import sqlite3 import os.path # Static path current_dir = os.path.dirname(os.path.abspath(__file__)) db_path = (current_dir + r"\data\food_data.db") class FoodSearch: """ A class for searching food data in a SQLite database. Methods: search(user_input): Search for food data based on user input. Usage: food_search = FoodSearch() results = food_search.search("apple") """ def __init__(self): if not os.path.exists(db_path): raise FileNotFoundError("Database file not found.") self.db_path = db_path def search(self, user_input) -> list: """ Search for food data based on the user's input. Parameters: user_input (str): The input provided by the user to search for food data. Returns: list: A list of tuples representing the search results from the database. Raises: sqlite3.Error: If there is an error in executing the database query. """ try: with sqlite3.connect(self.db_path) as conn: conn.execute("CREATE INDEX IF NOT EXISTS idx_product_name ON food_data(product_name)") query = "SELECT * FROM food_data WHERE product_name LIKE ? LIMIT 100" user_input = f"%{user_input}%" results = conn.execute(query, (user_input,)).fetchall() return results except sqlite3.Error as e: print(f"Database error: {e}") return [] def nutrient_show(self, product_name) -> dict: """Get nutrient information for a given product name from the food database. Parameters: product_name (str): The name of the product to retrieve nutrient information for. Returns: dict: A dictionary containing nutrient information as key-value pairs, where the keys represent column names and the values represent the corresponding nutrient values. If no matching record is found, an empty dictionary is returned. Raises: sqlite3.Error: If there is an error while accessing the database. """ try: with sqlite3.connect(self.db_path) as conn: cursor = conn.cursor() query = """ SELECT * FROM food_data WHERE product_name = ? """ cursor.execute(query, (product_name,)) result = cursor.fetchone() column_names = [d[0] for d in cursor.description] if result: columns_nutrient = result[16:] data_dict = dict(zip(column_names[16:], columns_nutrient)) return data_dict else: return dict() except sqlite3.Error as e: print(f"Database error: {e}") return []