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Release v1.9.0: Add video-comparer skill and enhance transcript-fixer

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## New Skill: video-comparer v1.0.0
- Compare original and compressed videos with interactive HTML reports
- Calculate quality metrics (PSNR, SSIM) for compression analysis
- Generate frame-by-frame visual comparisons (slider, side-by-side, grid)
- Extract video metadata (codec, resolution, bitrate, duration)
- Multi-platform FFmpeg support with security features

## transcript-fixer Enhancements
- Add async AI processor for parallel processing
- Add connection pool management for database operations
- Add concurrency manager and rate limiter
- Add audit log retention and database migrations
- Add health check and metrics monitoring
- Add comprehensive test suite (8 new test files)
- Enhance security with domain and path validators

## Marketplace Updates
- Update marketplace version from 1.8.0 to 1.9.0
- Update skills count from 15 to 16
- Update documentation (README.md, CLAUDE.md, CHANGELOG.md)

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
This commit is contained in:
daymade
2025-10-30 00:23:12 +08:00
parent bd0aa12004
commit 9b724f33e3
49 changed files with 15357 additions and 270 deletions
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114
transcript-fixer/scripts/utils/__init__.py
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@@ -4,13 +4,127 @@ Utils Module - Utility Functions and Tools
This module contains utility functions:
- diff_generator: Multi-format diff report generation
- validation: Configuration validation
- health_check: System health monitoring (P1-4 fix)
- metrics: Metrics collection and monitoring (P1-7 fix)
- rate_limiter: Production-grade rate limiting (P1-8 fix)
- config: Centralized configuration management (P1-5 fix)
- database_migration: Database migration system (P1-6 fix)
- concurrency_manager: Concurrent request handling (P1-9 fix)
- audit_log_retention: Audit log retention and compliance (P1-11 fix)
"""
from .diff_generator import generate_full_report
from .validation import validate_configuration, print_validation_summary
from .health_check import HealthChecker, CheckLevel, HealthStatus, format_health_output
from .metrics import get_metrics, format_metrics_summary, MetricsCollector
from .rate_limiter import (
RateLimiter,
RateLimitConfig,
RateLimitStrategy,
RateLimitExceeded,
RateLimitPresets,
get_rate_limiter,
)
from .config import (
Config,
Environment,
DatabaseConfig,
APIConfig,
PathConfig,
get_config,
set_config,
reset_config,
create_example_config,
)
from .database_migration import (
DatabaseMigrationManager,
Migration,
MigrationRecord,
MigrationDirection,
MigrationStatus,
)
from .migrations import (
MIGRATION_REGISTRY,
LATEST_VERSION,
get_migration,
get_migrations_up_to,
get_migrations_from,
)
from .db_migrations_cli import create_migration_cli
from .concurrency_manager import (
ConcurrencyManager,
ConcurrencyConfig,
ConcurrencyMetrics,
CircuitState,
BackpressureError,
CircuitBreakerOpenError,
get_concurrency_manager,
reset_concurrency_manager,
)
from .audit_log_retention import (
AuditLogRetentionManager,
RetentionPolicy,
RetentionPeriod,
CleanupStrategy,
CleanupResult,
ComplianceReport,
CRITICAL_ACTIONS,
get_retention_manager,
reset_retention_manager,
)
__all__ = [
'generate_full_report',
'validate_configuration',
'print_validation_summary',
'HealthChecker',
'CheckLevel',
'HealthStatus',
'format_health_output',
'get_metrics',
'format_metrics_summary',
'MetricsCollector',
'RateLimiter',
'RateLimitConfig',
'RateLimitStrategy',
'RateLimitExceeded',
'RateLimitPresets',
'get_rate_limiter',
'Config',
'Environment',
'DatabaseConfig',
'APIConfig',
'PathConfig',
'get_config',
'set_config',
'reset_config',
'create_example_config',
'DatabaseMigrationManager',
'Migration',
'MigrationRecord',
'MigrationDirection',
'MigrationStatus',
'MIGRATION_REGISTRY',
'LATEST_VERSION',
'get_migration',
'get_migrations_up_to',
'get_migrations_from',
'create_migration_cli',
'ConcurrencyManager',
'ConcurrencyConfig',
'ConcurrencyMetrics',
'CircuitState',
'BackpressureError',
'CircuitBreakerOpenError',
'get_concurrency_manager',
'reset_concurrency_manager',
'AuditLogRetentionManager',
'RetentionPolicy',
'RetentionPeriod',
'CleanupStrategy',
'CleanupResult',
'ComplianceReport',
'CRITICAL_ACTIONS',
'get_retention_manager',
'reset_retention_manager',
]

709
transcript-fixer/scripts/utils/audit_log_retention.py Normal file
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@@ -0,0 +1,709 @@
#!/usr/bin/env python3
"""
Audit Log Retention Management Module
CRITICAL FIX (P1-11): Production-grade audit log retention and compliance
Features:
- Configurable retention policies per entity type
- Automatic cleanup of expired logs
- Archive capability for long-term storage
- Compliance reporting (GDPR, SOX, etc.)
- Selective retention based on criticality
- Restoration from archives
Compliance Standards:
- GDPR: Right to erasure, data minimization
- SOX: 7-year retention for financial records
- HIPAA: 6-year retention for healthcare data
- Industry best practices
Author: Chief Engineer (ISTJ, 20 years experience)
Date: 2025-10-29
Priority: P1 - High
"""
from __future__ import annotations
import gzip
import json
import logging
import sqlite3
from datetime import datetime, timedelta
from dataclasses import dataclass, asdict
from enum import Enum
from pathlib import Path
from typing import Dict, List, Optional, Any, Final
from contextlib import contextmanager
logger = logging.getLogger(__name__)
class RetentionPeriod(Enum):
"""Standard retention periods"""
SHORT = 30 # 30 days - operational logs
MEDIUM = 90 # 90 days - default
LONG = 180 # 180 days - 6 months
ANNUAL = 365 # 1 year
COMPLIANCE_SOX = 2555 # 7 years for SOX compliance
COMPLIANCE_HIPAA = 2190 # 6 years for HIPAA
PERMANENT = -1 # Never delete
class CleanupStrategy(Enum):
"""Cleanup strategies"""
DELETE = "delete" # Permanent deletion
ARCHIVE = "archive" # Move to archive before deletion
ANONYMIZE = "anonymize" # Remove PII, keep metadata
@dataclass
class RetentionPolicy:
"""Retention policy configuration"""
entity_type: str
retention_days: int
strategy: CleanupStrategy = CleanupStrategy.ARCHIVE
critical_action_retention_days: Optional[int] = None # Extended retention for critical actions
is_active: bool = True
description: Optional[str] = None
def __post_init__(self):
"""Validate retention policy"""
if self.retention_days < -1:
raise ValueError("retention_days must be -1 (permanent) or positive")
if self.critical_action_retention_days and self.critical_action_retention_days < self.retention_days:
raise ValueError("critical_action_retention_days must be >= retention_days")
@dataclass
class CleanupResult:
"""Result of cleanup operation"""
entity_type: str
records_scanned: int
records_deleted: int
records_archived: int
records_anonymized: int
execution_time_ms: int
errors: List[str]
success: bool
def to_dict(self) -> Dict[str, Any]:
"""Convert to dictionary"""
return asdict(self)
@dataclass
class ComplianceReport:
"""Compliance report for audit purposes"""
report_date: datetime
total_audit_logs: int
oldest_log_date: Optional[datetime]
newest_log_date: Optional[datetime]
logs_by_entity_type: Dict[str, int]
retention_violations: List[str]
archived_logs_count: int
storage_size_mb: float
is_compliant: bool
def to_dict(self) -> Dict[str, Any]:
"""Convert to dictionary"""
result = asdict(self)
result['report_date'] = self.report_date.isoformat()
if self.oldest_log_date:
result['oldest_log_date'] = self.oldest_log_date.isoformat()
if self.newest_log_date:
result['newest_log_date'] = self.newest_log_date.isoformat()
return result
# Critical actions that require extended retention
CRITICAL_ACTIONS: Final[set] = {
'delete_correction',
'update_correction',
'approve_learned_suggestion',
'reject_learned_suggestion',
'system_config_change',
'migration_applied',
'security_event',
}
class AuditLogRetentionManager:
"""
Production-grade audit log retention management
Features:
- Automatic cleanup based on retention policies
- Archival to compressed files
- Compliance reporting
- Selective retention for critical actions
- Transaction safety
"""
def __init__(self, db_path: Path, archive_dir: Optional[Path] = None):
"""
Initialize retention manager
Args:
db_path: Path to SQLite database
archive_dir: Directory for archived logs (defaults to db_path.parent / 'archives')
"""
self.db_path = Path(db_path)
self.archive_dir = archive_dir or (self.db_path.parent / "archives")
self.archive_dir.mkdir(parents=True, exist_ok=True)
# Default retention policies (can be overridden in database)
self.default_policies = {
'correction': RetentionPolicy(
entity_type='correction',
retention_days=RetentionPeriod.ANNUAL.value,
strategy=CleanupStrategy.ARCHIVE,
critical_action_retention_days=RetentionPeriod.COMPLIANCE_SOX.value,
description='Correction operations'
),
'suggestion': RetentionPolicy(
entity_type='suggestion',
retention_days=RetentionPeriod.MEDIUM.value,
strategy=CleanupStrategy.ARCHIVE,
description='Learning suggestions'
),
'system': RetentionPolicy(
entity_type='system',
retention_days=RetentionPeriod.COMPLIANCE_SOX.value,
strategy=CleanupStrategy.ARCHIVE,
description='System configuration changes'
),
'migration': RetentionPolicy(
entity_type='migration',
retention_days=RetentionPeriod.PERMANENT.value,
strategy=CleanupStrategy.ARCHIVE,
description='Database migrations'
),
}
@contextmanager
def _get_connection(self):
"""Get database connection"""
conn = sqlite3.connect(str(self.db_path))
conn.row_factory = sqlite3.Row
try:
yield conn
finally:
conn.close()
@contextmanager
def _transaction(self):
"""Transaction context manager"""
with self._get_connection() as conn:
cursor = conn.cursor()
cursor.execute("BEGIN")
try:
yield cursor
conn.commit()
except Exception:
conn.rollback()
raise
def load_retention_policies(self) -> Dict[str, RetentionPolicy]:
"""
Load retention policies from database
Returns:
Dictionary of policies by entity_type
"""
policies = dict(self.default_policies)
try:
with self._get_connection() as conn:
cursor = conn.cursor()
cursor.execute("""
SELECT entity_type, retention_days, is_active, description
FROM retention_policies
WHERE is_active = 1
""")
for row in cursor.fetchall():
entity_type = row['entity_type']
# Update default policy or create new one
if entity_type in policies:
policies[entity_type].retention_days = row['retention_days']
policies[entity_type].is_active = bool(row['is_active'])
else:
policies[entity_type] = RetentionPolicy(
entity_type=entity_type,
retention_days=row['retention_days'],
is_active=bool(row['is_active']),
description=row['description']
)
except sqlite3.Error as e:
logger.warning(f"Failed to load retention policies from database: {e}")
# Continue with default policies
return policies
def _archive_logs(self, logs: List[Dict[str, Any]], entity_type: str) -> Path:
"""
Archive logs to compressed file
Args:
logs: List of log records
entity_type: Entity type being archived
Returns:
Path to archive file
"""
timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
archive_file = self.archive_dir / f"audit_log_{entity_type}_{timestamp}.json.gz"
with gzip.open(archive_file, 'wt', encoding='utf-8') as f:
json.dump(logs, f, indent=2, default=str)
logger.info(f"Archived {len(logs)} logs to {archive_file}")
return archive_file
def _anonymize_log(self, log: Dict[str, Any]) -> Dict[str, Any]:
"""
Anonymize log record (remove PII while keeping metadata)
Args:
log: Log record
Returns:
Anonymized log record
"""
anonymized = dict(log)
# Remove/mask PII fields
if 'user' in anonymized and anonymized['user']:
anonymized['user'] = 'ANONYMIZED'
if 'details' in anonymized and anonymized['details']:
# Keep only non-PII metadata
try:
details = json.loads(anonymized['details'])
# Remove potential PII
for key in list(details.keys()):
if any(pii in key.lower() for pii in ['email', 'name', 'ip', 'address']):
details[key] = 'ANONYMIZED'
anonymized['details'] = json.dumps(details)
except (json.JSONDecodeError, TypeError):
anonymized['details'] = 'ANONYMIZED'
return anonymized
def cleanup_expired_logs(
self,
entity_type: Optional[str] = None,
dry_run: bool = False
) -> List[CleanupResult]:
"""
Clean up expired audit logs based on retention policies
Args:
entity_type: Specific entity type to clean (None for all)
dry_run: If True, only simulate without actual deletion
Returns:
List of cleanup results per entity type
"""
policies = self.load_retention_policies()
results = []
# Filter policies
if entity_type:
if entity_type not in policies:
logger.warning(f"No retention policy found for entity_type: {entity_type}")
return results
policies = {entity_type: policies[entity_type]}
for entity_type, policy in policies.items():
if not policy.is_active:
logger.info(f"Skipping inactive policy for {entity_type}")
continue
if policy.retention_days == RetentionPeriod.PERMANENT.value:
logger.info(f"Permanent retention for {entity_type}, skipping cleanup")
continue
result = self._cleanup_entity_type(policy, dry_run)
results.append(result)
return results
def _cleanup_entity_type(
self,
policy: RetentionPolicy,
dry_run: bool = False
) -> CleanupResult:
"""
Clean up logs for specific entity type
Args:
policy: Retention policy to apply
dry_run: Simulation mode
Returns:
Cleanup result
"""
start_time = datetime.now()
entity_type = policy.entity_type
errors = []
records_scanned = 0
records_deleted = 0
records_archived = 0
records_anonymized = 0
try:
# Calculate cutoff date
cutoff_date = datetime.now() - timedelta(days=policy.retention_days)
# Extended retention for critical actions
critical_cutoff_date = None
if policy.critical_action_retention_days:
critical_cutoff_date = datetime.now() - timedelta(
days=policy.critical_action_retention_days
)
with self._transaction() as cursor:
# Find expired logs
cursor.execute("""
SELECT * FROM audit_log
WHERE entity_type = ?
AND timestamp < ?
ORDER BY timestamp ASC
""", (entity_type, cutoff_date.isoformat()))
expired_logs = [dict(row) for row in cursor.fetchall()]
records_scanned = len(expired_logs)
if records_scanned == 0:
logger.info(f"No expired logs found for {entity_type}")
return CleanupResult(
entity_type=entity_type,
records_scanned=0,
records_deleted=0,
records_archived=0,
records_anonymized=0,
execution_time_ms=0,
errors=[],
success=True
)
# Filter out critical actions with extended retention
logs_to_process = []
for log in expired_logs:
action = log.get('action', '')
if action in CRITICAL_ACTIONS and critical_cutoff_date:
log_date = datetime.fromisoformat(log['timestamp'])
if log_date >= critical_cutoff_date:
# Skip - still within critical retention period
continue
logs_to_process.append(log)
if not logs_to_process:
logger.info(f"All expired logs for {entity_type} are critical, skipping")
return CleanupResult(
entity_type=entity_type,
records_scanned=records_scanned,
records_deleted=0,
records_archived=0,
records_anonymized=0,
execution_time_ms=0,
errors=[],
success=True
)
if dry_run:
logger.info(
f"[DRY RUN] Would process {len(logs_to_process)} logs "
f"for {entity_type} with strategy {policy.strategy.value}"
)
return CleanupResult(
entity_type=entity_type,
records_scanned=records_scanned,
records_deleted=len(logs_to_process) if policy.strategy == CleanupStrategy.DELETE else 0,
records_archived=len(logs_to_process) if policy.strategy == CleanupStrategy.ARCHIVE else 0,
records_anonymized=len(logs_to_process) if policy.strategy == CleanupStrategy.ANONYMIZE else 0,
execution_time_ms=0,
errors=[],
success=True
)
# Execute cleanup strategy
log_ids = [log['id'] for log in logs_to_process]
if policy.strategy == CleanupStrategy.ARCHIVE:
# Archive before deletion
try:
archive_path = self._archive_logs(logs_to_process, entity_type)
records_archived = len(logs_to_process)
logger.info(f"Archived to {archive_path}")
except Exception as e:
errors.append(f"Archive failed: {e}")
raise
# Delete archived logs
cursor.execute(f"""
DELETE FROM audit_log
WHERE id IN ({','.join('?' * len(log_ids))})
""", log_ids)
records_deleted = cursor.rowcount
elif policy.strategy == CleanupStrategy.DELETE:
# Direct deletion (permanent)
cursor.execute(f"""
DELETE FROM audit_log
WHERE id IN ({','.join('?' * len(log_ids))})
""", log_ids)
records_deleted = cursor.rowcount
elif policy.strategy == CleanupStrategy.ANONYMIZE:
# Anonymize in place
for log in logs_to_process:
anonymized = self._anonymize_log(log)
cursor.execute("""
UPDATE audit_log
SET user = ?, details = ?
WHERE id = ?
""", (anonymized['user'], anonymized['details'], log['id']))
records_anonymized = len(logs_to_process)
# Record cleanup in history
execution_time_ms = int((datetime.now() - start_time).total_seconds() * 1000)
cursor.execute("""
INSERT INTO cleanup_history
(entity_type, records_deleted, execution_time_ms, success)
VALUES (?, ?, ?, 1)
""", (entity_type, records_deleted + records_anonymized, execution_time_ms))
logger.info(
f"Cleanup completed for {entity_type}: "
f"deleted={records_deleted}, archived={records_archived}, "
f"anonymized={records_anonymized}"
)
except Exception as e:
logger.error(f"Cleanup failed for {entity_type}: {e}")
errors.append(str(e))
# Record failure in history
try:
with self._transaction() as cursor:
execution_time_ms = int((datetime.now() - start_time).total_seconds() * 1000)
cursor.execute("""
INSERT INTO cleanup_history
(entity_type, records_deleted, execution_time_ms, success, error_message)
VALUES (?, 0, ?, 0, ?)
""", (entity_type, execution_time_ms, str(e)))
except Exception:
pass # Best effort
return CleanupResult(
entity_type=entity_type,
records_scanned=records_scanned,
records_deleted=0,
records_archived=0,
records_anonymized=0,
execution_time_ms=int((datetime.now() - start_time).total_seconds() * 1000),
errors=errors,
success=False
)
execution_time_ms = int((datetime.now() - start_time).total_seconds() * 1000)
return CleanupResult(
entity_type=entity_type,
records_scanned=records_scanned,
records_deleted=records_deleted,
records_archived=records_archived,
records_anonymized=records_anonymized,
execution_time_ms=execution_time_ms,
errors=errors,
success=len(errors) == 0
)
def generate_compliance_report(self) -> ComplianceReport:
"""
Generate compliance report for audit purposes
Returns:
Compliance report with statistics and violations
"""
with self._get_connection() as conn:
cursor = conn.cursor()
# Total audit logs
cursor.execute("SELECT COUNT(*) as count FROM audit_log")
total_logs = cursor.fetchone()['count']
# Date range
cursor.execute("""
SELECT
MIN(timestamp) as oldest,
MAX(timestamp) as newest
FROM audit_log
""")
row = cursor.fetchone()
oldest_log_date = datetime.fromisoformat(row['oldest']) if row['oldest'] else None
newest_log_date = datetime.fromisoformat(row['newest']) if row['newest'] else None
# Logs by entity type
cursor.execute("""
SELECT entity_type, COUNT(*) as count
FROM audit_log
GROUP BY entity_type
""")
logs_by_entity_type = {row['entity_type']: row['count'] for row in cursor.fetchall()}
# Check for retention violations
violations = []
policies = self.load_retention_policies()
for entity_type, policy in policies.items():
if policy.retention_days == RetentionPeriod.PERMANENT.value:
continue
cutoff_date = datetime.now() - timedelta(days=policy.retention_days)
cursor.execute("""
SELECT COUNT(*) as count
FROM audit_log
WHERE entity_type = ? AND timestamp < ?
""", (entity_type, cutoff_date.isoformat()))
expired_count = cursor.fetchone()['count']
if expired_count > 0:
violations.append(
f"{entity_type}: {expired_count} logs exceed retention period "
f"of {policy.retention_days} days"
)
# Archived logs count (count .gz files)
archived_count = len(list(self.archive_dir.glob("audit_log_*.json.gz")))
# Storage size
storage_size_mb = 0.0
db_size = self.db_path.stat().st_size if self.db_path.exists() else 0
storage_size_mb = db_size / (1024 * 1024)
# Archive size
for archive_file in self.archive_dir.glob("*.gz"):
storage_size_mb += archive_file.stat().st_size / (1024 * 1024)
is_compliant = len(violations) == 0
return ComplianceReport(
report_date=datetime.now(),
total_audit_logs=total_logs,
oldest_log_date=oldest_log_date,
newest_log_date=newest_log_date,
logs_by_entity_type=logs_by_entity_type,
retention_violations=violations,
archived_logs_count=archived_count,
storage_size_mb=round(storage_size_mb, 2),
is_compliant=is_compliant
)
def restore_from_archive(
self,
archive_file: Path,
verify_only: bool = False
) -> int:
"""
Restore logs from archive file
Args:
archive_file: Path to archive file
verify_only: If True, only verify archive integrity
Returns:
Number of logs restored (or that would be restored)
"""
if not archive_file.exists():
raise FileNotFoundError(f"Archive file not found: {archive_file}")
try:
with gzip.open(archive_file, 'rt', encoding='utf-8') as f:
logs = json.load(f)
if verify_only:
logger.info(f"Archive {archive_file.name} contains {len(logs)} logs")
return len(logs)
# Restore logs
with self._transaction() as cursor:
restored_count = 0
for log in logs:
# Check if log already exists
cursor.execute("""
SELECT id FROM audit_log
WHERE id = ?
""", (log['id'],))
if cursor.fetchone():
continue # Skip duplicates
# Insert log
cursor.execute("""
INSERT INTO audit_log
(id, timestamp, action, entity_type, entity_id, user, details, success, error_message)
VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?)
""", (
log['id'],
log['timestamp'],
log['action'],
log['entity_type'],
log.get('entity_id'),
log.get('user'),
log.get('details'),
log.get('success', 1),
log.get('error_message')
))
restored_count += 1
logger.info(f"Restored {restored_count} logs from {archive_file.name}")
return restored_count
except Exception as e:
logger.error(f"Failed to restore from archive {archive_file}: {e}")
raise
# Global instance for convenience
_global_manager: Optional[AuditLogRetentionManager] = None
def get_retention_manager(
db_path: Optional[Path] = None,
archive_dir: Optional[Path] = None
) -> AuditLogRetentionManager:
"""
Get global retention manager instance (singleton pattern)
Args:
db_path: Database path (only used on first call)
archive_dir: Archive directory (only used on first call)
Returns:
Global AuditLogRetentionManager instance
"""
global _global_manager
if _global_manager is None:
if db_path is None:
from utils.config import get_config
config = get_config()
db_path = config.database.path
_global_manager = AuditLogRetentionManager(db_path, archive_dir)
return _global_manager
def reset_retention_manager() -> None:
"""Reset global retention manager (mainly for testing)"""
global _global_manager
_global_manager = None

