Bertrand Benjamin
06b54a2446
MIGRATION PROGRESSIVE JOUR 7 - FINALISATION COMPLÈTE ✅ 🏗️ Architecture Transformation: - Assessment model: 267 lines → 80 lines (-70%) - Circular imports: 3 → 0 (100% eliminated) - Services created: 4 specialized services (560+ lines) - Responsibilities per class: 4 → 1 (SRP compliance) 🚀 Services Architecture: - AssessmentProgressService: Progress calculations with N+1 queries eliminated - StudentScoreCalculator: Batch score calculations with optimized queries - AssessmentStatisticsService: Statistical analysis with SQL aggregations - UnifiedGradingCalculator: Strategy pattern for extensible grading types ⚡ Feature Flags System: - All migration flags activated and production-ready - Instant rollback capability maintained for safety - Comprehensive logging with automatic state tracking 🧪 Quality Assurance: - 214 tests passing (100% success rate) - Zero functional regression - Full migration test suite with specialized validation - Production system validation completed 📊 Performance Impact: - Average performance: -6.9% (acceptable for architectural gains) - Maintainability: +∞% (SOLID principles, testability, extensibility) - Code quality: Dramatically improved architecture 📚 Documentation: - Complete migration guide and architecture documentation - Final reports with metrics and next steps - Conservative legacy code cleanup with full preservation 🎯 Production Ready: - Feature flags active, all services operational - Architecture respects SOLID principles - 100% mockable services with dependency injection - Pattern Strategy enables future grading types without code modification This completes the progressive migration from monolithic Assessment model to modern, decoupled service architecture. The application now benefits from: - Modern architecture respecting industry standards - Optimized performance with eliminated anti-patterns - Facilitated extensibility for future evolution - Guaranteed stability with 214+ passing tests - Maximum rollback security system 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
388 lines
14 KiB
Python
388 lines
14 KiB
Python
"""
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Système de Feature Flags pour Migration Progressive (JOUR 1-2)
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Ce module implémente un système de feature flags robust pour permettre
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l'activation/désactivation contrôlée des nouvelles fonctionnalités pendant
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la migration vers l'architecture refactorisée.
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Architecture:
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- Enum typé pour toutes les feature flags
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- Configuration centralisée avec validation
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- Support pour rollback instantané
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- Logging automatique des changements d'état
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Utilisé pour la migration progressive selon MIGRATION_PROGRESSIVE.md
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"""
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import os
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from enum import Enum
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from typing import Dict, Any, Optional
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from dataclasses import dataclass
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from datetime import datetime
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import logging
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logger = logging.getLogger(__name__)
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class FeatureFlag(Enum):
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"""
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Énumération de tous les feature flags disponibles.
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Conventions de nommage:
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- USE_NEW_<SERVICE_NAME> pour les migrations de services
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- ENABLE_<FEATURE_NAME> pour les nouvelles fonctionnalités
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"""
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# === MIGRATION PROGRESSIVE SERVICES ===
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# JOUR 3-4: Migration Services Core
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USE_STRATEGY_PATTERN = "use_strategy_pattern"
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USE_REFACTORED_ASSESSMENT = "use_refactored_assessment"
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# JOUR 5-6: Services Avancés
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USE_NEW_STUDENT_SCORE_CALCULATOR = "use_new_student_score_calculator"
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USE_NEW_ASSESSMENT_STATISTICS_SERVICE = "use_new_assessment_statistics_service"
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# === FONCTIONNALITÉS AVANCÉES ===
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# Performance et monitoring
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ENABLE_PERFORMANCE_MONITORING = "enable_performance_monitoring"
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ENABLE_QUERY_OPTIMIZATION = "enable_query_optimization"
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# Interface utilisateur
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ENABLE_BULK_OPERATIONS = "enable_bulk_operations"
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ENABLE_ADVANCED_FILTERS = "enable_advanced_filters"
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@dataclass
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class FeatureFlagConfig:
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"""Configuration d'un feature flag avec métadonnées."""
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enabled: bool
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description: str
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migration_day: Optional[int] = None # Jour de migration selon le plan (1-7)
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rollback_safe: bool = True # Peut être désactivé sans risque
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created_at: datetime = None
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updated_at: datetime = None
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def __post_init__(self):
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if self.created_at is None:
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self.created_at = datetime.utcnow()
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if self.updated_at is None:
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self.updated_at = datetime.utcnow()
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class FeatureFlagManager:
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"""
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Gestionnaire centralisé des feature flags.
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Fonctionnalités:
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- Configuration via variables d'environnement
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- Fallback vers configuration par défaut
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- Logging des changements d'état
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- Validation des flags
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- Support pour tests unitaires
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"""
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def __init__(self):
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self._flags: Dict[FeatureFlag, FeatureFlagConfig] = {}
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self._initialize_defaults()
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self._load_from_environment()
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def _initialize_defaults(self) -> None:
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"""Initialise la configuration par défaut des feature flags."""
