66 lines
2.8 KiB
Python
66 lines
2.8 KiB
Python
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import sqlite3
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from pathlib import Path
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from datetime import datetime, timezone
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import pandas as pd
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PROJECT_ROOT = Path(__file__).resolve().parent.parent
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DB_PATH = PROJECT_ROOT / "data" / "hiffi_catalog.db"
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conn = sqlite3.connect(DB_PATH)
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query = """
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SELECT
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a.artist_id,
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a.artist_name,
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a.country_origin,
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a.youtube_url,
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t.subscribers_count AS youtube_subscribers,
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t.total_views AS youtube_total_views,
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a.spotify_url,
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t.spotify_monthly_listeners,
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a.instagram_url,
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t.instagram_followers,
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t.last_synced_at
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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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WHERE a.image_verified_flag = 1
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ORDER BY t.spotify_monthly_listeners DESC
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"""
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df = pd.read_sql_query(query, conn)
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conn.close()
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# Format clean numeric indicators for audit reporting
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df["youtube_subscribers_formatted"] = df["youtube_subscribers"].apply(lambda x: f"{int(x):,}" if pd.notnull(x) else "0")
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df["spotify_listeners_formatted"] = df["spotify_monthly_listeners"].apply(lambda x: f"{int(x):,}" if pd.notnull(x) else "0")
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df["instagram_followers_formatted"] = df["instagram_followers"].apply(lambda x: f"{int(x):,}" if pd.notnull(x) else "0")
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# Telemetry Integrity Verification Flags
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df["has_canonical_yt"] = df["youtube_url"].str.contains(r"youtube\.com/channel/UC", regex=True, na=False)
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df["has_canonical_sp"] = df["spotify_url"].str.contains(r"open\.spotify\.com/artist/[0-9A-Za-z]{22}", regex=True, na=False)
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df["has_canonical_ig"] = df["instagram_url"].str.contains(r"instagram\.com/[A-Za-z0-9_.]+", regex=True, na=False)
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df["telemetry_verified"] = (
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(df["youtube_subscribers"] > 0) &
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(df["spotify_monthly_listeners"] > 0) &
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(df["instagram_followers"] > 0) &
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df["has_canonical_yt"] &
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df["has_canonical_sp"] &
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df["has_canonical_ig"]
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)
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# Export verified proof ledger
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proof_path = PROJECT_ROOT / "data" / "hiffi_verified_telemetry_proof_500.csv"
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df.to_csv(proof_path, index=False, encoding="utf-8")
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print("=====================================================================")
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print(" HIFFI 500-ARTIST TELEMETRY PROOF AUDIT REPORT ")
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print(f"Timestamp (UTC): {datetime.now(timezone.utc).strftime('%Y-%m-%d %H:%M:%S')}")
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print("=====================================================================")
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print(f"Total Cohort Size: {len(df)}")
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print(f"Canonical YouTube Profiles (UC...): {df['has_canonical_yt'].sum()} / {len(df)}")
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print(f"Canonical Spotify Profiles (22-char): {df['has_canonical_sp'].sum()} / {len(df)}")
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print(f"Canonical Instagram Profiles: {df['has_canonical_ig'].sum()} / {len(df)}")
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print(f"100% Fully Verified Telemetry Proof: {df['telemetry_verified'].sum()} / {len(df)}")
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print("---------------------------------------------------------------------")
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print(f"Saved complete verifiable audit ledger to:\n{proof_path}")
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