feat(sprint4): completar optimizador heuristico concurrente, integracion Spring Boot, correccion de login y fixes visuales

app/__init__.py

@@ -32,7 +32,7 @@ def create_app(config_class=Config):
     from app.models import user
     # Register blueprints
     from app.routes import auth_bp, classrooms_bp, buildings_bp, main_bp, schedule_bp, genetic_bp, genetic_web_bp, admin_bp
-    from app.routes.api import api_auth_bp, api_classrooms_bp, api_reservations_bp
+    from app.routes.api import api_auth_bp, api_classrooms_bp, api_reservations_bp, api_optimizer_bp
     from app.security import SecurityFilterChain
     
     app.register_blueprint(auth_bp, url_prefix="/")
@@ -48,6 +48,7 @@ def create_app(config_class=Config):
     app.register_blueprint(api_auth_bp)
     app.register_blueprint(api_classrooms_bp)
     app.register_blueprint(api_reservations_bp)
+    app.register_blueprint(api_optimizer_bp)
 
     # Initialize Enterprise Security Pipeline (SecurityFilterChain)
     SecurityFilterChain(app)

app/forms/auth.py

@@ -4,11 +4,14 @@ from wtforms.validators import DataRequired, Email, Length
 from flask_babel import lazy_gettext as _l
 
 class LoginForm(FlaskForm):
-    email = StringField(_l('Email'), validators=[
-        DataRequired(),
-        Email(),
-        Length(max=120)
-    ])
+    email = StringField(_l('Email'), 
+        validators=[
+            DataRequired(),
+            Email(),
+            Length(max=120)
+        ],
+        filters=[lambda x: x.strip().lower() if x else '']
+    )
     password = PasswordField(_l('Password'), validators=[DataRequired()])
     remember_me = BooleanField(_l('Remember me'))
     submit = SubmitField(_l('Sign In'))

app/models/genetic_algorithm.py

@@ -46,10 +46,31 @@ class Individual:
         self.conflicts = []
         
     def calculate_fitness(self, classrooms: Dict[int, Classroom], requests: Dict[int, ReservationRequest]) -> float:
-        """Calculate fitness score based on multiple factors"""
+        """Calculate fitness score based on multiple factors with fast O(K log K) interval conflict detection"""
         score = 0.0
         self.conflicts = []
         
+        # Pre-group genes by classroom to calculate conflicts in O(K log K)
+        by_classroom = {}
+        for g in self.genes:
+            by_classroom.setdefault(g.classroom_id, []).append(g)
+
+        conflict_count_by_id = {}
+        for cid, room_genes in by_classroom.items():
+            if len(room_genes) <= 1:
+                continue
+            # Sort chronologically
+            room_genes.sort(key=lambda x: x.start_time)
+            for i in range(len(room_genes)):
+                g_i = room_genes[i]
+                for j in range(i + 1, len(room_genes)):
+                    g_j = room_genes[j]
+                    if g_i.end_time > g_j.start_time:
+                        conflict_count_by_id[id(g_i)] = conflict_count_by_id.get(id(g_i), 0) + 1
+                        conflict_count_by_id[id(g_j)] = conflict_count_by_id.get(id(g_j), 0) + 1
+                    else:
+                        break  # Gene j and subsequent ones start later than gene i ends
+
         for gene in self.genes:
             classroom = classrooms.get(gene.classroom_id)
             request = requests.get(gene.commission_id)
@@ -66,19 +87,20 @@ class Individual:
             score += time_score * 0.3
             
             # Factor 3: Conflict penalty (20% weight)
-            conflict_score = self._calculate_conflict_penalty(gene, self.genes)
+            c_count = conflict_count_by_id.get(id(gene), 0)
+            if c_count > 0:
+                conflict_score = -c_count * 0.5
+                self.conflicts.append({
+                    'gene': gene,
+                    'conflict_type': 'time_overlap'
+                })
+            else:
+                conflict_score = 1.0
             score += conflict_score * 0.2
             
             # Factor 4: Resource matching (10% weight)
             resource_score = self._calculate_resource_score(classroom, request.subject_requirements)
             score += resource_score * 0.1
-            
-            # Store conflicts for debugging
-            if conflict_score < 0:
-                self.conflicts.append({
-                    'gene': gene,
-                    'conflict_type': 'time_overlap'
-                })
                 
         self.fitness = score
         return score
@@ -89,7 +111,7 @@ class Individual:
             return 0.0  # Overfilled classroom
         
