脚本并发问题：脚本并发执行时出现竞争条件，导致问题

#!/bin/bash
 
# 定义锁文件
LOCKFILE="/var/lock/my_script.lock" 
 
# 使用 flock 创建排他锁 
(
    flock -x 200
 
    # 关键代码段
    echo "脚本开始运行"
    sleep 10  # 模拟耗时操作
    echo "脚本结束运行"
 
) 200>"$LOCKFILE"

import fcntl
import time
 
# 定义锁文件
lock_file = open("/var/lock/my_script.lock",  "w")
 
try:
    # 获取排他锁
    fcntl.flock(lock_file,  fcntl.LOCK_EX)
    print("脚本开始运行")
    time.sleep(10)   # 模拟耗时操作
    print("脚本结束运行")
finally:
    # 释放锁
    fcntl.flock(lock_file,  fcntl.LOCK_UN)
    lock_file.close() 

import threading
import time 
 
# 定义信号量
semaphore = threading.Semaphore(1)
 
def critical_section():
    semaphore.acquire() 
    try:
        print("进入关键代码段")
        time.sleep(5)   # 模拟耗时操作
        print("退出关键代码段")
    finally:
        semaphore.release() 
 
# 模拟并发执行
threads = [threading.Thread(target=critical_section) for _ in range(5)]
for t in threads:
    t.start() 
for t in threads:
    t.join() 

START TRANSACTION;
 
-- 更新共享资源
UPDATE resource_table SET value = value + 1 WHERE id = 1;
 
COMMIT;

from sqlalchemy import create_engine
from sqlalchemy.orm  import sessionmaker
 
# 创建数据库连接
engine = create_engine("mysql+pymysql://user:password@host/dbname")
Session = sessionmaker(bind=engine)
session = Session()
 
try:
    # 开始事务 
    session.begin() 
 
    # 更新共享资源
    resource = session.execute("SELECT  * FROM resource_table WHERE id = 1 FOR UPDATE").fetchone()
    session.execute("UPDATE  resource_table SET value = value + 1 WHERE id = 1")
 
    # 提交事务
    session.commit() 
except Exception as e:
    # 回滚事务
    session.rollback() 
    print(f"发生错误: {e}")
finally:
    session.close() 

#!/bin/bash
 
# 最大并发数
MAX_CONCURRENT=1
 
# 检查当前运行的实例数
current_running=$(pgrep -fc "$(basename $0)" || true)
 
if [ "$current_running" -ge "$MAX_CONCURRENT" ]; then
    echo "已有 $current_running 个实例运行，退出"
    exit 1 
fi
 
# 脚本逻辑
echo "脚本开始运行"
sleep 10  # 模拟耗时操作
echo "脚本结束运行"

from concurrent.futures  import ThreadPoolExecutor
import time
 
def task():
    print("任务开始")
    time.sleep(5)   # 模拟耗时操作
    print("任务结束")
 
# 最大并发数
MAX_WORKERS = 2
 
with ThreadPoolExecutor(max_workers=MAX_WORKERS) as executor:
    futures = [executor.submit(task) for _ in range(5)]
    for future in futures:
        future.result()