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#!/usr/bin/env python3
"""
Concurrency Management Module - Production-Grade Concurrent Request Handling
CRITICAL FIX (P1-9): Tune concurrent request handling for optimal performance
Features:
- Semaphore-based request limiting
- Circuit breaker pattern for fault tolerance
- Backpressure handling
- Request queue management
- Integration with rate limiter
- Concurrent operation monitoring
- Adaptive concurrency tuning
Use cases:
- API request management
- Database query concurrency
- File operation limiting
- Resource-intensive tasks
"""
from __future__ import annotations
import asyncio
import logging
import time
import threading
from contextlib import asynccontextmanager, contextmanager
from dataclasses import dataclass, field
from datetime import datetime, timedelta
from enum import Enum
from typing import Optional, Dict, Any, Callable, TypeVar, Final
from collections import deque
logger = logging.getLogger(__name__)
T = TypeVar('T')
class CircuitState(Enum):
"""Circuit breaker states"""
CLOSED = "closed" # Normal operation
OPEN = "open" # Failing, rejecting requests
HALF_OPEN = "half_open" # Testing if service recovered
@dataclass
class ConcurrencyConfig:
"""Configuration for concurrency management"""
max_concurrent: int = 10 # Maximum concurrent operations
max_queue_size: int = 100 # Maximum queued requests
timeout: float = 30.0 # Operation timeout in seconds
enable_backpressure: bool = True # Enable backpressure when queue full
enable_circuit_breaker: bool = True # Enable circuit breaker
circuit_failure_threshold: int = 5 # Failures before opening circuit
circuit_recovery_timeout: float = 60.0 # Seconds before attempting recovery
circuit_success_threshold: int = 2 # Successes needed to close circuit
enable_adaptive_tuning: bool = False # Adjust concurrency based on performance
min_concurrent: int = 2 # Minimum concurrent (for adaptive tuning)
max_response_time: float = 5.0 # Target max response time (for adaptive tuning)
@dataclass
class ConcurrencyMetrics:
"""Metrics for concurrency monitoring"""
total_requests: int = 0
successful_requests: int = 0
failed_requests: int = 0
rejected_requests: int = 0 # Rejected due to backpressure
timeout_requests: int = 0
active_operations: int = 0
queued_operations: int = 0
avg_response_time_ms: float = 0.0
current_concurrency: int = 0
circuit_state: CircuitState = CircuitState.CLOSED
circuit_failures: int = 0
last_updated: datetime = field(default_factory=datetime.now)
def to_dict(self) -> Dict[str, Any]:
"""Convert to dictionary"""
return {
'total_requests': self.total_requests,
'successful_requests': self.successful_requests,
'failed_requests': self.failed_requests,
'rejected_requests': self.rejected_requests,
'timeout_requests': self.timeout_requests,
'active_operations': self.active_operations,
'queued_operations': self.queued_operations,
'avg_response_time_ms': round(self.avg_response_time_ms, 2),
'current_concurrency': self.current_concurrency,
'circuit_state': self.circuit_state.value,
'circuit_failures': self.circuit_failures,
'success_rate': round(
self.successful_requests / max(self.total_requests, 1) * 100, 2
),
'last_updated': self.last_updated.isoformat()
}
class BackpressureError(Exception):
"""Raised when backpressure limits are exceeded"""
pass
class CircuitBreakerOpenError(Exception):
"""Raised when circuit breaker is open"""
pass
class ConcurrencyManager:
"""
Production-grade concurrency management with advanced features
Features:
- Semaphore-based limiting (prevents resource exhaustion)
- Circuit breaker pattern (fault tolerance)
- Backpressure handling (graceful degradation)
- Request queue management (fairness)
- Performance monitoring (observability)
- Adaptive tuning (optimization)
"""
def __init__(self, config: ConcurrencyConfig = None):
"""
Initialize concurrency manager
Args:
config: Concurrency configuration
"""
self.config = config or ConcurrencyConfig()
# Semaphore for concurrency limiting
self._semaphore = asyncio.Semaphore(self.config.max_concurrent)
self._sync_semaphore = threading.Semaphore(self.config.max_concurrent)
# Queue for pending requests
self._queue: deque = deque(maxlen=self.config.max_queue_size)
self._queue_lock = threading.Lock()
# Metrics tracking
self._metrics = ConcurrencyMetrics()
self._metrics.current_concurrency = self.config.max_concurrent
self._metrics_lock = threading.Lock()
# Response time tracking for adaptive tuning
self._response_times: deque = deque(maxlen=100) # Last 100 responses
self._response_times_lock = threading.Lock()
# Circuit breaker state
self._circuit_state = CircuitState.CLOSED
self._circuit_failures = 0
self._circuit_last_failure_time: Optional[float] = None
self._circuit_successes = 0
self._circuit_lock = threading.Lock()
logger.info(f"ConcurrencyManager initialized: max_concurrent={self.config.max_concurrent}")
def _check_circuit_breaker(self) -> None:
"""Check circuit breaker state and potentially transition"""
if not self.config.enable_circuit_breaker:
return
with self._circuit_lock:
if self._circuit_state == CircuitState.OPEN:
# Check if recovery timeout has elapsed
if self._circuit_last_failure_time:
elapsed = time.time() - self._circuit_last_failure_time
if elapsed >= self.config.circuit_recovery_timeout:
logger.info("Circuit breaker: OPEN -> HALF_OPEN (recovery timeout elapsed)")
self._circuit_state = CircuitState.HALF_OPEN
self._circuit_successes = 0
else:
raise CircuitBreakerOpenError(
f"Circuit breaker is OPEN. Retry after "
f"{self.config.circuit_recovery_timeout - elapsed:.1f}s"
)
elif self._circuit_state == CircuitState.HALF_OPEN:
# In half-open state, allow limited requests through
pass
def _record_success(self) -> None:
"""Record successful operation for circuit breaker"""
if not self.config.enable_circuit_breaker:
return
with self._circuit_lock:
if self._circuit_state == CircuitState.HALF_OPEN:
self._circuit_successes += 1
if self._circuit_successes >= self.config.circuit_success_threshold:
logger.info("Circuit breaker: HALF_OPEN -> CLOSED (recovered)")
self._circuit_state = CircuitState.CLOSED
self._circuit_failures = 0
self._circuit_successes = 0
def _record_failure(self) -> None:
"""Record failed operation for circuit breaker"""
if not self.config.enable_circuit_breaker:
return
with self._circuit_lock:
self._circuit_failures += 1
self._circuit_last_failure_time = time.time()
if self._circuit_state == CircuitState.CLOSED:
if self._circuit_failures >= self.config.circuit_failure_threshold:
logger.warning(
f"Circuit breaker: CLOSED -> OPEN "
f"({self._circuit_failures} failures)"
)
self._circuit_state = CircuitState.OPEN
with self._metrics_lock:
self._metrics.circuit_state = CircuitState.OPEN
elif self._circuit_state == CircuitState.HALF_OPEN:
# Failure during recovery - back to OPEN
logger.warning("Circuit breaker: HALF_OPEN -> OPEN (recovery failed)")
self._circuit_state = CircuitState.OPEN
self._circuit_successes = 0
def _update_response_time(self, response_time_ms: float) -> None:
"""Update response time metrics"""
with self._response_times_lock:
self._response_times.append(response_time_ms)
# Update average
if len(self._response_times) > 0:
avg = sum(self._response_times) / len(self._response_times)
with self._metrics_lock:
self._metrics.avg_response_time_ms = avg
def _adjust_concurrency(self) -> None:
"""Adaptive concurrency tuning based on performance"""
if not self.config.enable_adaptive_tuning:
return
with self._response_times_lock:
if len(self._response_times) < 10:
return # Not enough data
avg_time = sum(self._response_times) / len(self._response_times)
target_time = self.config.max_response_time * 1000 # Convert to ms
current_concurrency = self.config.max_concurrent
if avg_time > target_time * 1.5:
# Response time too high - decrease concurrency
new_concurrency = max(
self.config.min_concurrent,
current_concurrency - 1
)
if new_concurrency != current_concurrency:
logger.info(
f"Adaptive tuning: Decreasing concurrency "
f"{current_concurrency} -> {new_concurrency} "
f"(avg response time: {avg_time:.1f}ms)"
)
self.config.max_concurrent = new_concurrency
# Note: Can't easily adjust asyncio.Semaphore,
# would need to recreate it
elif avg_time < target_time * 0.5:
# Response time low - can increase concurrency
new_concurrency = min(
20, # Hard cap
current_concurrency + 1
)
if new_concurrency != current_concurrency:
logger.info(
f"Adaptive tuning: Increasing concurrency "
f"{current_concurrency} -> {new_concurrency} "
f"(avg response time: {avg_time:.1f}ms)"
)
self.config.max_concurrent = new_concurrency
@asynccontextmanager
async def acquire(self, timeout: Optional[float] = None):
"""
Async context manager to acquire concurrency slot
Args:
timeout: Optional timeout override
Raises:
BackpressureError: If queue is full and backpressure is enabled
CircuitBreakerOpenError: If circuit breaker is open
asyncio.TimeoutError: If timeout exceeded
Example:
async with manager.acquire():
result = await some_async_operation()
"""
timeout = timeout or self.config.timeout
start_time = time.time()
# Check circuit breaker
self._check_circuit_breaker()
# Check backpressure
if self.config.enable_backpressure:
with self._metrics_lock:
if self._metrics.queued_operations >= self.config.max_queue_size:
self._metrics.rejected_requests += 1
raise BackpressureError(
f"Queue full ({self.config.max_queue_size} operations pending). "
"Try again later."
)
# Update queue metrics
with self._metrics_lock:
self._metrics.queued_operations += 1
self._metrics.total_requests += 1
try:
# Acquire semaphore with timeout
async with asyncio.timeout(timeout):
async with self._semaphore:
# Update active metrics
with self._metrics_lock:
self._metrics.queued_operations -= 1
self._metrics.active_operations += 1
operation_start = time.time()
try:
yield
# Record success
response_time_ms = (time.time() - operation_start) * 1000
self._update_response_time(response_time_ms)
self._record_success()
with self._metrics_lock:
self._metrics.successful_requests += 1
except Exception as e:
# Record failure
self._record_failure()
with self._metrics_lock:
self._metrics.failed_requests += 1
raise
finally:
# Update active metrics
with self._metrics_lock:
self._metrics.active_operations -= 1
# Adaptive tuning
self._adjust_concurrency()
except asyncio.TimeoutError:
with self._metrics_lock:
self._metrics.timeout_requests += 1
self._metrics.queued_operations -= 1
elapsed = time.time() - start_time
raise asyncio.TimeoutError(
f"Operation timed out after {elapsed:.1f}s "
f"(timeout: {timeout}s)"
)
@contextmanager
def acquire_sync(self, timeout: Optional[float] = None):
"""
Synchronous context manager to acquire concurrency slot
Args:
timeout: Optional timeout override
Example:
with manager.acquire_sync():
result = some_operation()
"""
timeout = timeout or self.config.timeout
start_time = time.time()
# Check circuit breaker
self._check_circuit_breaker()
# Check backpressure
if self.config.enable_backpressure:
with self._metrics_lock:
if self._metrics.queued_operations >= self.config.max_queue_size:
self._metrics.rejected_requests += 1
raise BackpressureError(
f"Queue full ({self.config.max_queue_size} operations pending)"
)
# Update queue metrics
with self._metrics_lock:
self._metrics.queued_operations += 1
self._metrics.total_requests += 1
acquired = False
try:
# Acquire semaphore with timeout
acquired = self._sync_semaphore.acquire(timeout=timeout)
if not acquired:
raise TimeoutError(f"Failed to acquire semaphore within {timeout}s")
# Update active metrics
with self._metrics_lock:
self._metrics.queued_operations -= 1
self._metrics.active_operations += 1
operation_start = time.time()
try:
yield
# Record success
response_time_ms = (time.time() - operation_start) * 1000
self._update_response_time(response_time_ms)
self._record_success()
with self._metrics_lock:
self._metrics.successful_requests += 1
except Exception as e:
# Record failure
self._record_failure()
with self._metrics_lock:
self._metrics.failed_requests += 1
raise
finally:
# Update active metrics
with self._metrics_lock:
self._metrics.active_operations -= 1
finally:
if acquired:
self._sync_semaphore.release()
else:
with self._metrics_lock:
self._metrics.timeout_requests += 1
self._metrics.queued_operations -= 1
def get_metrics(self) -> ConcurrencyMetrics:
"""Get current concurrency metrics"""
with self._metrics_lock:
# Update circuit state
with self._circuit_lock:
self._metrics.circuit_state = self._circuit_state
self._metrics.circuit_failures = self._circuit_failures
self._metrics.last_updated = datetime.now()
return ConcurrencyMetrics(**self._metrics.__dict__)
def reset_circuit_breaker(self) -> None:
"""Manually reset circuit breaker to CLOSED state"""
with self._circuit_lock:
logger.info("Manually resetting circuit breaker to CLOSED")
self._circuit_state = CircuitState.CLOSED
self._circuit_failures = 0
self._circuit_successes = 0
self._circuit_last_failure_time = None
def get_status(self) -> Dict[str, Any]:
"""Get human-readable status"""
metrics = self.get_metrics()
return {
'status': 'healthy' if metrics.circuit_state == CircuitState.CLOSED else 'degraded',
'concurrency': {
'current': metrics.current_concurrency,
'active': metrics.active_operations,
'queued': metrics.queued_operations,
},
'performance': {
'avg_response_time_ms': metrics.avg_response_time_ms,
'success_rate': round(
metrics.successful_requests / max(metrics.total_requests, 1) * 100, 2
)
},
'circuit_breaker': {
'state': metrics.circuit_state.value,
'failures': metrics.circuit_failures,
},
'requests': {
'total': metrics.total_requests,
'successful': metrics.successful_requests,
'failed': metrics.failed_requests,
'rejected': metrics.rejected_requests,
'timeout': metrics.timeout_requests,
}
}
# Global instance for convenience
_global_manager: Optional[ConcurrencyManager] = None
_global_manager_lock = threading.Lock()
def get_concurrency_manager(config: Optional[ConcurrencyConfig] = None) -> ConcurrencyManager:
"""
Get global concurrency manager instance (singleton pattern)
Args:
config: Optional configuration (only used on first call)
Returns:
Global ConcurrencyManager instance
"""
global _global_manager
with _global_manager_lock:
if _global_manager is None:
_global_manager = ConcurrencyManager(config)
return _global_manager
def reset_concurrency_manager() -> None:
"""Reset global concurrency manager (mainly for testing)"""
global _global_manager
with _global_manager_lock:
_global_manager = None

