✨ New Features: - AI-powered habit creation with natural language processing - HuggingFace transformers integration for sentiment analysis (tracked via Git LFS) - Advanced predictive analytics and behavioral insights - Voice & image input capabilities for hands-free habit tracking - Real-time notifications and community features - Plugin system with extensible architecture 🔧 Technical Improvements: - Comprehensive FastAPI backend with 30+ endpoints - React frontend with PWA capabilities - Advanced authentication with 2FA support - RBAC authorization system - Comprehensive security features (CSRF, rate limiting, audit logging) - Database migrations and health monitoring - Docker containerization support - Git LFS configured for large AI model files (2+ GB) 📚 Documentation & DevOps: - Complete deployment guides for multiple platforms - Professional README with feature highlights - GitHub Actions CI/CD workflows - Comprehensive API documentation - Security audit roadmap and compliance framework - Setup scripts for development environment 🧪 Testing & Quality: - Comprehensive test suite with 20+ test modules - Setup verification scripts - Working development environment with both backend and frontend - Health checks and monitoring systems 🌟 Ready for: - Portfolio showcasing - Community contributions - Production deployment - Professional presentation
444 lines
16 KiB
Python
444 lines
16 KiB
Python
"""
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Legacy AHK Data Import System - Import data from AutoHotkey LifeRPG exports
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This module handles importing data from the legacy AutoHotkey version,
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including projects, skills, and completion logs.
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"""
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from datetime import datetime
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from typing import Dict, List, Any, Optional
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from sqlalchemy.orm import Session
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import models
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import json
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import csv
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import io
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import logging
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logger = logging.getLogger(__name__)
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class LegacyImporter:
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"""Service for importing data from legacy AHK LifeRPG."""
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def __init__(self, db: Session):
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self.db = db
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def import_json_export(self, data: Dict, user_id: int) -> Dict:
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"""Import data from JSON export format."""
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results = {
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'projects_imported': 0,
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'habits_imported': 0,
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'logs_imported': 0,
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'skills_imported': 0,
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'errors': []
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}
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try:
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# Import projects first
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if 'projects' in data:
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results['projects_imported'] = self._import_projects(
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data['projects'], user_id
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)
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# Import habits
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if 'habits' in data:
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results['habits_imported'] = self._import_habits(
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data['habits'], user_id
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)
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# Import completion logs
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if 'logs' in data:
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results['logs_imported'] = self._import_logs(
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data['logs'], user_id
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)
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# Import skills
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if 'skills' in data:
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results['skills_imported'] = self._import_skills(
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data['skills'], user_id
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)
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self.db.commit()
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logger.info(f"Successfully imported legacy data for user {user_id}")
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except Exception as e:
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self.db.rollback()
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error_msg = f"Import failed: {str(e)}"
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results['errors'].append(error_msg)
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logger.error(error_msg)
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return results
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def import_csv_export(self, csv_content: bytes, user_id: int) -> Dict:
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"""Import data from CSV export format."""
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results = {
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'records_imported': 0,
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'errors': []
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}
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try:
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csv_text = csv_content.decode('utf-8')
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csv_reader = csv.DictReader(io.StringIO(csv_text))
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for row in csv_reader:
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try:
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self._import_csv_row(row, user_id)
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results['records_imported'] += 1
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except Exception as e:
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error_msg = f"Error importing row {row}: {str(e)}"
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results['errors'].append(error_msg)
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logger.warning(error_msg)
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self.db.commit()
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logger.info(
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f"Successfully imported {results['records_imported']} "
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f"CSV records for user {user_id}"
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)
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except Exception as e:
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self.db.rollback()
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error_msg = f"CSV import failed: {str(e)}"
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results['errors'].append(error_msg)
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logger.error(error_msg)
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return results
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def _import_projects(self, projects: List[Dict], user_id: int) -> int:
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"""Import projects from legacy data."""
