Python必备shelve与dbm本地持久化存储数据的两个强大工具

import shelve

# 创建一个shelve文件并写入数据
with shelve.open('mydata') as shelf:
    shelf['key1'] = {'name': 'Alice', 'age': 25}
    shelf['key2'] = [1, 2, 3, 4]

# 读取shelve文件中的数据
with shelve.open('mydata') as shelf:
    data1 = shelf['key1']
    data2 = shelf['key2']
    print(data1)
    print(data2)

import dbm

# 创建一个dbm数据库文件并写入数据
with dbm.open('mydb', 'c') as db:
    db['key1'] = 'value1'
    db['key2'] = 'value2'

# 读取dbm数据库中的数据
with dbm.open('mydb', 'r') as db:
    data1 = db['key1']
    data2 = db['key2']
    print(data1)
    print(data2)

import shelve

# 使用shelve存储大型数据集
with shelve.open('largedata') as shelf:
    for i in range(100000):
        shelf[f'key{i}'] = f'value{i}'

# 使用锁处理并发访问
import threading
def write_data(key, value):
    with shelve.open('mydata') as shelf:
        shelf[key] = value
# 创建多个线程同时写入数据
threads = []
for i in range(5):
    thread = threading.Thread(target=write_data, args=(f'key{i}', f'value{i}'))
    threads.append(thread)
    thread.start()
for thread in threads:
    thread.join()