132 lines
5.1 KiB
Python
132 lines
5.1 KiB
Python
import sqlite3
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from collections import defaultdict
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# Connect to database
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DATABASE_PATH = r'' # Path to your database
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conn = sqlite3.connect(DATABASE_PATH)
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cursor = conn.cursor()
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# Query to get total unique problem types
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cursor.execute("SELECT COUNT(DISTINCT problem) FROM Models")
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total_problem_types = cursor.fetchone()[0]
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print(f"Total Problem Types in Database: {total_problem_types}")
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print()
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# Query to get health status by problem type
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query = """
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SELECT
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problem,
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health_status,
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COUNT(*) as count
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FROM Models
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GROUP BY problem, health_status
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ORDER BY problem, count DESC
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"""
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cursor.execute(query)
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results = cursor.fetchall()
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# Organize data by problem type
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problem_stats = defaultdict(lambda: {
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'total': 0,
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'tested': 0,
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'ok': 0,
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'failed': 0,
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'untested': 0,
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'failure_types': defaultdict(int)
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})
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for problem, status, count in results:
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problem_stats[problem]['total'] += count
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if status is None:
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problem_stats[problem]['untested'] += count
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else:
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problem_stats[problem]['tested'] += count
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if status == 'OK':
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problem_stats[problem]['ok'] += count
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else:
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problem_stats[problem]['failed'] += count
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problem_stats[problem]['failure_types'][status] += count
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# Generate Report
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print("=" * 80)
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print("MODEL HEALTH STATUS REPORT BY PROBLEM TYPE")
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print("=" * 80)
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print()
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# Overall Summary
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total_models = sum(stats['total'] for stats in problem_stats.values())
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total_tested = sum(stats['tested'] for stats in problem_stats.values())
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total_ok = sum(stats['ok'] for stats in problem_stats.values())
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total_failed = sum(stats['failed'] for stats in problem_stats.values())
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total_untested = sum(stats['untested'] for stats in problem_stats.values())
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print(f"OVERALL SUMMARY:")
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print(f" Total Models in Database: {total_models:,}")
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print(f" Models Tested: {total_tested:,} ({total_tested/total_models*100:.1f}%)")
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print(f" Models Passed (OK): {total_ok:,} ({total_ok/total_tested*100:.1f}% of tested)" if total_tested > 0 else " Models Passed (OK): 0")
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print(f" Models Failed: {total_failed:,} ({total_failed/total_tested*100:.1f}% of tested)" if total_tested > 0 else " Models Failed: 0")
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print(f" Models Untested: {total_untested:,} ({total_untested/total_models*100:.1f}%)")
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print()
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print("=" * 80)
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print()
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# Detailed report by problem type
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for problem in sorted(problem_stats.keys()):
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stats = problem_stats[problem]
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print(f"PROBLEM TYPE: {problem}")
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print("-" * 80)
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print(f" Total Models: {stats['total']:,}")
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print(f" Tested: {stats['tested']:,} ({stats['tested']/stats['total']*100:.1f}%)")
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print(f" Untested: {stats['untested']:,} ({stats['untested']/stats['total']*100:.1f}%)")
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if stats['tested'] > 0:
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print(f" Status OK: {stats['ok']:,} ({stats['ok']/stats['tested']*100:.1f}% of tested)")
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print(f" Status FAILED: {stats['failed']:,} ({stats['failed']/stats['tested']*100:.1f}% of tested)")
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if stats['failure_types']:
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print(f" Failure Types:")
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for failure_type, count in sorted(stats['failure_types'].items(), key=lambda x: x[1], reverse=True):
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print(f" - {failure_type}: {count:,} models")
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print()
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# Save to file
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with open('health_report.txt', 'w') as f:
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f.write("=" * 80 + "\n")
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f.write("MODEL HEALTH STATUS REPORT BY PROBLEM TYPE\n")
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f.write("=" * 80 + "\n\n")
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f.write(f"OVERALL SUMMARY:\n")
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f.write(f" Total Models in Database: {total_models:,}\n")
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f.write(f" Models Tested: {total_tested:,} ({total_tested/total_models*100:.1f}%)\n")
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f.write(f" Models Passed (OK): {total_ok:,} ({total_ok/total_tested*100:.1f}% of tested)\n" if total_tested > 0 else " Models Passed (OK): 0\n")
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f.write(f" Models Failed: {total_failed:,} ({total_failed/total_tested*100:.1f}% of tested)\n" if total_tested > 0 else " Models Failed: 0\n")
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f.write(f" Models Untested: {total_untested:,} ({total_untested/total_models*100:.1f}%)\n")
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f.write("\n" + "=" * 80 + "\n\n")
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for problem in sorted(problem_stats.keys()):
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stats = problem_stats[problem]
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f.write(f"PROBLEM TYPE: {problem}\n")
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f.write("-" * 80 + "\n")
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f.write(f" Total Models: {stats['total']:,}\n")
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f.write(f" Tested: {stats['tested']:,} ({stats['tested']/stats['total']*100:.1f}%)\n")
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f.write(f" Untested: {stats['untested']:,} ({stats['untested']/stats['total']*100:.1f}%)\n")
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if stats['tested'] > 0:
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f.write(f" Status OK: {stats['ok']:,} ({stats['ok']/stats['tested']*100:.1f}% of tested)\n")
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f.write(f" Status FAILED: {stats['failed']:,} ({stats['failed']/stats['tested']*100:.1f}% of tested)\n")
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if stats['failure_types']:
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f.write(f" Failure Types:\n")
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for failure_type, count in sorted(stats['failure_types'].items(), key=lambda x: x[1], reverse=True):
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f.write(f" - {failure_type}: {count:,} models\n")
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f.write("\n")
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print("=" * 80)
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print("Report saved to 'health_report.txt'")
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print("=" * 80) |