我想使用mysql表中的数据在pyqt中制作一个实时图,但我不确定如何。该表将每秒更新一次,并具有CPU百分比(例如2.5,3.5,4.5)。我不知道如何使用mysql中的数据制作实时图表。
我在下面制作了一个简单的matplotlib图。我试图合并mysql数据,但我无法满足这个实时图的需要。
import sys
from PyQt4 import QtGui
from matplotlib.figure import Figure
from matplotlib.backends.backend_qt4agg \
import FigureCanvasQTAgg as FigureCanvas
import psutil as p
# Total number of iterations
MAXITERS = 2000
class CPUMonitor(FigureCanvas):
"""Matplotlib Figure widget to display CPU utilization"""
def __init__(self):
# save the current CPU info (used by updating algorithm)
self.before = self.prepare_cpu_usage()
# first image setup
self.fig = Figure()
self.ax = self.fig.add_subplot(111)
# initialization of the canvas
FigureCanvas.__init__(self, self.fig)
# set specific limits for X and Y axes
self.ax.set_xlim(0, 2000)
self.ax.set_ylim(0, 100)
# and disable figure-wide autoscale
self.ax.set_autoscale_on(False)
# generates first "empty" plots
self.user, self.nice, self.sys, self.idle =[], [], [], []
self.l_user, = self.ax.plot([],self.user, label='User %')
self.l_nice, = self.ax.plot([],self.nice, label='Nice %')
self.l_sys, = self.ax.plot([],self.sys, label='Sys %')
self.l_idle, = self.ax.plot([],self.idle, label='Idle %')
# add legend to plot
self.ax.legend()
# force a redraw of the Figure
self.fig.canvas.draw()
# initialize the iteration counter
self.cnt = 0
# call the update method (to speed-up visualization)
self.timerEvent(None)
# start timer, trigger event every 1000 millisecs (=1sec)
self.timer = self.startTimer(1000)
def prepare_cpu_usage(self):
"""helper function to return CPU usage info"""
# get the CPU times using psutil module
t = p.cpu_times()
# return only the values we're interested in
if hasattr(t, 'nice'):
return [t.user, t.nice, t.system, t.idle]
else:
# special case focr Windows, without 'nice' value
return [t.user, 0, t.system, t.idle]
def get_cpu_usage(self):
"""Compute CPU usage comparing previous and current measurements"""
# take the current CPU usage information
now = self.prepare_cpu_usage()
# compute delta between current and previous measurements
delta = [now[i]-self.before[i] for i in range(len(now))]
# compute the total (needed for percentages calculation)
total = sum(delta)
# save the current measurement to before object
self.before = now
# return the percentage of CPU usage for our 4 categories
return [(100.0*dt)/total for dt in delta]
def timerEvent(self, evt):
# get the cpu percentage usage
result = self.get_cpu_usage()
# append new data to the datasets
self.user.append(result[0])
self.nice.append(result[1])
self.sys.append( result[2])
self.idle.append(result[3])
# update lines data using the lists with new data
self.l_user.set_data(range(len(self.user)), self.user)
self.l_nice.set_data(range(len(self.nice)), self.nice)
self.l_sys.set_data( range(len(self.sys)), self.sys)
self.l_idle.set_data(range(len(self.idle)), self.idle)
# force a redraw of the Figure
self.fig.canvas.draw()
if self.cnt == MAXITERS:
# stop the timer
self.killTimer(self.timer)
else:
#else, we increment the counter
self.cnt += 1
# create the GUI application
widget = CPUMonitor()
widget.setWindowTitle("30 Seconds of CPU Usage Updated in RealTime")
widget.show()
sys.exit(app.exec_())
答案 0 :(得分:0)
一种选择是在无限循环中运行它。循环每秒都会检查表,然后每次都重新绘制matplotlib图。
虽然这不是一个非常有效的解决方案。