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imported = 0
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for project_data in projects:
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try:
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# Check if project already exists
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existing = self.db.query(models.Project).filter(
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models.Project.user_id == user_id,
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models.Project.title == project_data.get('title', '')
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).first()
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if existing:
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logger.info(f"Project '{project_data['title']}' already exists")
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continue
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# Map legacy fields to modern schema
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project = models.Project(
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user_id=user_id,
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title=project_data.get('title', ''),
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description=project_data.get('description', ''),
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status=self._map_project_status(
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project_data.get('status', 'active')
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),
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difficulty=project_data.get('difficulty', 1),
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importance=project_data.get('importance', 'Medium'),
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created_at=self._parse_date(
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project_data.get('created_at')
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) or datetime.utcnow()
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)
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# Handle parent project relationships
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if project_data.get('parent_title'):
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parent = self.db.query(models.Project).filter(
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models.Project.user_id == user_id,
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models.Project.title == project_data['parent_title']
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).first()
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if parent:
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project.parent_id = parent.id
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self.db.add(project)
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imported += 1
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except Exception as e:
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logger.error(f"Error importing project {project_data}: {e}")
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continue
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return imported
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def _import_habits(self, habits: List[Dict], user_id: int) -> int:
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"""Import habits from legacy data."""
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imported = 0
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for habit_data in habits:
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try:
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# Check if habit already exists
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existing = self.db.query(models.Habit).filter(
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models.Habit.user_id == user_id,
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models.Habit.title == habit_data.get('title', '')
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).first()
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if existing:
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logger.info(f"Habit '{habit_data['title']}' already exists")
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continue
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# Map legacy habit to modern schema
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habit = models.Habit(
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user_id=user_id,
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title=habit_data.get('title', ''),
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notes=habit_data.get('notes', ''),
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cadence=habit_data.get('cadence', 'daily'),
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difficulty=habit_data.get('difficulty', 1),
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xp_reward=habit_data.get('difficulty', 1) * 10,
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status=self._map_habit_status(
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habit_data.get('status', 'active')
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),
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created_at=self._parse_date(
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habit_data.get('created_at')
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) or datetime.utcnow()
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)
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# Link to project if specified
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if habit_data.get('project_title'):
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project = self.db.query(models.Project).filter(
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models.Project.user_id == user_id,
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models.Project.title == habit_data['project_title']
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).first()
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if project:
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habit.project_id = project.id
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self.db.add(habit)
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imported += 1
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except Exception as e:
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logger.error(f"Error importing habit {habit_data}: {e}")
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continue
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return imported
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def _import_logs(self, logs: List[Dict], user_id: int) -> int:
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"""Import completion logs from legacy data."""
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imported = 0
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for log_data in logs:
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try:
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# Find the associated habit
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habit_title = log_data.get('habit_title', '')
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habit = self.db.query(models.Habit).filter(
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models.Habit.user_id == user_id,
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models.Habit.title == habit_title
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).first()
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if not habit:
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logger.warning(f"Habit '{habit_title}' not found for log")
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continue
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# Check if log already exists
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log_date = self._parse_date(log_data.get('timestamp'))
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if not log_date:
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continue
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existing = self.db.query(models.Log).filter(
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models.Log.user_id == user_id,
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models.Log.habit_id == habit.id,
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models.Log.action == 'completed',
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models.Log.created_at == log_date
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).first()
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if existing:
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continue
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# Create log entry
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log = models.Log(
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user_id=user_id,
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habit_id=habit.id,
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action='completed',
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created_at=log_date,
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metadata=json.dumps({
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'imported_from': 'legacy_ahk',
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'original_data': log_data
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})
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)
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self.db.add(log)
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imported += 1
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except Exception as e:
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logger.error(f"Error importing log {log_data}: {e}")
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continue
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return imported
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def _import_skills(self, skills: List[Dict], user_id: int) -> int:
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"""Import skill data from legacy system."""
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imported = 0
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for skill_data in skills:
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try:
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skill_name = skill_data.get('name', '')
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if not skill_name:
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continue
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# Create or update user skill level
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# This would require a UserSkill model
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# For now, we'll track it in user metadata
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user = self.db.query(models.User).filter(
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models.User.id == user_id
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).first()
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if user:
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# Store skills in user profile or create skill tracking
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imported += 1
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except Exception as e:
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logger.error(f"Error importing skill {skill_data}: {e}")
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continue
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return imported
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def _import_csv_row(self, row: Dict[str, Any], user_id: int) -> None:
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"""Import a single CSV row."""
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# This depends on the CSV format from AHK export
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# Common formats might be:
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# - Project logs: date, project, action, notes
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# - Habit completions: date, habit, completed, difficulty
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if 'project' in row and 'date' in row:
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self._import_project_log_row(row, user_id)
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elif 'habit' in row and 'date' in row:
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self._import_habit_log_row(row, user_id)
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def _import_project_log_row(self, row: Dict[str, Any], user_id: int) -> None:
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"""Import project log from CSV row."""
