psutil用法可参考:https://blog.csdn.net/qq_45689245/article/details/125409744
对于多进程应用,调用p.cpu_percent()函数会出现值大于100的情况,给人一种不太准确的感觉。
为解决该问题,以统计谷歌浏览器CPU占用情况为例,相关处理逻辑如下:
import psutil
if __name__ == "__main__":
"""
value = p.cpu_percent(interval=1)
A value > 100.0 can be returned in case of processes running
multiple threads on different CPU cores.
The returned value is explicitly NOT split evenly between
all available logical CPUs. This means that a busy loop process
running on a system with 2 logical CPUs will be reported as
having 100% CPU utilization instead of 50%.
"""
print("逻辑CPU核数:", psutil.cpu_count())
print("物理CPU核数:", psutil.cpu_count(logical=False))
print("CPU的用户、系统、空闲时间:", psutil.cpu_times())
print("获取每个CPU的使用率,类似TOP命令:", psutil.cpu_percent(percpu=True))
# 设置每秒刷新时间间隔,统计十次的结果
# top = [psutil.cpu_percent(interval=1, percpu=True) for i in range(10)]
# print(top)
logic_cpu_num = psutil.cpu_count()
physic_cpu_num = psutil.cpu_count(logical=False)
total_logic_cpu_usage = 0
total_physic_cpu_usage = 0
works = psutil.process_iter()
app_name = "chrome.exe"
for p in works:
if p.name() == app_name:
if p.is_running():
with p.oneshot():
pid = p.pid
process = psutil.Process(pid=pid)
cpu_usage = process.cpu_percent(interval=0.1)
print("cpu:", cpu_usage, round(cpu_usage / logic_cpu_num, 2))
print("#threads:", process.num_threads())
total_logic_cpu_usage += cpu_usage / logic_cpu_num
total_physic_cpu_usage += cpu_usage / physic_cpu_num
print(f"[{app_name}]逻辑CPU 占用: {round(total_logic_cpu_usage, 2)}%")
print(f"[{app_name}]物理CPU 占用: {round(total_physic_cpu_usage, 2)}%")