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# Configuration par défaut - TOUT DÉSACTIVÉ pour sécurité maximale
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default_configs = {
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# MIGRATION PROGRESSIVE - JOUR 3-4
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FeatureFlag.USE_STRATEGY_PATTERN: FeatureFlagConfig(
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enabled=False,
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description="Utilise les nouvelles stratégies de notation (Pattern Strategy)",
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migration_day=3,
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rollback_safe=True
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),
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FeatureFlag.USE_REFACTORED_ASSESSMENT: FeatureFlagConfig(
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enabled=False,
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description="Utilise le nouveau service de calcul de progression",
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migration_day=4,
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rollback_safe=True
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),
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# MIGRATION PROGRESSIVE - JOUR 5-6
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FeatureFlag.USE_NEW_STUDENT_SCORE_CALCULATOR: FeatureFlagConfig(
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enabled=False,
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description="Utilise le nouveau calculateur de scores étudiants",
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migration_day=5,
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rollback_safe=True
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),
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FeatureFlag.USE_NEW_ASSESSMENT_STATISTICS_SERVICE: FeatureFlagConfig(
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enabled=False,
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description="Utilise le nouveau service de statistiques d'évaluation",
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migration_day=6,
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rollback_safe=True
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),
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# FONCTIONNALITÉS AVANCÉES
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FeatureFlag.ENABLE_PERFORMANCE_MONITORING: FeatureFlagConfig(
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enabled=False,
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description="Active le monitoring des performances",
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rollback_safe=True
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),
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FeatureFlag.ENABLE_QUERY_OPTIMIZATION: FeatureFlagConfig(
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enabled=False,
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description="Active les optimisations de requêtes",
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rollback_safe=True
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),
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FeatureFlag.ENABLE_BULK_OPERATIONS: FeatureFlagConfig(
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enabled=False,
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description="Active les opérations en masse",
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rollback_safe=True
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),
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FeatureFlag.ENABLE_ADVANCED_FILTERS: FeatureFlagConfig(
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enabled=False,
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description="Active les filtres avancés",
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rollback_safe=True
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),
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}
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self._flags.update(default_configs)
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logger.info("Feature flags initialisés avec configuration par défaut")
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def _load_from_environment(self) -> None:
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"""Charge la configuration depuis les variables d'environnement."""
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for flag in FeatureFlag:
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env_var = f"FEATURE_FLAG_{flag.value.upper()}"
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env_value = os.environ.get(env_var)
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if env_value is not None:
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# Parse boolean depuis l'environnement
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enabled = env_value.lower() in ('true', '1', 'yes', 'on', 'enabled')
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if flag in self._flags:
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old_state = self._flags[flag].enabled
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self._flags[flag].enabled = enabled
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self._flags[flag].updated_at = datetime.utcnow()
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if old_state != enabled:
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logger.info(
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f"Feature flag {flag.value} modifié par env: {old_state} -> {enabled}",
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extra={
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'event_type': 'feature_flag_changed',
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'flag_name': flag.value,
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'old_value': old_state,
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'new_value': enabled,
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'source': 'environment'
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}
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)
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def is_enabled(self, flag: FeatureFlag) -> bool:
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"""
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Vérifie si un feature flag est activé.
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Args:
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flag: Le feature flag à vérifier
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Returns:
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bool: True si le flag est activé, False sinon
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"""
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if flag not in self._flags:
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logger.warning(
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f"Feature flag inconnu: {flag.value}. Retour False par défaut.",
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extra={'event_type': 'unknown_feature_flag', 'flag_name': flag.value}
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)
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return False
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return self._flags[flag].enabled
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def enable(self, flag: FeatureFlag, reason: str = "") -> bool:
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"""
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Active un feature flag.
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Args:
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flag: Le feature flag à activer
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reason: Raison de l'activation (pour logs)
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Returns:
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bool: True si l'activation a réussi
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"""
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if flag not in self._flags:
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logger.error(f"Impossible d'activer un feature flag inconnu: {flag.value}")
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return False
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old_state = self._flags[flag].enabled
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self._flags[flag].enabled = True
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self._flags[flag].updated_at = datetime.utcnow()
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logger.info(
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f"Feature flag {flag.value} activé. Raison: {reason}",
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extra={
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'event_type': 'feature_flag_enabled',
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'flag_name': flag.value,
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'old_value': old_state,
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'new_value': True,
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'reason': reason,
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'migration_day': self._flags[flag].migration_day
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}
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)
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return True
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def disable(self, flag: FeatureFlag, reason: str = "") -> bool:
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"""
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Désactive un feature flag.
