input: Write a function to generate a sales report from a SQL database and a DataFrame using pandas.
  assert generate_sales_report('example_db.db', 'orders').equals(pd.DataFrame({'product': ['Product1', 'Product2'], 'quantity': [3, 4], 'price': [100, 150], 'total_sales': [300, 600]}))
  assert generate_sales_report('example_db_2.db', 'orders_2').equals(pd.DataFrame({'product': ['Product3', 'Product4'], 'quantity': [5, 6], 'price': [200, 250], 'total_sales': [1000, 1500]}))
  assert generate_sales_report('example_db_3.db', 'orders_3').equals(pd.DataFrame({'product': ['Product5', 'Product6'], 'quantity': [7, 8], 'price': [300, 350], 'total_sales': [2100, 2800]}))
output: import sqlite3
  import pandas as pd
  
  def generate_sales_report(db_name, table_name):
      conn = sqlite3.connect(db_name)
      query = f"SELECT product, quantity, price FROM {table_name}"
      df = pd.read_sql_query(query, conn)
      conn.close()
      df['total_sales'] = df['quantity'] * df['price']
      return df