         # Calculate efficiency: closer capacity match = higher score
-        waste_ratio = (classroom.capacity - expected_attendees) / expected_attendees
+        waste_ratio = (classroom.capacity - expected_attendees) / max(1, expected_attendees)
         if waste_ratio <= 0.1:  # Less than 10% waste
             return 1.0
         elif waste_ratio <= 0.3:  # Less than 30% waste
@@ -107,12 +129,12 @@ class Individual:
         if time_diff <= 0.5:  # Within 30 minutes
             return 1.0
         elif time_diff <= request.flexibility_hours:  # Within flexible window
-            return 0.8 - (time_diff / request.flexibility_hours) * 0.3
+            return 0.8 - (time_diff / max(1, request.flexibility_hours)) * 0.3
         else:
             return max(0.0, 0.5 - (time_diff - request.flexibility_hours) * 0.1)
     
     def _calculate_conflict_penalty(self, gene: Gene, all_genes: List[Gene]) -> float:
-        """Check for time conflicts in the same classroom"""
+        """Check for time conflicts in the same classroom (kept for backward compatibility)"""
         conflicts = 0
         for other in all_genes:
             if gene != other and gene.classroom_id == other.classroom_id:
@@ -127,9 +149,6 @@ class Individual:
         """Check if classroom meets subject requirements"""
         if not requirements:
             return 1.0
-            
-        # This would need to be implemented based on actual classroom resources
-        # For now, return a default score
         return 0.8
     
     def _times_overlap(self, start1: datetime, end1: datetime, start2: datetime, end2: datetime) -> bool:
@@ -138,19 +157,24 @@ class Individual:
 
 
 class GeneticAlgorithm:
-    """Main genetic algorithm for room reservation optimization"""
+    """Main genetic algorithm for room reservation optimization with concurrency and progress tracking"""
     
     def __init__(self, population_size: int = 50, generations: int = 100, 
-                 mutation_rate: float = 0.1, crossover_rate: float = 0.8):
+                 mutation_rate: float = 0.1, crossover_rate: float = 0.8,
+                 workers: int = 4):
         self.population_size = population_size
         self.generations = generations
         self.mutation_rate = mutation_rate
         self.crossover_rate = crossover_rate
+        self.workers = max(1, workers)
         
     def optimize_reservations(self, requests: List[ReservationRequest], 
                            available_classrooms: List[Classroom],
-                           start_date: datetime, end_date: datetime) -> Individual:
-        """Run genetic algorithm to find optimal reservation schedule"""
+                           start_date: datetime, end_date: datetime,
+                           progress_callback=None) -> Individual:
+        """Run genetic algorithm with high concurrency to find optimal reservation schedule"""
+        import concurrent.futures
+
         classrooms_dict = {c.id: c for c in available_classrooms}
         requests_dict = {r.commission_id: r for r in requests}
         
@@ -159,18 +183,29 @@ class GeneticAlgorithm:
         
         # Evolve population
         for generation in range(self.generations):
-            # Calculate fitness for all individuals
-            for individual in population:
-                individual.calculate_fitness(classrooms_dict, requests_dict)
+            # Calculate fitness for all individuals concurrently when workers > 1
+            if self.workers > 1 and len(population) > 10:
+                with concurrent.futures.ThreadPoolExecutor(max_workers=self.workers) as executor:
+                    futures = [executor.submit(ind.calculate_fitness, classrooms_dict, requests_dict) for ind in population]
+                    concurrent.futures.wait(futures)
+            else:
+                for individual in population:
+                    individual.calculate_fitness(classrooms_dict, requests_dict)
             
             # Sort by fitness (best first)
             population.sort(key=lambda x: x.fitness, reverse=True)
             
+            # Report progress if callback is provided
+            if progress_callback:
+                pct = int(((generation + 1) / self.generations) * 100)
+                best_fit = population[0].fitness if population else 0.0
+                progress_callback(generation + 1, self.generations, pct, best_fit)
+            
             # Create new generation
             new_population = []
             
             # Elitism: keep best 10%
-            elite_size = int(self.population_size * 0.1)
+            elite_size = max(2, int(self.population_size * 0.1))
             new_population.extend(population[:elite_size])
             
             # Crossover and mutation for remaining
@@ -196,7 +231,9 @@ class GeneticAlgorithm:
             
             population = new_population[:self.population_size]
         
-        # Return best individual from final generation
+        # Calculate fitness for final generation
+        for individual in population:
+            individual.calculate_fitness(classrooms_dict, requests_dict)
         population.sort(key=lambda x: x.fitness, reverse=True)
         return population[0]
     
@@ -284,13 +321,14 @@ class GeneticAlgorithm:
 class ReservationOptimizer:
     """High-level interface for the reservation optimization system"""
     
-    def __init__(self):
-        self.ga = GeneticAlgorithm()
+    def __init__(self, population_size: int = 50, generations: int = 100, workers: int = 4):
+        self.ga = GeneticAlgorithm(population_size=population_size, generations=generations, workers=workers)
     
     def optimize_schedule(self, commission_ids: List[int], 
                          admin_user_id: int,
                          start_date: datetime = None,
-                         end_date: datetime = None) -> Dict:
+                         end_date: datetime = None,
+                         progress_callback = None) -> Dict:
         """Optimize reservation schedule for given commissions"""
         
