{"id":1157397,"date":"2025-01-13T18:28:11","date_gmt":"2025-01-13T10:28:11","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1157397.html"},"modified":"2025-01-13T18:28:14","modified_gmt":"2025-01-13T10:28:14","slug":"%e5%a6%82%e4%bd%95%e7%94%a8python%e5%ae%9e%e6%97%b6%e7%9b%91%e6%8e%a7","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1157397.html","title":{"rendered":"\u5982\u4f55\u7528python\u5b9e\u65f6\u76d1\u63a7"},"content":{"rendered":"

\"\u5982\u4f55\u7528python\u5b9e\u65f6\u76d1\u63a7\"<\/p>\n

\u5982\u4f55\u7528Python\u5b9e\u65f6\u76d1\u63a7\uff1a\u4f7f\u7528\u7cfb\u7edf\u76d1\u63a7\u5de5\u5177\u3001\u7f16\u5199\u81ea\u5b9a\u4e49\u811a\u672c\u3001\u5229\u7528\u7b2c\u4e09\u65b9\u5e93\u3001\u5b9e\u73b0\u6570\u636e\u53ef\u89c6\u5316\u3002<\/strong> \u5728\u8fd9\u51e0\u79cd\u65b9\u6cd5\u4e2d\uff0c\u5229\u7528\u7b2c\u4e09\u65b9\u5e93\u662f\u6700\u4e3a\u9ad8\u6548\u4e14\u7075\u6d3b\u7684\u65b9\u5f0f\u3002Python\u6709\u8bb8\u591a\u5f3a\u5927\u7684\u5e93\u53ef\u4ee5\u7528\u4e8e\u5b9e\u65f6\u76d1\u63a7\uff0c\u5982psutil\u3001py-cpuinfo\u7b49\uff0c\u53ef\u4ee5\u65b9\u4fbf\u5730\u83b7\u53d6\u7cfb\u7edf\u7684\u5404\u9879\u6027\u80fd\u6307\u6807\uff0c\u5e76\u4e14\u901a\u8fc7\u7ed3\u5408matplotlib\u3001plotly\u7b49\u53ef\u89c6\u5316\u5de5\u5177\uff0c\u53ef\u4ee5\u5b9e\u65f6\u5c55\u793a\u8fd9\u4e9b\u6570\u636e\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u4f7f\u7528\u7cfb\u7edf\u76d1\u63a7\u5de5\u5177<\/h3>\n<\/p>\n

1. Psutil\u5e93<\/h4>\n<\/p>\n

Psutil\uff08Python system and process utilities\uff09\u662f\u4e00\u4e2a\u8de8\u5e73\u53f0\u5e93\uff0c\u80fd\u591f\u8f7b\u677e\u83b7\u53d6\u7cfb\u7edf\u8fd0\u884c\u65f6\u7684\u5404\u79cd\u6027\u80fd\u6307\u6807\uff0c\u5982CPU\u4f7f\u7528\u7387\u3001\u5185\u5b58\u4f7f\u7528\u7387\u3001\u78c1\u76d8\u8bfb\u5199\u901f\u7387\u3001\u7f51\u7edc\u6d41\u91cf\u7b49\u3002\u5b83\u63d0\u4f9b\u4e86\u4e00\u4e2a\u65b9\u4fbf\u7684\u63a5\u53e3\u6765\u83b7\u53d6\u7cfb\u7edf\u4fe1\u606f\u5e76\u8fdb\u884c\u5b9e\u65f6\u76d1\u63a7\u3002<\/p>\n<\/p>\n

import psutil<\/p>\n
import time<\/p>\n
def monitor_system(interval=1):<\/p>\n
    while True:<\/p>\n
        cpu_usage = psutil.cpu_percent(interval=interval)<\/p>\n
        memory_info = psutil.virtual_memory()<\/p>\n
        disk_usage = psutil.disk_usage('\/')<\/p>\n
        net_io = psutil.net_io_counters()<\/p>\n
        print(f"CPU Usage: {cpu_usage}%")<\/p>\n
        print(f"Memory Usage: {memory_info.percent}%")<\/p>\n
        print(f"Disk Usage: {disk_usage.percent}%")<\/p>\n