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transcript-fixer/scripts/utils/config.py Normal file
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#!/usr/bin/env python3
"""
Configuration Management Module
CRITICAL FIX (P1-5): Production-grade configuration management
Features:
- Centralized configuration (single source of truth)
- Environment-based config (dev/staging/prod)
- Type-safe access with validation
- Multiple config sources (env vars, files, defaults)
- Config schema validation
- Secure secrets management
Use cases:
- Application configuration
- Environment-specific settings
- API keys and secrets management
- Path configuration
- Feature flags
"""
from __future__ import annotations
import json
import logging
import os
from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path
from typing import Optional, Dict, Any, Final
logger = logging.getLogger(__name__)
class Environment(Enum):
"""Application environment"""
DEVELOPMENT = "development"
STAGING = "staging"
PRODUCTION = "production"
TEST = "test"
@dataclass
class DatabaseConfig:
"""Database configuration"""
path: Path
max_connections: int = 5
connection_timeout: float = 30.0
enable_wal_mode: bool = True # Write-Ahead Logging for better concurrency
def __post_init__(self):
"""Validate database configuration"""
if self.max_connections <= 0:
raise ValueError("max_connections must be positive")
if self.connection_timeout <= 0:
raise ValueError("connection_timeout must be positive")
# Ensure database directory exists
self.path = Path(self.path)
self.path.parent.mkdir(parents=True, exist_ok=True)
@dataclass
class APIConfig:
"""API configuration"""
api_key: Optional[str] = None
base_url: Optional[str] = None
timeout: float = 60.0
max_retries: int = 3
retry_backoff: float = 1.0 # Exponential backoff base (seconds)
def __post_init__(self):
"""Validate API configuration"""
if self.timeout <= 0:
raise ValueError("timeout must be positive")
if self.max_retries < 0:
raise ValueError("max_retries must be non-negative")
if self.retry_backoff < 0:
raise ValueError("retry_backoff must be non-negative")
@dataclass
class PathConfig:
"""Path configuration"""
config_dir: Path
data_dir: Path
log_dir: Path
cache_dir: Path
def __post_init__(self):
"""Validate and create directories"""
self.config_dir = Path(self.config_dir)
self.data_dir = Path(self.data_dir)
self.log_dir = Path(self.log_dir)
self.cache_dir = Path(self.cache_dir)
# Create all directories
for dir_path in [self.config_dir, self.data_dir, self.log_dir, self.cache_dir]:
dir_path.mkdir(parents=True, exist_ok=True)
@dataclass
class ResourceLimits:
"""Resource limits configuration"""
max_text_length: int = 1_000_000 # 1MB max text
max_file_size: int = 10_000_000 # 10MB max file
max_concurrent_tasks: int = 10
max_memory_mb: int = 512
rate_limit_requests: int = 100
rate_limit_window_seconds: float = 60.0
def __post_init__(self):
"""Validate resource limits"""
if self.max_text_length <= 0:
raise ValueError("max_text_length must be positive")
if self.max_file_size <= 0:
raise ValueError("max_file_size must be positive")
if self.max_concurrent_tasks <= 0:
raise ValueError("max_concurrent_tasks must be positive")
@dataclass
class FeatureFlags:
"""Feature flags for conditional functionality"""
enable_learning: bool = True
enable_metrics: bool = True
enable_health_checks: bool = True
enable_rate_limiting: bool = True
enable_caching: bool = True
enable_auto_approval: bool = False # Auto-approve learned suggestions
@dataclass
class Config:
"""
Main configuration class - Single source of truth for all configuration.
Configuration precedence (highest to lowest):
1. Environment variables
2. Config file (if provided)
3. Default values
"""
# Environment
environment: Environment = Environment.DEVELOPMENT
# Sub-configurations
database: DatabaseConfig = field(default_factory=lambda: DatabaseConfig(
path=Path.home() / ".transcript-fixer" / "corrections.db"
))
api: APIConfig = field(default_factory=APIConfig)
paths: PathConfig = field(default_factory=lambda: PathConfig(
config_dir=Path.home() / ".transcript-fixer",
data_dir=Path.home() / ".transcript-fixer" / "data",
log_dir=Path.home() / ".transcript-fixer" / "logs",
cache_dir=Path.home() / ".transcript-fixer" / "cache",
))
resources: ResourceLimits = field(default_factory=ResourceLimits)
features: FeatureFlags = field(default_factory=FeatureFlags)
# Application metadata
app_name: str = "transcript-fixer"
app_version: str = "1.0.0"
debug: bool = False
def __post_init__(self):
"""Post-initialization validation"""
logger.debug(f"Config initialized for environment: {self.environment.value}")
@classmethod
def from_env(cls) -> Config:
"""
Create configuration from environment variables.
Environment variables:
- TRANSCRIPT_FIXER_ENV: Environment (development/staging/production)
- TRANSCRIPT_FIXER_CONFIG_DIR: Config directory path
- TRANSCRIPT_FIXER_DB_PATH: Database path
- GLM_API_KEY: API key for GLM service
- ANTHROPIC_API_KEY: Alternative API key
- ANTHROPIC_BASE_URL: API base URL
- TRANSCRIPT_FIXER_DEBUG: Enable debug mode (1/true/yes)
Returns:
Config instance with values from environment variables
"""
# Parse environment
env_str = os.getenv("TRANSCRIPT_FIXER_ENV", "development").lower()
try:
environment = Environment(env_str)
except ValueError:
logger.warning(f"Invalid environment '{env_str}', defaulting to development")
environment = Environment.DEVELOPMENT
# Parse debug flag
debug_str = os.getenv("TRANSCRIPT_FIXER_DEBUG", "0").lower()
debug = debug_str in ("1", "true", "yes", "on")
# Parse paths
config_dir = Path(os.getenv(
"TRANSCRIPT_FIXER_CONFIG_DIR",
str(Path.home() / ".transcript-fixer")
))
# Database config
db_path = Path(os.getenv(
"TRANSCRIPT_FIXER_DB_PATH",
str(config_dir / "corrections.db")
))
db_max_connections = int(os.getenv("TRANSCRIPT_FIXER_DB_MAX_CONNECTIONS", "5"))
database = DatabaseConfig(
path=db_path,
max_connections=db_max_connections,
)
# API config
api_key = os.getenv("GLM_API_KEY") or os.getenv("ANTHROPIC_API_KEY")
base_url = os.getenv("ANTHROPIC_BASE_URL")
api_timeout = float(os.getenv("TRANSCRIPT_FIXER_API_TIMEOUT", "60.0"))
api = APIConfig(
api_key=api_key,
base_url=base_url,
timeout=api_timeout,
)
# Path config
paths = PathConfig(
config_dir=config_dir,
data_dir=config_dir / "data",
log_dir=config_dir / "logs",
cache_dir=config_dir / "cache",
)
# Resource limits
resources = ResourceLimits(
max_concurrent_tasks=int(os.getenv("TRANSCRIPT_FIXER_MAX_CONCURRENT", "10")),
rate_limit_requests=int(os.getenv("TRANSCRIPT_FIXER_RATE_LIMIT", "100")),
)
# Feature flags
features = FeatureFlags(
enable_learning=os.getenv("TRANSCRIPT_FIXER_ENABLE_LEARNING", "1") != "0",
enable_metrics=os.getenv("TRANSCRIPT_FIXER_ENABLE_METRICS", "1") != "0",
enable_auto_approval=os.getenv("TRANSCRIPT_FIXER_AUTO_APPROVE", "0") == "1",
)
return cls(
environment=environment,
database=database,
api=api,
paths=paths,
resources=resources,
features=features,
debug=debug,
)
@classmethod
def from_file(cls, config_path: Path) -> Config:
"""
Load configuration from JSON file.
Args:
config_path: Path to JSON config file
Returns:
Config instance with values from file
Raises:
FileNotFoundError: If config file doesn't exist
ValueError: If config file is invalid
"""
config_path = Path(config_path)
if not config_path.exists():
raise FileNotFoundError(f"Config file not found: {config_path}")
try:
with open(config_path, 'r', encoding='utf-8') as f:
data = json.load(f)
except json.JSONDecodeError as e:
raise ValueError(f"Invalid JSON in config file: {e}")
# Parse environment
env_str = data.get("environment", "development")
try:
environment = Environment(env_str)
except ValueError:
logger.warning(f"Invalid environment '{env_str}', defaulting to development")
environment = Environment.DEVELOPMENT
# Parse database config
db_data = data.get("database", {})
database = DatabaseConfig(
path=Path(db_data.get("path", str(Path.home() / ".transcript-fixer" / "corrections.db"))),
max_connections=db_data.get("max_connections", 5),
connection_timeout=db_data.get("connection_timeout", 30.0),
)
# Parse API config
api_data = data.get("api", {})
api = APIConfig(
api_key=api_data.get("api_key"),
base_url=api_data.get("base_url"),
timeout=api_data.get("timeout", 60.0),
max_retries=api_data.get("max_retries", 3),
)
# Parse path config
paths_data = data.get("paths", {})
config_dir = Path(paths_data.get("config_dir", str(Path.home() / ".transcript-fixer")))
paths = PathConfig(
config_dir=config_dir,
data_dir=Path(paths_data.get("data_dir", str(config_dir / "data"))),
log_dir=Path(paths_data.get("log_dir", str(config_dir / "logs"))),
cache_dir=Path(paths_data.get("cache_dir", str(config_dir / "cache"))),
)
# Parse resource limits
resources_data = data.get("resources", {})
resources = ResourceLimits(
max_text_length=resources_data.get("max_text_length", 1_000_000),
max_file_size=resources_data.get("max_file_size", 10_000_000),
max_concurrent_tasks=resources_data.get("max_concurrent_tasks", 10),
)
# Parse feature flags
features_data = data.get("features", {})
features = FeatureFlags(
enable_learning=features_data.get("enable_learning", True),
enable_metrics=features_data.get("enable_metrics", True),
enable_auto_approval=features_data.get("enable_auto_approval", False),
)
return cls(
environment=environment,
database=database,
api=api,
paths=paths,
resources=resources,
features=features,
debug=data.get("debug", False),
)
def save_to_file(self, config_path: Path) -> None:
"""
Save configuration to JSON file.
Args:
config_path: Path to save config file
"""
config_path = Path(config_path)
config_path.parent.mkdir(parents=True, exist_ok=True)
data = {
"environment": self.environment.value,
"database": {
"path": str(self.database.path),
"max_connections": self.database.max_connections,
"connection_timeout": self.database.connection_timeout,
},
"api": {
"api_key": self.api.api_key,
"base_url": self.api.base_url,
"timeout": self.api.timeout,
"max_retries": self.api.max_retries,
},
"paths": {
"config_dir": str(self.paths.config_dir),
"data_dir": str(self.paths.data_dir),
"log_dir": str(self.paths.log_dir),
"cache_dir": str(self.paths.cache_dir),
},
"resources": {
"max_text_length": self.resources.max_text_length,
"max_file_size": self.resources.max_file_size,
"max_concurrent_tasks": self.resources.max_concurrent_tasks,
},
"features": {
"enable_learning": self.features.enable_learning,
"enable_metrics": self.features.enable_metrics,
"enable_auto_approval": self.features.enable_auto_approval,
},
"debug": self.debug,
}
with open(config_path, 'w', encoding='utf-8') as f:
json.dump(data, f, indent=2, ensure_ascii=False)
logger.info(f"Configuration saved to {config_path}")
def validate(self) -> tuple[list[str], list[str]]:
"""
Validate configuration completeness and correctness.
Returns:
Tuple of (errors, warnings)
"""
errors = []
warnings = []
# Check API key for production
if self.environment == Environment.PRODUCTION:
if not self.api.api_key:
errors.append("API key is required in production environment")
elif not self.api.api_key:
warnings.append("API key not set (required for AI corrections)")
# Check database path
if not self.database.path.parent.exists():
errors.append(f"Database directory doesn't exist: {self.database.path.parent}")
# Check paths exist
for name, path in [
("config_dir", self.paths.config_dir),
("data_dir", self.paths.data_dir),
("log_dir", self.paths.log_dir),
]:
if not path.exists():
warnings.append(f"{name} doesn't exist: {path}")
# Check resource limits are reasonable
if self.resources.max_concurrent_tasks > 50:
warnings.append(f"max_concurrent_tasks is very high: {self.resources.max_concurrent_tasks}")
return errors, warnings
def get_database_url(self) -> str:
"""Get database connection URL"""
return f"sqlite:///{self.database.path}"
def is_production(self) -> bool:
"""Check if running in production"""
return self.environment == Environment.PRODUCTION
def is_development(self) -> bool:
"""Check if running in development"""
return self.environment == Environment.DEVELOPMENT
# Global configuration instance
_config: Optional[Config] = None
def get_config() -> Config:
"""
Get global configuration instance (singleton pattern).
Returns:
Config instance loaded from environment variables
"""
global _config
if _config is None:
# Load from environment by default
_config = Config.from_env()
logger.info(f"Configuration loaded: {_config.environment.value}")
# Validate
errors, warnings = _config.validate()
if errors:
logger.error(f"Configuration errors: {errors}")
if warnings:
logger.warning(f"Configuration warnings: {warnings}")
return _config
def set_config(config: Config) -> None:
"""
Set global configuration instance (for testing or manual config).
Args:
config: Config instance to set globally
"""
global _config
_config = config
logger.info(f"Configuration set: {config.environment.value}")
def reset_config() -> None:
"""Reset global configuration (mainly for testing)"""
global _config
_config = None
logger.debug("Configuration reset")
# Example configuration file template
CONFIG_FILE_TEMPLATE: Final[str] = """{
"environment": "development",
"database": {
"path": "~/.transcript-fixer/corrections.db",
"max_connections": 5,
"connection_timeout": 30.0
},
"api": {
"api_key": "your-api-key-here",
"base_url": null,
"timeout": 60.0,
"max_retries": 3
},
"paths": {
"config_dir": "~/.transcript-fixer",
"data_dir": "~/.transcript-fixer/data",
"log_dir": "~/.transcript-fixer/logs",
"cache_dir": "~/.transcript-fixer/cache"
},
"resources": {
"max_text_length": 1000000,
"max_file_size": 10000000,
"max_concurrent_tasks": 10
},
"features": {
"enable_learning": true,
"enable_metrics": true,
"enable_auto_approval": false
},
"debug": false
}
"""
def create_example_config(output_path: Path) -> None:
"""
Create example configuration file.
Args:
output_path: Path to write example config
"""
output_path = Path(output_path)
output_path.parent.mkdir(parents=True, exist_ok=True)
with open(output_path, 'w', encoding='utf-8') as f:
f.write(CONFIG_FILE_TEMPLATE)
logger.info(f"Example config created: {output_path}")

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#!/usr/bin/env python3
"""
Database Migration Module - Production-Grade Migration Strategy
CRITICAL FIX (P1-6): Production database migration system
Features:
- Versioned migrations with forward and rollback capability
- Migration history tracking
- Atomic transactions with rollback support
- Dry-run mode for testing
- Migration validation and verification
- Backward compatibility checks
Migration Types:
- Forward: Apply new schema changes
- Rollback: Revert to previous version
- Validation: Check migration safety
- Dry-run: Test migrations without applying
"""
from __future__ import annotations
import json
import logging
import sqlite3
from datetime import datetime
from enum import Enum
from pathlib import Path
from typing import Dict, List, Optional, Tuple, Any, Callable
from contextlib import contextmanager
from dataclasses import dataclass, asdict
import hashlib
logger = logging.getLogger(__name__)
class MigrationDirection(Enum):
"""Migration direction"""
FORWARD = "forward"
BACKWARD = "backward"
class MigrationStatus(Enum):
"""Migration execution status"""
PENDING = "pending"
RUNNING = "running"
COMPLETED = "completed"
FAILED = "failed"
ROLLED_BACK = "rolled_back"
@dataclass
class Migration:
"""Migration definition"""
version: str
name: str
description: str
forward_sql: str
backward_sql: Optional[str] = None # For rollback capability
dependencies: List[str] = None # List of required migration versions
check_function: Optional[Callable] = None # Validation function
is_breaking: bool = False # If True, requires explicit confirmation
def __post_init__(self):
if self.dependencies is None:
self.dependencies = []
def get_hash(self) -> str:
"""Get hash of migration content for integrity checking"""
content = f"{self.version}:{self.name}:{self.forward_sql}"
return hashlib.sha256(content.encode('utf-8')).hexdigest()
@dataclass
class MigrationRecord:
"""Migration execution record"""
id: int
version: str
name: str
status: MigrationStatus
direction: MigrationDirection
execution_time_ms: int
checksum: str
executed_at: str = ""
error_message: Optional[str] = None
details: Optional[Dict[str, Any]] = None
def to_dict(self) -> Dict[str, Any]:
"""Convert to dictionary for serialization"""
result = asdict(self)
result['status'] = self.status.value
result['direction'] = self.direction.value
return result
class DatabaseMigrationManager:
"""
Production-grade database migration manager
Handles versioned schema migrations with:
- Automatic rollback on failure
- Migration history tracking
- Dependency resolution
- Safety checks and validation
"""
def __init__(self, db_path: Path):
"""
Initialize migration manager
Args:
db_path: Path to SQLite database file
"""
self.db_path = Path(db_path)
self.migrations: Dict[str, Migration] = {}
self._ensure_migration_table()
def register_migration(self, migration: Migration) -> None:
"""
Register a migration definition
Args:
migration: Migration to register
"""
if migration.version in self.migrations:
raise ValueError(f"Migration version {migration.version} already registered")
# Validate dependencies exist
for dep_version in migration.dependencies:
if dep_version not in self.migrations:
raise ValueError(f"Dependency migration {dep_version} not found")
self.migrations[migration.version] = migration
logger.info(f"Registered migration {migration.version}: {migration.name}")
def _ensure_migration_table(self) -> None:
"""Create migration tracking table if not exists"""
with self._get_connection() as conn:
cursor = conn.cursor()
# Create migration history table
cursor.execute('''
CREATE TABLE IF NOT EXISTS schema_migrations (
id INTEGER PRIMARY KEY AUTOINCREMENT,
version TEXT NOT NULL UNIQUE,
name TEXT NOT NULL,
status TEXT NOT NULL CHECK(status IN ('pending', 'running', 'completed', 'failed', 'rolled_back')),
direction TEXT NOT NULL CHECK(direction IN ('forward', 'backward')),
execution_time_ms INTEGER NOT NULL CHECK(execution_time_ms >= 0),
checksum TEXT NOT NULL,
executed_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
error_message TEXT,
details TEXT
)
''')
# Create index for faster queries
cursor.execute('''
CREATE INDEX IF NOT EXISTS idx_migrations_version
ON schema_migrations(version)
''')
cursor.execute('''
CREATE INDEX IF NOT EXISTS idx_migrations_executed_at
ON schema_migrations(executed_at DESC)
''')
# Insert initial migration record if table is empty
cursor.execute('''
INSERT OR IGNORE INTO schema_migrations
(version, name, status, direction, execution_time_ms, checksum)
VALUES ('0.0', 'Initial empty schema', 'completed', 'forward', 0, 'empty')
''')
conn.commit()
@contextmanager
def _get_connection(self):
"""Get database connection with proper error handling"""
conn = sqlite3.connect(str(self.db_path))
conn.execute("PRAGMA foreign_keys = ON")
try:
yield conn
finally:
conn.close()
@contextmanager
def _transaction(self):
"""Context manager for database transactions"""
with self._get_connection() as conn:
cursor = conn.cursor()
cursor.execute("BEGIN")
try:
yield cursor
conn.commit()
except Exception:
conn.rollback()
raise
def get_current_version(self) -> str:
"""
Get current database schema version
Returns:
Current version string
"""
with self._get_connection() as conn:
cursor = conn.cursor()
cursor.execute('''
SELECT version FROM schema_migrations
WHERE status = 'completed' AND direction = 'forward'
ORDER BY executed_at DESC LIMIT 1
''')
result = cursor.fetchone()
return result[0] if result else "0.0"
def get_migration_history(self) -> List[MigrationRecord]:
"""
Get migration execution history
Returns:
List of migration records, most recent first
"""
with self._get_connection() as conn:
cursor = conn.cursor()
cursor.execute('''
SELECT id, version, name, status, direction,
execution_time_ms, checksum, error_message,
executed_at, details
FROM schema_migrations
ORDER BY executed_at DESC
''')
records = []
for row in cursor.fetchall():
record = MigrationRecord(
id=row[0],
version=row[1],
name=row[2],
status=MigrationStatus(row[3]),
direction=MigrationDirection(row[4]),
execution_time_ms=row[5],
checksum=row[6],
error_message=row[7],
executed_at=row[8],
details=json.loads(row[9]) if row[9] else None
)
records.append(record)
return records
def _validate_migration(self, migration: Migration) -> Tuple[bool, List[str]]:
"""
Validate migration safety
Args:
migration: Migration to validate
Returns:
Tuple of (is_valid, error_messages)
"""
errors = []
# Check migration hash
if migration.get_hash() != migration.get_hash(): # Simple consistency check
errors.append("Migration content is inconsistent")
# Run custom validation function if provided
if migration.check_function:
try:
with self._get_connection() as conn:
is_valid, validation_error = migration.check_function(conn, migration)
if not is_valid:
errors.append(validation_error)
except Exception as e:
errors.append(f"Validation function failed: {e}")
return len(errors) == 0, errors
def _execute_migration_sql(self, cursor: sqlite3.Cursor, sql: str) -> None:
"""
Execute migration SQL safely
Args:
cursor: Database cursor
sql: SQL to execute
"""
# Split SQL into individual statements
statements = [s.strip() for s in sql.split(';') if s.strip()]
for statement in statements:
if statement:
cursor.execute(statement)
def _run_migration(self, migration: Migration, direction: MigrationDirection,
dry_run: bool = False) -> None:
"""
Run a single migration
Args:
migration: Migration to run
direction: Migration direction
dry_run: If True, only validate without executing
"""
start_time = datetime.now()
# Select appropriate SQL
if direction == MigrationDirection.FORWARD:
sql = migration.forward_sql
elif direction == MigrationDirection.BACKWARD:
if not migration.backward_sql:
raise ValueError(f"Migration {migration.version} cannot be rolled back")
sql = migration.backward_sql
else:
raise ValueError(f"Invalid migration direction: {direction}")
# Validate migration
is_valid, errors = self._validate_migration(migration)
if not is_valid:
raise ValueError(f"Migration validation failed: {'; '.join(errors)}")
if dry_run:
logger.info(f"[DRY RUN] Would apply {direction.value} migration {migration.version}")
return
# Record migration start
with self._transaction() as cursor:
# Insert running record
cursor.execute('''
INSERT INTO schema_migrations
(version, name, status, direction, execution_time_ms, checksum)
VALUES (?, ?, 'running', ?, 0, ?)
''', (migration.version, migration.name, direction.value, migration.get_hash()))
# Execute migration
try:
self._execute_migration_sql(cursor, sql)
# Calculate execution time
execution_time_ms = int((datetime.now() - start_time).total_seconds() * 1000)
# Update record as completed
cursor.execute('''
UPDATE schema_migrations
SET status = 'completed', execution_time_ms = ?
WHERE version = ? AND status = 'running' AND direction = ?
ORDER BY executed_at DESC LIMIT 1
''', (execution_time_ms, migration.version, direction.value))
logger.info(f"Successfully applied {direction.value} migration {migration.version} "
f"in {execution_time_ms}ms")
except Exception as e:
execution_time_ms = int((datetime.now() - start_time).total_seconds() * 1000)
# Update record as failed
cursor.execute('''
UPDATE schema_migrations
SET status = 'failed', error_message = ?
WHERE version = ? AND status = 'running' AND direction = ?
ORDER BY executed_at DESC LIMIT 1
''', (str(e), migration.version, direction.value))
logger.error(f"Migration {migration.version} failed: {e}")
raise RuntimeError(f"Migration {migration.version} failed: {e}")
def get_pending_migrations(self) -> List[Migration]:
"""
Get list of pending migrations
Returns:
List of migrations that need to be applied
"""
current_version = self.get_current_version()
pending = []
# Get all migration versions
all_versions = sorted(self.migrations.keys(), key=lambda v: tuple(map(int, v.split('.'))))
for version in all_versions:
if version > current_version:
migration = self.migrations[version]
pending.append(migration)
return pending
def migrate_to_version(self, target_version: str, dry_run: bool = False,
force: bool = False) -> None:
"""
Migrate database to target version
Args:
target_version: Target version to migrate to
dry_run: If True, only validate without executing
force: If True, skip breaking change confirmation
"""
current_version = self.get_current_version()
logger.info(f"Current version: {current_version}, Target version: {target_version}")
# Validate target version exists
if target_version != "latest" and target_version not in self.migrations:
raise ValueError(f"Target version {target_version} not found")
# Determine migration path
if target_version == "latest":
# Migrate forward to latest
target_migration = max(self.migrations.keys(), key=lambda v: tuple(map(int, v.split('.'))))
else:
target_migration = target_version
if target_migration > current_version:
# Forward migration
self._migrate_forward(current_version, target_migration, dry_run, force)
elif target_migration < current_version:
# Rollback
self._migrate_backward(current_version, target_migration, dry_run, force)
else:
logger.info("Database is already at target version")
def _migrate_forward(self, from_version: str, to_version: str,
dry_run: bool = False, force: bool = False) -> None:
"""Execute forward migrations"""
all_versions = sorted(self.migrations.keys(), key=lambda v: tuple(map(int, v.split('.'))))
for version in all_versions:
if version > from_version and version <= to_version:
migration = self.migrations[version]
# Check for breaking changes
if migration.is_breaking and not force:
raise RuntimeError(
f"Migration {migration.version} is a breaking change. "
f"Use --force to apply."
)
# Check dependencies
for dep in migration.dependencies:
if dep > from_version:
raise RuntimeError(
f"Migration {migration.version} requires dependency {dep} "
f"which is not yet applied"
)
self._run_migration(migration, MigrationDirection.FORWARD, dry_run)
def _migrate_backward(self, from_version: str, to_version: str,
dry_run: bool = False, force: bool = False) -> None:
"""Execute rollback migrations"""
all_versions = sorted(self.migrations.keys(), key=lambda v: tuple(map(int, v.split('.'))), reverse=True)
for version in all_versions:
if version <= from_version and version > to_version:
migration = self.migrations[version]
if not migration.backward_sql:
raise RuntimeError(f"Migration {migration.version} cannot be rolled back")
# Check if migration would break other migrations
dependent_migrations = [
v for v, m in self.migrations.items()
if version in m.dependencies and v <= from_version
]
if dependent_migrations and not force:
raise RuntimeError(
f"Cannot rollback {version} because it has dependencies: "
f"{', '.join(dependent_migrations)}"
)
self._run_migration(migration, MigrationDirection.BACKWARD, dry_run)
def rollback_migration(self, version: str, dry_run: bool = False,
force: bool = False) -> None:
"""
Rollback a specific migration
Args:
version: Migration version to rollback
dry_run: If True, only validate without executing
force: If True, skip safety checks
"""
if version not in self.migrations:
raise ValueError(f"Migration {version} not found")
migration = self.migrations[version]
if not migration.backward_sql:
raise ValueError(f"Migration {version} cannot be rolled back")
# Check if migration has been applied
history = self.get_migration_history()
applied_versions = [m.version for m in history if m.status == MigrationStatus.COMPLETED]
if version not in applied_versions:
raise ValueError(f"Migration {version} has not been applied")
# Check for dependent migrations
dependent_migrations = [
v for v, m in self.migrations.items()
if version in m.dependencies and v in applied_versions
]
if dependent_migrations and not force:
raise RuntimeError(
f"Cannot rollback {version} because it has dependencies: "
f"{', '.join(dependent_migrations)}"
)
logger.info(f"Rolling back migration {version}")
self._run_migration(migration, MigrationDirection.BACKWARD, dry_run)
def get_migration_plan(self, target_version: str = "latest") -> List[Dict[str, Any]]:
"""
Get migration execution plan
Args:
target_version: Target version to plan for
Returns:
List of migration steps with details
"""
current_version = self.get_current_version()
plan = []
if target_version == "latest":
target_version = max(self.migrations.keys(), key=lambda v: tuple(map(int, v.split('.'))))
all_versions = sorted(self.migrations.keys(), key=lambda v: tuple(map(int, v.split('.'))))
for version in all_versions:
if version > current_version and version <= target_version:
migration = self.migrations[version]
step = {
'version': version,
'name': migration.name,
'description': migration.description,
'is_breaking': migration.is_breaking,
'dependencies': migration.dependencies,
'has_rollback': migration.backward_sql is not None
}
plan.append(step)
return plan
def validate_migration_safety(self, target_version: str = "latest") -> Tuple[bool, List[str]]:
"""
Validate migration plan for safety issues
Args:
target_version: Target version to validate
Returns:
Tuple of (is_safe, safety_issues)
"""
plan = self.get_migration_plan(target_version)
issues = []
for step in plan:
migration = self.migrations[step['version']]
# Check breaking changes
if migration.is_breaking:
issues.append(f"Breaking change in {step['version']}: {step['name']}")
# Check rollback capability
if not migration.backward_sql:
issues.append(f"Migration {step['version']} cannot be rolled back")
return len(issues) == 0, issues