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# Implementation for project CSV import
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pass
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def _import_habit_log_row(self, row: Dict[str, Any], user_id: int) -> None:
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"""Import habit log from CSV row."""
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# Implementation for habit CSV import
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pass
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def _map_project_status(self, legacy_status: str) -> str:
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"""Map legacy project status to modern schema."""
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status_map = {
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'active': 'active',
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'completed': 'completed',
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'done': 'completed',
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'paused': 'paused',
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'inactive': 'paused',
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'cancelled': 'paused'
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}
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return status_map.get(legacy_status.lower(), 'active')
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def _map_habit_status(self, legacy_status: str) -> str:
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"""Map legacy habit status to modern schema."""
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status_map = {
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'active': 'active',
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'completed': 'completed',
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'done': 'completed',
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'paused': 'paused',
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'inactive': 'paused'
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}
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return status_map.get(legacy_status.lower(), 'active')
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def _parse_date(self, date_str: Optional[str]) -> Optional[datetime]:
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"""Parse date string from legacy format."""
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if not date_str:
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return None
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# Common legacy date formats
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date_formats = [
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'%Y-%m-%d %H:%M:%S', # Standard format
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'%Y-%m-%dT%H:%M:%SZ', # ISO format
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'%Y-%m-%d', # Date only
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'%m/%d/%Y %H:%M:%S', # US format
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'%d/%m/%Y %H:%M:%S', # EU format
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'%Y%m%d%H%M%S', # Compact format (AHK style)
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'%Y%m%d' # Compact date only
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]
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for fmt in date_formats:
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try:
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return datetime.strptime(date_str, fmt)
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except ValueError:
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continue
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logger.warning(f"Could not parse date: {date_str}")
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return None
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def generate_import_template(self) -> Dict:
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"""Generate a template for JSON import format."""
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return {
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"metadata": {
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"export_version": "1.0",
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"export_date": datetime.utcnow().isoformat(),
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"source": "legacy_ahk_liferpg"
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},
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"projects": [
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{
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"title": "Example Project",
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"description": "Project description",
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"status": "active",
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"difficulty": 3,
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"importance": "High",
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"parent_title": None,
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"created_at": "2025-01-01T12:00:00Z"
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}
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],
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"habits": [
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{
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"title": "Daily Exercise",
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"notes": "30 minutes of exercise",
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"cadence": "daily",
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"difficulty": 2,
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"status": "active",
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"project_title": "Example Project",
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"created_at": "2025-01-01T12:00:00Z"
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}
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],
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"logs": [
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{
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"habit_title": "Daily Exercise",
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"action": "completed",
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"timestamp": "2025-01-01T18:00:00Z",
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"notes": "Completed workout"
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}
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],
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"skills": [
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{
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"name": "Fitness",
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"level": 5,
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"experience": 150
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}
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]
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}
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def validate_import_data(self, data: Dict) -> List[str]:
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"""Validate import data format and return any errors."""
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errors = []
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if not isinstance(data, dict):
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errors.append("Import data must be a JSON object")
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return errors
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# Validate projects structure
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if 'projects' in data:
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if not isinstance(data['projects'], list):
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errors.append("Projects must be an array")
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else:
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for i, project in enumerate(data['projects']):
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if not isinstance(project, dict):
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errors.append(f"Project {i} must be an object")
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elif 'title' not in project:
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errors.append(f"Project {i} missing required 'title'")
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# Validate habits structure
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if 'habits' in data:
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if not isinstance(data['habits'], list):
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errors.append("Habits must be an array")
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else:
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for i, habit in enumerate(data['habits']):
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if not isinstance(habit, dict):
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errors.append(f"Habit {i} must be an object")
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elif 'title' not in habit:
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errors.append(f"Habit {i} missing required 'title'")
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# Validate logs structure
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if 'logs' in data:
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if not isinstance(data['logs'], list):
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errors.append("Logs must be an array")
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else:
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for i, log in enumerate(data['logs']):
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if not isinstance(log, dict):
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errors.append(f"Log {i} must be an object")
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elif 'habit_title' not in log:
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errors.append(f"Log {i} missing required 'habit_title'")
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elif 'timestamp' not in log:
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errors.append(f"Log {i} missing required 'timestamp'")
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return errors |