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"""
In-memory storage implementation for TutorX-MCP.
This module provides in-memory storage for development and testing.
In production, this would be replaced with database-backed storage.
"""
import json
import pickle
from datetime import datetime, timedelta
from typing import Dict, List, Optional, Any, Union
from pathlib import Path
import threading
from collections import defaultdict
from ..models.student_profile import StudentProfile
class MemoryStore:
"""
In-memory storage implementation for adaptive learning data.
This provides a simple storage layer for development and testing.
In production, this would be replaced with a proper database.
"""
def __init__(self, persistence_file: Optional[str] = None):
"""
Initialize the memory store.
Args:
persistence_file: Optional file path for data persistence
"""
self.persistence_file = persistence_file
self._lock = threading.RLock()
# Storage containers
self.student_profiles: Dict[str, StudentProfile] = {}
self.performance_data: Dict[str, Dict[str, Any]] = defaultdict(dict)
self.session_data: Dict[str, Dict[str, Any]] = {}
self.analytics_cache: Dict[str, Dict[str, Any]] = defaultdict(dict)
self.adaptation_history: Dict[str, List[Dict[str, Any]]] = defaultdict(list)
# Load persisted data if available
if self.persistence_file:
self._load_from_file()
def _load_from_file(self):
"""Load data from persistence file."""
try:
if Path(self.persistence_file).exists():
with open(self.persistence_file, 'rb') as f:
data = pickle.load(f)
self.student_profiles = data.get('student_profiles', {})
self.performance_data = data.get('performance_data', defaultdict(dict))
self.session_data = data.get('session_data', {})
self.analytics_cache = data.get('analytics_cache', defaultdict(dict))
self.adaptation_history = data.get('adaptation_history', defaultdict(list))
print(f"Loaded data from {self.persistence_file}")
except Exception as e:
print(f"Error loading data from {self.persistence_file}: {e}")
def _save_to_file(self):
"""Save data to persistence file."""
if not self.persistence_file:
return
try:
data = {
'student_profiles': self.student_profiles,
'performance_data': dict(self.performance_data),
'session_data': self.session_data,
'analytics_cache': dict(self.analytics_cache),
'adaptation_history': dict(self.adaptation_history)
}
with open(self.persistence_file, 'wb') as f:
pickle.dump(data, f)
except Exception as e:
print(f"Error saving data to {self.persistence_file}: {e}")
# Student Profile Operations
def save_student_profile(self, profile: StudentProfile) -> bool:
"""Save a student profile."""
with self._lock:
try:
self.student_profiles[profile.student_id] = profile
self._save_to_file()
return True
except Exception as e:
print(f"Error saving student profile: {e}")
return False
def get_student_profile(self, student_id: str) -> Optional[StudentProfile]:
"""Get a student profile by ID."""
with self._lock:
return self.student_profiles.get(student_id)
def update_student_profile(self, student_id: str, updates: Dict[str, Any]) -> bool:
"""Update a student profile with new data."""
with self._lock:
try:
if student_id not in self.student_profiles:
return False
profile = self.student_profiles[student_id]
# Update profile attributes
for key, value in updates.items():
if hasattr(profile, key):
setattr(profile, key, value)
profile.last_updated = datetime.utcnow()
self._save_to_file()
return True
except Exception as e:
print(f"Error updating student profile: {e}")
return False
def delete_student_profile(self, student_id: str) -> bool:
"""Delete a student profile."""
with self._lock:
try:
if student_id in self.student_profiles:
del self.student_profiles[student_id]
self._save_to_file()
return True
return False
except Exception as e:
print(f"Error deleting student profile: {e}")
return False
def list_student_profiles(self, active_only: bool = False,
days: int = 30) -> List[StudentProfile]:
"""List student profiles, optionally filtering by activity."""
