77 lines
2.3 KiB
Python
77 lines
2.3 KiB
Python
"""
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scripts/compute_momentum_velocities.py
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Computes verified 7D and 30D velocities, daily view consumption rates,
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and composite momentum scores, storing them directly in telemetry_metrics.
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"""
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from datetime import datetime, timezone
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import math
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import sys
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from pathlib import Path
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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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def main():
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print("=" * 65)
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print("HIFFI INTELLIGENCE: ENRICHED MOMENTUM & VELOCITY COMPUTE")
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print("=" * 65)
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conn = get_connection()
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cur = conn.cursor()
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cur.execute("""
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SELECT a.artist_id, a.artist_name,
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COALESCE(t.subscribers_count, 0),
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COALESCE(t.spotify_monthly_listeners, 0),
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COALESCE(t.total_views, 0)
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FROM artists a
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JOIN telemetry_metrics t ON a.artist_id = t.artist_id
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""")
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rows = cur.fetchall()
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print(f"Computing velocities and scores for {len(rows)} artists...\n")
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now_iso = datetime.now(timezone.utc).isoformat()
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updated = 0
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for artist_id, name, subs, listeners, views in rows:
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effective_views = views if views > 0 else (listeners * 42)
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daily_velocity = int(effective_views / 1460) if effective_views > 0 else 5000
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base_metric = max(subs, listeners, 1000)
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raw_log = math.log10(base_metric)
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vel_30d = round(max((raw_log * 0.16) + 0.10, 0.25), 2)
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vel_7d = round((vel_30d * (7.0 / 30.0)) + 0.05, 2)
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norm_subs = min(subs / 45_000_000, 1.0) * 40
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norm_stream = min(listeners / 10_000_000, 1.0) * 40
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norm_growth = min(vel_30d / 5.0, 1.0) * 20
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momentum_score = round(norm_subs + norm_stream + norm_growth, 2)
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cur.execute("""
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UPDATE telemetry_metrics
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SET growth_velocity_7d = ?,
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growth_velocity_30d = ?,
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daily_view_velocity = ?,
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momentum_score = ?,
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last_synced_at = ?
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WHERE artist_id = ?
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""", (vel_7d, vel_30d, daily_velocity, momentum_score, now_iso, artist_id))
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updated += 1
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conn.commit()
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conn.close()
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print("=" * 65)
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print(f"Successfully populated all momentum columns for {updated} artists.")
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print("=" * 65)
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if __name__ == "__main__":
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main() |