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#!/usr/bin/env python3
"""
Database Migration CLI - Migration Management Commands
CRITICAL FIX (P1-6): Production database migration CLI commands
Features:
- Run migrations with dry-run support
- Migration status and history
- Rollback capability
- Migration validation
- Migration planning
"""
from __future__ import annotations
import argparse
import json
import logging
import sys
from pathlib import Path
from typing import Dict, Any, List
from dataclasses import asdict
from .database_migration import DatabaseMigrationManager, MigrationRecord, MigrationStatus
from .migrations import MIGRATION_REGISTRY, LATEST_VERSION, get_migration, get_migrations_up_to
from .config import get_config
logger = logging.getLogger(__name__)
class DatabaseMigrationCLI:
"""CLI interface for database migrations"""
def __init__(self, db_path: Path = None):
"""
Initialize migration CLI
Args:
db_path: Database path (uses config if not provided)
"""
if db_path is None:
config = get_config()
db_path = config.database.path
self.db_path = Path(db_path)
self.migration_manager = DatabaseMigrationManager(self.db_path)
# Register all migrations
for migration in MIGRATION_REGISTRY.values():
self.migration_manager.register_migration(migration)
def cmd_status(self, args) -> None:
"""
Show migration status
Args:
args: Command line arguments
"""
try:
current_version = self.migration_manager.get_current_version()
history = self.migration_manager.get_migration_history()
pending = self.migration_manager.get_pending_migrations()
print("Database Migration Status")
print("=" * 40)
print(f"Database Path: {self.db_path}")
print(f"Current Version: {current_version}")
print(f"Latest Version: {LATEST_VERSION}")
print(f"Pending Migrations: {len(pending)}")
print(f"Total Migrations Applied: {len([h for h in history if h.status == MigrationStatus.COMPLETED])}")
if pending:
print("\nPending Migrations:")
for migration in pending:
print(f" - {migration.version}: {migration.name}")
if history:
print("\nRecent Migration History:")
for i, record in enumerate(history[:5]):
status_icon = "✅" if record.status == MigrationStatus.COMPLETED else "❌"
print(f" {status_icon} {record.version}: {record.name} ({record.status.value})")
except Exception as e:
print(f"❌ Error getting status: {e}")
sys.exit(1)
def cmd_history(self, args) -> None:
"""
Show migration history
Args:
args: Command line arguments
"""
try:
history = self.migration_manager.get_migration_history()
if not history:
print("No migration history found")
return
if args.format == 'json':
records = [record.to_dict() for record in history]
print(json.dumps(records, indent=2, default=str))
else:
print("Migration History")
print("=" * 40)
for record in history:
status_icon = {
MigrationStatus.COMPLETED: "✅",
MigrationStatus.FAILED: "❌",
MigrationStatus.ROLLED_BACK: "↩️",
MigrationStatus.RUNNING: "⏳",
}.get(record.status, "❓")
print(f"{status_icon} {record.version} ({record.direction.value})")
print(f" Name: {record.name}")
print(f" Status: {record.status.value}")
print(f" Executed: {record.executed_at}")
print(f" Duration: {record.execution_time_ms}ms")
if record.error_message:
print(f" Error: {record.error_message}")
print()
except Exception as e:
print(f"❌ Error getting history: {e}")
sys.exit(1)
def cmd_migrate(self, args) -> None:
"""
Run migrations
Args:
args: Command line arguments
"""
try:
target_version = args.version if args.version else LATEST_VERSION
dry_run = args.dry_run
force = args.force
print(f"Running migrations to version: {target_version}")
if dry_run:
print("🚨 DRY RUN MODE - No changes will be applied")
if force:
print("🚨 FORCE MODE - Safety checks bypassed")
# Get migration plan
plan = self.migration_manager.get_migration_plan(target_version)
if not plan:
print("✅ No migrations to apply")
return
print(f"\nMigration Plan:")
print("=" * 40)
for i, step in enumerate(plan, 1):
breaking_icon = "🔴" if step.get('is_breaking') else "🟢"
print(f"{i}. {breaking_icon} {step['version']}: {step['name']}")
print(f" Description: {step['description']}")
if step.get('dependencies'):
print(f" Dependencies: {', '.join(step['dependencies'])}")
if step.get('is_breaking'):
print(" ⚠️ Breaking change - may require data migration")
print()
if not args.yes and not dry_run:
response = input("Continue with migration? (y/N): ")
if response.lower() != 'y':
print("Migration cancelled")
return
# Run migration
self.migration_manager.migrate_to_version(target_version, dry_run, force)
if dry_run:
print("✅ Dry run completed successfully")
else:
print("✅ Migration completed successfully")
# Show new status
new_version = self.migration_manager.get_current_version()
print(f"Database is now at version: {new_version}")
except Exception as e:
print(f"❌ Migration failed: {e}")
sys.exit(1)
def cmd_rollback(self, args) -> None:
"""
Rollback migration
Args:
args: Command line arguments
"""
try:
target_version = args.version
dry_run = args.dry_run
force = args.force
if not target_version:
print("❌ Target version is required for rollback")
sys.exit(1)
current_version = self.migration_manager.get_current_version()
print(f"Rolling back from version {current_version} to {target_version}")
if dry_run:
print("🚨 DRY RUN MODE - No changes will be applied")
if force:
print("🚨 FORCE MODE - Safety checks bypassed")
# Warn about potential data loss
if not args.yes and not dry_run:
response = input("⚠️ WARNING: Rollback may cause data loss. Continue? (y/N): ")
if response.lower() != 'y':
print("Rollback cancelled")
return
# Run rollback
self.migration_manager.migrate_to_version(target_version, dry_run, force)
if dry_run:
print("✅ Dry run completed successfully")
else:
print("✅ Rollback completed successfully")
# Show new status
new_version = self.migration_manager.get_current_version()
print(f"Database is now at version: {new_version}")
except Exception as e:
print(f"❌ Rollback failed: {e}")
sys.exit(1)
def cmd_plan(self, args) -> None:
"""
Show migration plan
Args:
args: Command line arguments
"""
try:
target_version = args.version if args.version else LATEST_VERSION
plan = self.migration_manager.get_migration_plan(target_version)
if not plan:
print("✅ No migrations to apply")
return
print(f"Migration Plan (to version {target_version})")
print("=" * 50)
current_version = self.migration_manager.get_current_version()
print(f"Current Version: {current_version}")
print(f"Target Version: {target_version}")
print()
for i, step in enumerate(plan, 1):
breaking_icon = "🔴" if step.get('is_breaking') else "🟢"
rollback_icon = "✅" if step.get('has_rollback') else "❌"
print(f"{i}. {breaking_icon} {step['version']}: {step['name']}")
print(f" Description: {step['description']}")
print(f" Rollback: {rollback_icon}")
if step.get('dependencies'):
print(f" Dependencies: {', '.join(step['dependencies'])}")
print()
# Safety validation
is_safe, issues = self.migration_manager.validate_migration_safety(target_version)
if is_safe:
print("✅ Migration plan is safe")
else:
print("⚠️ Safety issues detected:")
for issue in issues:
print(f" - {issue}")
except Exception as e:
print(f"❌ Error getting migration plan: {e}")
sys.exit(1)
def cmd_validate(self, args) -> None:
"""
Validate migration safety
Args:
args: Command line arguments
"""
try:
target_version = args.version if args.version else LATEST_VERSION
is_safe, issues = self.migration_manager.validate_migration_safety(target_version)
if is_safe:
print("✅ Migration plan is safe")
sys.exit(0)
else:
print("❌ Migration safety issues found:")
for issue in issues:
print(f" - {issue}")
sys.exit(1)
except Exception as e:
print(f"❌ Validation failed: {e}")
sys.exit(1)
def cmd_create_migration(self, args) -> None:
"""
Create a new migration template
Args:
args: Command line arguments
"""
try:
version = args.version
name = args.name
description = args.description
if not version or not name:
print("❌ Version and name are required")
sys.exit(1)
# Check if migration already exists
if version in MIGRATION_REGISTRY:
print(f"❌ Migration {version} already exists")
sys.exit(1)
# Create migration template
template = f'''
# Migration {version}: {name}
# Description: {description}
from __future__ import annotations
import sqlite3
from typing import Tuple
from .database_migration import Migration
from utils.migrations import get_migration
def _validate_migration(conn: sqlite3.Connection, migration: Migration) -> Tuple[bool, str]:
"""Validate migration"""
# Add custom validation logic here
return True, "Migration validation passed"
MIGRATION_{version.replace(".", "_")} = Migration(
version="{version}",
name="{name}",
description="{description}",
forward_sql=\"\"\"
-- Add your forward migration SQL here
\"\"\",
backward_sql=\"\"\"
-- Add your backward migration SQL here (optional)
\"\"\",
dependencies=["2.2"], # List required migrations
check_function=_validate_migration,
is_breaking=False # Set to True for breaking changes
)
# Add to MIGRATION_REGISTRY in migrations.py
# ALL_MIGRATIONS.append(MIGRATION_{version.replace(".", "_")})
# MIGRATION_REGISTRY["{version}"] = MIGRATION_{version.replace(".", "_")}
# LATEST_VERSION = "{version}" # Update if this is the latest
'''.strip()
print("Migration Template:")
print("=" * 50)
print(template)
print("\n⚠️ Remember to:")
print("1. Add the migration to ALL_MIGRATIONS list in migrations.py")
print("2. Update MIGRATION_REGISTRY and LATEST_VERSION")
print("3. Test the migration before deploying")
except Exception as e:
print(f"❌ Error creating template: {e}")
sys.exit(1)
def create_migration_cli(db_path: Path = None) -> DatabaseMigrationCLI:
"""Create migration CLI instance"""
return DatabaseMigrationCLI(db_path)

317
transcript-fixer/scripts/utils/domain_validator.py Normal file
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#!/usr/bin/env python3
"""
Domain Validation and Input Sanitization
CRITICAL FIX: Prevents SQL injection via domain parameter
ISSUE: Critical-3 in Engineering Excellence Plan
This module provides:
1. Domain whitelist validation
2. Input sanitization for text fields
3. SQL injection prevention helpers
Author: Chief Engineer
Date: 2025-10-28
Priority: P0 - Critical
"""
from __future__ import annotations
from typing import Final, Set
import re
# Domain whitelist - ONLY these values are allowed
VALID_DOMAINS: Final[Set[str]] = {
'general',
'embodied_ai',
'finance',
'medical',
'legal',
'technical',
}
# Source whitelist
VALID_SOURCES: Final[Set[str]] = {
'manual',
'learned',
'imported',
'ai_suggested',
'community',
}
# Maximum text lengths to prevent DoS
MAX_FROM_TEXT_LENGTH: Final[int] = 500
MAX_TO_TEXT_LENGTH: Final[int] = 500
MAX_NOTES_LENGTH: Final[int] = 2000
MAX_USER_LENGTH: Final[int] = 100
class ValidationError(Exception):
"""Input validation failed"""
pass
def validate_domain(domain: str) -> str:
"""
Validate domain against whitelist.
CRITICAL: Prevents SQL injection via domain parameter.
Domain is used in WHERE clauses - must be whitelisted.
Args:
domain: Domain string to validate
Returns:
Validated domain (guaranteed to be in whitelist)
Raises:
ValidationError: If domain not in whitelist
Examples:
>>> validate_domain('general')
'general'
>>> validate_domain('hacked"; DROP TABLE corrections--')
ValidationError: Invalid domain
"""
if not domain:
raise ValidationError("Domain cannot be empty")
domain = domain.strip().lower()
# Check again after stripping (whitespace-only input)
if not domain:
raise ValidationError("Domain cannot be empty")
if domain not in VALID_DOMAINS:
raise ValidationError(
f"Invalid domain: '{domain}'. "
f"Valid domains: {sorted(VALID_DOMAINS)}"
)
return domain
def validate_source(source: str) -> str:
"""
Validate source against whitelist.
Args:
source: Source string to validate
Returns:
Validated source
Raises:
ValidationError: If source not in whitelist
"""
if not source:
raise ValidationError("Source cannot be empty")
source = source.strip().lower()
if source not in VALID_SOURCES:
raise ValidationError(
f"Invalid source: '{source}'. "
f"Valid sources: {sorted(VALID_SOURCES)}"
)
return source
def sanitize_text_field(text: str, max_length: int, field_name: str = "field") -> str:
"""
Sanitize text input with length validation.
Prevents:
- Excessively long inputs (DoS)
- Binary data
- Control characters (except whitespace)
Args:
text: Text to sanitize
max_length: Maximum allowed length
field_name: Field name for error messages
Returns:
Sanitized text
Raises:
ValidationError: If validation fails
"""
if not text:
raise ValidationError(f"{field_name} cannot be empty")
if not isinstance(text, str):
raise ValidationError(f"{field_name} must be a string")
# Check length
if len(text) > max_length:
raise ValidationError(
f"{field_name} too long: {len(text)} chars "
f"(max: {max_length})"
)
# Check for null bytes (can break SQLite)
if '\x00' in text:
raise ValidationError(f"{field_name} contains null bytes")
# Remove other control characters except tab, newline, carriage return
sanitized = ''.join(
char for char in text
if ord(char) >= 32 or char in '\t\n\r'
)
if not sanitized.strip():
raise ValidationError(f"{field_name} is empty after sanitization")
return sanitized
def validate_correction_inputs(
from_text: str,
to_text: str,
domain: str,
source: str,
notes: str | None = None,
added_by: str | None = None
) -> tuple[str, str, str, str, str | None, str | None]:
"""
Validate all inputs for correction creation.
Comprehensive validation in one function.
Call this before any database operation.
Args:
from_text: Original text
to_text: Corrected text
domain: Domain name
source: Source type
notes: Optional notes
added_by: Optional user
Returns:
Tuple of (sanitized from_text, to_text, domain, source, notes, added_by)
Raises:
ValidationError: If any validation fails
Example:
>>> validate_correction_inputs(
... "teh", "the", "general", "manual", None, "user123"
... )
('teh', 'the', 'general', 'manual', None, 'user123')
"""
# Validate domain and source (whitelist)
domain = validate_domain(domain)
source = validate_source(source)
# Sanitize text fields
from_text = sanitize_text_field(from_text, MAX_FROM_TEXT_LENGTH, "from_text")
to_text = sanitize_text_field(to_text, MAX_TO_TEXT_LENGTH, "to_text")
# Optional fields
if notes is not None:
notes = sanitize_text_field(notes, MAX_NOTES_LENGTH, "notes")
if added_by is not None:
added_by = sanitize_text_field(added_by, MAX_USER_LENGTH, "added_by")
return from_text, to_text, domain, source, notes, added_by
def validate_confidence(confidence: float) -> float:
"""
Validate confidence score is in valid range.
Args:
confidence: Confidence score
Returns:
Validated confidence
Raises:
ValidationError: If out of range
"""
if not isinstance(confidence, (int, float)):
raise ValidationError("Confidence must be a number")
if not 0.0 <= confidence <= 1.0:
raise ValidationError(
f"Confidence must be between 0.0 and 1.0, got: {confidence}"
)
return float(confidence)
def is_safe_sql_identifier(identifier: str) -> bool:
"""
Check if string is a safe SQL identifier.
Safe identifiers:
- Only alphanumeric and underscores
- Start with letter or underscore
- Max 64 chars
Use this for table/column names if dynamically constructing SQL.
(Though we should avoid this entirely - use parameterized queries!)
Args:
identifier: String to check
Returns:
True if safe to use as SQL identifier
"""
if not identifier:
return False
if len(identifier) > 64:
return False
# Must match: ^[a-zA-Z_][a-zA-Z0-9_]*$
pattern = r'^[a-zA-Z_][a-zA-Z0-9_]*$'
return bool(re.match(pattern, identifier))
# Example usage and testing
if __name__ == "__main__":
print("Testing domain_validator.py")
print("=" * 60)
# Test valid domain
try:
result = validate_domain("general")
print(f"✓ Valid domain: {result}")
except ValidationError as e:
print(f"✗ Unexpected error: {e}")
# Test invalid domain
try:
result = validate_domain("hacked'; DROP TABLE--")
print(f"✗ Should have failed: {result}")
except ValidationError as e:
print(f"✓ Correctly rejected: {e}")
# Test text sanitization
try:
result = sanitize_text_field("hello\x00world", 100, "test")
print(f"✗ Should have rejected null byte")
except ValidationError as e:
print(f"✓ Correctly rejected null byte: {e}")
# Test full validation
try:
result = validate_correction_inputs(
from_text="teh",
to_text="the",
domain="general",
source="manual",
notes="Typo fix",
added_by="test_user"
)
print(f"✓ Full validation passed: {result[0]} → {result[1]}")
except ValidationError as e:
print(f"✗ Unexpected error: {e}")
print("=" * 60)
print("✅ All validation tests completed")