with self._lock:
profiles = list(self.student_profiles.values())
if active_only:
cutoff_date = datetime.utcnow() - timedelta(days=days)
profiles = [
p for p in profiles
if p.last_active and p.last_active >= cutoff_date
]
return profiles
# Performance Data Operations
def save_performance_data(self, student_id: str, concept_id: str,
data: Dict[str, Any]) -> bool:
"""Save performance data for a student and concept."""
with self._lock:
try:
if student_id not in self.performance_data:
self.performance_data[student_id] = {}
self.performance_data[student_id][concept_id] = {
**data,
'last_updated': datetime.utcnow().isoformat()
}
self._save_to_file()
return True
except Exception as e:
print(f"Error saving performance data: {e}")
return False
def get_performance_data(self, student_id: str,
concept_id: Optional[str] = None) -> Optional[Dict[str, Any]]:
"""Get performance data for a student and optionally a specific concept."""
with self._lock:
if student_id not in self.performance_data:
return None
if concept_id:
return self.performance_data[student_id].get(concept_id)
else:
return self.performance_data[student_id]
def update_performance_data(self, student_id: str, concept_id: str,
updates: Dict[str, Any]) -> bool:
"""Update performance data for a student and concept."""
with self._lock:
try:
if student_id not in self.performance_data:
self.performance_data[student_id] = {}
if concept_id not in self.performance_data[student_id]:
self.performance_data[student_id][concept_id] = {}
self.performance_data[student_id][concept_id].update(updates)
self.performance_data[student_id][concept_id]['last_updated'] = datetime.utcnow().isoformat()
self._save_to_file()
return True
except Exception as e:
print(f"Error updating performance data: {e}")
return False
# Session Data Operations
def save_session_data(self, session_id: str, data: Dict[str, Any]) -> bool:
"""Save session data."""
with self._lock:
try:
self.session_data[session_id] = {
**data,
'saved_at': datetime.utcnow().isoformat()
}
self._save_to_file()
return True
except Exception as e:
print(f"Error saving session data: {e}")
return False
def get_session_data(self, session_id: str) -> Optional[Dict[str, Any]]:
"""Get session data by ID."""
with self._lock:
return self.session_data.get(session_id)
def delete_session_data(self, session_id: str) -> bool:
"""Delete session data."""
with self._lock:
try:
if session_id in self.session_data:
del self.session_data[session_id]
self._save_to_file()
return True
return False
except Exception as e:
print(f"Error deleting session data: {e}")
return False
def cleanup_old_sessions(self, days: int = 7) -> int:
"""Clean up old session data."""
with self._lock:
try:
cutoff_date = datetime.utcnow() - timedelta(days=days)
sessions_to_delete = []
for session_id, data in self.session_data.items():
saved_at_str = data.get('saved_at')
if saved_at_str:
saved_at = datetime.fromisoformat(saved_at_str)
if saved_at < cutoff_date:
sessions_to_delete.append(session_id)
for session_id in sessions_to_delete:
del self.session_data[session_id]
if sessions_to_delete:
self._save_to_file()
return len(sessions_to_delete)
except Exception as e:
print(f"Error cleaning up old sessions: {e}")
return 0
# Analytics Cache Operations
def cache_analytics_result(self, cache_key: str, data: Dict[str, Any],
ttl_minutes: int = 60) -> bool:
"""Cache analytics result with TTL."""
with self._lock:
try:
expiry_time = datetime.utcnow() + timedelta(minutes=ttl_minutes)
self.analytics_cache[cache_key] = {
'data': data,
'expires_at': expiry_time.isoformat(),
'cached_at': datetime.utcnow().isoformat()
}
return True
except Exception as e:
print(f"Error caching analytics result: {e}")
return False
def get_cached_analytics(self, cache_key: str) -> Optional[Dict[str, Any]]:
"""Get cached analytics result if not expired."""
with self._lock:
if cache_key not in self.analytics_cache:
return None
cached_item = self.analytics_cache[cache_key]
expires_at = datetime.fromisoformat(cached_item['expires_at'])
if datetime.utcnow() > expires_at:
# Cache expired, remove it
del self.analytics_cache[cache_key]
return None
return cached_item['data']
def clear_analytics_cache(self, pattern: Optional[str] = None) -> int:
"""Clear analytics cache, optionally matching a pattern."""
