{"id":989805,"date":"2024-12-27T08:14:46","date_gmt":"2024-12-27T00:14:46","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/989805.html"},"modified":"2024-12-27T08:14:48","modified_gmt":"2024-12-27T00:14:48","slug":"python%e5%a6%82%e4%bd%95%e5%ae%9e%e6%97%b6%e7%9b%91%e6%8e%a7%e7%b3%bb%e7%bb%9f","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/989805.html","title":{"rendered":"python\u5982\u4f55\u5b9e\u65f6\u76d1\u63a7\u7cfb\u7edf"},"content":{"rendered":"<p style=\"text-align:center;\" ><img decoding=\"async\" src=\"https:\/\/cdn-kb.worktile.com\/kb\/wp-content\/uploads\/2024\/04\/25064821\/6233b6b3-2d33-4734-a47c-12fadec7b53f.webp\" alt=\"python\u5982\u4f55\u5b9e\u65f6\u76d1\u63a7\u7cfb\u7edf\" \/><\/p>\n<p><p> <strong>\u4f7f\u7528Python\u5b9e\u65f6\u76d1\u63a7\u7cfb\u7edf\u7684\u65b9\u6cd5\u5305\u62ec\uff1a\u4f7f\u7528psutil\u5e93\u83b7\u53d6\u7cfb\u7edf\u4fe1\u606f\u3001\u7ed3\u5408matplotlib\u5e93\u53ef\u89c6\u5316\u6570\u636e\u3001\u5229\u7528\u591a\u7ebf\u7a0b\u5b9e\u73b0\u6570\u636e\u7684\u5f02\u6b65\u91c7\u96c6\u3002<\/strong> \u5728\u8fd9\u4e9b\u65b9\u6cd5\u4e2d\uff0cpsutil\u5e93\u662f\u4e00\u4e2a\u5f3a\u5927\u7684\u5de5\u5177\uff0c\u5b83\u63d0\u4f9b\u4e86\u83b7\u53d6\u6709\u5173\u7cfb\u7edf\u8fdb\u7a0b\u548c\u7cfb\u7edf\u5229\u7528\u7387\uff08CPU\u3001\u5185\u5b58\u3001\u78c1\u76d8\u3001\u7f51\u7edc\u7b49\uff09\u7684\u4e00\u7cfb\u5217\u529f\u80fd\u3002\u901a\u8fc7\u7ed3\u5408psutil\u548cmatplotlib\u5e93\uff0c\u6211\u4eec\u53ef\u4ee5\u521b\u5efa\u52a8\u6001\u66f4\u65b0\u7684\u56fe\u8868\u6765\u5b9e\u65f6\u76d1\u63a7\u7cfb\u7edf\u6027\u80fd\u3002\u6b64\u5916\uff0c\u901a\u8fc7\u4f7f\u7528Python\u7684\u591a\u7ebf\u7a0b\u6280\u672f\uff0c\u6211\u4eec\u53ef\u4ee5\u786e\u4fdd\u6570\u636e\u7684\u91c7\u96c6\u548c\u5904\u7406\u4e0d\u4f1a\u4e92\u76f8\u963b\u585e\uff0c\u4ece\u800c\u5b9e\u73b0\u66f4\u9ad8\u6548\u7684\u5b9e\u65f6\u76d1\u63a7\u3002<\/p>\n<\/p>\n<p><p>\u4e00\u3001PSUTIL\u5e93\u7684\u4f7f\u7528<\/p>\n<\/p>\n<p><p>psutil\u662f\u4e00\u4e2a\u8de8\u5e73\u53f0\u7684\u5e93\uff0c\u53ef\u4ee5\u8f7b\u677e\u5730\u8bbf\u95ee\u7cfb\u7edf\u7684\u8fd0\u884c\u65f6\u4fe1\u606f\u3002\u5b83\u7684\u7b80\u5355\u63a5\u53e3\u548c\u5f3a\u5927\u7684\u529f\u80fd\u4f7f\u5f97\u5b83\u6210\u4e3aPython\u5f00\u53d1\u8005\u8fdb\u884c\u7cfb\u7edf\u76d1\u63a7\u7684\u9996\u9009\u5de5\u5177\u3002<\/p>\n<\/p>\n<ol>\n<li>\u5b89\u88c5\u548c\u57fa\u672c\u4f7f\u7528<\/li>\n<\/ol>\n<p><p>\u8981\u4f7f\u7528psutil\u5e93\uff0c\u9996\u5148\u9700\u8981\u5b89\u88c5\u5b83\u3002\u53ef\u4ee5\u901a\u8fc7pip\u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-bash\">pip