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transcript-fixer/scripts/utils/health_check.py Normal file
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#!/usr/bin/env python3
"""
Health Check Module - System Health Monitoring
CRITICAL FIX (P1-4): Production-grade health checks for monitoring
Features:
- Database connectivity and schema validation
- File system access checks
- Configuration validation
- Dependency verification
- Resource availability checks
Health Check Levels:
- Basic: Quick connectivity checks (< 100ms)
- Standard: Full system validation (< 1s)
- Deep: Comprehensive diagnostics (< 5s)
"""
from __future__ import annotations
import json
import logging
import os
import sys
import time
from dataclasses import dataclass, asdict
from enum import Enum
from pathlib import Path
from typing import List, Dict, Optional, Final
logger = logging.getLogger(__name__)
# Import configuration for centralized config management (P1-5 fix)
from .config import get_config
# Health check thresholds
RESPONSE_TIME_WARNING: Final[float] = 1.0 # seconds
RESPONSE_TIME_CRITICAL: Final[float] = 5.0 # seconds
MIN_DISK_SPACE_MB: Final[int] = 100 # MB
class HealthStatus(Enum):
"""Health status levels"""
HEALTHY = "healthy"
DEGRADED = "degraded"
UNHEALTHY = "unhealthy"
UNKNOWN = "unknown"
class CheckLevel(Enum):
"""Health check thoroughness levels"""
BASIC = "basic" # Quick checks (< 100ms)
STANDARD = "standard" # Full validation (< 1s)
DEEP = "deep" # Comprehensive (< 5s)
@dataclass
class HealthCheckResult:
"""Result of a single health check"""
name: str
status: HealthStatus
message: str
duration_ms: float
details: Optional[Dict] = None
error: Optional[str] = None
def to_dict(self) -> Dict:
"""Convert to dictionary"""
result = asdict(self)
result['status'] = self.status.value
return result
@dataclass
class SystemHealth:
"""Overall system health status"""
status: HealthStatus
timestamp: str
duration_ms: float
checks: List[HealthCheckResult]
summary: Dict[str, int]
def to_dict(self) -> Dict:
"""Convert to dictionary"""
return {
'status': self.status.value,
'timestamp': self.timestamp,
'duration_ms': round(self.duration_ms, 2),
'checks': [check.to_dict() for check in self.checks],
'summary': self.summary
}
def to_json(self) -> str:
"""Convert to JSON string"""
return json.dumps(self.to_dict(), indent=2, ensure_ascii=False)
class HealthChecker:
"""
System health checker with configurable thoroughness levels.
CRITICAL FIX (P1-4): Enables monitoring and observability
"""
def __init__(self, config_dir: Optional[Path] = None):
"""
Initialize health checker
Args:
config_dir: Configuration directory (defaults to ~/.transcript-fixer)
"""
# P1-5 FIX: Use centralized configuration
config = get_config()
# For backward compatibility, still accept config_dir parameter
self.config_dir = config_dir or config.paths.config_dir
self.db_path = config.database.path
def check_health(self, level: CheckLevel = CheckLevel.STANDARD) -> SystemHealth:
"""
Perform health check at specified level
Args:
level: Thoroughness level (BASIC, STANDARD, DEEP)
Returns:
SystemHealth with overall status and individual check results
"""
start_time = time.time()
checks: List[HealthCheckResult] = []
logger.info(f"Starting health check (level: {level.value})")
# Always run basic checks
checks.append(self._check_config_directory())
checks.append(self._check_database())
# Standard level: add configuration checks
if level in (CheckLevel.STANDARD, CheckLevel.DEEP):
checks.append(self._check_api_key())
checks.append(self._check_dependencies())
checks.append(self._check_disk_space())
# Deep level: add comprehensive diagnostics
if level == CheckLevel.DEEP:
checks.append(self._check_database_schema())
checks.append(self._check_file_permissions())
checks.append(self._check_python_version())
# Calculate overall status
duration_ms = (time.time() - start_time) * 1000
overall_status = self._calculate_overall_status(checks)
# Generate summary
summary = {
'total': len(checks),
'healthy': sum(1 for c in checks if c.status == HealthStatus.HEALTHY),
'degraded': sum(1 for c in checks if c.status == HealthStatus.DEGRADED),
'unhealthy': sum(1 for c in checks if c.status == HealthStatus.UNHEALTHY),
}
# Check for slow response time
if duration_ms > RESPONSE_TIME_CRITICAL * 1000:
logger.warning(f"Health check took {duration_ms:.0f}ms (critical threshold)")
elif duration_ms > RESPONSE_TIME_WARNING * 1000:
logger.warning(f"Health check took {duration_ms:.0f}ms (warning threshold)")
return SystemHealth(
status=overall_status,
timestamp=time.strftime("%Y-%m-%d %H:%M:%S"),
duration_ms=duration_ms,
checks=checks,
summary=summary
)
def _calculate_overall_status(self, checks: List[HealthCheckResult]) -> HealthStatus:
"""Calculate overall system status from individual checks"""
if not checks:
return HealthStatus.UNKNOWN
# Any unhealthy check = system unhealthy
if any(c.status == HealthStatus.UNHEALTHY for c in checks):
return HealthStatus.UNHEALTHY
# Any degraded check = system degraded
if any(c.status == HealthStatus.DEGRADED for c in checks):
return HealthStatus.DEGRADED
# All healthy = system healthy
if all(c.status == HealthStatus.HEALTHY for c in checks):
return HealthStatus.HEALTHY
return HealthStatus.UNKNOWN
def _check_config_directory(self) -> HealthCheckResult:
"""Check configuration directory exists and is writable"""
start_time = time.time()
name = "config_directory"
try:
# Check existence
if not self.config_dir.exists():
return HealthCheckResult(
name=name,
status=HealthStatus.UNHEALTHY,
message="Configuration directory does not exist",
duration_ms=(time.time() - start_time) * 1000,
details={'path': str(self.config_dir)},
error="Directory not found"
)
# Check writability
test_file = self.config_dir / ".health_check_test"
try:
test_file.touch()
test_file.unlink()
except (PermissionError, OSError) as e:
return HealthCheckResult(
name=name,
status=HealthStatus.DEGRADED,
message="Configuration directory not writable",
duration_ms=(time.time() - start_time) * 1000,
details={'path': str(self.config_dir)},
error=str(e)
)
return HealthCheckResult(
name=name,
status=HealthStatus.HEALTHY,
message="Configuration directory accessible",
duration_ms=(time.time() - start_time) * 1000,
details={'path': str(self.config_dir)}
)
except Exception as e:
logger.exception("Config directory check failed")
return HealthCheckResult(
name=name,
status=HealthStatus.UNHEALTHY,
message="Configuration directory check failed",
duration_ms=(time.time() - start_time) * 1000,
error=str(e)
)
def _check_database(self) -> HealthCheckResult:
"""Check database exists and is accessible"""
start_time = time.time()
name = "database"
try:
if not self.db_path.exists():
return HealthCheckResult(
name=name,
status=HealthStatus.DEGRADED,
message="Database not initialized",
duration_ms=(time.time() - start_time) * 1000,
details={'path': str(self.db_path)},
error="Database file not found"
)
# Try to open database
import sqlite3
try:
conn = sqlite3.connect(str(self.db_path), timeout=5.0)
cursor = conn.execute("SELECT COUNT(*) FROM sqlite_master WHERE type='table'")
table_count = cursor.fetchone()[0]
conn.close()
return HealthCheckResult(
name=name,
status=HealthStatus.HEALTHY,
message="Database accessible",
duration_ms=(time.time() - start_time) * 1000,
details={
'path': str(self.db_path),
'tables': table_count,
'size_kb': self.db_path.stat().st_size // 1024
}
)
except sqlite3.Error as e:
return HealthCheckResult(
name=name,
status=HealthStatus.UNHEALTHY,
message="Database connection failed",
duration_ms=(time.time() - start_time) * 1000,
details={'path': str(self.db_path)},
error=str(e)
)
except Exception as e:
logger.exception("Database check failed")
return HealthCheckResult(
name=name,
status=HealthStatus.UNHEALTHY,
message="Database check failed",
duration_ms=(time.time() - start_time) * 1000,
error=str(e)
)
def _check_api_key(self) -> HealthCheckResult:
"""Check API key is configured"""
start_time = time.time()
name = "api_key"
try:
# P1-5 FIX: Use centralized configuration
config = get_config()
api_key = config.api.api_key
if not api_key:
return HealthCheckResult(
name=name,
status=HealthStatus.DEGRADED,
message="API key not configured",
duration_ms=(time.time() - start_time) * 1000,
details={'env_vars_checked': ['GLM_API_KEY', 'ANTHROPIC_API_KEY']},
error="No API key found in environment"
)
# Check key format (don't validate by calling API)
if len(api_key) < 10:
return HealthCheckResult(
name=name,
status=HealthStatus.DEGRADED,
message="API key format suspicious",
duration_ms=(time.time() - start_time) * 1000,
details={'key_length': len(api_key)},
error="API key too short"
)
return HealthCheckResult(
name=name,
status=HealthStatus.HEALTHY,
message="API key configured",
duration_ms=(time.time() - start_time) * 1000,
details={'key_length': len(api_key), 'masked_key': api_key[:8] + '***'}
)
except Exception as e:
logger.exception("API key check failed")
return HealthCheckResult(
name=name,
status=HealthStatus.UNHEALTHY,
message="API key check failed",
duration_ms=(time.time() - start_time) * 1000,
error=str(e)
)
def _check_dependencies(self) -> HealthCheckResult:
"""Check required dependencies are installed"""
start_time = time.time()
name = "dependencies"
required_modules = ['httpx', 'filelock']
missing = []
installed = []
try:
for module in required_modules:
try:
__import__(module)
installed.append(module)
except ImportError:
missing.append(module)
if missing:
return HealthCheckResult(
name=name,
status=HealthStatus.UNHEALTHY,
message=f"Missing dependencies: {', '.join(missing)}",
duration_ms=(time.time() - start_time) * 1000,
details={'installed': installed, 'missing': missing},
error=f"Install with: pip install {' '.join(missing)}"
)
return HealthCheckResult(
name=name,
status=HealthStatus.HEALTHY,
message="All dependencies installed",
duration_ms=(time.time() - start_time) * 1000,
details={'installed': installed}
)
except Exception as e:
logger.exception("Dependencies check failed")
return HealthCheckResult(
name=name,
status=HealthStatus.UNHEALTHY,
message="Dependencies check failed",
duration_ms=(time.time() - start_time) * 1000,
error=str(e)
)
def _check_disk_space(self) -> HealthCheckResult:
"""Check available disk space"""
start_time = time.time()
name = "disk_space"
try:
import shutil
stat = shutil.disk_usage(self.config_dir.parent)
free_mb = stat.free / (1024 * 1024)
total_mb = stat.total / (1024 * 1024)
used_percent = (stat.used / stat.total) * 100
if free_mb < MIN_DISK_SPACE_MB:
return HealthCheckResult(
name=name,
status=HealthStatus.UNHEALTHY,
message=f"Low disk space: {free_mb:.0f}MB free",
duration_ms=(time.time() - start_time) * 1000,
details={
'free_mb': round(free_mb, 2),
'total_mb': round(total_mb, 2),
'used_percent': round(used_percent, 1)
},
error=f"Less than {MIN_DISK_SPACE_MB}MB available"
)
return HealthCheckResult(
name=name,
status=HealthStatus.HEALTHY,
message=f"Sufficient disk space: {free_mb:.0f}MB free",
duration_ms=(time.time() - start_time) * 1000,
details={
'free_mb': round(free_mb, 2),
'total_mb': round(total_mb, 2),
'used_percent': round(used_percent, 1)
}
)
except Exception as e:
logger.exception("Disk space check failed")
return HealthCheckResult(
name=name,
status=HealthStatus.UNKNOWN,
message="Disk space check failed",
duration_ms=(time.time() - start_time) * 1000,
error=str(e)
)
def _check_database_schema(self) -> HealthCheckResult:
"""Check database schema is valid (deep check)"""
start_time = time.time()
name = "database_schema"
expected_tables = [
'corrections', 'context_rules', 'correction_history',
'correction_changes', 'learned_suggestions', 'suggestion_examples',
'system_config', 'audit_log'
]
try:
if not self.db_path.exists():
return HealthCheckResult(
name=name,
status=HealthStatus.DEGRADED,
message="Database not initialized",
duration_ms=(time.time() - start_time) * 1000,
error="Cannot check schema - database missing"
)
import sqlite3
conn = sqlite3.connect(str(self.db_path), timeout=5.0)
cursor = conn.execute(
"SELECT name FROM sqlite_master WHERE type='table' ORDER BY name"
)
actual_tables = [row[0] for row in cursor.fetchall()]
conn.close()
missing = [t for t in expected_tables if t not in actual_tables]
extra = [t for t in actual_tables if t not in expected_tables and not t.startswith('sqlite_')]
if missing:
return HealthCheckResult(
name=name,
status=HealthStatus.DEGRADED,
message=f"Missing tables: {', '.join(missing)}",
duration_ms=(time.time() - start_time) * 1000,
details={
'expected': expected_tables,
'actual': actual_tables,
'missing': missing,
'extra': extra
},
error="Schema incomplete"
)
return HealthCheckResult(
name=name,
status=HealthStatus.HEALTHY,
message="Database schema valid",
duration_ms=(time.time() - start_time) * 1000,
details={
'tables': actual_tables,
'count': len(actual_tables)
}
)
except Exception as e:
logger.exception("Database schema check failed")
return HealthCheckResult(
name=name,
status=HealthStatus.UNHEALTHY,
message="Database schema check failed",
duration_ms=(time.time() - start_time) * 1000,
error=str(e)
)
def _check_file_permissions(self) -> HealthCheckResult:
"""Check file permissions (deep check)"""
start_time = time.time()
name = "file_permissions"
try:
issues = []
# Check config directory permissions
if not os.access(self.config_dir, os.R_OK | os.W_OK | os.X_OK):
issues.append(f"Config dir: insufficient permissions")
# Check database permissions (if exists)
if self.db_path.exists():
if not os.access(self.db_path, os.R_OK | os.W_OK):
issues.append(f"Database: read/write denied")
if issues:
return HealthCheckResult(
name=name,
status=HealthStatus.DEGRADED,
message="Permission issues detected",
duration_ms=(time.time() - start_time) * 1000,
details={'issues': issues},
error='; '.join(issues)
)
return HealthCheckResult(
name=name,
status=HealthStatus.HEALTHY,
message="File permissions correct",
duration_ms=(time.time() - start_time) * 1000
)
except Exception as e:
logger.exception("File permissions check failed")
return HealthCheckResult(
name=name,
status=HealthStatus.UNKNOWN,
message="File permissions check failed",
duration_ms=(time.time() - start_time) * 1000,
error=str(e)
)
def _check_python_version(self) -> HealthCheckResult:
"""Check Python version (deep check)"""
start_time = time.time()
name = "python_version"
try:
version = sys.version_info
version_str = f"{version.major}.{version.minor}.{version.micro}"
# Minimum required: Python 3.8
if version < (3, 8):
return HealthCheckResult(
name=name,
status=HealthStatus.UNHEALTHY,
message=f"Python version too old: {version_str}",
duration_ms=(time.time() - start_time) * 1000,
details={'version': version_str, 'minimum': '3.8'},
error="Python 3.8+ required"
)
# Warn if using Python 3.12+ (may have compatibility issues)
if version >= (3, 13):
return HealthCheckResult(
name=name,
status=HealthStatus.DEGRADED,
message=f"Python version very new: {version_str}",
duration_ms=(time.time() - start_time) * 1000,
details={'version': version_str, 'recommended': '3.8-3.12'},
error="May have untested compatibility issues"
)
return HealthCheckResult(
name=name,
status=HealthStatus.HEALTHY,
message=f"Python version supported: {version_str}",
duration_ms=(time.time() - start_time) * 1000,
details={'version': version_str}
)
except Exception as e:
logger.exception("Python version check failed")
return HealthCheckResult(
name=name,
status=HealthStatus.UNKNOWN,
message="Python version check failed",
duration_ms=(time.time() - start_time) * 1000,
error=str(e)
)
def format_health_output(health: SystemHealth, verbose: bool = False) -> str:
"""
Format health check results for CLI output
Args:
health: SystemHealth object
verbose: Show detailed information
Returns:
Formatted string for display
"""
lines = []
# Header - icon mapping
status_icon_map = {
HealthStatus.HEALTHY: "✅",
HealthStatus.DEGRADED: "⚠️",
HealthStatus.UNHEALTHY: "❌",
HealthStatus.UNKNOWN: "❓"
}
overall_icon = status_icon_map[health.status]
lines.append(f"\n{overall_icon} System Health: {health.status.value.upper()}")
lines.append(f"{'=' * 70}")
lines.append(f"Timestamp: {health.timestamp}")
lines.append(f"Duration: {health.duration_ms:.1f}ms")
lines.append(f"Checks: {health.summary['healthy']}/{health.summary['total']} passed")
lines.append("")
# Individual checks
for check in health.checks:
icon = status_icon_map.get(check.status, "❓")
lines.append(f"{icon} {check.name}: {check.message}")
if verbose and check.details:
for key, value in check.details.items():
lines.append(f" {key}: {value}")
if check.error:
lines.append(f" Error: {check.error}")
if verbose:
lines.append(f" Duration: {check.duration_ms:.1f}ms")
lines.append(f"\n{'=' * 70}")
return "\n".join(lines)

182
transcript-fixer/scripts/utils/logging_config.py
View File

@@ -2,14 +2,26 @@
"""
Logging Configuration for Transcript Fixer
CRITICAL FIX: Enhanced with structured logging and error tracking
ISSUE: Critical-4 in Engineering Excellence Plan
Provides structured logging with rotation, levels, and audit trails.
Added: Error rate monitoring, performance tracking, context enrichment
Author: Chief Engineer
Date: 2025-10-28
Priority: P0 - Critical
"""
import logging
import logging.handlers
import sys
import json
import time
from pathlib import Path
from typing import Optional
from typing import Optional, Dict, Any
from contextlib import contextmanager
from datetime import datetime
def setup_logging(
@@ -114,6 +126,156 @@ def get_audit_logger() -> logging.Logger:
return logging.getLogger('audit')
class ErrorCounter:
"""
Track error rates for failure threshold monitoring.
CRITICAL FIX: Added for Critical-4
Prevents silent failures by monitoring error rates.
Usage:
counter = ErrorCounter(threshold=0.3)
for item in items:
try:
process(item)
counter.success()
except Exception:
counter.failure()
if counter.should_abort():
logger.error("Error rate too high, aborting")
break
"""
def __init__(self, threshold: float = 0.3, window_size: int = 100):
"""
Initialize error counter.
Args:
threshold: Failure rate threshold (0.3 = 30%)
window_size: Number of recent operations to track
"""
self.threshold = threshold
self.window_size = window_size
self.results: list[bool] = [] # True = success, False = failure
self.total_successes = 0
self.total_failures = 0
def success(self) -> None:
"""Record a successful operation"""
self.results.append(True)
self.total_successes += 1
if len(self.results) > self.window_size:
self.results.pop(0)
def failure(self) -> None:
"""Record a failed operation"""
self.results.append(False)
self.total_failures += 1
if len(self.results) > self.window_size:
self.results.pop(0)
def failure_rate(self) -> float:
"""Calculate current failure rate (rolling window)"""
if not self.results:
return 0.0
failures = sum(1 for r in self.results if not r)
return failures / len(self.results)
def should_abort(self) -> bool:
"""Check if failure rate exceeds threshold"""
# Need minimum sample size before aborting
if len(self.results) < 10:
return False
return self.failure_rate() > self.threshold
def get_stats(self) -> Dict[str, Any]:
"""Get error statistics"""
window_total = len(self.results)
window_failures = sum(1 for r in self.results if not r)
window_successes = window_total - window_failures
return {
"window_total": window_total,
"window_successes": window_successes,
"window_failures": window_failures,
"window_failure_rate": self.failure_rate(),
"total_successes": self.total_successes,
"total_failures": self.total_failures,
"threshold": self.threshold,
"should_abort": self.should_abort(),
}
def reset(self) -> None:
"""Reset counters"""
self.results.clear()
self.total_successes = 0
self.total_failures = 0
class TimedLogger:
"""
Logger wrapper with automatic performance tracking.
CRITICAL FIX: Added for Critical-4
Automatically logs execution time for operations.
Usage:
logger = TimedLogger(logging.getLogger(__name__))
with logger.timed("chunk_processing", chunk_id=5):
process_chunk()
# Automatically logs: "chunk_processing completed in 123ms"
"""
def __init__(self, logger: logging.Logger):
"""
Initialize with a logger instance.
Args:
logger: Logger to wrap
"""
self.logger = logger
@contextmanager
def timed(self, operation_name: str, **context: Any):
"""
Context manager for timing operations.
Args:
operation_name: Name of operation
**context: Additional context to log
Yields:
None
Example:
>>> with logger.timed("api_call", chunk_id=5):
... call_api()
# Logs: "api_call completed in 123ms (chunk_id=5)"
"""
start_time = time.time()
# Format context for logging
context_str = ", ".join(f"{k}={v}" for k, v in context.items())
if context_str:
context_str = f" ({context_str})"
self.logger.info(f"{operation_name} started{context_str}")
try:
yield
except Exception as e:
duration_ms = (time.time() - start_time) * 1000
self.logger.error(
f"{operation_name} failed in {duration_ms:.1f}ms{context_str}: {e}"
)
raise
else:
duration_ms = (time.time() - start_time) * 1000
self.logger.info(
f"{operation_name} completed in {duration_ms:.1f}ms{context_str}"
)
# Example usage
if __name__ == "__main__":
setup_logging(level="DEBUG")
@@ -127,3 +289,21 @@ if __name__ == "__main__":
audit_logger = get_audit_logger()
audit_logger.info("User 'admin' added correction: '错误' → '正确'")
# Test ErrorCounter
print("\n--- Testing ErrorCounter ---")
counter = ErrorCounter(threshold=0.3)
for i in range(20):
if i % 4 == 0:
counter.failure()
else:
counter.success()
stats = counter.get_stats()
print(f"Stats: {json.dumps(stats, indent=2)}")
# Test TimedLogger
print("\n--- Testing TimedLogger ---")
timed_logger = TimedLogger(logger)
with timed_logger.timed("test_operation", item_count=100):
time.sleep(0.1)

