{"id":936832,"date":"2024-12-26T19:38:32","date_gmt":"2024-12-26T11:38:32","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/936832.html"},"modified":"2024-12-26T19:38:35","modified_gmt":"2024-12-26T11:38:35","slug":"python-%e5%a6%82%e4%bd%95%e6%9f%a5%e7%9c%8b%e8%af%be%e8%a1%a8","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/936832.html","title":{"rendered":"python \u5982\u4f55\u67e5\u770b\u8bfe\u8868"},"content":{"rendered":"<p style=\"text-align:center;\" ><img decoding=\"async\" src=\"https:\/\/cdn-kb.worktile.com\/kb\/wp-content\/uploads\/2024\/04\/25072937\/aaeba3a0-ebf6-4469-acdf-237d71ea5f36.webp\" alt=\"python \u5982\u4f55\u67e5\u770b\u8bfe\u8868\" \/><\/p>\n<p><p> <strong>\u67e5\u770bPython\u8bfe\u8868\u7684\u65b9\u6cd5\u5305\u62ec\uff1a\u4f7f\u7528\u5b66\u6821\u7684\u5b66\u4e60\u7ba1\u7406\u7cfb\u7edf\u3001\u901a\u8fc7Python\u7f16\u5199\u7a0b\u5e8f\u4ece\u5728\u7ebf\u8bfe\u8868\u83b7\u53d6\u6570\u636e\u3001\u4f7f\u7528\u722c\u866b\u6280\u672f\u6293\u53d6\u7f51\u9875\u4fe1\u606f\u3002<\/strong>\u5176\u4e2d\uff0c\u4f7f\u7528Python\u7f16\u5199\u7a0b\u5e8f\u4ece\u5728\u7ebf\u8bfe\u8868\u83b7\u53d6\u6570\u636e\u662f\u4e00\u79cd\u7075\u6d3b\u4e14\u53ef\u5b9a\u5236\u7684\u65b9\u6cd5\u3002\u53ef\u4ee5\u901a\u8fc7Python\u7684\u5e93\u5982<code>requests<\/code>\u548c<code>BeautifulSoup<\/code>\u4ece\u5b66\u6821\u7f51\u7ad9\u6293\u53d6\u8bfe\u8868\u4fe1\u606f\uff0c\u7136\u540e\u7528<code>pandas<\/code>\u5e93\u8fdb\u884c\u6570\u636e\u5904\u7406\u548c\u5c55\u793a\u3002\u4e0b\u9762\u6211\u5c06\u8be6\u7ec6\u63cf\u8ff0\u5982\u4f55\u4f7f\u7528Python\u7f16\u5199\u7a0b\u5e8f\u4ece\u5728\u7ebf\u8bfe\u8868\u83b7\u53d6\u6570\u636e\u3002<\/p>\n<\/p>\n<p><p>\u4e00\u3001\u4f7f\u7528\u5b66\u6821\u7684\u5b66\u4e60\u7ba1\u7406\u7cfb\u7edf<\/p>\n<\/p>\n<p><p>\u8bb8\u591a\u5b66\u6821\u90fd\u6709\u81ea\u5df1\u7684\u5b66\u4e60\u7ba1\u7406\u7cfb\u7edf\uff08LMS\uff09\uff0c\u4f8b\u5982Moodle\u3001Blackboard\u6216Canvas\uff0c\u8fd9\u4e9b\u7cfb\u7edf\u901a\u5e38\u4f1a\u63d0\u4f9b\u8bfe\u8868\u67e5\u770b\u529f\u80fd\u3002\u5b66\u751f\u53ef\u4ee5\u901a\u8fc7\u767b\u5f55\u8fd9\u4e9b\u5e73\u53f0\uff0c\u67e5\u770b\u4e2a\u4eba\u8bfe\u8868\u3001\u8bfe\u7a0b\u4fe1\u606f\u53ca\u76f8\u5173\u901a\u77e5\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u6b65\u9aa4\uff0c\u5e2e\u52a9\u60a8\u66f4\u597d\u5730\u4f7f\u7528LMS\u67e5\u770b\u8bfe\u8868\uff1a<\/p>\n<\/p>\n<ol>\n<li>\n<p><strong>\u767b\u5f55\u7cfb\u7edf<\/strong><br \/>\u9996\u5148\uff0c\u60a8\u9700\u8981\u901a\u8fc7\u5b66\u6821\u63d0\u4f9b\u7684\u7528\u6237\u540d\u548c\u5bc6\u7801\u767b\u5f55\u5230LMS\u7cfb\u7edf\u3002\u901a\u5e38\uff0c\u60a8\u53ef\u4ee5\u5728\u5b66\u6821\u7684\u5b98\u65b9\u7f51\u7ad9\u627e\u5230LMS\u7684\u94fe\u63a5\u3002<\/p>\n<\/p>\n<\/li>\n<li>\n<p><strong>\u5bfc\u822a\u5230\u8bfe\u8868\u6a21\u5757<\/strong><br \/>\u5728LMS\u4e2d\u627e\u5230\u201c\u8bfe\u8868\u201d\u6216\u201c\u8bfe\u7a0b\u5b89\u6392\u201d\u6a21\u5757\u3002\u8fd9\u901a\u5e38\u4f4d\u4e8e\u4e3b\u9875\u9762\u7684\u5bfc\u822a\u680f\u4e2d\u3002\u70b9\u51fb\u8fdb\u5165\u540e\uff0c\u60a8\u4f1a\u770b\u5230\u5f53\u524d\u5b66\u671f\u7684\u8bfe\u7a0b\u5b89\u6392\u3002<\/p>\n<\/p>\n<\/li>\n<li>\n<p><strong>\u67e5\u770b\u548c\u4e0b\u8f7d\u8bfe\u8868<\/strong><br \/>\u5728\u8bfe\u8868\u6a21\u5757\u4e2d\uff0c\u60a8\u53ef\u4ee5\u67e5\u770b\u6bcf\u5468\u7684\u8bfe\u7a0b\u5b89\u6392\u3002\u6709\u4e9b\u7cfb\u7edf\u8fd8\u63d0\u4f9b\u4e0b\u8f7d\u529f\u80fd\uff0c\u60a8\u53ef\u4ee5\u5c06\u8bfe\u8868\u4e0b\u8f7d\u4e3aPDF\u6216Excel\u6587\u4ef6\uff0c\u4ee5\u4fbf\u79bb\u7ebf\u67e5\u770b\u3002<\/p>\n<\/p>\n<\/li>\n<\/ol>\n<p><p>\u4e8c\u3001\u901a\u8fc7Python\u7f16\u5199\u7a0b\u5e8f\u4ece\u5728\u7ebf\u8bfe\u8868\u83b7\u53d6\u6570\u636e<\/p>\n<\/p>\n<p><p>Python\u662f\u4e00\u79cd\u5f3a\u5927\u7684\u7f16\u7a0b\u8bed\u8a00\uff0c\u53ef\u4ee5\u7528\u6765\u81ea\u52a8\u5316\u8bb8\u591a\u4efb\u52a1\uff0c\u5305\u62ec\u4ece\u5728\u7ebf\u5e73\u53f0\u83b7\u53d6\u8bfe\u8868\u4fe1\u606f\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u6b65\u9aa4\uff0c\u5e2e\u52a9\u60a8\u7f16\u5199Python\u7a0b\u5e8f\u83b7\u53d6\u8bfe\u8868\u6570\u636e\uff1a<\/p>\n<\/p>\n<ol>\n<li>\n<p><strong>\u5b89\u88c5\u5fc5\u8981\u7684Python\u5e93<\/strong><br \/>\u5728\u5f00\u59cb\u7f16\u5199\u7a0b\u5e8f\u4e4b\u524d\uff0c\u60a8\u9700\u8981\u5b89\u88c5\u4e00\u4e9bPython\u5e93\uff0c\u5982<code>requests<\/code>\u3001<code>BeautifulSoup<\/code>\u548c<code>pandas<\/code>\u3002\u8fd9\u4e9b\u5e93\u53ef\u4ee5\u5e2e\u52a9\u60a8\u6293\u53d6\u7f51\u9875\u6570\u636e\u5e76\u8fdb\u884c\u6570\u636e\u5904\u7406\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-bash\">pip install requests beautifulsoup4 pandas<\/p>\n<p><\/code><\/pre>\n<\/p>\n<\/li>\n<li>\n<p><strong>\u6293\u53d6\u7f51\u9875\u6570\u636e<\/strong><br \/>\u4f7f\u7528<code>requests<\/code>\u5e93\u53d1\u9001HTTP\u8bf7\u6c42\uff0c\u83b7\u53d6\u8bfe\u8868\u6240\u5728\u7f51\u9875\u7684HTML\u5185\u5bb9\u3002\u7136\u540e\u4f7f\u7528<code>BeautifulSoup<\/code>\u89e3\u6790HTML\uff0c\u63d0\u53d6\u8bfe\u8868\u6570\u636e\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import requests<\/p>\n<p>from bs4 import BeautifulSoup<\/p>\n<p>url = &#39;http:\/\/example.com\/schedule&#39;  # \u66ff\u6362\u4e3a\u5b9e\u9645\u7684\u8bfe\u8868\u7f51\u5740<\/p>\n<p>response = requests.get(url)<\/p>\n<p>soup = BeautifulSoup(response.content, &#39;html.parser&#39;)<\/p>\n<h2><strong>\u6839\u636e\u7f51\u9875\u7ed3\u6784\u5b9a\u4f4d\u8bfe\u8868\u6570\u636e<\/strong><\/h2>\n<p>table = soup.find(&#39;table&#39;, {&#39;id&#39;: &#39;schedule&#39;})<\/p>\n<p><\/code><\/pre>\n<\/p>\n<\/li>\n<li>\n<p><strong>\u5904\u7406\u548c\u5c55\u793a\u6570\u636e<\/strong><br \/>\u4f7f\u7528<code>pandas<\/code>\u5e93\u5c06\u63d0\u53d6\u7684\u6570\u636e\u8f6c\u6362\u4e3aDataFrame\uff0c\u4fbf\u4e8e\u8fdb\u4e00\u6b65\u5206\u6790\u548c\u5c55\u793a\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import pandas as pd<\/p>\n<h2><strong>\u5047\u8bbe\u8868\u683c\u7684\u6bcf\u4e00\u884c\u4ee3\u8868\u4e00\u95e8\u8bfe\u7a0b<\/strong><\/h2>\n<p>rows = table.find_all(&#39;tr&#39;)<\/p>\n<p>data = []<\/p>\n<p>for row in rows:<\/p>\n<p>    cols = row.find_all(&#39;td&#39;)<\/p>\n<p>    data.append([col.text for col in cols])<\/p>\n<p>df = pd.DataFrame(data, columns=[&#39;Course&#39;, &#39;Day&#39;, &#39;Time&#39;, &#39;Location&#39;])<\/p>\n<p>print(df)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<\/li>\n<li>\n<p><strong>\u4fdd\u5b58\u6570\u636e<\/strong><br \/>\u53ef\u4ee5\u5c06\u5904\u7406\u540e\u7684\u8bfe\u8868\u6570\u636e\u4fdd\u5b58\u4e3aCSV\u6587\u4ef6\uff0c\u4ee5\u4fbf\u79bb\u7ebf\u67e5\u770b\u6216\u5728\u5176\u4ed6\u7a0b\u5e8f\u4e2d\u4f7f\u7528\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">df.to_csv(&#39;schedule.csv&#39;, index=False)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<\/li>\n<\/ol>\n<p><p>\u4e09\u3001\u4f7f\u7528\u722c\u866b\u6280\u672f\u6293\u53d6\u7f51\u9875\u4fe1\u606f<\/p>\n<\/p>\n<p><p>\u6709\u65f6\uff0c\u5b66\u6821\u7684\u8bfe\u8868\u4fe1\u606f\u53ef\u80fd\u4e0d\u4f1a\u76f4\u63a5\u663e\u793a\u5728LMS\u4e2d\uff0c\u6216\u8005\u60a8\u9700\u8981\u83b7\u53d6\u5927\u91cf\u8bfe\u7a0b\u6570\u636e\u3002\u8fd9\u79cd\u60c5\u51b5\u4e0b\uff0c\u53ef\u4ee5\u4f7f\u7528\u722c\u866b\u6280\u672f\u6293\u53d6\u7f51\u9875\u4fe1\u606f\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u6b65\u9aa4\uff0c\u5e2e\u52a9\u60a8\u4f7f\u7528Python\u7f16\u5199\u722c\u866b\u7a0b\u5e8f\uff1a<\/p>\n<\/p>\n<ol>\n<li>\n<p><strong>\u8bc6\u522b\u76ee\u6807\u7f51\u7ad9\u7684\u7ed3\u6784<\/strong><br \/>\u5728\u7f16\u5199\u722c\u866b\u4e4b\u524d\uff0c\u9996\u5148\u9700\u8981\u4e86\u89e3\u76ee\u6807\u7f51\u7ad9\u7684\u7ed3\u6784\uff0c\u7279\u522b\u662f\u8bfe\u8868\u4fe1\u606f\u6240\u5728\u7684HTML\u5143\u7d20\u548c\u5c5e\u6027\u3002\u8fd9\u53ef\u4ee5\u901a\u8fc7\u6d4f\u89c8\u5668\u7684\u5f00\u53d1\u8005\u5de5\u5177\u5b9e\u73b0\u3002<\/p>\n<\/p>\n<\/li>\n<li>\n<p><strong>\u7f16\u5199\u722c\u866b\u7a0b\u5e8f<\/strong><br \/>\u4f7f\u7528<code>requests<\/code>\u548c<code>BeautifulSoup<\/code>\u5e93\u6293\u53d6\u548c\u89e3\u6790\u7f51\u9875\u6570\u636e\u3002\u901a\u8fc7\u5206\u6790\u7f51\u9875\u7ed3\u6784\uff0c\u53ef\u4ee5\u5b9a\u4f4d\u8bfe\u8868\u6570\u636e\u6240\u5728\u7684HTML\u5143\u7d20\u3002<\/p>\n<\/p>\n<\/li>\n<li>\n<p><strong>\u5904\u7406\u548c\u5b58\u50a8\u6570\u636e<\/strong><br \/>\u4f7f\u7528<code>pandas<\/code>\u5e93\u5904\u7406\u6293\u53d6\u5230\u7684\u6570\u636e\uff0c\u5e76\u5c06\u5176\u5b58\u50a8\u4e3aCSV\u6216Excel\u6587\u4ef6\u3002<\/p>\n<\/p>\n<\/li>\n<li>\n<p><strong>\u9075\u5faa\u722c\u866b\u793c\u8282<\/strong><br \/>\u7f16\u5199\u722c\u866b\u65f6\uff0c\u8981\u9075\u5faa\u7f51\u7ad9\u7684robots.txt\u534f\u8bae\uff0c\u907f\u514d\u8fc7\u4e8e\u9891\u7e41\u7684\u8bf7\u6c42\uff0c\u5f71\u54cd\u7f51\u7ad9\u7684\u6b63\u5e38\u8fd0\u884c\u3002\u540c\u65f6\uff0c\u786e\u4fdd\u4ec5\u6293\u53d6\u516c\u5f00\u7684\u3001\u53ef\u5408\u6cd5\u8bbf\u95ee\u7684\u6570\u636e\u3002<\/p>\n<\/p>\n<\/li>\n<\/ol>\n<p><p>\u901a\u8fc7\u4ee5\u4e0a\u4e09\u79cd\u65b9\u6cd5\uff0c\u60a8\u53ef\u4ee5\u8f7b\u677e\u67e5\u770b\u548c\u83b7\u53d6Python\u8bfe\u8868\u4fe1\u606f\u3002\u6839\u636e\u4e2a\u4eba\u9700\u6c42\u548c\u6280\u672f\u6c34\u5e73\uff0c\u9009\u62e9\u6700\u9002\u5408\u60a8\u7684\u65b9\u6cd5\u6765\u7ba1\u7406\u548c\u67e5\u770b\u8bfe\u8868\u6570\u636e\u3002<\/p>\n<\/p>\n<h2><strong>\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n<p> <strong>\u5982\u4f55\u5728Python\u4e2d\u8bfb\u53d6\u548c\u5c55\u793a\u8bfe\u8868\u6570\u636e\uff1f<\/strong><br \/>\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528pandas\u5e93\u6765\u8bfb\u53d6\u8bfe\u8868\u6570\u636e\uff0c\u901a\u5e38\u5b58\u50a8\u5728CSV\u6216Excel\u6587\u4ef6\u4e2d\u3002\u9996\u5148\uff0c\u5b89\u88c5pandas\u5e93\uff0c\u7136\u540e\u4f7f\u7528<code>pd.read_csv()<\/code>\u6216<code>pd.read_excel()<\/code>\u51fd\u6570\u8bfb\u53d6\u6587\u4ef6\u3002\u8bfb\u53d6\u540e\uff0c\u53ef\u4ee5\u4f7f\u7528<code>DataFrame<\/code>\u5bf9\u8c61\u5c55\u793a\u8bfe\u8868\uff0c\u5e76\u53ef\u4ee5\u901a\u8fc7<code>print()<\/code>\u6216<code>head()<\/code>\u65b9\u6cd5\u67e5\u770b\u524d\u51e0\u884c\u6570\u636e\u3002<\/p>\n<p><strong>\u6709\u54ea\u4e9b\u5e93\u53ef\u4ee5\u5e2e\u52a9\u6211\u5728Python\u4e2d\u5904\u7406\u8bfe\u8868\u6570\u636e\uff1f<\/strong><br 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