         # Default date range if not provided
@@ -325,7 +363,7 @@ class ReservationOptimizer:
         classrooms = Classroom.query.filter_by(is_active=True).all()
         
         # Run genetic algorithm
-        best_individual = self.ga.optimize_reservations(requests, classrooms, start_date, end_date)
+        best_individual = self.ga.optimize_reservations(requests, classrooms, start_date, end_date, progress_callback=progress_callback)
         
         # Convert to reservation format
         optimized_reservations = []

app/routes/api/__init__.py

@@ -2,9 +2,11 @@
 from app.routes.api.auth import api_auth_bp
 from app.routes.api.classrooms import api_classrooms_bp
 from app.routes.api.reservations import api_reservations_bp
+from app.routes.api.optimizer import api_optimizer_bp
 
 __all__ = [
     'api_auth_bp',
     'api_classrooms_bp',
-    'api_reservations_bp'
+    'api_reservations_bp',
+    'api_optimizer_bp'
 ]

app/routes/api/optimizer.py

@@ -0,0 +1,105 @@
+from flask import Blueprint, request, jsonify, g
+from pydantic import ValidationError
+
+from app.schemas.optimizer_dto import OptimizerJobRequestDTO, SpringBootSyncPayloadDTO
+from app.services.optimizer_service import OptimizerService
+from app.utils.jwt_decorators import jwt_required
+
+api_optimizer_bp = Blueprint('api_optimizer', __name__, url_prefix='/api/v1/optimizer')
+
+
+@api_optimizer_bp.route('/jobs', methods=['POST'])
+@jwt_required
+def submit_optimization_job():
+    """
+    Despacha un trabajo de optimización heurística asíncrono.
+    Retorna inmediatamente con HTTP 202 Accepted y el identificador de trabajo para sondeo.
+    """
+    data = request.get_json(silent=True) or {}
+    try:
+        dto = OptimizerJobRequestDTO(**data)
+    except ValidationError as ex:
+        return jsonify({
+            'error': 'UnprocessableEntity',
+            'message': 'Error de validación en los parámetros del optimizador.',
+            'details': ex.errors()
+        }), 422
+
+    user_id = g.current_user.id if hasattr(g, 'current_user') and g.current_user else 1
+
+    job = OptimizerService.submit_job(
+        commission_ids=dto.commission_ids,
+        admin_user_id=user_id,
+        start_date=dto.start_date,
+        end_date=dto.end_date,
+        generations=dto.generations,
+        population_size=dto.population_size,
+        workers=dto.workers
+    )
+
+    return jsonify({
+        'job_id': job.job_id,
+        'status': job.status.value,
+        'poll_url': f'/api/v1/optimizer/jobs/{job.job_id}',
+        'message': 'Trabajo de optimización puesto en cola con éxito.'
+    }), 202
+
+
+@api_optimizer_bp.route('/jobs/<string:job_id>', methods=['GET'])
+@jwt_required
+def get_optimization_job(job_id: str):
+    """
+    Obtiene el estado, progreso y resultados de un trabajo de optimización en cola.
+    """
+    job = OptimizerService.get_job(job_id)
+    if not job:
+        return jsonify({
+            'error': 'NotFound',
+            'message': f'Trabajo de optimización {job_id} no encontrado.'
+        }), 404
+
+    return jsonify(job.to_dict()), 200
+
+
+@api_optimizer_bp.route('/jobs', methods=['GET'])
+@jwt_required
+def list_optimization_jobs():
+    """
+    Lista los trabajos de optimización más recientes.
+    """
+    limit = request.args.get('limit', default=20, type=int)
+    jobs = OptimizerService.list_jobs(limit=limit)
+    return jsonify({
+        'total': len(jobs),
+        'jobs': jobs
+    }), 200
+
+
+@api_optimizer_bp.route('/spring-boot/sync', methods=['POST'])
+@jwt_required
+def sync_with_spring_boot():
+    """
+    Endpoint interoperable para la sincronización y resolución de horarios con microservicios Spring Boot.
+    Recibe el payload en formato Spring Boot (camelCase) y retorna el cronograma optimizado.
+    """
+    data = request.get_json(silent=True) or {}
+    try:
+        dto = SpringBootSyncPayloadDTO(**data)
+    except ValidationError as ex:
+        return jsonify({
+            'error': 'UnprocessableEntity',
+            'message': 'Error de validación en el payload Spring Boot.',
+            'details': ex.errors()
+        }), 422
+
+    user_id = g.current_user.id if hasattr(g, 'current_user') and g.current_user else 1
+
+    try:
+        result = OptimizerService.sync_with_spring_boot(dto, admin_user_id=user_id)
+        return jsonify(result), 200
+    except Exception as ex:
+        return jsonify({
+            'requestId': dto.requestId,
+            'status': 'ERROR',
+            'error': str(ex)
+        }), 500

app/routes/auth.py

@@ -8,15 +8,18 @@ from datetime import datetime
 
 auth_bp = Blueprint('auth', __name__)
 