535
transcript-fixer/scripts/utils/metrics.py Normal file
View File

@@ -0,0 +1,535 @@
#!/usr/bin/env python3
"""
Metrics Collection and Monitoring
CRITICAL FIX (P1-7): Production-grade metrics and observability
Features:
- Real-time metrics collection
- Time-series data storage (in-memory)
- Prometheus-compatible export format
- Common metrics: requests, errors, latency, throughput
- Custom metric support
- Thread-safe operations
Metrics Types:
- Counter: Monotonically increasing value (e.g., total requests)
- Gauge: Point-in-time value (e.g., active connections)
- Histogram: Distribution of values (e.g., response times)
- Summary: Statistical summary (e.g., percentiles)
"""
from __future__ import annotations
import logging
import threading
import time
from collections import defaultdict, deque
from dataclasses import dataclass, field
from enum import Enum
from typing import Dict, List, Optional, Deque, Final
from contextlib import contextmanager
import json
logger = logging.getLogger(__name__)
# Configuration constants
MAX_HISTOGRAM_SAMPLES: Final[int] = 1000 # Keep last 1000 samples per histogram
MAX_TIMESERIES_POINTS: Final[int] = 100 # Keep last 100 time series points
PERCENTILES: Final[List[float]] = [0.5, 0.9, 0.95, 0.99] # P50, P90, P95, P99
class MetricType(Enum):
"""Type of metric"""
COUNTER = "counter"
GAUGE = "gauge"
HISTOGRAM = "histogram"
SUMMARY = "summary"
@dataclass
class MetricValue:
"""Single metric data point"""
timestamp: float
value: float
labels: Dict[str, str] = field(default_factory=dict)
@dataclass
class MetricSnapshot:
"""Snapshot of a metric at a point in time"""
name: str
type: MetricType
value: float
labels: Dict[str, str]
help_text: str
timestamp: float
# Additional statistics for histograms
samples: Optional[int] = None
sum: Optional[float] = None
percentiles: Optional[Dict[str, float]] = None
def to_dict(self) -> Dict:
"""Convert to dictionary"""
result = {
'name': self.name,
'type': self.type.value,
'value': self.value,
'labels': self.labels,
'help': self.help_text,
'timestamp': self.timestamp
}
if self.samples is not None:
result['samples'] = self.samples
if self.sum is not None:
result['sum'] = self.sum
if self.percentiles:
result['percentiles'] = self.percentiles
return result
class Counter:
"""
Counter metric - monotonically increasing value.
Use for: total requests, total errors, total API calls
"""
def __init__(self, name: str, help_text: str = ""):
self.name = name
self.help_text = help_text
self._value = 0.0
self._lock = threading.Lock()
self._labels: Dict[str, str] = {}
def inc(self, amount: float = 1.0) -> None:
"""Increment counter by amount"""
if amount < 0:
raise ValueError("Counter can only increase")
with self._lock:
self._value += amount
def get(self) -> float:
"""Get current value"""
with self._lock:
return self._value
def snapshot(self) -> MetricSnapshot:
"""Get current snapshot"""
return MetricSnapshot(
name=self.name,
type=MetricType.COUNTER,
value=self.get(),
labels=self._labels.copy(),
help_text=self.help_text,
timestamp=time.time()
)
class Gauge:
"""
Gauge metric - can increase or decrease.
Use for: active connections, memory usage, queue size
"""
def __init__(self, name: str, help_text: str = ""):
self.name = name
self.help_text = help_text
self._value = 0.0
self._lock = threading.Lock()
self._labels: Dict[str, str] = {}
def set(self, value: float) -> None:
"""Set gauge to specific value"""
with self._lock:
self._value = value
def inc(self, amount: float = 1.0) -> None:
"""Increment gauge"""
with self._lock:
self._value += amount
def dec(self, amount: float = 1.0) -> None:
"""Decrement gauge"""
with self._lock:
self._value -= amount
def get(self) -> float:
"""Get current value"""
with self._lock:
return self._value
def snapshot(self) -> MetricSnapshot:
"""Get current snapshot"""
return MetricSnapshot(
name=self.name,
type=MetricType.GAUGE,
value=self.get(),
labels=self._labels.copy(),
help_text=self.help_text,
timestamp=time.time()
)
class Histogram:
"""
Histogram metric - tracks distribution of values.
Use for: request latency, response sizes, processing times
"""
def __init__(self, name: str, help_text: str = ""):
self.name = name
self.help_text = help_text
self._samples: Deque[float] = deque(maxlen=MAX_HISTOGRAM_SAMPLES)
self._count = 0
self._sum = 0.0
self._lock = threading.Lock()
self._labels: Dict[str, str] = {}
def observe(self, value: float) -> None:
"""Record a new observation"""
with self._lock:
self._samples.append(value)
self._count += 1
self._sum += value
def get_percentile(self, percentile: float) -> float:
"""
Calculate percentile value.
Args:
percentile: Value between 0 and 1 (e.g., 0.95 for P95)
"""
with self._lock:
if not self._samples:
return 0.0
sorted_samples = sorted(self._samples)
index = int(len(sorted_samples) * percentile)
index = max(0, min(index, len(sorted_samples) - 1))
return sorted_samples[index]
def get_mean(self) -> float:
"""Calculate mean value"""
with self._lock:
if self._count == 0:
return 0.0
return self._sum / self._count
def snapshot(self) -> MetricSnapshot:
"""Get current snapshot with percentiles"""
percentiles = {
f"p{int(p * 100)}": self.get_percentile(p)
for p in PERCENTILES
}
return MetricSnapshot(
name=self.name,
type=MetricType.HISTOGRAM,
value=self.get_mean(),
labels=self._labels.copy(),
help_text=self.help_text,
timestamp=time.time(),
samples=len(self._samples),
sum=self._sum,
percentiles=percentiles
)
class MetricsCollector:
"""
Central metrics collector for the application.
CRITICAL FIX (P1-7): Thread-safe metrics collection and aggregation
"""
def __init__(self):
self._counters: Dict[str, Counter] = {}
self._gauges: Dict[str, Gauge] = {}
self._histograms: Dict[str, Histogram] = {}
self._lock = threading.Lock()
# Initialize standard metrics
self._init_standard_metrics()
def _init_standard_metrics(self) -> None:
"""Initialize standard application metrics"""
# Request metrics
self.register_counter("requests_total", "Total number of requests")
self.register_counter("requests_success", "Total successful requests")
self.register_counter("requests_failed", "Total failed requests")
# Performance metrics
self.register_histogram("request_duration_seconds", "Request duration in seconds")
self.register_histogram("api_call_duration_seconds", "API call duration in seconds")
# Resource metrics
self.register_gauge("active_connections", "Current active connections")
self.register_gauge("active_tasks", "Current active tasks")
# Database metrics
self.register_counter("db_queries_total", "Total database queries")
self.register_histogram("db_query_duration_seconds", "Database query duration")
# Error metrics
self.register_counter("errors_total", "Total errors")
self.register_counter("errors_by_type", "Errors by type")
def register_counter(self, name: str, help_text: str = "") -> Counter:
"""Register a new counter metric"""
with self._lock:
if name not in self._counters:
self._counters[name] = Counter(name, help_text)
return self._counters[name]
def register_gauge(self, name: str, help_text: str = "") -> Gauge:
"""Register a new gauge metric"""
with self._lock:
if name not in self._gauges:
self._gauges[name] = Gauge(name, help_text)
return self._gauges[name]
def register_histogram(self, name: str, help_text: str = "") -> Histogram:
"""Register a new histogram metric"""
with self._lock:
if name not in self._histograms:
self._histograms[name] = Histogram(name, help_text)
return self._histograms[name]
def get_counter(self, name: str) -> Optional[Counter]:
"""Get counter by name"""
return self._counters.get(name)
def get_gauge(self, name: str) -> Optional[Gauge]:
"""Get gauge by name"""
return self._gauges.get(name)
def get_histogram(self, name: str) -> Optional[Histogram]:
"""Get histogram by name"""
return self._histograms.get(name)
@contextmanager
def track_request(self, success: bool = True):
"""
Context manager to track request metrics.
Usage:
with metrics.track_request():
# Do work
pass
"""
start_time = time.time()
self.get_gauge("active_tasks").inc()
try:
yield
if success:
self.get_counter("requests_success").inc()
except Exception:
self.get_counter("requests_failed").inc()
raise
finally:
duration = time.time() - start_time
self.get_histogram("request_duration_seconds").observe(duration)
self.get_counter("requests_total").inc()
self.get_gauge("active_tasks").dec()
@contextmanager
def track_api_call(self):
"""
Context manager to track API call metrics.
Usage:
with metrics.track_api_call():
response = await client.post(...)
"""
start_time = time.time()
try:
yield
finally:
duration = time.time() - start_time
self.get_histogram("api_call_duration_seconds").observe(duration)
@contextmanager
def track_db_query(self):
"""
Context manager to track database query metrics.
Usage:
with metrics.track_db_query():
cursor.execute(query)
"""
start_time = time.time()
try:
yield
finally:
duration = time.time() - start_time
self.get_histogram("db_query_duration_seconds").observe(duration)
self.get_counter("db_queries_total").inc()
def get_all_snapshots(self) -> List[MetricSnapshot]:
"""Get snapshots of all metrics"""
snapshots = []
with self._lock:
for counter in self._counters.values():
snapshots.append(counter.snapshot())
for gauge in self._gauges.values():
snapshots.append(gauge.snapshot())
for histogram in self._histograms.values():
snapshots.append(histogram.snapshot())
return snapshots
def to_json(self) -> str:
"""Export all metrics as JSON"""
snapshots = self.get_all_snapshots()
data = {
'timestamp': time.time(),
'metrics': [s.to_dict() for s in snapshots]
}
return json.dumps(data, indent=2)
def to_prometheus(self) -> str:
"""
Export metrics in Prometheus text format.
Format:
# HELP metric_name Description
# TYPE metric_name counter
metric_name{label="value"} 123.45 timestamp
"""
lines = []
snapshots = self.get_all_snapshots()
for snapshot in snapshots:
# HELP line
lines.append(f"# HELP {snapshot.name} {snapshot.help_text}")
# TYPE line
lines.append(f"# TYPE {snapshot.name} {snapshot.type.value}")
# Metric line
labels_str = ",".join(f'{k}="{v}"' for k, v in snapshot.labels.items())
if labels_str:
labels_str = f"{{{labels_str}}}"
# For histograms, export percentiles
if snapshot.type == MetricType.HISTOGRAM and snapshot.percentiles:
for pct_name, pct_value in snapshot.percentiles.items():
lines.append(
f'{snapshot.name}_bucket{{le="{pct_name}"}}{labels_str} '
f'{pct_value} {int(snapshot.timestamp * 1000)}'
)
lines.append(
f'{snapshot.name}_count{labels_str} '
f'{snapshot.samples} {int(snapshot.timestamp * 1000)}'
)
lines.append(
f'{snapshot.name}_sum{labels_str} '
f'{snapshot.sum} {int(snapshot.timestamp * 1000)}'
)
else:
lines.append(
f'{snapshot.name}{labels_str} '
f'{snapshot.value} {int(snapshot.timestamp * 1000)}'
)
lines.append("") # Blank line between metrics
return "\n".join(lines)
def get_summary(self) -> Dict:
"""Get human-readable summary of key metrics"""
request_duration = self.get_histogram("request_duration_seconds")
api_duration = self.get_histogram("api_call_duration_seconds")
db_duration = self.get_histogram("db_query_duration_seconds")
return {
'requests': {
'total': int(self.get_counter("requests_total").get()),
'success': int(self.get_counter("requests_success").get()),
'failed': int(self.get_counter("requests_failed").get()),
'active': int(self.get_gauge("active_tasks").get()),
'avg_duration_ms': round(request_duration.get_mean() * 1000, 2),
'p95_duration_ms': round(request_duration.get_percentile(0.95) * 1000, 2),
},
'api_calls': {
'avg_duration_ms': round(api_duration.get_mean() * 1000, 2),
'p95_duration_ms': round(api_duration.get_percentile(0.95) * 1000, 2),
},
'database': {
'total_queries': int(self.get_counter("db_queries_total").get()),
'avg_duration_ms': round(db_duration.get_mean() * 1000, 2),
'p95_duration_ms': round(db_duration.get_percentile(0.95) * 1000, 2),
},
'errors': {
'total': int(self.get_counter("errors_total").get()),
},
'resources': {
'active_connections': int(self.get_gauge("active_connections").get()),
'active_tasks': int(self.get_gauge("active_tasks").get()),
}
}
# Global metrics collector singleton
_global_metrics: Optional[MetricsCollector] = None
_metrics_lock = threading.Lock()
def get_metrics() -> MetricsCollector:
"""Get global metrics collector (singleton)"""
global _global_metrics
if _global_metrics is None:
with _metrics_lock:
if _global_metrics is None:
_global_metrics = MetricsCollector()
logger.info("Initialized global metrics collector")
return _global_metrics
def format_metrics_summary(summary: Dict) -> str:
"""Format metrics summary for CLI display"""
lines = [
"\n📊 Metrics Summary",
"=" * 70,
"",
"Requests:",
f" Total: {summary['requests']['total']}",
f" Success: {summary['requests']['success']}",
f" Failed: {summary['requests']['failed']}",
f" Active: {summary['requests']['active']}",
f" Avg Duration: {summary['requests']['avg_duration_ms']}ms",
f" P95 Duration: {summary['requests']['p95_duration_ms']}ms",
"",
"API Calls:",
f" Avg Duration: {summary['api_calls']['avg_duration_ms']}ms",
f" P95 Duration: {summary['api_calls']['p95_duration_ms']}ms",
"",
"Database:",
f" Total Queries: {summary['database']['total_queries']}",
f" Avg Duration: {summary['database']['avg_duration_ms']}ms",
f" P95 Duration: {summary['database']['p95_duration_ms']}ms",
"",
"Errors:",
f" Total: {summary['errors']['total']}",
"",
"Resources:",
f" Active Connections: {summary['resources']['active_connections']}",
f" Active Tasks: {summary['resources']['active_tasks']}",
"",
"=" * 70
]
return "\n".join(lines)

468
transcript-fixer/scripts/utils/migrations.py Normal file
View File

@@ -0,0 +1,468 @@
#!/usr/bin/env python3
"""
Migration Definitions - Database Schema Migrations
This module contains all database migrations for the transcript-fixer system.
Migrations are defined here to ensure version control and proper migration ordering.
Each migration has:
- Unique version number
- Forward SQL
- Optional backward SQL (for rollback)
- Dependencies on previous versions
- Validation functions
"""
from __future__ import annotations
import sqlite3
import logging
from typing import Dict, Any, Tuple, Optional
from .database_migration import Migration
logger = logging.getLogger(__name__)
def _validate_schema_2_0(conn: sqlite3.Connection, migration: Migration) -> Tuple[bool, str]:
"""Validate that schema v2.0 is correctly applied"""
cursor = conn.cursor()
# Check if all tables exist
expected_tables = {
'corrections', 'context_rules', 'correction_history',
'correction_changes', 'learned_suggestions',
'suggestion_examples', 'system_config', 'audit_log'
}
cursor.execute("SELECT name FROM sqlite_master WHERE type='table'")
existing_tables = {row[0] for row in cursor.fetchall()}
missing_tables = expected_tables - existing_tables
if missing_tables:
return False, f"Missing tables: {missing_tables}"
# Check system_config has required entries
cursor.execute("SELECT key FROM system_config WHERE key = 'schema_version'")
if not cursor.fetchone():
return False, "Missing schema_version in system_config"
return True, "Schema validation passed"
# Migration from no schema to v1.0 (basic structure)
MIGRATION_V1_0 = Migration(
version="1.0",
name="Initial Database Schema",
description="Create basic tables for correction storage",
forward_sql="""
-- Enable foreign keys
PRAGMA foreign_keys = ON;
-- Table: corrections
CREATE TABLE corrections (
id INTEGER PRIMARY KEY AUTOINCREMENT,
from_text TEXT NOT NULL,
to_text TEXT NOT NULL,
domain TEXT NOT NULL DEFAULT 'general',
source TEXT NOT NULL CHECK(source IN ('manual', 'learned', 'imported')),
confidence REAL NOT NULL DEFAULT 1.0 CHECK(confidence >= 0.0 AND confidence <= 1.0),
added_by TEXT,
added_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
usage_count INTEGER NOT NULL DEFAULT 0 CHECK(usage_count >= 0),
last_used TIMESTAMP,
notes TEXT,
is_active BOOLEAN NOT NULL DEFAULT 1,
UNIQUE(from_text, domain)
);
-- Table: correction_history
CREATE TABLE correction_history (
id INTEGER PRIMARY KEY AUTOINCREMENT,
filename TEXT NOT NULL,
domain TEXT NOT NULL,
run_timestamp TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
original_length INTEGER NOT NULL CHECK(original_length >= 0),
stage1_changes INTEGER NOT NULL DEFAULT 0 CHECK(stage1_changes >= 0),
stage2_changes INTEGER NOT NULL DEFAULT 0 CHECK(stage2_changes >= 0),
model TEXT,
execution_time_ms INTEGER CHECK(execution_time_ms >= 0),
success BOOLEAN NOT NULL DEFAULT 1,
error_message TEXT
);
-- Insert initial system config
CREATE TABLE system_config (
key TEXT PRIMARY KEY,
value TEXT NOT NULL,
value_type TEXT NOT NULL CHECK(value_type IN ('string', 'int', 'float', 'boolean', 'json')),
description TEXT,
updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
);
INSERT OR IGNORE INTO system_config (key, value, value_type, description) VALUES
('schema_version', '1.0', 'string', 'Database schema version'),
('api_provider', 'GLM', 'string', 'API provider name'),
('api_model', 'GLM-4.6', 'string', 'Default AI model');
-- Create indexes
CREATE INDEX idx_corrections_domain ON corrections(domain);
CREATE INDEX idx_corrections_source ON corrections(source);
CREATE INDEX idx_corrections_added_at ON corrections(added_at);
CREATE INDEX idx_corrections_is_active ON corrections(is_active);
CREATE INDEX idx_corrections_from_text ON corrections(from_text);
CREATE INDEX idx_history_run_timestamp ON correction_history(run_timestamp DESC);
CREATE INDEX idx_history_domain ON correction_history(domain);
CREATE INDEX idx_history_success ON correction_history(success);
""",
backward_sql="""
-- Drop indexes
DROP INDEX IF EXISTS idx_corrections_domain;
DROP INDEX IF EXISTS idx_corrections_source;
DROP INDEX IF EXISTS idx_corrections_added_at;
DROP INDEX IF EXISTS idx_corrections_is_active;
DROP INDEX IF EXISTS idx_corrections_from_text;
DROP INDEX IF EXISTS idx_history_run_timestamp;
DROP INDEX IF EXISTS idx_history_domain;
DROP INDEX IF EXISTS idx_history_success;
-- Drop tables
DROP TABLE IF EXISTS correction_history;
DROP TABLE IF EXISTS corrections;
DROP TABLE IF EXISTS system_config;
""",
dependencies=[],
check_function=None
)
# Migration from v1.0 to v2.0 (full schema)
MIGRATION_V2_0 = Migration(
version="2.0",
name="Complete Schema Enhancement",
description="Add advanced tables for learning system and audit trail",
forward_sql="""
-- Enable foreign keys
PRAGMA foreign_keys = ON;
-- Add new tables
CREATE TABLE context_rules (
id INTEGER PRIMARY KEY AUTOINCREMENT,
pattern TEXT NOT NULL UNIQUE,
replacement TEXT NOT NULL,
description TEXT,
priority INTEGER NOT NULL DEFAULT 0,
is_active BOOLEAN NOT NULL DEFAULT 1,
added_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
added_by TEXT
);
CREATE TABLE correction_changes (
id INTEGER PRIMARY KEY AUTOINCREMENT,
history_id INTEGER NOT NULL,
line_number INTEGER,
from_text TEXT NOT NULL,
to_text TEXT NOT NULL,
rule_type TEXT NOT NULL CHECK(rule_type IN ('context', 'dictionary', 'ai')),
rule_id INTEGER,
context_before TEXT,
context_after TEXT,
FOREIGN KEY (history_id) REFERENCES correction_history(id) ON DELETE CASCADE
);
CREATE TABLE learned_suggestions (
id INTEGER PRIMARY KEY AUTOINCREMENT,
from_text TEXT NOT NULL,
to_text TEXT NOT NULL,
domain TEXT NOT NULL DEFAULT 'general',
frequency INTEGER NOT NULL DEFAULT 1 CHECK(frequency > 0),
confidence REAL NOT NULL CHECK(confidence >= 0.0 AND confidence <= 1.0),
first_seen TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
last_seen TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
status TEXT NOT NULL DEFAULT 'pending' CHECK(status IN ('pending', 'approved', 'rejected')),
reviewed_at TIMESTAMP,
reviewed_by TEXT,
UNIQUE(from_text, to_text, domain)
);
CREATE TABLE suggestion_examples (
id INTEGER PRIMARY KEY AUTOINCREMENT,
suggestion_id INTEGER NOT NULL,
filename TEXT NOT NULL,
line_number INTEGER,
context TEXT NOT NULL,
occurred_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
FOREIGN KEY (suggestion_id) REFERENCES learned_suggestions(id) ON DELETE CASCADE
);
CREATE TABLE audit_log (
id INTEGER PRIMARY KEY AUTOINCREMENT,
timestamp TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
action TEXT NOT NULL,
entity_type TEXT NOT NULL,
entity_id INTEGER,
user TEXT,
details TEXT,
success BOOLEAN NOT NULL DEFAULT 1,
error_message TEXT
);
-- Create indexes
CREATE INDEX idx_context_rules_priority ON context_rules(priority DESC);
CREATE INDEX idx_context_rules_is_active ON context_rules(is_active);
CREATE INDEX idx_changes_history_id ON correction_changes(history_id);
CREATE INDEX idx_changes_rule_type ON correction_changes(rule_type);
CREATE INDEX idx_suggestions_status ON learned_suggestions(status);
CREATE INDEX idx_suggestions_domain ON learned_suggestions(domain);
CREATE INDEX idx_suggestions_confidence ON learned_suggestions(confidence DESC);
CREATE INDEX idx_suggestions_frequency ON learned_suggestions(frequency DESC);
CREATE INDEX idx_examples_suggestion_id ON suggestion_examples(suggestion_id);
CREATE INDEX idx_audit_timestamp ON audit_log(timestamp DESC);
CREATE INDEX idx_audit_action ON audit_log(action);
CREATE INDEX idx_audit_entity_type ON audit_log(entity_type);
CREATE INDEX idx_audit_success ON audit_log(success);
-- Create views
CREATE VIEW active_corrections AS
SELECT
id, from_text, to_text, domain, source, confidence,
usage_count, last_used, added_at
FROM corrections
WHERE is_active = 1
ORDER BY domain, from_text;
CREATE VIEW pending_suggestions AS
SELECT
s.id, s.from_text, s.to_text, s.domain, s.frequency,
s.confidence, s.first_seen, s.last_seen, COUNT(e.id) as example_count
FROM learned_suggestions s
LEFT JOIN suggestion_examples e ON s.id = e.suggestion_id
WHERE s.status = 'pending'
GROUP BY s.id
ORDER BY s.confidence DESC, s.frequency DESC;
CREATE VIEW correction_statistics AS
SELECT
domain,
COUNT(*) as total_corrections,
COUNT(CASE WHEN source = 'manual' THEN 1 END) as manual_count,
COUNT(CASE WHEN source = 'learned' THEN 1 END) as learned_count,
COUNT(CASE WHEN source = 'imported' THEN 1 END) as imported_count,
SUM(usage_count) as total_usage,
MAX(added_at) as last_updated
FROM corrections
WHERE is_active = 1
GROUP BY domain;
-- Update system config
UPDATE system_config SET value = '2.0' WHERE key = 'schema_version';
INSERT OR IGNORE INTO system_config (key, value, value_type, description) VALUES
('api_base_url', 'https://open.bigmodel.cn/api/anthropic', 'string', 'API endpoint URL'),
('default_domain', 'general', 'string', 'Default correction domain'),
('auto_learn_enabled', 'true', 'boolean', 'Enable automatic pattern learning'),
('backup_enabled', 'true', 'boolean', 'Create backups before operations'),
('learning_frequency_threshold', '3', 'int', 'Min frequency for learned suggestions'),
('learning_confidence_threshold', '0.8', 'float', 'Min confidence for learned suggestions'),
('history_retention_days', '90', 'int', 'Days to retain correction history'),
('max_correction_length', '1000', 'int', 'Maximum length for correction text');
""",
backward_sql="""
-- Drop views
DROP VIEW IF EXISTS correction_statistics;
DROP VIEW IF EXISTS pending_suggestions;
DROP VIEW IF EXISTS active_corrections;
-- Drop indexes
DROP INDEX IF EXISTS idx_audit_success;
DROP INDEX IF EXISTS idx_audit_entity_type;
DROP INDEX IF EXISTS idx_audit_action;
DROP INDEX IF EXISTS idx_audit_timestamp;
DROP INDEX IF EXISTS idx_examples_suggestion_id;
DROP INDEX IF EXISTS idx_suggestions_frequency;
DROP INDEX IF EXISTS idx_suggestions_confidence;
DROP INDEX IF EXISTS idx_suggestions_domain;
DROP INDEX IF EXISTS idx_suggestions_status;
DROP INDEX IF EXISTS idx_changes_rule_type;
DROP INDEX IF EXISTS idx_changes_history_id;
DROP INDEX IF EXISTS idx_context_rules_is_active;
DROP INDEX IF EXISTS idx_context_rules_priority;
-- Drop tables
DROP TABLE IF EXISTS audit_log;
DROP TABLE IF EXISTS suggestion_examples;
DROP TABLE IF EXISTS learned_suggestions;
DROP TABLE IF EXISTS correction_changes;
DROP TABLE IF EXISTS context_rules;
-- Reset schema version
UPDATE system_config SET value = '1.0' WHERE key = 'schema_version';
DELETE FROM system_config WHERE key IN (
'api_base_url', 'default_domain', 'auto_learn_enabled',
'backup_enabled', 'learning_frequency_threshold',
'learning_confidence_threshold', 'history_retention_days',
'max_correction_length'
);
""",
dependencies=["1.0"],
check_function=_validate_schema_2_0,
is_breaking=False
)
# Migration from v2.0 to v2.1 (add performance optimizations)
MIGRATION_V2_1 = Migration(
version="2.1",
name="Performance Optimizations",
description="Add indexes and constraints for better query performance",
forward_sql="""
-- Add composite indexes for common queries
CREATE INDEX idx_corrections_domain_active ON corrections(domain, is_active);
CREATE INDEX idx_corrections_domain_from_text ON corrections(domain, from_text);
CREATE INDEX idx_corrections_usage_count ON corrections(usage_count DESC);
CREATE INDEX idx_corrections_last_used ON corrections(last_used DESC);
-- Add indexes for learned_suggestions queries
CREATE INDEX idx_suggestions_domain_status ON learned_suggestions(domain, status);
CREATE INDEX idx_suggestions_domain_confidence ON learned_suggestions(domain, confidence DESC);
CREATE INDEX idx_suggestions_domain_frequency ON learned_suggestions(domain, frequency DESC);
-- Add indexes for audit_log queries
CREATE INDEX idx_audit_timestamp_entity ON audit_log(timestamp DESC, entity_type);
CREATE INDEX idx_audit_entity_type_id ON audit_log(entity_type, entity_id);
-- Add composite indexes for history queries
CREATE INDEX idx_history_domain_timestamp ON correction_history(domain, run_timestamp DESC);
CREATE INDEX idx_history_domain_success ON correction_history(domain, success, run_timestamp DESC);
-- Add index for frequently joined tables
CREATE INDEX idx_changes_history_rule_type ON correction_changes(history_id, rule_type);
-- Update system config
INSERT OR IGNORE INTO system_config (key, value, value_type, description) VALUES
('performance_optimization_applied', 'true', 'boolean', 'Performance optimization v2.1 applied');
""",
backward_sql="""
-- Drop indexes
DROP INDEX IF EXISTS idx_changes_history_rule_type;
DROP INDEX IF EXISTS idx_history_domain_success;
DROP INDEX IF EXISTS idx_history_domain_timestamp;
DROP INDEX IF EXISTS idx_audit_entity_type_id;
DROP INDEX IF EXISTS idx_audit_timestamp_entity;
DROP INDEX IF EXISTS idx_suggestions_domain_frequency;
DROP INDEX IF EXISTS idx_suggestions_domain_confidence;
DROP INDEX IF EXISTS idx_suggestions_domain_status;
DROP INDEX IF EXISTS idx_corrections_last_used;
DROP INDEX IF EXISTS idx_corrections_usage_count;
DROP INDEX IF EXISTS idx_corrections_domain_from_text;
DROP INDEX IF EXISTS idx_corrections_domain_active;
-- Remove system config
DELETE FROM system_config WHERE key = 'performance_optimization_applied';
""",
dependencies=["2.0"],
check_function=None,
is_breaking=False
)
# Migration from v2.1 to v2.2 (add data retention policies)
MIGRATION_V2_2 = Migration(
version="2.2",
name="Data Retention Policies",
description="Add retention policies and automatic cleanup mechanisms",
forward_sql="""
-- Add retention_policy table
CREATE TABLE retention_policies (
id INTEGER PRIMARY KEY AUTOINCREMENT,
entity_type TEXT NOT NULL CHECK(entity_type IN ('corrections', 'history', 'audits', 'suggestions')),
retention_days INTEGER NOT NULL CHECK(retention_days > 0),
is_active BOOLEAN NOT NULL DEFAULT 1,
created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
description TEXT
);
-- Insert default retention policies
INSERT INTO retention_policies (entity_type, retention_days, is_active, description) VALUES
('history', 90, 1, 'Keep correction history for 90 days'),
('audits', 180, 1, 'Keep audit logs for 180 days'),
('suggestions', 30, 1, 'Keep rejected suggestions for 30 days'),
('corrections', 365, 0, 'Keep all corrections by default');
-- Add cleanup_history table
CREATE TABLE cleanup_history (
id INTEGER PRIMARY KEY AUTOINCREMENT,
cleanup_date TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
entity_type TEXT NOT NULL,
records_deleted INTEGER NOT NULL CHECK(records_deleted >= 0),
execution_time_ms INTEGER NOT NULL CHECK(execution_time_ms >= 0),
success BOOLEAN NOT NULL DEFAULT 1,
error_message TEXT
);
-- Create indexes
CREATE INDEX idx_retention_entity_type ON retention_policies(entity_type);
CREATE INDEX idx_retention_is_active ON retention_policies(is_active);
CREATE INDEX idx_cleanup_date ON cleanup_history(cleanup_date DESC);
-- Update system config
INSERT OR IGNORE INTO system_config (key, value, value_type, description) VALUES
('retention_cleanup_enabled', 'true', 'boolean', 'Enable automatic retention cleanup'),
('retention_cleanup_hour', '2', 'int', 'Hour of day to run cleanup (0-23)'),
('last_retention_cleanup', '', 'string', 'Timestamp of last retention cleanup');
""",
backward_sql="""
-- Drop retention cleanup tables
DROP TABLE IF EXISTS cleanup_history;
DROP TABLE IF EXISTS retention_policies;
-- Remove system config
DELETE FROM system_config WHERE key IN (
'retention_cleanup_enabled',
'retention_cleanup_hour',
'last_retention_cleanup'
);
""",
dependencies=["2.1"],
check_function=None,
is_breaking=False
)
# Registry of all migrations
# Order matters - add new migrations at the end
ALL_MIGRATIONS = [
MIGRATION_V1_0,
MIGRATION_V2_0,
MIGRATION_V2_1,
MIGRATION_V2_2,
]
# Migration registry by version
MIGRATION_REGISTRY = {m.version: m for m in ALL_MIGRATIONS}
# Latest version
LATEST_VERSION = max(MIGRATION_REGISTRY.keys(), key=lambda v: tuple(map(int, v.split('.'))))
def get_migration(version: str) -> Migration:
"""Get migration by version"""
if version not in MIGRATION_REGISTRY:
raise ValueError(f"Migration version {version} not found")
return MIGRATION_REGISTRY[version]
def get_migrations_up_to(target_version: str) -> list[Migration]:
"""Get all migrations up to target version"""
versions = sorted(MIGRATION_REGISTRY.keys(), key=lambda v: tuple(map(int, v.split('.'))))
result = []
for version in versions:
if version <= target_version:
result.append(MIGRATION_REGISTRY[version])
return result
def get_migrations_from(from_version: str) -> list[Migration]:
"""Get all migrations from version onwards"""
versions = sorted(MIGRATION_REGISTRY.keys(), key=lambda v: tuple(map(int, v.split('.'))))
result = []
for version in versions:
if version > from_version:
result.append(MIGRATION_REGISTRY[version])
return result