        print(f"Network Sent: {net_io.bytes_sent} bytes, Received: {net_io.bytes_recv} bytes")<\/p>\n
        time.sleep(interval)<\/p>\n
Call the function to start monitoring<\/strong><\/h2>\n
monitor_system()<\/p>\n
<\/code><\/pre>\n<\/p>\n
2. Py-cpuinfo\u5e93<\/h4>\n<\/p>\n
Py-cpuinfo\u662f\u4e00\u4e2a\u4e13\u95e8\u7528\u4e8e\u83b7\u53d6CPU\u4fe1\u606f\u7684\u5e93\u3002\u5b83\u53ef\u4ee5\u83b7\u53d6\u5305\u62ecCPU\u578b\u53f7\u3001\u67b6\u6784\u3001\u9891\u7387\u7b49\u8be6\u7ec6\u4fe1\u606f\uff0c\u975e\u5e38\u9002\u5408\u9700\u8981\u76d1\u63a7CPU\u72b6\u6001\u7684\u573a\u666f\u3002<\/p>\n<\/p>\n
import cpuinfo<\/p>\n
def get_cpu_info():<\/p>\n
    info = cpuinfo.get_cpu_info()<\/p>\n
    for key, value in info.items():<\/p>\n
        print(f"{key}: {value}")<\/p>\n
Call the function to get CPU information<\/strong><\/h2>\n
get_cpu_info()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e8c\u3001\u7f16\u5199\u81ea\u5b9a\u4e49\u811a\u672c<\/h3>\n<\/p>\n
1. \u81ea\u5b9a\u4e49\u8d44\u6e90\u76d1\u63a7\u811a\u672c<\/h4>\n<\/p>\n
\u53ef\u4ee5\u6839\u636e\u5b9e\u9645\u9700\u6c42\u7f16\u5199\u81ea\u5b9a\u4e49\u811a\u672c\uff0c\u5b9e\u73b0\u7279\u5b9a\u7684\u76d1\u63a7\u529f\u80fd\u3002\u4f8b\u5982\uff0c\u76d1\u63a7\u7279\u5b9a\u8fdb\u7a0b\u7684CPU\u548c\u5185\u5b58\u4f7f\u7528\u7387\u3002<\/p>\n<\/p>\n
import psutil<\/p>\n
import time<\/p>\n
def monitor_process(pid, interval=1):<\/p>\n
    try:<\/p>\n
        process = psutil.Process(pid)<\/p>\n
        while True:<\/p>\n
            cpu_usage = process.cpu_percent(interval=interval)<\/p>\n
            memory_info = process.memory_info()<\/p>\n
            print(f"Process {pid} CPU Usage: {cpu_usage}%")<\/p>\n
            print(f"Process {pid} Memory Usage: {memory_info.rss \/ 1024 \/ 1024} MB")<\/p>\n
            time.sleep(interval)<\/p>\n
    except psutil.NoSuchProcess:<\/p>\n
        print(f"No process found with PID {pid}")<\/p>\n
Call the function to start monitoring a specific process<\/strong><\/h2>\n
monitor_process(12345)<\/p>\n
<\/code><\/pre>\n<\/p>\n
2. \u81ea\u5b9a\u4e49\u7f51\u7edc\u76d1\u63a7\u811a\u672c<\/h4>\n<\/p>\n
\u53ef\u4ee5\u7f16\u5199\u811a\u672c\u5b9e\u65f6\u76d1\u63a7\u7f51\u7edc\u6d41\u91cf\uff0c\u8bb0\u5f55\u7f51\u7edc\u6570\u636e\u5305\u7684\u53d1\u9001\u548c\u63a5\u6536\u60c5\u51b5\u3002<\/p>\n<\/p>\n
import psutil<\/p>\n
import time<\/p>\n
def monitor_network(interval=1):<\/p>\n
    while True:<\/p>\n
        net_io = psutil.net_io_counters()<\/p>\n
        print(f"Network Sent: {net_io.bytes_sent} bytes, Received: {net_io.bytes_recv} bytes")<\/p>\n