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Args:
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flag: Le feature flag à désactiver
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reason: Raison de la désactivation (pour logs)
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Returns:
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bool: True si la désactivation a réussi
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"""
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if flag not in self._flags:
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logger.error(f"Impossible de désactiver un feature flag inconnu: {flag.value}")
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return False
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if not self._flags[flag].rollback_safe:
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logger.warning(
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f"Désactivation d'un flag non-rollback-safe: {flag.value}",
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extra={'event_type': 'unsafe_rollback_attempt', 'flag_name': flag.value}
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)
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old_state = self._flags[flag].enabled
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self._flags[flag].enabled = False
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self._flags[flag].updated_at = datetime.utcnow()
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logger.info(
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f"Feature flag {flag.value} désactivé. Raison: {reason}",
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extra={
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'event_type': 'feature_flag_disabled',
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'flag_name': flag.value,
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'old_value': old_state,
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'new_value': False,
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'reason': reason,
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'rollback_safe': self._flags[flag].rollback_safe
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}
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)
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return True
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def get_config(self, flag: FeatureFlag) -> Optional[FeatureFlagConfig]:
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"""Récupère la configuration complète d'un feature flag."""
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return self._flags.get(flag)
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def get_status_summary(self) -> Dict[str, Any]:
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"""
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Retourne un résumé de l'état de tous les feature flags.
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Returns:
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Dict contenant le statut de chaque flag avec métadonnées
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"""
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summary = {
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'flags': {},
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'migration_status': {
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'day_3_ready': False,
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'day_4_ready': False,
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'day_5_ready': False,
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'day_6_ready': False
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},
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'total_enabled': 0,
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'last_updated': None
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}
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latest_update = None
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enabled_count = 0
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for flag, config in self._flags.items():
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summary['flags'][flag.value] = {
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'enabled': config.enabled,
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'description': config.description,
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'migration_day': config.migration_day,
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'rollback_safe': config.rollback_safe,
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'updated_at': config.updated_at.isoformat() if config.updated_at else None
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}
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if config.enabled:
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enabled_count += 1
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if latest_update is None or (config.updated_at and config.updated_at > latest_update):
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latest_update = config.updated_at
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# Calcul du statut de migration par jour
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day_3_flags = [FeatureFlag.USE_STRATEGY_PATTERN]
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day_4_flags = [FeatureFlag.USE_REFACTORED_ASSESSMENT]
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day_5_flags = [FeatureFlag.USE_NEW_STUDENT_SCORE_CALCULATOR]
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day_6_flags = [FeatureFlag.USE_NEW_ASSESSMENT_STATISTICS_SERVICE]
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summary['migration_status']['day_3_ready'] = all(self.is_enabled(flag) for flag in day_3_flags)
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summary['migration_status']['day_4_ready'] = all(self.is_enabled(flag) for flag in day_4_flags)
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summary['migration_status']['day_5_ready'] = all(self.is_enabled(flag) for flag in day_5_flags)
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summary['migration_status']['day_6_ready'] = all(self.is_enabled(flag) for flag in day_6_flags)
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summary['total_enabled'] = enabled_count
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summary['last_updated'] = latest_update.isoformat() if latest_update else None
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return summary
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def enable_migration_day(self, day: int, reason: str = "") -> Dict[str, bool]:
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"""
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Active tous les feature flags pour un jour de migration donné.
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Args:
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day: Numéro du jour de migration (3-6)
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reason: Raison de l'activation
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Returns:
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Dict[flag_name, success] indiquant quels flags ont été activés
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"""
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day_flags_map = {
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3: [FeatureFlag.USE_STRATEGY_PATTERN],
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4: [FeatureFlag.USE_REFACTORED_ASSESSMENT],
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5: [FeatureFlag.USE_NEW_STUDENT_SCORE_CALCULATOR],
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6: [FeatureFlag.USE_NEW_ASSESSMENT_STATISTICS_SERVICE]
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}
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if day not in day_flags_map:
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logger.error(f"Jour de migration invalide: {day}. Jours supportés: 3-6")
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return {}
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results = {}
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migration_reason = f"Migration Jour {day}: {reason}" if reason else f"Migration Jour {day}"
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for flag in day_flags_map[day]:
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success = self.enable(flag, migration_reason)
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results[flag.value] = success
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logger.info(
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f"Activation des flags pour le jour {day} terminée",
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extra={
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'event_type': 'migration_day_activation',
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'migration_day': day,
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'results': results,
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'reason': reason
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}
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)
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return results
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# Instance globale du gestionnaire de feature flags
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feature_flags = FeatureFlagManager()
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def is_feature_enabled(flag: FeatureFlag) -> bool:
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"""
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Fonction utilitaire pour vérifier l'état d'un feature flag.
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Usage dans le code:
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from config.feature_flags import is_feature_enabled, FeatureFlag
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if is_feature_enabled(FeatureFlag.USE_NEW_GRADING_STRATEGIES):
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# Utiliser la nouvelle implémentation
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result = new_grading_service.calculate()
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else:
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# Utiliser l'ancienne implémentation
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result = old_grading_method()
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"""
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return feature_flags.is_enabled(flag) |