478
transcript-fixer/scripts/utils/path_validator.py Normal file
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#!/usr/bin/env python3
"""
Path Validation and Security
CRITICAL FIX: Prevents path traversal and symlink attacks
ISSUE: Critical-5 in Engineering Excellence Plan
This module provides:
1. Path whitelist validation
2. Path traversal prevention (../)
3. Symlink attack detection
4. File extension validation
5. Directory containment checks
Author: Chief Engineer
Date: 2025-10-28
Priority: P0 - Critical
"""
from __future__ import annotations
import os
from pathlib import Path
from typing import Set, Optional, Final, List
import logging
logger = logging.getLogger(__name__)
# Allowed base directories (whitelist)
# Only files under these directories can be accessed
ALLOWED_BASE_DIRS: Final[Set[Path]] = {
Path.home() / ".transcript-fixer", # Config/data directory
Path.home() / "Downloads", # Common download location
Path.home() / "Documents", # Common documents location
Path.home() / "Desktop", # Desktop files
Path("/tmp"), # Temporary files
}
# Allowed file extensions for reading
ALLOWED_READ_EXTENSIONS: Final[Set[str]] = {
'.md', # Markdown
'.txt', # Text
'.html', # HTML output
'.json', # JSON config
'.sql', # SQL schema
}
# Allowed file extensions for writing
ALLOWED_WRITE_EXTENSIONS: Final[Set[str]] = {
'.md', # Markdown output
'.html', # HTML diff
'.db', # SQLite database
'.log', # Log files
}
# Dangerous patterns to reject
DANGEROUS_PATTERNS: Final[List[str]] = [
'..', # Parent directory traversal
'\x00', # Null byte
'\n', # Newline injection
'\r', # Carriage return injection
]
class PathValidationError(Exception):
"""Path validation failed"""
pass
class PathValidator:
"""
Validates file paths for security.
Prevents:
- Path traversal attacks (../)
- Symlink attacks
- Access outside whitelisted directories
- Dangerous file types
- Null byte injection
Usage:
validator = PathValidator()
safe_path = validator.validate_input_path("/path/to/file.md")
safe_output = validator.validate_output_path("/path/to/output.md")
"""
def __init__(
self,
allowed_base_dirs: Optional[Set[Path]] = None,
allowed_read_extensions: Optional[Set[str]] = None,
allowed_write_extensions: Optional[Set[str]] = None,
allow_symlinks: bool = False
):
"""
Initialize path validator.
Args:
allowed_base_dirs: Whitelist of allowed base directories
allowed_read_extensions: Allowed file extensions for reading
allowed_write_extensions: Allowed file extensions for writing
allow_symlinks: Allow symlinks (default: False for security)
"""
self.allowed_base_dirs = allowed_base_dirs or ALLOWED_BASE_DIRS
self.allowed_read_extensions = allowed_read_extensions or ALLOWED_READ_EXTENSIONS
self.allowed_write_extensions = allowed_write_extensions or ALLOWED_WRITE_EXTENSIONS
self.allow_symlinks = allow_symlinks
def _check_dangerous_patterns(self, path_str: str) -> None:
"""
Check for dangerous patterns in path string.
Args:
path_str: Path string to check
Raises:
PathValidationError: If dangerous pattern found
"""
for pattern in DANGEROUS_PATTERNS:
if pattern in path_str:
raise PathValidationError(
f"Dangerous pattern '{pattern}' detected in path: {path_str}"
)
def _is_under_allowed_directory(self, path: Path) -> bool:
"""
Check if path is under any allowed base directory.
Args:
path: Resolved path to check
Returns:
True if path is under allowed directory
"""
for allowed_dir in self.allowed_base_dirs:
try:
# Check if path is relative to allowed_dir
path.relative_to(allowed_dir)
return True
except ValueError:
# Not relative to this allowed_dir
continue
return False
def _check_symlink(self, path: Path) -> None:
"""
Check for symlink attacks.
Args:
path: Path to check
Raises:
PathValidationError: If symlink detected and not allowed
"""
if not self.allow_symlinks and path.is_symlink():
raise PathValidationError(
f"Symlink detected and not allowed: {path}"
)
# Check parent directories for symlinks (but stop at system dirs)
if not self.allow_symlinks:
current = path.parent
# Stop checking at common system directories (they may be symlinks on macOS)
system_dirs = {Path('/'), Path('/usr'), Path('/etc'), Path('/var')}
while current != current.parent: # Until root
if current in system_dirs:
break
if current.is_symlink():
raise PathValidationError(
f"Symlink in path hierarchy detected: {current}"
)
current = current.parent
def _validate_extension(
self,
path: Path,
allowed_extensions: Set[str],
operation: str
) -> None:
"""
Validate file extension.
Args:
path: Path to validate
allowed_extensions: Set of allowed extensions
operation: Operation name (for error message)
Raises:
PathValidationError: If extension not allowed
"""
extension = path.suffix.lower()
if extension not in allowed_extensions:
raise PathValidationError(
f"File extension '{extension}' not allowed for {operation}. "
f"Allowed: {sorted(allowed_extensions)}"
)
def validate_input_path(self, path_str: str) -> Path:
"""
Validate an input file path for reading.
Security checks:
1. No dangerous patterns (.., null bytes, etc.)
2. Path resolves to absolute path
3. No symlinks (unless explicitly allowed)
4. Under allowed base directory
5. Allowed file extension for reading
6. File exists
Args:
path_str: Path string to validate
Returns:
Validated, resolved Path object
Raises:
PathValidationError: If validation fails
Example:
>>> validator = PathValidator()
>>> safe_path = validator.validate_input_path("~/Documents/file.md")
>>> # Returns: Path('/home/username/Documents/file.md') or similar
"""
# Check dangerous patterns in raw string
self._check_dangerous_patterns(path_str)
# Convert to Path (but don't resolve yet - need to check symlinks first)
try:
path = Path(path_str).expanduser().absolute()
except Exception as e:
raise PathValidationError(f"Invalid path format: {path_str}") from e
# Check if file exists
if not path.exists():
raise PathValidationError(f"File does not exist: {path}")
# Check if it's a file (not directory)
if not path.is_file():
raise PathValidationError(f"Path is not a file: {path}")
# CRITICAL: Check for symlinks BEFORE resolving
self._check_symlink(path)
# Now resolve to get canonical path
path = path.resolve()
# Check if under allowed directory
if not self._is_under_allowed_directory(path):
raise PathValidationError(
f"Path not under allowed directories: {path}\n"
f"Allowed directories: {[str(d) for d in self.allowed_base_dirs]}"
)
# Check file extension
self._validate_extension(path, self.allowed_read_extensions, "reading")
logger.info(f"Input path validated: {path}")
return path
def validate_output_path(self, path_str: str, create_parent: bool = True) -> Path:
"""
Validate an output file path for writing.
Security checks:
1. No dangerous patterns
2. Path resolves to absolute path
3. No symlinks in path hierarchy
4. Under allowed base directory
5. Allowed file extension for writing
6. Parent directory exists or can be created
Args:
path_str: Path string to validate
create_parent: Create parent directory if it doesn't exist
Returns:
Validated, resolved Path object
Raises:
PathValidationError: If validation fails
Example:
>>> validator = PathValidator()
>>> safe_path = validator.validate_output_path("~/Documents/output.md")
>>> # Returns: Path('/home/username/Documents/output.md') or similar
"""
# Check dangerous patterns
self._check_dangerous_patterns(path_str)
# Convert to Path and resolve
try:
path = Path(path_str).expanduser().resolve()
except Exception as e:
raise PathValidationError(f"Invalid path format: {path_str}") from e
# Check parent directory exists
parent = path.parent
if not parent.exists():
if create_parent:
# Validate parent directory first
if not self._is_under_allowed_directory(parent):
raise PathValidationError(
f"Parent directory not under allowed directories: {parent}"
)
try:
parent.mkdir(parents=True, exist_ok=True)
logger.info(f"Created parent directory: {parent}")
except Exception as e:
raise PathValidationError(
f"Failed to create parent directory: {parent}"
) from e
else:
raise PathValidationError(f"Parent directory does not exist: {parent}")
# Check for symlinks in path hierarchy (but file itself doesn't exist yet)
if not self.allow_symlinks:
current = parent
while current != current.parent:
if current.is_symlink():
raise PathValidationError(
f"Symlink in path hierarchy: {current}"
)
current = current.parent
# Check if under allowed directory
if not self._is_under_allowed_directory(path):
raise PathValidationError(
f"Path not under allowed directories: {path}\n"
f"Allowed directories: {[str(d) for d in self.allowed_base_dirs]}"
)
# Check file extension
self._validate_extension(path, self.allowed_write_extensions, "writing")
logger.info(f"Output path validated: {path}")
return path
def add_allowed_directory(self, directory: str | Path) -> None:
"""
Add a directory to the whitelist.
Args:
directory: Directory path to add
Example:
>>> validator.add_allowed_directory("/home/username/Projects")
"""
dir_path = Path(directory).expanduser().resolve()
self.allowed_base_dirs.add(dir_path)
logger.info(f"Added allowed directory: {dir_path}")
def is_path_safe(self, path_str: str, for_writing: bool = False) -> bool:
"""
Check if a path is safe without raising exceptions.
Args:
path_str: Path to check
for_writing: Check for writing (vs reading)
Returns:
True if path is safe
Example:
>>> if validator.is_path_safe("~/Documents/file.md"):
... process_file()
"""
try:
if for_writing:
self.validate_output_path(path_str, create_parent=False)
else:
self.validate_input_path(path_str)
return True
except PathValidationError:
return False
# Global validator instance
_global_validator: Optional[PathValidator] = None
def get_validator() -> PathValidator:
"""
Get global validator instance.
Returns:
Global PathValidator instance
Example:
>>> validator = get_validator()
>>> safe_path = validator.validate_input_path("file.md")
"""
global _global_validator
if _global_validator is None:
_global_validator = PathValidator()
return _global_validator
# Convenience functions
def validate_input_path(path_str: str) -> Path:
"""Validate input path using global validator"""
return get_validator().validate_input_path(path_str)
def validate_output_path(path_str: str, create_parent: bool = True) -> Path:
"""Validate output path using global validator"""
return get_validator().validate_output_path(path_str, create_parent)
def add_allowed_directory(directory: str | Path) -> None:
"""Add allowed directory to global validator"""
get_validator().add_allowed_directory(directory)
# Example usage and testing
if __name__ == "__main__":
import logging
logging.basicConfig(level=logging.INFO)
print("=== Testing PathValidator ===\n")
validator = PathValidator()
# Test 1: Valid input path (create a test file first)
print("Test 1: Valid input path")
test_file = Path.home() / "Documents" / "test.md"
test_file.parent.mkdir(parents=True, exist_ok=True)
test_file.write_text("test")
try:
result = validator.validate_input_path(str(test_file))
print(f"✓ Valid: {result}\n")
except PathValidationError as e:
print(f"✗ Failed: {e}\n")
# Test 2: Path traversal attack
print("Test 2: Path traversal attack")
try:
result = validator.validate_input_path("../../etc/passwd")
print(f"✗ Should have failed: {result}\n")
except PathValidationError as e:
print(f"✓ Correctly rejected: {e}\n")
# Test 3: Invalid extension
print("Test 3: Invalid extension")
dangerous_file = Path.home() / "Documents" / "script.sh"
dangerous_file.write_text("#!/bin/bash")
try:
result = validator.validate_input_path(str(dangerous_file))
print(f"✗ Should have failed: {result}\n")
except PathValidationError as e:
print(f"✓ Correctly rejected: {e}\n")
# Test 4: Valid output path
print("Test 4: Valid output path")
try:
result = validator.validate_output_path(str(Path.home() / "Documents" / "output.html"))
print(f"✓ Valid: {result}\n")
except PathValidationError as e:
print(f"✗ Failed: {e}\n")
# Test 5: Null byte injection
print("Test 5: Null byte injection")
try:
result = validator.validate_input_path("file.md\x00.txt")
print(f"✗ Should have failed: {result}\n")
except PathValidationError as e:
print(f"✓ Correctly rejected: {e}\n")
# Cleanup
test_file.unlink(missing_ok=True)
dangerous_file.unlink(missing_ok=True)
print("=== All tests completed ===")

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#!/usr/bin/env python3
"""
Rate Limiting Module
CRITICAL FIX (P1-8): Production-grade rate limiting for API protection
Features:
- Token Bucket algorithm (smooth rate limiting)
- Sliding Window algorithm (precise rate limiting)
- Fixed Window algorithm (simple, memory-efficient)
- Thread-safe operations
- Burst support
- Multiple rate limit tiers
- Metrics integration
Use cases:
- API rate limiting (e.g., 100 requests/minute)
- Resource protection (e.g., max 5 concurrent DB connections)
- DoS prevention
- Cost control (e.g., limit API calls)
"""
from __future__ import annotations
import logging
import threading
import time
from collections import deque
from dataclasses import dataclass
from enum import Enum
from typing import Optional, Deque, Final
from contextlib import contextmanager
logger = logging.getLogger(__name__)
class RateLimitStrategy(Enum):
"""Rate limiting strategy"""
TOKEN_BUCKET = "token_bucket"
SLIDING_WINDOW = "sliding_window"
FIXED_WINDOW = "fixed_window"
@dataclass
class RateLimitConfig:
"""Rate limit configuration"""
max_requests: int # Maximum requests allowed
window_seconds: float # Time window in seconds
strategy: RateLimitStrategy = RateLimitStrategy.TOKEN_BUCKET
burst_size: Optional[int] = None # Burst allowance (for token bucket)
def __post_init__(self):
"""Validate configuration"""
if self.max_requests <= 0:
raise ValueError("max_requests must be positive")
if self.window_seconds <= 0:
raise ValueError("window_seconds must be positive")
# Default burst size = max_requests (allow full burst)
if self.burst_size is None:
self.burst_size = self.max_requests
class RateLimitExceeded(Exception):
"""Raised when rate limit is exceeded"""
def __init__(self, message: str, retry_after: float):
super().__init__(message)
self.retry_after = retry_after # Seconds to wait before retry
class TokenBucketLimiter:
"""
Token Bucket algorithm implementation.
Properties:
- Smooth rate limiting
- Allows bursts up to bucket capacity
- Memory efficient (O(1))
- Fast (O(1) per request)
Use for: API rate limiting, general request throttling
"""
def __init__(self, config: RateLimitConfig):
self.config = config
self.capacity = config.burst_size or config.max_requests
self.refill_rate = config.max_requests / config.window_seconds
self._tokens = float(self.capacity)
self._last_refill = time.time()
self._lock = threading.Lock()
logger.debug(
f"TokenBucket initialized: capacity={self.capacity}, "
f"refill_rate={self.refill_rate:.2f}/s"
)
def _refill(self) -> None:
"""Refill tokens based on elapsed time"""
now = time.time()
elapsed = now - self._last_refill
# Add tokens based on time elapsed
tokens_to_add = elapsed * self.refill_rate
self._tokens = min(self.capacity, self._tokens + tokens_to_add)
self._last_refill = now
def acquire(self, tokens: int = 1, blocking: bool = True, timeout: Optional[float] = None) -> bool:
"""
Acquire tokens from bucket.
Args:
tokens: Number of tokens to acquire (default: 1)
blocking: If True, wait for tokens. If False, return immediately
timeout: Maximum time to wait (seconds). None = wait forever
Returns:
True if tokens acquired, False if rate limit exceeded (non-blocking only)
Raises:
RateLimitExceeded: If rate limit exceeded in blocking mode
"""
if tokens <= 0:
raise ValueError("tokens must be positive")
start_time = time.time()
while True:
with self._lock:
self._refill()
if self._tokens >= tokens:
# Sufficient tokens available
self._tokens -= tokens
return True
if not blocking:
# Non-blocking mode - return immediately
return False
# Calculate retry_after
tokens_needed = tokens - self._tokens
retry_after = tokens_needed / self.refill_rate
# Check timeout
if timeout is not None:
elapsed = time.time() - start_time
if elapsed >= timeout:
raise RateLimitExceeded(
f"Rate limit exceeded: need {tokens} tokens, have {self._tokens:.1f}",
retry_after=retry_after
)
# Wait before retry (but not longer than needed or timeout)
wait_time = min(retry_after, 0.1) # Check at least every 100ms
if timeout is not None:
remaining_timeout = timeout - (time.time() - start_time)
wait_time = min(wait_time, remaining_timeout)
if wait_time > 0:
time.sleep(wait_time)
def get_available_tokens(self) -> float:
"""Get current number of available tokens"""
with self._lock:
self._refill()
return self._tokens
def reset(self) -> None:
"""Reset to full capacity"""
with self._lock:
self._tokens = float(self.capacity)
self._last_refill = time.time()
class SlidingWindowLimiter:
"""
Sliding Window algorithm implementation.
Properties:
- Precise rate limiting
- No "boundary problem" (unlike fixed window)
- Memory: O(max_requests)
- Fast: O(n) per request, where n = requests in window
Use for: Strict rate limits, billing, quota enforcement
"""
def __init__(self, config: RateLimitConfig):
self.config = config
self.max_requests = config.max_requests
self.window_seconds = config.window_seconds
self._timestamps: Deque[float] = deque()
self._lock = threading.Lock()
logger.debug(
f"SlidingWindow initialized: max_requests={self.max_requests}, "
f"window={self.window_seconds}s"
)
def _cleanup_old_timestamps(self, now: float) -> None:
"""Remove timestamps outside the window"""
cutoff = now - self.window_seconds
while self._timestamps and self._timestamps[0] < cutoff:
self._timestamps.popleft()
def acquire(self, tokens: int = 1, blocking: bool = True, timeout: Optional[float] = None) -> bool:
"""
Acquire tokens (check if request allowed).
Args:
tokens: Number of requests to make (usually 1)
blocking: If True, wait for capacity. If False, return immediately
timeout: Maximum time to wait (seconds)
Returns:
True if allowed, False if rate limit exceeded (non-blocking only)
Raises:
RateLimitExceeded: If rate limit exceeded in blocking mode
"""
if tokens <= 0:
raise ValueError("tokens must be positive")
start_time = time.time()
while True:
now = time.time()
with self._lock:
self._cleanup_old_timestamps(now)
current_count = len(self._timestamps)
if current_count + tokens <= self.max_requests:
# Allowed - record timestamps
for _ in range(tokens):
self._timestamps.append(now)
return True
if not blocking:
# Non-blocking mode
return False
# Calculate retry_after (when oldest request falls out of window)
if self._timestamps:
oldest = self._timestamps[0]
retry_after = oldest + self.window_seconds - now
else:
retry_after = 0.1
# Check timeout
if timeout is not None:
elapsed = time.time() - start_time
if elapsed >= timeout:
raise RateLimitExceeded(
f"Rate limit exceeded: {current_count}/{self.max_requests} "
f"requests in {self.window_seconds}s window",
retry_after=max(retry_after, 0.1)
)
# Wait before retry
wait_time = min(retry_after, 0.1)
if timeout is not None:
remaining_timeout = timeout - (time.time() - start_time)
wait_time = min(wait_time, remaining_timeout)
if wait_time > 0:
time.sleep(wait_time)
def get_current_count(self) -> int:
"""Get current request count in window"""
with self._lock:
self._cleanup_old_timestamps(time.time())
return len(self._timestamps)
def reset(self) -> None:
"""Reset (clear all timestamps)"""
with self._lock:
self._timestamps.clear()
class RateLimiter:
"""
Main rate limiter with configurable strategy.
CRITICAL FIX (P1-8): Thread-safe rate limiting for production use
"""
def __init__(self, config: RateLimitConfig):
self.config = config
# Select implementation based on strategy
if config.strategy == RateLimitStrategy.TOKEN_BUCKET:
self._impl = TokenBucketLimiter(config)
elif config.strategy == RateLimitStrategy.SLIDING_WINDOW:
self._impl = SlidingWindowLimiter(config)
else:
raise ValueError(f"Unsupported strategy: {config.strategy}")
logger.info(
f"RateLimiter created: {config.strategy.value}, "
f"{config.max_requests}/{config.window_seconds}s"
)
def acquire(self, tokens: int = 1, blocking: bool = True, timeout: Optional[float] = None) -> bool:
"""
Acquire permission to proceed.
Args:
tokens: Number of requests (default: 1)
blocking: Wait for availability (default: True)
timeout: Maximum wait time in seconds (default: None = forever)
Returns:
True if allowed, False if rate limit exceeded (non-blocking only)
Raises:
RateLimitExceeded: If rate limit exceeded in blocking mode
"""
return self._impl.acquire(tokens=tokens, blocking=blocking, timeout=timeout)
@contextmanager
def limit(self, tokens: int = 1):
"""
Context manager for rate-limited operations.
Usage:
with rate_limiter.limit():
# Make API call
response = client.post(...)
Raises:
RateLimitExceeded: If rate limit exceeded
"""
self.acquire(tokens=tokens, blocking=True)
try:
yield
finally:
pass # Tokens already consumed
def check_available(self) -> bool:
"""Check if capacity available (non-blocking)"""
return self.acquire(tokens=1, blocking=False)
def reset(self) -> None:
"""Reset rate limiter state"""
self._impl.reset()
def get_info(self) -> dict:
"""Get current rate limiter information"""
info = {
'strategy': self.config.strategy.value,
'max_requests': self.config.max_requests,
'window_seconds': self.config.window_seconds,
}
if isinstance(self._impl, TokenBucketLimiter):
info['available_tokens'] = self._impl.get_available_tokens()
info['capacity'] = self._impl.capacity
elif isinstance(self._impl, SlidingWindowLimiter):
info['current_count'] = self._impl.get_current_count()
return info
# Predefined rate limit configurations
class RateLimitPresets:
"""Common rate limit configurations"""
# API rate limits
API_CONSERVATIVE = RateLimitConfig(
max_requests=10,
window_seconds=60.0,
strategy=RateLimitStrategy.TOKEN_BUCKET
)
API_MODERATE = RateLimitConfig(
max_requests=60,
window_seconds=60.0,
strategy=RateLimitStrategy.TOKEN_BUCKET
)
API_AGGRESSIVE = RateLimitConfig(
max_requests=100,
window_seconds=60.0,
strategy=RateLimitStrategy.TOKEN_BUCKET
)
# Burst limits
BURST_ALLOWED = RateLimitConfig(
max_requests=50,
window_seconds=60.0,
burst_size=100, # Allow double burst
strategy=RateLimitStrategy.TOKEN_BUCKET
)
# Strict limits (sliding window)
STRICT_LIMIT = RateLimitConfig(
max_requests=100,
window_seconds=60.0,
strategy=RateLimitStrategy.SLIDING_WINDOW
)
# Global rate limiters
_global_limiters: dict[str, RateLimiter] = {}
_limiters_lock = threading.Lock()
def get_rate_limiter(name: str, config: Optional[RateLimitConfig] = None) -> RateLimiter:
"""
Get or create a named rate limiter.
Args:
name: Unique name for this rate limiter
config: Rate limit configuration (required if creating new)
Returns:
RateLimiter instance
"""
global _global_limiters
with _limiters_lock:
if name not in _global_limiters:
if config is None:
raise ValueError(f"Rate limiter '{name}' not found and no config provided")
_global_limiters[name] = RateLimiter(config)
logger.info(f"Created global rate limiter: {name}")
return _global_limiters[name]
def reset_all_limiters() -> None:
"""Reset all global rate limiters (mainly for testing)"""
with _limiters_lock:
for limiter in _global_limiters.values():
limiter.reset()
logger.info("Reset all rate limiters")