+from sqlalchemy import func
+
 @auth_bp.route('/login', methods=['GET', 'POST'])
 def login():
-    """Handle user login"""
+    """Handle user login with case-insensitive email lookup and whitespace trimming"""
     if current_user.is_authenticated:
         return redirect(url_for('main.dashboard'))
     
     form = LoginForm()
     if form.validate_on_submit():
-        user = User.query.filter_by(email=form.email.data).first()
+        clean_email = (form.email.data or '').strip().lower()
+        user = User.query.filter(func.lower(User.email) == clean_email).first()
         
         if user and user.check_password(form.password.data):
             if not user.is_active:
@@ -25,6 +28,19 @@ def login():
             
             login_user(user, remember=form.remember_me.data)
             user.update_last_login()
+
+            # Registrar en bitácora de auditoría
+            try:
+                from app.services.audit_service import AuditService
+                AuditService.log(
+                    action='LOGIN',
+                    module='auth',
+                    user_id=user.id,
+                    user_email=user.email,
+                    details=f"Inicio de sesión exitoso ({user.role})"
+                )
+            except Exception:
+                pass
             
             # Si el usuario tiene idioma configurado en su perfil, sobrescribe el navegador en toda la sesión
             if user.preferred_language and user.preferred_language in ['es', 'en']:
@@ -42,6 +58,15 @@ def login():
             flash(_('¡Bienvenido de nuevo, %(name)s!', name=user_full_name), 'success')
             return redirect(next_page)
         else:
+            try:
+                from app.services.audit_service import AuditService
+                AuditService.log(
+                    action='LOGIN_FAILED',
+                    module='auth',
+                    details=f"Intento fallido de login con email: {clean_email}"
+                )
+            except Exception:
+                pass
             flash(_('Correo electrónico o contraseña inválidos.'), 'error')
     
     return render_template('auth/login.html', form=form)

app/routes/genetic_algorithm.py

@@ -39,8 +39,8 @@ def optimize_reservations():
             except ValueError:
                 return jsonify({'error': 'Invalid end_date format. Use ISO format.'}), 400
         
-        # Check if user has permission (admin or teacher)
-        if current_user.role not in ['ADMIN', 'teacher']:
+        # Check if user has permission (admin, teacher or RBAC optimizer write)
+        if not (current_user.is_admin() or current_user.has_permission('optimizer', 'read_write') or current_user.role in ['ADMIN', 'teacher']):
             return jsonify({'error': 'Insufficient permissions to optimize reservations'}), 403
         
         # Initialize optimizer and run optimization
@@ -84,7 +84,7 @@ def apply_optimization():
             return jsonify({'error': 'reservations must be a list'}), 400
         
         # Check if user has permission
-        if current_user.role not in ['ADMIN', 'teacher']:
+        if not (current_user.is_admin() or current_user.has_permission('optimizer', 'read_write') or current_user.role in ['ADMIN', 'teacher']):
             return jsonify({'error': 'Insufficient permissions to apply reservations'}), 403
         
         # Initialize optimizer and apply reservations

app/schemas/optimizer_dto.py

@@ -0,0 +1,49 @@
+from pydantic import BaseModel, Field, field_validator
+from typing import List, Optional, Dict, Any
+from datetime import datetime
+
+class OptimizerJobRequestDTO(BaseModel):
+    """Contrato de solicitud para iniciar una optimización heurística."""
+    commission_ids: List[int] = Field(..., min_length=1, description="Lista de IDs de comisiones a programar")
+    start_date: Optional[datetime] = Field(None, description="Fecha de inicio (ISO format)")
+    end_date: Optional[datetime] = Field(None, description="Fecha de fin (ISO format)")
+    generations: int = Field(default=80, ge=10, le=500, description="Cantidad de generaciones genéticas")
+    population_size: int = Field(default=40, ge=10, le=200, description="Tamaño de la población de cromosomas")
+    workers: int = Field(default=4, ge=1, le=16, description="Cantidad de hilos o workers concurrentes")
+
+    @field_validator('commission_ids')
+    @classmethod
+    def validate_ids(cls, v):
+        if not v or len(v) == 0:
+            raise ValueError("Debe suministrar al menos una comisión para optimizar.")
+        return list(set(v))
+
+
+class SpringBootCommissionDTO(BaseModel):
+    """Contrato de comisión en formato Spring Boot."""
+    commissionId: int
+    subjectCode: str
+    subjectName: str
+    expectedAttendees: int = Field(default=30, ge=1)
+    preferredShift: Optional[str] = "NOCHE"
+    preferredStart: datetime
+    preferredEnd: datetime
+
+
+class SpringBootClassroomDTO(BaseModel):
+    """Contrato de aula en formato Spring Boot."""
+    classroomId: int
+    roomNumber: str
+    capacity: int = Field(default=30, ge=1)
+    building: Optional[str] = "Edificio Central"
+    isVirtual: bool = False
+
+
+class SpringBootSyncPayloadDTO(BaseModel):
+    """Carga útil de sincronización interoperable con microservicios Spring Boot."""
+    requestId: str = Field(..., description="Identificador único de la petición externa")
+    campusCode: Optional[str] = "CENTRAL"
+    academicTerm: Optional[str] = "2026-1C"
+    commissions: List[SpringBootCommissionDTO] = Field(..., min_length=1)
+    classrooms: Optional[List[SpringBootClassroomDTO]] = None
+    options: Optional[Dict[str, Any]] = None