        time.sleep(interval)<\/p>\n
Call the function to start monitoring network traffic<\/strong><\/h2>\n
monitor_network()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e09\u3001\u5229\u7528\u7b2c\u4e09\u65b9\u5e93<\/h3>\n<\/p>\n
1. Matplotlib\u5e93<\/h4>\n<\/p>\n
Matplotlib\u662f\u4e00\u4e2a\u5f3a\u5927\u7684\u7ed8\u56fe\u5e93\uff0c\u53ef\u4ee5\u7528\u4e8e\u5b9e\u65f6\u7ed8\u5236\u7cfb\u7edf\u6027\u80fd\u6307\u6807\u56fe\u8868\uff0c\u5e2e\u52a9\u53ef\u89c6\u5316\u76d1\u63a7\u6570\u636e\u3002<\/p>\n<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
import matplotlib.animation as animation<\/p>\n
import psutil<\/p>\n
fig, ax = plt.subplots()<\/p>\n
xdata, ydata = [], []<\/p>\n
ln, = plt.plot([], [], 'r-', animated=True)<\/p>\n
def init():<\/p>\n
    ax.set_xlim(0, 10)<\/p>\n
    ax.set_ylim(0, 100)<\/p>\n
    return ln,<\/p>\n
def update(frame):<\/p>\n
    xdata.append(frame)<\/p>\n
    ydata.append(psutil.cpu_percent())<\/p>\n
    ln.set_data(xdata, ydata)<\/p>\n
    ax.set_xlim(0, max(10, frame))<\/p>\n
    return ln,<\/p>\n
ani = animation.FuncAnimation(fig, update, frames=range(100), init_func=init, blit=True)<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
2. Plotly\u5e93<\/h4>\n<\/p>\n
Plotly\u662f\u53e6\u4e00\u4e2a\u975e\u5e38\u6d41\u884c\u7684\u53ef\u89c6\u5316\u5e93\uff0c\u652f\u6301\u4ea4\u4e92\u5f0f\u56fe\u8868\u548c\u5b9e\u65f6\u6570\u636e\u66f4\u65b0\u3002<\/p>\n<\/p>\n
import plotly.graph_objs as go<\/p>\n
from plotly.subplots import make_subplots<\/p>\n
import psutil<\/p>\n
import time<\/p>\n
fig = make_subplots(rows=1, cols=1)<\/p>\n
def update_plot():<\/p>\n
    fig.add_trace(go.Scatter(x=[], y=[], mode='lines', name='CPU Usage'))<\/p>\n
    while True:<\/p>\n
        cpu_usage = psutil.cpu_percent()<\/p>\n
        fig.update_traces(go.Scatter(x=[time.time()], y=[cpu_usage]))<\/p>\n
        time.sleep(1)<\/p>\n
Call the function to start updating the plot<\/strong><\/h2>\n
update_plot()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56db\u3001\u5b9e\u73b0\u6570\u636e\u53ef\u89c6\u5316<\/h3>\n<\/p>\n
1. \u4f7f\u7528Dash\u6846\u67b6<\/h4>\n<\/p>\n
Dash\u662fPlotly\u7684\u4e00\u4e2a\u6846\u67b6\uff0c\u53ef\u4ee5\u7528\u4e8e\u6784\u5efa\u4ea4\u4e92\u5f0fWeb\u5e94\u7528\uff0c\u9002\u5408\u5b9e\u73b0\u5b9e\u65f6\u76d1\u63a7\u9762\u677f\u3002<\/p>\n<\/p>\n
import dash<\/p>\n
from dash import dcc, html<\/p>\n
from dash.dependencies import Input, Output<\/p>\n
import psutil<\/p>\n
import time<\/p>\n