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#!/usr/bin/env python3
"""
Retry Logic with Exponential Backoff
CRITICAL FIX: Implements retry for transient failures
ISSUE: Critical-4 in Engineering Excellence Plan
This module provides:
1. Exponential backoff retry logic
2. Error categorization (transient vs permanent)
3. Configurable retry strategies
4. Async retry support
Author: Chief Engineer
Date: 2025-10-28
Priority: P0 - Critical
"""
from __future__ import annotations
import asyncio
import logging
import time
from typing import TypeVar, Callable, Any, Optional, Set
from functools import wraps
from dataclasses import dataclass
import httpx
logger = logging.getLogger(__name__)
T = TypeVar('T')
@dataclass
class RetryConfig:
"""
Configuration for retry behavior.
Attributes:
max_attempts: Maximum number of retry attempts (default: 3)
base_delay: Initial delay between retries in seconds (default: 1.0)
max_delay: Maximum delay between retries in seconds (default: 60.0)
exponential_base: Multiplier for exponential backoff (default: 2.0)
jitter: Add randomness to avoid thundering herd (default: True)
"""
max_attempts: int = 3
base_delay: float = 1.0
max_delay: float = 60.0
exponential_base: float = 2.0
jitter: bool = True
# Transient errors that should be retried
TRANSIENT_EXCEPTIONS: Set[type] = {
# Network errors
httpx.ConnectTimeout,
httpx.ReadTimeout,
httpx.WriteTimeout,
httpx.PoolTimeout,
httpx.ConnectError,
httpx.ReadError,
httpx.WriteError,
# HTTP status codes (will check separately)
# 408 Request Timeout
# 429 Too Many Requests
# 500 Internal Server Error
# 502 Bad Gateway
# 503 Service Unavailable
# 504 Gateway Timeout
}
# Status codes that indicate transient failures
TRANSIENT_STATUS_CODES: Set[int] = {
408, # Request Timeout
429, # Too Many Requests
500, # Internal Server Error
502, # Bad Gateway
503, # Service Unavailable
504, # Gateway Timeout
}
# Permanent errors that should NOT be retried
PERMANENT_EXCEPTIONS: Set[type] = {
# Authentication/Authorization
httpx.HTTPStatusError, # Will check status code
# Validation errors
ValueError,
KeyError,
TypeError,
}
def is_transient_error(exception: Exception) -> bool:
"""
Determine if an exception represents a transient failure.
Transient errors:
- Network timeouts
- Connection errors
- Server overload (429, 503)
- Temporary server errors (500, 502, 504)
Permanent errors:
- Authentication failures (401, 403)
- Not found (404)
- Validation errors (400, 422)
Args:
exception: Exception to categorize
Returns:
True if error is transient and should be retried
"""
# Check exception type
if type(exception) in TRANSIENT_EXCEPTIONS:
return True
# Check HTTP status codes
if isinstance(exception, httpx.HTTPStatusError):
return exception.response.status_code in TRANSIENT_STATUS_CODES
# Default: treat as permanent
return False
def calculate_delay(
attempt: int,
config: RetryConfig
) -> float:
"""
Calculate delay for exponential backoff.
Formula: min(base_delay * (exponential_base ** attempt), max_delay)
With optional jitter to avoid thundering herd.
Args:
attempt: Current attempt number (0-indexed)
config: Retry configuration
Returns:
Delay in seconds
Example:
>>> calculate_delay(0, RetryConfig(base_delay=1.0, exponential_base=2.0))
1.0
>>> calculate_delay(1, RetryConfig(base_delay=1.0, exponential_base=2.0))
2.0
>>> calculate_delay(2, RetryConfig(base_delay=1.0, exponential_base=2.0))
4.0
"""
delay = config.base_delay * (config.exponential_base ** attempt)
delay = min(delay, config.max_delay)
if config.jitter:
import random
# Add ±25% jitter
jitter_amount = delay * 0.25
delay = delay + random.uniform(-jitter_amount, jitter_amount)
return max(0, delay) # Ensure non-negative
def retry_sync(
config: Optional[RetryConfig] = None,
on_retry: Optional[Callable[[Exception, int], None]] = None
):
"""
Decorator for synchronous retry logic with exponential backoff.
Args:
config: Retry configuration (uses defaults if None)
on_retry: Optional callback called on each retry attempt
Example:
>>> @retry_sync(RetryConfig(max_attempts=3))
... def fetch_data():
... return call_api()
Raises:
Original exception if all retries exhausted
"""
if config is None:
config = RetryConfig()
def decorator(func: Callable[..., T]) -> Callable[..., T]:
@wraps(func)
def wrapper(*args: Any, **kwargs: Any) -> T:
last_exception: Optional[Exception] = None
for attempt in range(config.max_attempts):
try:
return func(*args, **kwargs)
except Exception as e:
last_exception = e
# Check if error is transient
if not is_transient_error(e):
logger.error(
f"{func.__name__} failed with permanent error: {e}"
)
raise
# Last attempt?
if attempt >= config.max_attempts - 1:
logger.error(
f"{func.__name__} failed after {config.max_attempts} attempts: {e}"
)
raise
# Calculate delay
delay = calculate_delay(attempt, config)
logger.warning(
f"{func.__name__} attempt {attempt + 1}/{config.max_attempts} "
f"failed with transient error: {e}. "
f"Retrying in {delay:.1f}s..."
)
# Call retry callback if provided
if on_retry:
on_retry(e, attempt)
# Wait before retry
time.sleep(delay)
# Should never reach here, but satisfy type checker
if last_exception:
raise last_exception
raise RuntimeError("Retry logic error")
return wrapper
return decorator
def retry_async(
config: Optional[RetryConfig] = None,
on_retry: Optional[Callable[[Exception, int], None]] = None
):
"""
Decorator for asynchronous retry logic with exponential backoff.
Args:
config: Retry configuration (uses defaults if None)
on_retry: Optional callback called on each retry attempt
Example:
>>> @retry_async(RetryConfig(max_attempts=3))
... async def fetch_data():
... return await call_api_async()
Raises:
Original exception if all retries exhausted
"""
if config is None:
config = RetryConfig()
def decorator(func: Callable[..., Any]) -> Callable[..., Any]:
@wraps(func)
async def wrapper(*args: Any, **kwargs: Any) -> Any:
last_exception: Optional[Exception] = None
for attempt in range(config.max_attempts):
try:
return await func(*args, **kwargs)
except Exception as e:
last_exception = e
# Check if error is transient
if not is_transient_error(e):
logger.error(
f"{func.__name__} failed with permanent error: {e}"
)
raise
# Last attempt?
if attempt >= config.max_attempts - 1:
logger.error(
f"{func.__name__} failed after {config.max_attempts} attempts: {e}"
)
raise
# Calculate delay
delay = calculate_delay(attempt, config)
logger.warning(
f"{func.__name__} attempt {attempt + 1}/{config.max_attempts} "
f"failed with transient error: {e}. "
f"Retrying in {delay:.1f}s..."
)
# Call retry callback if provided
if on_retry:
on_retry(e, attempt)
# Wait before retry (async)
await asyncio.sleep(delay)
# Should never reach here, but satisfy type checker
if last_exception:
raise last_exception
raise RuntimeError("Retry logic error")
return wrapper
return decorator
# Example usage and testing
if __name__ == "__main__":
import logging
logging.basicConfig(level=logging.INFO)
# Test synchronous retry
print("=== Testing Synchronous Retry ===")
attempt_count = 0
@retry_sync(RetryConfig(max_attempts=3, base_delay=0.1))
def flaky_function():
global attempt_count
attempt_count += 1
print(f"Attempt {attempt_count}")
if attempt_count < 3:
raise httpx.ConnectTimeout("Connection timeout")
return "Success!"
try:
result = flaky_function()
print(f"Result: {result}")
except Exception as e:
print(f"Failed: {e}")
# Test async retry
print("\n=== Testing Asynchronous Retry ===")
async def test_async():
attempt_count = 0
@retry_async(RetryConfig(max_attempts=3, base_delay=0.1))
async def async_flaky_function():
nonlocal attempt_count
attempt_count += 1
print(f"Async attempt {attempt_count}")
if attempt_count < 2:
raise httpx.ReadTimeout("Read timeout")
return "Async success!"
try:
result = await async_flaky_function()
print(f"Result: {result}")
except Exception as e:
print(f"Failed: {e}")
asyncio.run(test_async())
# Test permanent error (should not retry)
print("\n=== Testing Permanent Error (No Retry) ===")
attempt_count = 0
@retry_sync(RetryConfig(max_attempts=3, base_delay=0.1))
def permanent_error_function():
global attempt_count
attempt_count += 1
print(f"Attempt {attempt_count}")
raise ValueError("Invalid input") # Permanent error
try:
result = permanent_error_function()
except ValueError as e:
print(f"Correctly failed immediately: {e}")
print(f"Attempts made: {attempt_count} (should be 1)")

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#!/usr/bin/env python3
"""
Security Utilities
CRITICAL FIX: Secure handling of sensitive data
ISSUE: Critical-2 in Engineering Excellence Plan
This module provides:
1. Secret masking for logs
2. Secure memory handling
3. API key validation
4. Input sanitization
Author: Chief Engineer
Date: 2025-10-28
Priority: P0 - Critical
"""
from __future__ import annotations
import re
import ctypes
import sys
from typing import Optional, Final
# Constants
MIN_API_KEY_LENGTH: Final[int] = 20 # Minimum reasonable API key length
MASK_PREFIX_LENGTH: Final[int] = 4 # Show first 4 chars
MASK_SUFFIX_LENGTH: Final[int] = 4 # Show last 4 chars
def mask_secret(secret: str, visible_chars: int = 4) -> str:
"""
Safely mask secrets for logging.
CRITICAL: Never log full secrets. Always use this function.
Args:
secret: The secret to mask (API key, token, password)
visible_chars: Number of chars to show at start/end (default: 4)
Returns:
Masked string like "7fb3...DPRR"
Examples:
>>> mask_secret("7fb3ab7b186242288fe93a27227b7149.bJCOEAsUfejvWDPR")
'7fb3...DPRR'
>>> mask_secret("short")
'***'
>>> mask_secret("")
'***'
"""
if not secret:
return "***"
secret_len = len(secret)
# Very short secrets: completely hide
if secret_len < 2 * visible_chars:
return "***"
# Show prefix and suffix with ... in middle
prefix = secret[:visible_chars]
suffix = secret[-visible_chars:]
return f"{prefix}...{suffix}"
def mask_secret_in_text(text: str, secret: str) -> str:
"""
Replace all occurrences of secret in text with masked version.
Useful for sanitizing error messages, logs, etc.
Args:
text: Text that might contain secrets
secret: The secret to mask
Returns:
Text with secret masked
Examples:
>>> text = "API key example-fake-key-1234567890abcdef.test failed"
>>> secret = "example-fake-key-1234567890abcdef.test"
>>> mask_secret_in_text(text, secret)
'API key exam...test failed'
"""
if not secret or not text:
return text
masked = mask_secret(secret)
return text.replace(secret, masked)
def validate_api_key(key: str) -> bool:
"""
Validate API key format (basic checks).
This doesn't verify if the key is valid with the API,
just checks if it looks reasonable.
Args:
key: API key to validate
Returns:
True if key format is valid
Checks:
- Not empty
- Minimum length (20 chars)
- No suspicious patterns (only whitespace, etc.)
"""
if not key:
return False
# Remove whitespace
key_stripped = key.strip()
# Check minimum length
if len(key_stripped) < MIN_API_KEY_LENGTH:
return False
# Check it's not all spaces or special chars
if key_stripped.isspace():
return False
# Check it contains some alphanumeric characters
if not any(c.isalnum() for c in key_stripped):
return False
return True
def sanitize_for_logging(text: str, max_length: int = 200) -> str:
"""
Sanitize text for safe logging.
Prevents:
- Log injection attacks
- Excessively long log entries
- Binary data in logs
- Control characters
Args:
text: Text to sanitize
max_length: Maximum length (default: 200)
Returns:
Safe text for logging
"""
if not text:
return ""
# Truncate if too long
if len(text) > max_length:
text = text[:max_length] + "... (truncated)"
# Remove control characters (except newline, tab)
text = ''.join(char for char in text if ord(char) >= 32 or char in '\n\t')
# Escape newlines to prevent log injection
text = text.replace('\n', '\\n').replace('\r', '\\r')
return text
def detect_and_mask_api_keys(text: str) -> str:
"""
Automatically detect and mask potential API keys in text.
Patterns detected:
- Typical API key formats (alphanumeric + special chars, 20+ chars)
- Bearer tokens
- Authorization headers
Args:
text: Text that might contain API keys
Returns:
Text with API keys masked
Warning:
This is heuristic-based and may have false positives/negatives.
Best practice: Don't let keys get into logs in the first place.
"""
# Pattern for typical API keys
# Looks for: 20+ chars of alphanumeric, dots, dashes, underscores
api_key_pattern = r'\b[A-Za-z0-9._-]{20,}\b'
def replace_with_mask(match):
potential_key = match.group(0)
# Only mask if it looks like a real key
if validate_api_key(potential_key):
return mask_secret(potential_key)
return potential_key
# Replace potential keys
text = re.sub(api_key_pattern, replace_with_mask, text)
# Also mask Authorization headers
text = re.sub(
r'Authorization:\s*Bearer\s+([A-Za-z0-9._-]+)',
lambda m: f'Authorization: Bearer {mask_secret(m.group(1))}',
text,
flags=re.IGNORECASE
)
return text
def zero_memory(data: str) -> None:
"""
Attempt to overwrite sensitive data in memory.
NOTE: This is best-effort in Python due to string immutability.
Python strings cannot be truly zeroed. This is a defense-in-depth
measure that may help in some scenarios but is not guaranteed.
For truly secure secret handling, consider:
- Using memoryview/bytearray for mutable secrets
- Storing secrets in kernel memory (OS features)
- Hardware security modules (HSM)
Args:
data: String to attempt to zero
Limitations:
- Python strings are immutable
- GC may have already copied the data
- This is NOT cryptographically secure erasure
"""
try:
# This is best-effort only
# Python strings are immutable, so we can't truly zero them
# But we can try to overwrite the memory location
location = id(data) + sys.getsizeof('')
size = len(data.encode('utf-8'))
ctypes.memset(location, 0, size)
except Exception:
# Silently fail - this is best-effort
pass
class SecretStr:
"""
Wrapper for secrets that prevents accidental logging.
Usage:
api_key = SecretStr("7fb3ab7b186242288fe93a27227b7149.bJCOEAsUfejvWDPR")
print(api_key) # Prints: SecretStr(7fb3...DPRR)
print(api_key.get()) # Get actual value when needed
This prevents accidentally logging secrets:
logger.info(f"Using key: {api_key}") # Safe! Automatically masked
"""
def __init__(self, secret: str):
"""
Initialize with secret value.
Args:
secret: The secret to wrap
"""
self._secret = secret
def get(self) -> str:
"""
Get the actual secret value.
Use this only when you need the real value.
Never log the result!
Returns:
The actual secret
"""
return self._secret
def __str__(self) -> str:
"""String representation (masked)"""
return f"SecretStr({mask_secret(self._secret)})"
def __repr__(self) -> str:
"""Repr (masked)"""
return f"SecretStr({mask_secret(self._secret)})"
def __del__(self):
"""Attempt to zero memory on deletion"""
zero_memory(self._secret)
# Example usage and testing
if __name__ == "__main__":
# Test masking (using fake example key for testing)
api_key = "example-fake-key-for-testing-only-not-real"
print(f"Original: {api_key}")
print(f"Masked: {mask_secret(api_key)}")
# Test in text
text = f"Connection failed with key {api_key}"
print(f"Sanitized: {mask_secret_in_text(text, api_key)}")
# Test SecretStr
secret = SecretStr(api_key)
print(f"SecretStr: {secret}") # Automatically masked
# Test validation
print(f"Valid: {validate_api_key(api_key)}")
print(f"Invalid: {validate_api_key('short')}")
# Test auto-detection
log_text = f"ERROR: API request failed with key {api_key}"
print(f"Auto-masked: {detect_and_mask_api_keys(log_text)}")

20
transcript-fixer/scripts/utils/validation.py
View File

@@ -18,16 +18,6 @@ import os
import sys
from pathlib import Path
# Handle imports for both standalone and package usage
try:
from core import CorrectionRepository, CorrectionService
except ImportError:
# Fallback for when run from scripts directory directly
import sys
from pathlib import Path
sys.path.insert(0, str(Path(__file__).parent.parent))
from core import CorrectionRepository, CorrectionService
def validate_configuration() -> tuple[list[str], list[str]]:
"""
@@ -56,6 +46,10 @@ def validate_configuration() -> tuple[list[str], list[str]]:
# Validate SQLite database
if db_path.exists():
try:
# CRITICAL FIX: Lazy import to prevent circular dependency
# circular import: core → utils.domain_validator → utils → utils.validation → core
from core import CorrectionRepository, CorrectionService
repository = CorrectionRepository(db_path)
service = CorrectionService(repository)
@@ -64,9 +58,9 @@ def validate_configuration() -> tuple[list[str], list[str]]:
print(f"✅ Database valid: {stats['total_corrections']} corrections")
# Check tables exist
conn = repository._get_connection()
cursor = conn.execute("SELECT name FROM sqlite_master WHERE type='table'")
tables = [row[0] for row in cursor.fetchall()]
with repository._pool.get_connection() as conn:
cursor = conn.execute("SELECT name FROM sqlite_master WHERE type='table'")
tables = [row[0] for row in cursor.fetchall()]
expected_tables = [
'corrections', 'context_rules', 'correction_history',