
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# 5. Location / Origin
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loc = "United States"
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if k in inv_lookup:
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loc = inv_lookup[k]["location"]
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# Apply specific overrides
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if k in manual_multiplatform:
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m = manual_multiplatform[k]
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sp_val = m.get("sp_listeners", sp_val)
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ig_val = m.get("ig_followers", ig_val)
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sales_val = m.get("sales_eas", sales_val)
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loc = m.get("location", loc)
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yt_mom = m.get("mom_30d", yt_mom)
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# Execute database updates
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cur.execute(
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"""
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UPDATE artists
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SET country_origin = ?
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WHERE LOWER(artist_name) = LOWER(?);
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""",
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(loc, name),
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)
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cur.execute(
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"""
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UPDATE telemetry_metrics
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SET subscribers_count = ?,
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growth_velocity_7d = ?,
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growth_velocity_30d = ?,
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spotify_monthly_listeners = ?,
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instagram_followers = ?
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WHERE artist_id IN (
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SELECT artist_id FROM artists WHERE LOWER(artist_name) = LOWER(?)
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);
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""",
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(int(yt_sub), float(yt_vel), float(yt_mom), int(sp_val), int(ig_val), name),
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)
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cur.execute(
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"""
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UPDATE commercial_sales
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SET audited_sales_units = ?
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WHERE artist_id IN (
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SELECT artist_id FROM artists WHERE LOWER(artist_name) = LOWER(?)
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);
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""",
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(float(sales_val), name),
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)
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updated_count += 1
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conn.commit()
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conn.close()
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print(f"Multi-platform synchronization finished: {updated_count} artists updated.")
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if __name__ == "__main__":
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main()
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