app = dash.Dash(__name__)<\/p>\n
app.layout = html.Div([<\/p>\n
    dcc.Graph(id='live-update-graph'),<\/p>\n
    dcc.Interval(id='interval-component', interval=1*1000, n_intervals=0)<\/p>\n
])<\/p>\n
@app.callback(Output('live-update-graph', 'figure'),<\/p>\n
              [Input('interval-component', 'n_intervals')])<\/p>\n
def update_graph_live(n):<\/p>\n
    cpu_usage = psutil.cpu_percent()<\/p>\n
    fig = go.Figure(go.Scatter(x=[time.time()], y=[cpu_usage], mode='lines', name='CPU Usage'))<\/p>\n
    return fig<\/p>\n
if __name__ == '__mAI<\/a>n__':<\/p>\n
    app.run_server(debug=True)<\/p>\n
<\/code><\/pre>\n<\/p>\n
2. \u4f7f\u7528Bokeh\u5e93<\/h4>\n<\/p>\n
Bokeh\u662f\u4e00\u4e2a\u7528\u4e8e\u521b\u5efa\u4ea4\u4e92\u5f0f\u56fe\u8868\u548c\u6570\u636e\u5e94\u7528\u7684\u5e93\uff0c\u9002\u5408\u7528\u4e8e\u5b9e\u65f6\u6570\u636e\u53ef\u89c6\u5316\u3002<\/p>\n<\/p>\n
from bokeh.io import curdoc<\/p>\n
from bokeh.layouts import column<\/p>\n
from bokeh.models import ColumnDataSource<\/p>\n
from bokeh.plotting import figure<\/p>\n
import psutil<\/p>\n
import time<\/p>\n
source = ColumnDataSource(data=dict(x=[], y=[]))<\/p>\n
p = figure(title="CPU Usage", x_axis_type='datetime')<\/p>\n
p.line(x='x', y='y', source=source)<\/p>\n
def update():<\/p>\n
    new_data = dict(x=[time.time()], y=[psutil.cpu_percent()])<\/p>\n
    source.stream(new_data, rollover=200)<\/p>\n
curdoc().add_periodic_callback(update, 1000)<\/p>\n
curdoc().add_root(column(p))<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e94\u3001\u7efc\u5408\u5e94\u7528\u793a\u4f8b<\/h3>\n<\/p>\n
1. \u7efc\u5408\u7cfb\u7edf\u76d1\u63a7<\/h4>\n<\/p>\n
\u53ef\u4ee5\u7ed3\u5408\u4e0a\u8ff0\u5404\u7c7b\u5e93\u548c\u65b9\u6cd5\uff0c\u5b9e\u73b0\u4e00\u4e2a\u7efc\u5408\u7684\u7cfb\u7edf\u76d1\u63a7\u811a\u672c\uff0c\u76d1\u63a7CPU\u3001\u5185\u5b58\u3001\u78c1\u76d8\u3001\u7f51\u7edc\u7b49\u591a\u4e2a\u6307\u6807\uff0c\u5e76\u5b9e\u65f6\u5c55\u793a\u3002<\/p>\n<\/p>\n
import psutil<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
import matplotlib.animation as animation<\/p>\n
import time<\/p>\n
fig, (ax1, ax2, ax3, ax4) = plt.subplots(4, 1)<\/p>\n
cpu_data, mem_data, disk_data, net_data = [], [], [], []<\/p>\n
def update(frame):<\/p>\n
    cpu_data.append(psutil.cpu_percent())<\/p>\n
    mem_data.append(psutil.virtual_memory().percent)<\/p>\n
    disk_data.append(psutil.disk_usage('\/').percent)<\/p>\n
    net_io = psutil.net_io_counters()<\/p>\n
    net_data.append(net_io.bytes_sent + net_io.bytes_recv)<\/p>\n
