基于Python实现实时监控CPU使用率

import matplotlib.pyplot as plt
import matplotlib.font_manager as font_manager
import psutil as p


POINTS = 300
fig, ax = plt.subplots()
ax.set_ylim([0, 100])
ax.set_xlim([0, POINTS])
ax.set_autoscale_on(False)
ax.set_xticks([])
ax.set_yticks(range(0, 101, 10))
ax.grid(True)
# 执行用户进程的时间百分比
user = [None] * POINT
# 执行内核进程和中断的时间百分比
sys = [None] * POINT
# CPU处于空闲状态的时间百分比
idle = [None] * POINT
l_user, = ax.plot(range(POINTS), user, label='User %')
l_sys, = ax.plot(range(POINTS), sys, label='Sys %')
l_idle, = ax.plot(range(POINTS), idle, label='Idle %')
ax.legend(loc='upper center', ncol=4, prop=font_manager.FontProperties(size=10))
bg = fig.canvas.copy_from_bbox(ax.bbox)


def cpu_usage():
	t = p.cpu_times()
	return [t.user, t.system, t.idle]


before = cpu_usage()


def get_cpu_usage():
	global before
	now = cpu_usage()
	delta = [now[i] - before[i] for i in range(len(now))]
	total = sum(delta)
	before = now
	return [(100.0*dt)/(total+0.1) for dt in delta]


def OnTimer(ax):
	global user, sys, idle, bg
	tmp = get_cpu_usage()
	user = user[1:] + [tmp[0]]
	sys = sys[1:] + [tmp[1]]
	idle = idle[1:] + [tmp[2]]
	l_user.set_ydata(user)
	l_sys.set_ydata(sys)
	l_idle.set_ydata(idle)
	while True:
		try:
			ax.draw_artist(l_user)
			ax.draw_artist(l_sys)
			ax.draw_artist(l_idle)
			break
		except:
			pass
	ax.figure.canvas.draw()


def start_monitor():
	timer = fig.canvas.new_timer(interval=100)
	timer.add_callback(OnTimer, ax)
	timer.start()
	plt.show()


if __name__ == '__main__':
	start_monitor()