feat: complete Day 2 handoff with API service, PM2 process daemons, and test suites
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"""
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audit_system_integrity.py
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Complete pre-deployment audit tool for HIFFI Artist Intelligence.
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Checks CSV data hygiene, CPI engine calculations, Excel exports, and FastAPI imports.
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"""
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from pathlib import Path
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import pandas as pd
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import numpy as np
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DATA_PATH = Path("data/hiffi_multiplatform_500.csv")
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def run_pre_deployment_audit():
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print("==================================================")
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print("🔍 RUNNING PRE-DEPLOYMENT SYSTEM INTEGRITY AUDIT")
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print("==================================================\n")
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all_passed = True
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# ----------------------------------------------------
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# CHECK 1: CSV File Existence & Row Count
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# ----------------------------------------------------
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print("[1/5] Checking master CSV dataset...")
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if not DATA_PATH.exists():
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print(" ❌ FAIL: data/hiffi_multiplatform_500.csv does not exist!")
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return False
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df = pd.read_csv(DATA_PATH)
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if len(df) == 500:
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print(f" ✅ PASS: Exact cohort size verified: {len(df)} rows.")
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else:
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print(f" ⚠️ WARNING: Expected 500 rows, but found {len(df)} rows.")
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all_passed = False
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# ----------------------------------------------------
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# CHECK 2: Data Provenance & Sales Fields Hygiene
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# ----------------------------------------------------
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print("\n[2/5] Checking sales telemetry & status completeness...")
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valid_statuses = {"VERIFIED_CSPC", "VERIFIED_RIAA", "ESTIMATED_SEA"}
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actual_statuses = set(df["sales_data_status"].dropna().unique())
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invalid_statuses = actual_statuses - valid_statuses
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if not invalid_statuses:
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print(f" ✅ PASS: All rows use clean governance statuses: {actual_statuses}")
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else:
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print(f" ❌ FAIL: Unhandled/dirty statuses detected: {invalid_statuses}")
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all_passed = False
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# Check for NaN in total_eas_cspc
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nan_sales = df["total_eas_cspc"].isna().sum()
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if nan_sales == 0:
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print(" ✅ PASS: Zero NaN values in 'total_eas_cspc'.")
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else:
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print(f" ❌ FAIL: Found {nan_sales} NaN entries in 'total_eas_cspc'!")
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all_passed = False
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# Check that sales rank is complete
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nan_sales_rank = df["cohort_sales_rank"].isna().sum()
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if nan_sales_rank == 0:
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print(" ✅ PASS: 100% of cohort_sales_rank populated.")
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else:
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print(f" ❌ FAIL: Found {nan_sales_rank} missing sales ranks.")
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all_passed = False
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# ----------------------------------------------------
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# CHECK 3: Commercial Power Engine (CPI) Verification
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# ----------------------------------------------------
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print("\n[3/5] Testing CommercialPowerEngine on master data...")
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try:
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from core.cpi_engine import CommercialPowerEngine
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engine = CommercialPowerEngine()
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# Test CPI calculation
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cpi_series = engine.calculate_cpi(df)
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if len(cpi_series) == len(df) and not cpi_series.isna().any():
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print(f" ✅ PASS: CPI calculated for all rows (Min: {cpi_series.min():.1f}, Max: {cpi_series.max():.1f}).")
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else:
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print(" ❌ FAIL: CPI calculation produced NaN values.")
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all_passed = False
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# Test Simulation (matched_only)
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sim_matched = engine.simulate_ranking(df[df["sales_data_status"] == "VERIFIED_CSPC"], commercial_weight=0.15, mode="matched_only")
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if not sim_matched.empty and "simulated_rank" in sim_matched.columns:
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print(" ✅ PASS: Simulation engine (matched_only) ran cleanly.")
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else:
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print(" ❌ FAIL: Simulation engine failed on matched_only.")
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all_passed = False
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# Test Simulation (global_redistribution)
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sim_global = engine.simulate_ranking(df, commercial_weight=0.15, mode="global_redistribution")
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if not sim_global.empty and "simulated_rank" in sim_global.columns:
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print(" ✅ PASS: Simulation engine (global_redistribution) ran cleanly.")
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else:
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print(" ❌ FAIL: Simulation engine failed on global_redistribution.")
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all_passed = False
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except Exception as e:
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print(f" ❌ FAIL: Error running CommercialPowerEngine: {e}")
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all_passed = False
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# ----------------------------------------------------
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# CHECK 4: Excel Audit Workbook Exporter
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# ----------------------------------------------------
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print("\n[4/5] Testing Excel multi-tab workbook exporter...")
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try:
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from exporters.excel_workbook import generate_executive_sales_workbook
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excel_bytes = generate_executive_sales_workbook(df, commercial_weight=0.15, mode="global_redistribution")
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if excel_bytes and len(excel_bytes) > 1000:
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print(f" ✅ PASS: Excel workbook generated successfully ({len(excel_bytes):,} bytes).")
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else:
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print(" ❌ FAIL: Excel workbook payload is empty.")
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all_passed = False
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except Exception as e:
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print(f" ❌ FAIL: Error in generate_executive_sales_workbook: {e}")
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all_passed = False
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# ----------------------------------------------------
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# CHECK 5: FastAPI App Loadability
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# ----------------------------------------------------
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print("\n[5/5] Testing FastAPI routes and schemas in api.py...")
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try:
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import api
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routes = [route.path for route in api.app.routes]
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expected_routes = ["/health", "/telemetry/coverage", "/artists", "/simulate"]
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missing = [r for r in expected_routes if r not in routes]
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if not missing:
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print(f" ✅ PASS: All required API endpoints present: {expected_routes}")
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else:
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print(f" ❌ FAIL: Missing API routes: {missing}")
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all_passed = False
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except Exception as e:
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print(f" ❌ FAIL: Error importing api.py: {e}")
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all_passed = False
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# ----------------------------------------------------
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# FINAL VERDICT
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# ----------------------------------------------------
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print("\n==================================================")
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if all_passed:
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print("🎯 AUDIT RESULT: 100% CLEAN! ZERO DISCREPANCIES.")
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print("All modules, formulas, exports, and APIs are verified.")
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else:
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print("⚠️ AUDIT RESULT: ISSUES DETECTED. Review logs above.")
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print("==================================================")
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if __name__ == "__main__":
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run_pre_deployment_audit()
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