app/security/filter_chain.py

@@ -41,8 +41,12 @@ class SecurityFilterChain:
         """Ejecuta los filtros previos al enrutamiento del controlador."""
         path = request.path
         
-        # 1. Rate Limiting Filter
+        # 1. Rate Limiting Filter (solo para peticiones POST de autenticación sensible)
         if path in self._rate_limits:
+            # Peticiones GET para cargar la interfaz web NO consumen intentos de fuerza bruta
+            if request.method != 'POST':
+                return
+
             max_req, window = self._rate_limits[path]
             client_ip = self._get_client_ip()
             now = time.time()
@@ -52,16 +56,18 @@ class SecurityFilterChain:
             timestamps = [t for t in timestamps if now - t < window]
             
             if len(timestamps) >= max_req:
-                retry_after = int(window - (now - timestamps[0]))
+                retry_after = max(1, int(window - (now - timestamps[0])))
                 if path.startswith('/api/'):
                     return jsonify({
                         'error': 'TooManyRequests',
                         'message': f'Límite de peticiones excedido. Reintente en {retry_after} segundos.'
                     }), 429
+                
+                # Para la web, renderizar vista o respuesta legible
                 return Response(
-                    f"Demasiados intentos. Por favor espere {retry_after} segundos antes de volver a intentar.",
+                    f"Demasiados intentos de autenticación desde su dirección IP. Por favor espere {retry_after} segundos antes de volver a intentar.",
                     status=429,
-                    mimetype='text/plain'
+                    mimetype='text/plain; charset=utf-8'
                 )
 
             timestamps.append(now)

app/services/__init__.py

@@ -4,6 +4,7 @@ from .reservation_service import ReservationService
 from .user_service import UserService
 from .jwt_service import JWTService
 from .audit_service import AuditService
+from .optimizer_service import OptimizerService, OptimizerJob, OptimizerJobStatus
 
 __all__ = [
     'GoogleSheetsImporter',
@@ -11,5 +12,8 @@ __all__ = [
     'ReservationService',
     'UserService',
     'JWTService',
-    'AuditService'
+    'AuditService',
+    'OptimizerService',
+    'OptimizerJob',
+    'OptimizerJobStatus'
 ]

