Log a timestamp when memory usage is over 90%, per minute.

memory_log.py

from apscheduler.schedulers.blocking import BlockingScheduler
# APScheduler库用于定时执行，BlockingScheduler为前台运行的定时器
from psutil import virtual_memory
from datetime import datetime

def main():
    memory = virtual_memory()
    occ_rate = memory.used / memory.total
    # 若内存占用率大于90%：
    if occ_rate > 0.9:
        # With关键字实现写入文件并自动关闭，a+模式为附加到文件最后，若文件不存在新建
        with open('memory_log.txt', mode='a+') as f:
            # f-string格式化字符串写起来更短
            f.write(f'{datetime.now():%Y-%m-%d %H:%M:%S}: {occ_rate*100:.2f}%\n')

if __name__ == '__main__':
    # 新建一个定时器
    scheduler = BlockingScheduler()
    # 加入定时运行的任务，间隔1分钟执行一次
    scheduler.add_job(main, 'interval', minutes=1)
    # 定时器开跑
    scheduler.start()