with self._lock:
try:
if pattern is None:
count = len(self.analytics_cache)
self.analytics_cache.clear()
return count
else:
keys_to_delete = [
key for key in self.analytics_cache.keys()
if pattern in key
]
for key in keys_to_delete:
del self.analytics_cache[key]
return len(keys_to_delete)
except Exception as e:
print(f"Error clearing analytics cache: {e}")
return 0
# Adaptation History Operations
def add_adaptation_record(self, student_id: str, record: Dict[str, Any]) -> bool:
"""Add an adaptation record for a student."""
with self._lock:
try:
self.adaptation_history[student_id].append({
**record,
'recorded_at': datetime.utcnow().isoformat()
})
# Keep only last 100 records per student
if len(self.adaptation_history[student_id]) > 100:
self.adaptation_history[student_id] = self.adaptation_history[student_id][-100:]
self._save_to_file()
return True
except Exception as e:
print(f"Error adding adaptation record: {e}")
return False
def get_adaptation_history(self, student_id: str,
days: Optional[int] = None) -> List[Dict[str, Any]]:
"""Get adaptation history for a student."""
with self._lock:
if student_id not in self.adaptation_history:
return []
records = self.adaptation_history[student_id]
if days is not None:
cutoff_date = datetime.utcnow() - timedelta(days=days)
records = [
record for record in records
if datetime.fromisoformat(record['recorded_at']) >= cutoff_date
]
return records
# Utility Operations
def get_storage_stats(self) -> Dict[str, Any]:
"""Get storage statistics."""
with self._lock:
return {
'student_profiles_count': len(self.student_profiles),
'performance_data_students': len(self.performance_data),
'total_performance_records': sum(
len(concepts) for concepts in self.performance_data.values()
),
'active_sessions': len(self.session_data),
'cached_analytics': len(self.analytics_cache),
'adaptation_records': sum(
len(records) for records in self.adaptation_history.values()
),
'persistence_enabled': self.persistence_file is not None,
'last_updated': datetime.utcnow().isoformat()
}
def export_data(self, format: str = 'json') -> Union[str, bytes]:
"""Export all data in specified format."""
with self._lock:
data = {
'student_profiles': {
sid: profile.to_dict()
for sid, profile in self.student_profiles.items()
},
'performance_data': dict(self.performance_data),
'session_data': self.session_data,
'analytics_cache': dict(self.analytics_cache),
'adaptation_history': dict(self.adaptation_history),
'exported_at': datetime.utcnow().isoformat()
}
if format.lower() == 'json':
return json.dumps(data, indent=2)
elif format.lower() == 'pickle':
return pickle.dumps(data)
else:
raise ValueError(f"Unsupported export format: {format}")
def import_data(self, data: Union[str, bytes], format: str = 'json') -> bool:
"""Import data from specified format."""
with self._lock:
try:
if format.lower() == 'json':
imported_data = json.loads(data)
elif format.lower() == 'pickle':
imported_data = pickle.loads(data)
else:
raise ValueError(f"Unsupported import format: {format}")
# Import student profiles
if 'student_profiles' in imported_data:
for sid, profile_data in imported_data['student_profiles'].items():
profile = StudentProfile.from_dict(profile_data)
self.student_profiles[sid] = profile
# Import other data
if 'performance_data' in imported_data:
self.performance_data.update(imported_data['performance_data'])
if 'session_data' in imported_data:
self.session_data.update(imported_data['session_data'])
if 'analytics_cache' in imported_data:
self.analytics_cache.update(imported_data['analytics_cache'])
if 'adaptation_history' in imported_data:
self.adaptation_history.update(imported_data['adaptation_history'])
self._save_to_file()
return True
except Exception as e:
print(f"Error importing data: {e}")
return False
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