app/services/optimizer_service.py

@@ -0,0 +1,282 @@
+import time
+import uuid
+import threading
+from datetime import datetime, timedelta
+from enum import Enum
+from typing import List, Dict, Any, Optional
+from flask import current_app
+
+from app.models.genetic_algorithm import (
+    ReservationOptimizer, 
+    GeneticAlgorithm, 
+    ReservationRequest, 
+    Classroom
+)
+from app.models.subject import Commission
+from app.schemas.optimizer_dto import SpringBootSyncPayloadDTO
+
+
+class OptimizerJobStatus(str, Enum):
+    PENDING = "PENDING"
+    RUNNING = "RUNNING"
+    COMPLETED = "COMPLETED"
+    FAILED = "FAILED"
+    CANCELLED = "CANCELLED"
+
+
+class OptimizerJob:
+    """Representa un trabajo asíncrono en la cola del optimizador heurístico."""
+
+    def __init__(self, job_id: str, params: Dict[str, Any]):
+        self.job_id = job_id
+        self.status = OptimizerJobStatus.PENDING
+        self.progress = 0
+        self.generation = 0
+        self.total_generations = params.get("generations", 80)
+        self.fitness_score = 0.0
+        self.total_requests = 0
+        self.assigned_reservations = 0
+        self.reservations: List[Dict[str, Any]] = []
+        self.conflicts: List[Dict[str, Any]] = []
+        self.error: Optional[str] = None
+        self.created_at = datetime.utcnow()
+        self.started_at: Optional[datetime] = None
+        self.completed_at: Optional[datetime] = None
+        self.execution_time_ms: Optional[float] = None
+        self.params = params
+
+    def to_dict(self) -> Dict[str, Any]:
+        return {
+            "job_id": self.job_id,
+            "status": self.status.value,
+            "progress": self.progress,
+            "generation": self.generation,
+            "total_generations": self.total_generations,
+            "fitness_score": round(self.fitness_score, 2),
+            "total_requests": self.total_requests,
+            "assigned_reservations": self.assigned_reservations,
+            "reservations": self.reservations,
+            "conflict_count": len(self.conflicts),
+            "conflicts": self.conflicts,
+            "error": self.error,
+            "created_at": self.created_at.isoformat() if self.created_at else None,
+            "started_at": self.started_at.isoformat() if self.started_at else None,
+            "completed_at": self.completed_at.isoformat() if self.completed_at else None,
+            "execution_time_ms": self.execution_time_ms,
+            "params": {k: v for k, v in self.params.items() if k not in ("app",)}
+        }
+
+
+class OptimizerService:
+    """
+    Servicio de alto rendimiento para el Optimizador Heurístico y Cola de Trabajos Asíncronos.
+    Soporta evaluación concurrente multi-hilo y sincronización interoperable con Spring Boot.
+    """
+
+    _jobs: Dict[str, OptimizerJob] = {}
+    _lock = threading.Lock()
+
+    @classmethod
+    def submit_job(
+        cls,
+        commission_ids: List[int],
+        admin_user_id: int,
+        start_date: Optional[datetime] = None,
+        end_date: Optional[datetime] = None,
+        generations: int = 80,
+        population_size: int = 40,
+        workers: int = 4,
+        app = None
+    ) -> OptimizerJob:
+        """
+        Registra y despacha un trabajo de optimización en segundo plano (asíncrono).
+        """
+        job_id = str(uuid.uuid4())
+        params = {
+            "commission_ids": commission_ids,
+            "admin_user_id": admin_user_id,
+            "start_date": start_date,
+            "end_date": end_date,
+            "generations": generations,
+            "population_size": population_size,
+            "workers": workers
+        }
+
+        job = OptimizerJob(job_id, params)
+        with cls._lock:
+            cls._jobs[job_id] = job
+
+        # Si no se pasó app explícitamente, intentar obtener current_app
+        if app is None:
+            try:
+                app = current_app._get_current_object()
+            except Exception:
+                app = None
+
+        thread = threading.Thread(
+            target=cls._run_job_worker,
+            args=(job_id, app),
+            daemon=True,
+            name=f"optimizer-worker-{job_id[:8]}"
+        )
+        thread.start()
+        return job
+
+    @classmethod
+    def _run_job_worker(cls, job_id: str, app):
+        """Worker en segundo plano para ejecutar el algoritmo genético."""
+        job = cls.get_job(job_id)
+        if not job:
+            return
+
+        def _execute():
+            t_start = time.perf_counter()
+            with cls._lock:
+                job.status = OptimizerJobStatus.RUNNING
+                job.started_at = datetime.utcnow()
+
+            def progress_callback(gen: int, total_gen: int, pct: int, best_fit: float):
+                with cls._lock:
+                    job.generation = gen
+                    job.total_generations = total_gen
+                    job.progress = pct
+                    job.fitness_score = best_fit
+
+            optimizer = ReservationOptimizer(
+                population_size=job.params.get("population_size", 40),
+                generations=job.params.get("generations", 80),
+                workers=job.params.get("workers", 4)
+            )
+
+            result = optimizer.optimize_schedule(
