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Oli Passey
228
src/database.py
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228
src/database.py
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"""
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Database management for price tracking
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"""
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import sqlite3
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from datetime import datetime, timedelta
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from typing import List, Dict, Any, Optional
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import json
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import logging
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logger = logging.getLogger(__name__)
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class DatabaseManager:
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"""Manages SQLite database operations for price tracking."""
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def __init__(self, db_path: str):
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self.db_path = db_path
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self._init_database()
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def _init_database(self):
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"""Initialize database tables."""
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with sqlite3.connect(self.db_path) as conn:
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conn.execute('''
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CREATE TABLE IF NOT EXISTS products (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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name TEXT NOT NULL,
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description TEXT,
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target_price REAL,
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urls TEXT NOT NULL, -- JSON string of site URLs
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created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
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updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
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active BOOLEAN DEFAULT 1
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)
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''')
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conn.execute('''
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CREATE TABLE IF NOT EXISTS price_history (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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product_id INTEGER NOT NULL,
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site_name TEXT NOT NULL,
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price REAL NOT NULL,
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currency TEXT DEFAULT 'GBP',
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availability BOOLEAN DEFAULT 1,
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timestamp TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
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FOREIGN KEY (product_id) REFERENCES products (id)
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)
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''')
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conn.execute('''
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CREATE TABLE IF NOT EXISTS price_alerts (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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product_id INTEGER NOT NULL,
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site_name TEXT NOT NULL,
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alert_price REAL NOT NULL,
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triggered_at TIMESTAMP,
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notified BOOLEAN DEFAULT 0,
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FOREIGN KEY (product_id) REFERENCES products (id)
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)
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''')
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conn.execute('''
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CREATE INDEX IF NOT EXISTS idx_price_history_product_id
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ON price_history (product_id)
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''')
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conn.execute('''
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CREATE INDEX IF NOT EXISTS idx_price_history_timestamp
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ON price_history (timestamp)
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''')
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def add_product(self, name: str, urls: Dict[str, str],
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description: str = None, target_price: float = None) -> int:
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"""Add a new product to track."""
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urls_json = json.dumps(urls)
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with sqlite3.connect(self.db_path) as conn:
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cursor = conn.execute('''
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INSERT INTO products (name, description, target_price, urls)
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VALUES (?, ?, ?, ?)
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''', (name, description, target_price, urls_json))
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product_id = cursor.lastrowid
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logger.info(f"Added product: {name} (ID: {product_id})")
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return product_id
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def get_product(self, product_id: int) -> Optional[Dict[str, Any]]:
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"""Get product by ID."""
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with sqlite3.connect(self.db_path) as conn:
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conn.row_factory = sqlite3.Row
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cursor = conn.execute('''
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SELECT * FROM products WHERE id = ? AND active = 1
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''', (product_id,))
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row = cursor.fetchone()
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if row:
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product = dict(row)
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product['urls'] = json.loads(product['urls'])
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return product
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return None
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def get_all_products(self) -> List[Dict[str, Any]]:
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"""Get all active products."""
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with sqlite3.connect(self.db_path) as conn:
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conn.row_factory = sqlite3.Row
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cursor = conn.execute('''
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SELECT * FROM products WHERE active = 1 ORDER BY name
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''')
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products = []
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for row in cursor.fetchall():
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product = dict(row)
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product['urls'] = json.loads(product['urls'])
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products.append(product)
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return products
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def update_product(self, product_id: int, **kwargs):
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"""Update product information."""
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allowed_fields = ['name', 'description', 'target_price', 'urls']
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updates = []
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values = []
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for field, value in kwargs.items():
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if field in allowed_fields:
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if field == 'urls':
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value = json.dumps(value)
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updates.append(f"{field} = ?")
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values.append(value)
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if not updates:
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return
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updates.append("updated_at = ?")
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values.append(datetime.now())
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values.append(product_id)
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with sqlite3.connect(self.db_path) as conn:
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conn.execute(f'''
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UPDATE products SET {', '.join(updates)} WHERE id = ?
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''', values)
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def deactivate_product(self, product_id: int):
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"""Deactivate a product (soft delete)."""
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with sqlite3.connect(self.db_path) as conn:
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conn.execute('''
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UPDATE products SET active = 0, updated_at = ? WHERE id = ?
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''', (datetime.now(), product_id))
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def save_price_history(self, product_id: int, site_name: str, price: float,
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currency: str = 'GBP', availability: bool = True,
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timestamp: datetime = None):
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"""Save price history entry."""
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if timestamp is None:
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timestamp = datetime.now()
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with sqlite3.connect(self.db_path) as conn:
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conn.execute('''
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INSERT INTO price_history
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(product_id, site_name, price, currency, availability, timestamp)
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VALUES (?, ?, ?, ?, ?, ?)
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''', (product_id, site_name, price, currency, availability, timestamp))
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def get_price_history(self, product_id: int, days: int = 30) -> List[Dict[str, Any]]:
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"""Get price history for a product."""
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start_date = datetime.now() - timedelta(days=days)
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with sqlite3.connect(self.db_path) as conn:
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conn.row_factory = sqlite3.Row
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cursor = conn.execute('''
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SELECT * FROM price_history
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WHERE product_id = ? AND timestamp >= ?
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ORDER BY timestamp DESC
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''', (product_id, start_date))
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return [dict(row) for row in cursor.fetchall()]
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def get_latest_prices(self, product_id: int) -> Dict[str, Dict[str, Any]]:
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"""Get latest price for each site for a product."""
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with sqlite3.connect(self.db_path) as conn:
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conn.row_factory = sqlite3.Row
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cursor = conn.execute('''
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SELECT DISTINCT site_name,
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FIRST_VALUE(price) OVER (PARTITION BY site_name ORDER BY timestamp DESC) as price,
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FIRST_VALUE(currency) OVER (PARTITION BY site_name ORDER BY timestamp DESC) as currency,
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FIRST_VALUE(availability) OVER (PARTITION BY site_name ORDER BY timestamp DESC) as availability,
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FIRST_VALUE(timestamp) OVER (PARTITION BY site_name ORDER BY timestamp DESC) as timestamp
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FROM price_history
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WHERE product_id = ?
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''', (product_id,))
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result = {}
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for row in cursor.fetchall():
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result[row['site_name']] = {
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'price': row['price'],
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'currency': row['currency'],
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'availability': bool(row['availability']),
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'timestamp': row['timestamp']
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}
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return result
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def get_price_statistics(self, product_id: int, days: int = 30) -> Dict[str, Any]:
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"""Get price statistics for a product."""
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start_date = datetime.now() - timedelta(days=days)
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with sqlite3.connect(self.db_path) as conn:
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cursor = conn.execute('''
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SELECT site_name,
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MIN(price) as min_price,
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MAX(price) as max_price,
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AVG(price) as avg_price,
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COUNT(*) as data_points
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FROM price_history
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WHERE product_id = ? AND timestamp >= ?
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GROUP BY site_name
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''', (product_id, start_date))
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stats = {}
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for row in cursor.fetchall():
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stats[row[0]] = {
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'min_price': row[1],
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'max_price': row[2],
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'avg_price': round(row[3], 2),
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'data_points': row[4]
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}
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return stats
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