install psutil<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5b89\u88c5\u5b8c\u6210\u540e\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528psutil\u5e93\u6765\u83b7\u53d6CPU\u3001\u5185\u5b58\u3001\u78c1\u76d8\u548c\u7f51\u7edc\u7b49\u4fe1\u606f\u3002\u4f8b\u5982\uff0c\u83b7\u53d6CPU\u4f7f\u7528\u7387\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u4ee3\u7801\u5b9e\u73b0\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import psutil<\/p>\n<h2><strong>\u83b7\u53d6CPU\u4f7f\u7528\u7387<\/strong><\/h2>\n<p>cpu_usage = psutil.cpu_percent(interval=1)<\/p>\n<p>print(f&quot;CPU Usage: {cpu_usage}%&quot;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<ol start=\"2\">\n<li>\u83b7\u53d6\u5185\u5b58\u548c\u78c1\u76d8\u4fe1\u606f<\/li>\n<\/ol>\n<p><p>\u9664\u4e86CPU\u4f7f\u7528\u7387\uff0cpsutil\u8fd8\u53ef\u4ee5\u83b7\u53d6\u5185\u5b58\u548c\u78c1\u76d8\u7684\u4f7f\u7528\u60c5\u51b5\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u83b7\u53d6\u5185\u5b58\u4f7f\u7528\u4fe1\u606f<\/p>\n<p>memory_info = psutil.virtual_memory()<\/p>\n<p>print(f&quot;Memory Usage: {memory_info.percent}%&quot;)<\/p>\n<h2><strong>\u83b7\u53d6\u78c1\u76d8\u4f7f\u7528\u4fe1\u606f<\/strong><\/h2>\n<p>disk_info = psutil.disk_usage(&#39;\/&#39;)<\/p>\n<p>print(f&quot;Disk Usage: {disk_info.percent}%&quot;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<ol start=\"3\">\n<li>\u83b7\u53d6\u7f51\u7edc\u4fe1\u606f<\/li>\n<\/ol>\n<p><p>psutil\u8fd8\u53ef\u4ee5\u7528\u6765\u83b7\u53d6\u7f51\u7edc\u63a5\u53e3\u7684\u4fe1\u606f\uff0c\u5982\u7f51\u7edc\u6d41\u91cf\u7b49\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u83b7\u53d6\u7f51\u7edcIO\u4fe1\u606f<\/p>\n<p>net_io = psutil.net_io_counters()<\/p>\n<p>print(f&quot;Bytes Sent: {net_io.bytes_sent}, Bytes Received: {net_io.bytes_recv}&quot;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u4e8c\u3001\u7ed3\u5408MATPLOTLIB\u8fdb\u884c\u6570\u636e\u53ef\u89c6\u5316<\/p>\n<\/p>\n<p><p>\u4e3a\u4e86\u66f4\u76f4\u89c2\u5730\u5c55\u793a\u7cfb\u7edf\u76d1\u63a7\u7684\u6570\u636e\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528matplotlib\u5e93\u6765\u7ed8\u5236\u5b9e\u65f6\u66f4\u65b0\u7684\u56fe\u8868\u3002<\/p>\n<\/p>\n<ol>\n<li>\u5b89\u88c5matplotlib<\/li>\n<\/ol>\n<p><p>\u9996\u5148\uff0c\u9700\u8981\u5b89\u88c5matplotlib\u5e93\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-bash\">pip