元组特性与数据库交互：提高数据处理效率

# 创建一个简单的元组
my_tuple = (1, 2, 3, 4, 5)
print(my_tuple)  # 输出: (1, 2, 3, 4, 5)

# 元组中的元素可以是不同类型
mixed_tuple = (1, "hello", 3.14, True)
print(mixed_tuple)  # 输出: (1, 'hello', 3.14, True)
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my_tuple = (1, 2, 3)
try:
    my_tuple[0] = 10  # 尝试修改元组的第一个元素
except TypeError as e:
    print(e)  # 输出: 'tuple' object does not support item assignment
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my_tuple = (1, 2, 3, 4, 5)

# 访问元组中的单个元素
print(my_tuple[0])  # 输出: 1

# 切片操作
print(my_tuple[1:4])  # 输出: (2, 3, 4)
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# 元组解包
a, b, c = (1, 2, 3)
print(a, b, c)  # 输出: 1 2 3

# 使用星号 * 进行解包
first, *rest = (1, 2, 3, 4, 5)
print(first)  # 输出: 1
print(rest)  # 输出: [2, 3, 4, 5]
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import sqlite3

# 连接到 SQLite 数据库
conn = sqlite3.connect(':memory:')  # 使用内存中的临时数据库
cursor = conn.cursor()

# 创建表
cursor.execute('''
CREATE TABLE users (
    id INTEGER PRIMARY KEY,
    name TEXT,
    age INTEGER
)
''')

# 插入数据
cursor.executemany('INSERT INTO users (name, age) VALUES (?, ?)', [
    ('Alice', 30),
    ('Bob', 25),
    ('Charlie', 35)
])

# 查询数据
cursor.execute('SELECT * FROM users')
rows = cursor.fetchall()  # 返回一个包含所有行的列表，每行是一个元组

# 打印查询结果
for row in rows:
    print(row)  # 输出: (1, 'Alice', 30), (2, 'Bob', 25), (3, 'Charlie', 35)

# 关闭连接
conn.close()
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import sqlite3

# 连接到 SQLite 数据库
conn = sqlite3.connect(':memory:')
cursor = conn.cursor()

# 创建表
cursor.execute('''
CREATE TABLE orders (
    id INTEGER PRIMARY KEY,
    product TEXT,
    quantity INTEGER,
    price REAL
)
''')

# 准备要插入的数据
data = [
    ('Apple', 10, 2.5),
    ('Banana', 20, 1.0),
    ('Orange', 15, 1.5)
]

# 使用 executemany 方法批量插入数据
cursor.executemany('INSERT INTO orders (product, quantity, price) VALUES (?, ?, ?)', data)

# 提交事务
conn.commit()

# 查询数据
cursor.execute('SELECT * FROM orders')
rows = cursor.fetchall()

# 打印查询结果
for row in rows:
    print(row)  # 输出: (1, 'Apple', 10, 2.5), (2, 'Banana', 20, 1.0), (3, 'Orange', 15, 1.5)

# 关闭连接
conn.close()
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import csv
import sqlite3

# 读取 CSV 文件中的订单数据
def read_orders_from_csv(file_path):
    orders = []
    with open(file_path, newline='') as csvfile:
        reader = csv.reader(csvfile)
        next(reader)  # 跳过表头
        for row in reader:
            orders.append((row[0], int(row[1]), float(row[2])))
    return orders

# 连接数据库并创建表
def setup_database():
    conn = sqlite3.connect('orders.db')
    cursor = conn.cursor()
    cursor.execute('''
    CREATE TABLE IF NOT EXISTS orders (
        id INTEGER PRIMARY KEY,
        product TEXT,
        quantity INTEGER,
        price REAL
    )
    ''')
    return conn, cursor

# 批量插入订单数据
def insert_orders(conn, cursor, orders):
    cursor.executemany('INSERT INTO orders (product, quantity, price) VALUES (?, ?, ?)', orders)
    conn.commit()

# 查询订单数据
def query_orders(cursor):
    cursor.execute('SELECT * FROM orders')
    rows = cursor.fetchall()
    for row in rows:
        print(row)

# 主函数
def main():
    file_path = 'orders.csv'  # 假设订单数据存储在 orders.csv 文件中
    orders = read_orders_from_csv(file_path)
    
    conn, cursor = setup_database()
    insert_orders(conn, cursor, orders)
    query_orders(cursor)
    
    conn.close()

if __name__ == '__main__':
    main()
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