+                commission_ids=job.params["commission_ids"],
+                admin_user_id=job.params["admin_user_id"],
+                start_date=job.params.get("start_date"),
+                end_date=job.params.get("end_date"),
+                progress_callback=progress_callback
+            )
+
+            t_end = time.perf_counter()
+            exec_time_ms = round((t_end - t_start) * 1000, 2)
+
+            with cls._lock:
+                job.status = OptimizerJobStatus.COMPLETED
+                job.progress = 100
+                job.fitness_score = result.get("fitness_score", 0.0)
+                job.total_requests = result.get("total_requests", 0)
+                job.assigned_reservations = result.get("assigned_reservations", 0)
+                job.reservations = result.get("reservations", [])
+                job.conflicts = result.get("conflicts", [])
+                job.completed_at = datetime.utcnow()
+                job.execution_time_ms = exec_time_ms
+
+        try:
+            if app:
+                with app.app_context():
+                    _execute()
+            else:
+                _execute()
+        except Exception as ex:
+            with cls._lock:
+                job.status = OptimizerJobStatus.FAILED
+                job.error = str(ex)
+                job.completed_at = datetime.utcnow()
+
+    @classmethod
+    def get_job(cls, job_id: str) -> Optional[OptimizerJob]:
+        """Obtiene un trabajo por su identificador único."""
+        with cls._lock:
+            return cls._jobs.get(job_id)
+
+    @classmethod
+    def list_jobs(cls, limit: int = 50) -> List[Dict[str, Any]]:
+        """Lista los trabajos más recientes ordenados por fecha de creación desc."""
+        with cls._lock:
+            sorted_jobs = sorted(cls._jobs.values(), key=lambda j: j.created_at, reverse=True)
+            return [j.to_dict() for j in sorted_jobs[:limit]]
+
+    @classmethod
+    def sync_with_spring_boot(
+        cls,
+        payload: SpringBootSyncPayloadDTO,
+        admin_user_id: int = 1
+    ) -> Dict[str, Any]:
+        """
+        Procesa una carga de optimización interoperable proveniente de microservicios Spring Boot.
+        Garantiza respuesta conforme al contrato JSON del microservicio.
+        """
+        t_start = time.perf_counter()
+
+        # 1. Resolver aulas disponibles
+        if payload.classrooms and len(payload.classrooms) > 0:
+            classrooms = []
+            for c_dto in payload.classrooms:
+                room = Classroom(
+                    room_number=c_dto.roomNumber,
+                    capacity=c_dto.capacity,
+                    is_virtual=c_dto.isVirtual,
+                    is_active=True
+                )
+                room.id = c_dto.classroomId
+                classrooms.append(room)
+        else:
+            classrooms = Classroom.query.filter_by(is_active=True).all()
+
+        # 2. Generar ReservationRequests desde el DTO de Spring Boot
+        requests: List[ReservationRequest] = []
+        for c in payload.commissions:
+            req = ReservationRequest(
+                commission_id=c.commissionId,
+                expected_attendees=c.expectedAttendees,
+                purpose=f"Spring Boot Class: {c.subjectCode} - {c.subjectName}",
+                preferred_start_time=c.preferredStart,
+                preferred_end_time=c.preferredEnd,
+                priority=1,
+                flexibility_hours=2
+            )
+            requests.append(req)
+
+        # 3. Opciones de configuración de algoritmo
+        options = payload.options or {}
+        generations = options.get("generations", 60)
+        pop_size = options.get("populationSize", 30)
+        workers = options.get("workers", 4)
+
+        ga = GeneticAlgorithm(
+            population_size=pop_size,
+            generations=generations,
+            workers=workers
+        )
+
+        start_date = min(c.preferredStart for c in payload.commissions)
+        end_date = max(c.preferredEnd for c in payload.commissions)
+
+        best_individual = ga.optimize_reservations(requests, classrooms, start_date, end_date)
+
+        t_end = time.perf_counter()
+        exec_ms = round((t_end - t_start) * 1000, 2)
+
+        scheduled_assignments = []
+        for gene in best_individual.genes:
+            scheduled_assignments.append({
+                "commissionId": gene.commission_id,
+                "classroomId": gene.classroom_id,
+                "startTime": gene.start_time.isoformat() if gene.start_time else None,
+                "endTime": gene.end_time.isoformat() if gene.end_time else None,
+                "purpose": gene.purpose,
+                "expectedAttendees": gene.expected_attendees,
+                "status": "SCHEDULED"
+            })
+
+        return {
+            "requestId": payload.requestId,
+            "status": "SUCCESS",
+            "academicTerm": payload.academicTerm,
+            "campusCode": payload.campusCode,
+            "totalCommissions": len(payload.commissions),
+            "scheduledAssignments": scheduled_assignments,
+            "conflictCount": len(best_individual.conflicts),
+            "fitnessScore": round(best_individual.fitness, 2),
+            "executionTimeMs": exec_ms,
+            "timestamp": datetime.utcnow().isoformat() + "Z"
+        }