install matplotlib<\/p>\n<p><\/code><\/pre>\n<\/p>\n<ol start=\"2\">\n<li>\u521b\u5efa\u5b9e\u65f6\u66f4\u65b0\u7684\u56fe\u8868<\/li>\n<\/ol>\n<p><p>\u901a\u8fc7\u7ed3\u5408psutil\u548cmatplotlib\uff0c\u6211\u4eec\u53ef\u4ee5\u521b\u5efa\u4e00\u4e2a\u5b9e\u65f6\u66f4\u65b0\u7684\u56fe\u8868\u6765\u5c55\u793aCPU\u4f7f\u7528\u7387\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import matplotlib.pyplot as plt<\/p>\n<p>import psutil<\/p>\n<p>import time<\/p>\n<h2><strong>\u521d\u59cb\u5316\u6570\u636e<\/strong><\/h2>\n<p>cpu_usages = []<\/p>\n<h2><strong>\u8bbe\u7f6e\u56fe\u8868<\/strong><\/h2>\n<p>plt.ion()<\/p>\n<p>fig, ax = plt.subplots()<\/p>\n<p>line, = ax.plot(cpu_usages)<\/p>\n<p>ax.set_ylim(0, 100)<\/p>\n<p>ax.set_xlim(0, 50)<\/p>\n<p>plt.xlabel(&#39;Time (s)&#39;)<\/p>\n<p>plt.ylabel(&#39;CPU Usage (%)&#39;)<\/p>\n<p>while True:<\/p>\n<p>    # \u83b7\u53d6CPU\u4f7f\u7528\u7387<\/p>\n<p>    cpu_usage = psutil.cpu_percent(interval=1)<\/p>\n<p>    cpu_usages.append(cpu_usage)<\/p>\n<p>    # \u66f4\u65b0\u56fe\u8868\u6570\u636e<\/p>\n<p>    line.set_ydata(cpu_usages)<\/p>\n<p>    line.set_xdata(range(len(cpu_usages)))<\/p>\n<p>    # \u91cd\u7f6eX\u8f74<\/p>\n<p>    if len(cpu_usages) &gt; 50:<\/p>\n<p>        ax.set_xlim(len(cpu_usages) - 50, len(cpu_usages))<\/p>\n<p>    # \u7ed8\u5236\u56fe\u8868<\/p>\n<p>    fig.canvas.draw()<\/p>\n<p>    fig.canvas.flush_events()<\/p>\n<p>    # \u5ef6\u8fdf<\/p>\n<p>    time.sleep(1)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u8fd9\u6bb5\u4ee3\u7801\u521b\u5efa\u4e86\u4e00\u4e2a\u5b9e\u65f6\u66f4\u65b0\u7684\u6298\u7ebf\u56fe\uff0c\u5c55\u793a\u4e86CPU\u4f7f\u7528\u7387\u3002\u53ef\u4ee5\u6839\u636e\u9700\u8981\u8c03\u6574\u4ee3\u7801\uff0c\u4ee5\u5c55\u793a\u5185\u5b58\u3001\u78c1\u76d8\u6216\u7f51\u7edc\u7684\u4f7f\u7528\u60c5\u51b5\u3002<\/p>\n<\/p>\n<p><p>\u4e09\u3001\u5229\u7528\u591a\u7ebf\u7a0b\u5b9e\u73b0\u6570\u636e\u7684\u5f02\u6b65\u91c7\u96c6<\/p>\n<\/p>\n<p><p>\u5728\u8fdb\u884c\u5b9e\u65f6\u76d1\u63a7\u65f6\uff0c\u5355\u7ebf\u7a0b\u53ef\u80fd\u4f1a\u5bfc\u81f4\u6570\u636e\u91c7\u96c6\u548c\u5904