    ax1.clear()<\/p>\n
    ax2.clear()<\/p>\n
    ax3.clear()<\/p>\n
    ax4.clear()<\/p>\n
    ax1.plot(cpu_data, 'r-')<\/p>\n
    ax2.plot(mem_data, 'g-')<\/p>\n
    ax3.plot(disk_data, 'b-')<\/p>\n
    ax4.plot(net_data, 'y-')<\/p>\n
    ax1.set_title('CPU Usage')<\/p>\n
    ax2.set_title('Memory Usage')<\/p>\n
    ax3.set_title('Disk Usage')<\/p>\n
    ax4.set_title('Network Usage')<\/p>\n
ani = animation.FuncAnimation(fig, update, frames=range(100), interval=1000)<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
2. \u7efc\u5408\u7f51\u7edc\u76d1\u63a7<\/h4>\n<\/p>\n
\u53ef\u4ee5\u5b9e\u73b0\u4e00\u4e2a\u5b9e\u65f6\u76d1\u63a7\u7f51\u7edc\u6d41\u91cf\u7684\u811a\u672c\uff0c\u8bb0\u5f55\u6bcf\u4e2a\u65f6\u95f4\u6bb5\u5185\u7684\u6570\u636e\u5305\u53d1\u9001\u548c\u63a5\u6536\u60c5\u51b5\uff0c\u5e76\u53ef\u89c6\u5316\u5c55\u793a\u3002<\/p>\n<\/p>\n
import psutil<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
import matplotlib.animation as animation<\/p>\n
import time<\/p>\n
fig, ax = plt.subplots()<\/p>\n
net_data = []<\/p>\n
def update(frame):<\/p>\n
    net_io = psutil.net_io_counters()<\/p>\n
    net_data.append(net_io.bytes_sent + net_io.bytes_recv)<\/p>\n
    ax.clear()<\/p>\n
    ax.plot(net_data, 'y-')<\/p>\n
    ax.set_title('Network Usage')<\/p>\n
ani = animation.FuncAnimation(fig, update, frames=range(100), interval=1000)<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u901a\u8fc7\u4ee5\u4e0a\u51e0\u79cd\u65b9\u6cd5\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528Python\u5b9e\u73b0\u5404\u79cd\u5f62\u5f0f\u7684\u5b9e\u65f6\u76d1\u63a7\uff0c\u5e2e\u52a9\u66f4\u597d\u5730\u4e86\u89e3\u548c\u7ba1\u7406\u7cfb\u7edf\u7684\u5404\u9879\u6027\u80fd\u6307\u6807\u3002\u65e0\u8bba\u662f\u4f7f\u7528\u7cfb\u7edf\u76d1\u63a7\u5de5\u5177\u3001\u7f16\u5199\u81ea\u5b9a\u4e49\u811a\u672c\u3001\u5229\u7528\u7b2c\u4e09\u65b9\u5e93\u8fd8\u662f\u5b9e\u73b0\u6570\u636e\u53ef\u89c6\u5316\uff0c\u90fd\u80fd\u6ee1\u8db3\u4e0d\u540c\u7684\u76d1\u63a7\u9700\u6c42\uff0c\u63d0\u4f9b\u5b9e\u65f6\u7684\u76d1\u63a7\u6570\u636e\u548c\u53ef\u89c6\u5316\u5c55\u793a\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
 \u5b9e\u65f6\u76d1\u63a7\u5728Python\u4e2d\u6709\u54ea\u4e9b\u5e38\u89c1\u7684\u5e94\u7528\u573a\u666f\uff1f<\/strong>
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\u4f7f\u7528Python\u8fdb\u884c\u5b9e\u65f6\u76d1\u63a7\u9700\u8981\u54ea\u4e9b\u5e38\u7528\u5e93\u6216\u5de5\u5177\uff1f<\/strong>
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