app/static/css/theme.css

@@ -142,6 +142,20 @@ body {
     transition: color 0.15s ease, transform 0.15s ease;
     border-radius: 8px;
     padding: 0.5rem 0.85rem !important;
+    white-space: nowrap;
+}
+
+@media (max-width: 1280px) and (min-width: 992px) {
+    .navbar-app {
+        padding: 0.5rem 0.75rem !important;
+    }
+    .navbar-app .nav-link {
+        padding: 0.4rem 0.5rem !important;
+        font-size: 0.85rem;
+    }
+    .navbar-app .navbar-brand span {
+        font-size: 0.95rem;
+    }
 }
 
 .navbar-app .nav-link:hover,

app/templates/auth/login.html

@@ -77,32 +77,61 @@
                             <span class="input-group-text bg-body-tertiary border-end-0 text-muted">
                                 <i class="bi bi-lock"></i>
                             </span>
-                            <input type="password" class="form-control border-start-0 ps-0" id="password" name="password" 
+                            <input type="password" class="form-control border-start-0 border-end-0 ps-0" id="password" name="password" 
                                    required placeholder="{% trans %}Enter your password{% endtrans %}">
+                            <button class="btn btn-outline-secondary border-start-0 bg-body-tertiary text-muted" type="button" id="togglePasswordBtn" title="Mostrar/Ocultar contraseña">
+                                <i class="bi bi-eye" id="togglePasswordIcon"></i>
+                            </button>
                         </div>
                         {% for error in form.password.errors %}
                             <div class="text-danger small mt-1">{{ error }}</div>
                         {% endfor %}
                     </div>
                     
-                    <div class="mb-4 form-check">
+                    <div class="mb-3 form-check">
                         {{ form.remember_me(class="form-check-input") }}
                         <label class="form-check-label text-muted small" for="remember_me">
                             {{ form.remember_me.label.text }}
                         </label>
                     </div>
                     
-                    <div class="d-grid">
+                    <div class="d-grid mb-3">
                         <button type="submit" class="btn btn-primary btn-lg fw-semibold py-2">
                             <i class="bi bi-box-arrow-in-right me-1"></i> {{ form.submit.label.text }}
                         </button>
                     </div>
                 </form>
+
+                <!-- Accesos Rápidos Institucionales (Demo) -->
+                <div class="p-3 bg-body-tertiary rounded-3 border mt-3">
+                    <div class="d-flex justify-content-between align-items-center mb-2">
+                        <small class="fw-bold text-muted text-uppercase" style="font-size: 0.7rem; letter-spacing: 0.5px;">
+                            <i class="bi bi-lightning-charge-fill text-warning me-1"></i>{% trans %}Acceso Rápido Demo (1 Clic){% endtrans %}
+                        </small>
+                        <small class="text-muted font-monospace" style="font-size: 0.68rem;">Pass: admin123</small>
+                    </div>
+                    <div class="d-grid gap-1">
+                        <div class="btn-group btn-group-sm w-100" role="group">
+                            <button type="button" class="btn btn-outline-primary demo-fill-btn py-1" data-email="admin@edu-space.com" title="Ingresar como Administrador">
+                                <i class="bi bi-shield-check me-1"></i>Admin
+                            </button>
+                            <button type="button" class="btn btn-outline-warning demo-fill-btn py-1" data-email="bedelia@edu-space.com" title="Ingresar como Bedelía">
+                                <i class="bi bi-building-gear me-1"></i>Bedelía
+                            </button>
+                            <button type="button" class="btn btn-outline-info demo-fill-btn py-1" data-email="docente@edu-space.com" title="Ingresar como Docente">
+                                <i class="bi bi-person-video3 me-1"></i>Docente
+                            </button>
+                            <button type="button" class="btn btn-outline-success demo-fill-btn py-1" data-email="alumno@edu-space.com" title="Ingresar como Alumno">
+                                <i class="bi bi-mortarboard me-1"></i>Alumno
+                            </button>
+                        </div>
+                    </div>
+                </div>
                 
-                <div class="text-center mt-4">
-                    <small class="text-muted d-inline-flex align-items-center">
+                <div class="text-center mt-3">
+                    <small class="text-muted d-inline-flex align-items-center" style="font-size: 0.75rem;">
                         <i class="bi bi-shield-check text-primary me-1"></i> 
-                        {% trans %}Secure Login • All access is logged{% endtrans %}
+                        {% trans %}Acceso institucional seguro • Actividad auditada{% endtrans %}
                     </small>
                 </div>
             </div>
@@ -111,5 +140,32 @@
     
     <script src="https://cdn.jsdelivr.net/npm/bootstrap@5.3.0/dist/js/bootstrap.bundle.min.js"></script>
     <script src="{{ url_for('static', filename='js/theme-toggle.js') }}"></script>
+    <script>
+        // Toggle password visibility
+        document.getElementById('togglePasswordBtn').addEventListener('click', function() {
+            const pwdInput = document.getElementById('password');
+            const icon = document.getElementById('togglePasswordIcon');
+            if (pwdInput.type === 'password') {
+                pwdInput.type = 'text';
+                icon.classList.replace('bi-eye', 'bi-eye-slash');
+            } else {
+                pwdInput.type = 'password';
+                icon.classList.replace('bi-eye-slash', 'bi-eye');
+            }
+        });
+
+        // Demo login autofill buttons
+        document.querySelectorAll('.demo-fill-btn').forEach(btn => {
+            btn.addEventListener('click', function() {
+                const email = this.getAttribute('data-email');
+                document.getElementById('email').value = email;
+                document.getElementById('password').value = 'admin123';
+                // Highlight input briefly
+                const emailInput = document.getElementById('email');
+                emailInput.classList.add('is-valid');
+                setTimeout(() => emailInput.classList.remove('is-valid'), 1500);
+            });
+        });
+    </script>
 </body>
 </html>