\u7406\u51fa\u73b0\u5ef6\u8fdf\u6216\u963b\u585e\u3002\u56e0\u6b64\uff0c\u6211\u4eec\u53ef\u4ee5\u5229\u7528Python\u7684\u591a\u7ebf\u7a0b\u6280\u672f\u6765\u5b9e\u73b0\u5f02\u6b65\u91c7\u96c6\u6570\u636e\uff0c\u4ece\u800c\u63d0\u9ad8\u76d1\u63a7\u7684\u6548\u7387\u3002<\/p>\n<\/p>\n<ol>\n<li>\u4f7f\u7528\u591a\u7ebf\u7a0b\u8fdb\u884c\u6570\u636e\u91c7\u96c6<\/li>\n<\/ol>\n<p><p>Python\u7684<code>threading<\/code>\u6a21\u5757\u63d0\u4f9b\u4e86\u591a\u7ebf\u7a0b\u652f\u6301\uff0c\u53ef\u4ee5\u7528\u6765\u5b9e\u73b0\u6570\u636e\u7684\u5f02\u6b65\u91c7\u96c6\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import threading<\/p>\n<p>import psutil<\/p>\n<p>import time<\/p>\n<h2><strong>\u5b9a\u4e49\u5168\u5c40\u53d8\u91cf\u5b58\u50a8\u6570\u636e<\/strong><\/h2>\n<p>cpu_usage = 0<\/p>\n<h2><strong>\u5b9a\u4e49\u4e00\u4e2a\u7ebf\u7a0b\u51fd\u6570\u7528\u4e8e\u83b7\u53d6CPU\u4f7f\u7528\u7387<\/strong><\/h2>\n<p>def get_cpu_usage():<\/p>\n<p>    global cpu_usage<\/p>\n<p>    while True:<\/p>\n<p>        cpu_usage = psutil.cpu_percent(interval=1)<\/p>\n<p>        time.sleep(1)<\/p>\n<h2><strong>\u521b\u5efa\u5e76\u542f\u52a8\u7ebf\u7a0b<\/strong><\/h2>\n<p>thread = threading.Thread(target=get_cpu_usage)<\/p>\n<p>thread.start()<\/p>\n<h2><strong>\u4e3b\u7ebf\u7a0b\u7ee7\u7eed\u6267\u884c\u5176\u4ed6\u4efb\u52a1<\/strong><\/h2>\n<p>while True:<\/p>\n<p>    print(f&quot;CPU Usage: {cpu_usage}%&quot;)<\/p>\n<p>    time.sleep(2)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<ol start=\"2\">\n<li>\u591a\u7ebf\u7a0b\u4e0e\u6570\u636e\u53ef\u89c6\u5316\u7684\u7ed3\u5408<\/li>\n<\/ol>\n<p><p>\u6211\u4eec\u53ef\u4ee5\u5c06\u591a\u7ebf\u7a0b\u7684\u6570\u636e\u91c7\u96c6\u4e0ematplotlib\u7684\u53ef\u89c6\u5316\u7ed3\u5408\u8d77\u6765\uff0c\u4ee5\u5b9e\u73b0\u66f4\u9ad8\u6548\u7684\u5b9e\u65f6\u76d1\u63a7\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import matplotlib.pyplot as plt<\/p>\n<p>import threading<\/p>\n<p>import psutil<\/p>\n<p>import time<\/p>\n<p>cpu_usages = []<\/p>\n<p>def get_cpu_usage():<\/p>\n<p>    global cpu_usages<\/p>\n<p>    while True:<\/p>\n<p>        cpu_usage = psutil.cpu_percent(interval=1)<\/p>\n<p>        cpu_usages.append(cpu_usage)<\/p>\n<p>        time.sleep(1)<\/p>\n<h2><strong>\u542f\u52a8\u83b7\u53d6CPU\u4f7f\u7528\u7387\u7684\u7ebf\u7a0b<\/strong><\/h2>\n<p>thread = threading.Thread(target=get_cpu_usage)<\/p>\n<p>thread.start()<\/p>\n<h2><strong>\u521d\u59cb\u5316\u56fe\u8868<\/strong><\/h2>\n<p>plt.ion()<\/p>\n<p>fig, ax = plt.subplots()<\/p>\n<p>line, = ax.plot(cpu_usages)<\/p>\n<p>ax.set_ylim(0, 100)<\/p>\n<p>ax.set_xlim(0, 50)<\/p>\n<p>plt.xlabel(&#39;Time (s)&#39;)<\/p>\n<p>plt.ylabel(&#39;CPU Usage (%)&#39;)<\/p>\n<p>while True:<\/p>\n<p>    # \u66f4\u65b0\u56fe\u8868\u6570\u636e<\/p>\n<p>    if cpu_usages:<\/p>\n<p>        line.set_ydata(cpu_usages)<\/p>\n<p>        line.set_xdata(range(len(cpu_usages)))<\/p>\n<p>        # \u91cd\u7f6eX\u8f74<\/p>\n<p>        if len(cpu_usages) &gt; 50:<\/p>\n<p>            ax.set_xlim(len(cpu_usages) - 50, len(cpu_usages))<\/p>\n<p>        # \u7ed8\u5236\u56fe\u8868<\/p>\n<p>        fig.canvas.draw()<\/p>\n<p>        fig.canvas.flush_events()<\/p>\n<p>    # \u5ef6\u8fdf<\/p>\n<p>    time.sleep(1)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u901a\u8fc7\u8fd9\u79cd\u65b9\u5f0f\uff0c\u6211\u4eec\u53ef\u4ee5\u5728\u4e0d\u963b\u585e\u4e3b\u7ebf\u7a0b\u7684\u60c5\u51b5\u4e0b\uff0c\u5b9e\u65f6\u66f4\u65b0\u7cfb\u7edf\u76d1\u63a7\u6570\u636e\u3002<\/p>\n<\/p>\n<p><p>\u56db\u3001\u6269\u5c55\u5e94\u7528\u548c\u6539\u8fdb\u5efa\u8bae<\/p>\n<\/p>\n<ol>\n<li>\u6dfb\u52a0\u66f4\u591a\u76d1\u63a7\u6307\u6807<\/li>\n<\/ol>\n<p><p>\u9664\u4e86\u57fa\u672c\u7684CPU\u3001\u5185\u5b58\u3001\u78c1\u76d8\u548c\u7f51\u7edc\u76d1\u63a7\u5916\uff0c\u8fd8\u53ef\u4ee5\u901a\u8fc7psutil\u5e93\u83b7\u53d6\u66f4\u591a\u7684\u7cfb\u7edf\u4fe1\u606f\uff0c\u5982\u8fdb\u7a0b\u5217\u8868\u3001\u7cfb\u7edf\u542f\u52a8\u65f6\u95f4\u7b49\u3002\u6839\u636e\u5177\u4f53\u9700\u6c42\uff0c\u53ef\u4ee5\u5c06\u8fd9\u4e9b\u4fe1\u606f\u6dfb\u52a0\u5230\u76d1\u63a7\u7cfb\u7edf\u4e2d\u3002<\/p>\n<\/p>\n<ol start=\"2\">\n<li>\u4f7f\u7528\u6570\u636e\u5e93\u5b58\u50a8\u5386\u53f2\u6570\u636e<\/li>\n<\/ol>\n<p><p>\u4e3a\u4e86\u5206\u6790\u7cfb\u7edf\u6027\u80fd\u7684\u957f\u671f\u53d8\u5316\u8d8b\u52bf\uff0c\u53ef\u4ee5\u5c06\u76d1\u63a7\u6570\u636e\u5b58\u50a8\u5230\u6570\u636e\u5e93\u4e2d\u3002\u901a\u8fc7\u4f7f\u7528SQLite\u3001MySQL\u7b49\u6570\u636e\u5e93\uff0c\u53ef\u4ee5\u5b9e\u73b0\u6570\u636e\u7684\u6301\u4e45\u5316\u5b58\u50a8\uff0c\u5e76\u4e3a\u540e\u7eed\u7684\u6570\u636e\u5206\u6790\u63d0\u4f9b\u652f\u6301\u3002<\/p>\n<\/p>\n<ol 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