{"id":948204,"date":"2024-12-27T00:01:33","date_gmt":"2024-12-26T16:01:33","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/948204.html"},"modified":"2024-12-27T00:01:36","modified_gmt":"2024-12-26T16:01:36","slug":"python%e5%a6%82%e4%bd%95%e6%89%be%e6%96%87%e7%8c%ae","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/948204.html","title":{"rendered":"python\u5982\u4f55\u627e\u6587\u732e"},"content":{"rendered":"

\"python\u5982\u4f55\u627e\u6587\u732e\"<\/p>\n

\u5229\u7528Python\u627e\u6587\u732e\u7684\u65b9\u6cd5\u5305\u62ec\uff1a\u4f7f\u7528API\u8bbf\u95ee\u5b66\u672f\u6570\u636e\u5e93\u3001\u5229\u7528\u722c\u866b\u6280\u672f\u6293\u53d6\u7f51\u9875\u4fe1\u606f\u3001\u901a\u8fc7Python\u5e93\u8fdb\u884c\u6570\u636e\u5904\u7406\u4e0e\u5206\u6790\u3002<\/strong>\u5728\u8fd9\u4e9b\u65b9\u6cd5\u4e2d\uff0c\u5229\u7528API\u8bbf\u95ee\u5b66\u672f\u6570\u636e\u5e93\u662f\u4e00\u79cd\u76f4\u63a5\u4e14\u9ad8\u6548\u7684\u65b9\u5f0f\uff0c\u56e0\u4e3a\u8bb8\u591a\u5b66\u672f\u6570\u636e\u5e93\u63d0\u4f9b\u4e86API\u63a5\u53e3\uff0c\u5141\u8bb8\u7528\u6237\u901a\u8fc7\u7f16\u7a0b\u65b9\u5f0f\u8fdb\u884c\u6587\u732e\u68c0\u7d22\u3002\u4e0b\u9762\u5c06\u8be6\u7ec6\u63cf\u8ff0\u8fd9\u79cd\u65b9\u6cd5\u3002<\/p>\n<\/p>\n

\u4f7f\u7528API\u8bbf\u95ee\u5b66\u672f\u6570\u636e\u5e93\u662f\u4e00\u4e2a\u975e\u5e38\u4fbf\u6377\u7684\u9014\u5f84\uff0c\u56e0\u4e3a\u5b83\u5141\u8bb8\u7528\u6237\u76f4\u63a5\u4ece\u6570\u636e\u5e93\u4e2d\u83b7\u53d6\u7ed3\u6784\u5316\u7684\u6570\u636e\u3002\u4f8b\u5982\uff0c\u5b66\u672f\u641c\u7d22\u5f15\u64ce\u5982Google Scholar\u3001PubMed\u3001IEEE Xplore\u7b49\uff0c\u901a\u5e38\u63d0\u4f9bAPI\u63a5\u53e3\uff0c\u4f9b\u5f00\u53d1\u8005\u8fdb\u884c\u4e8c\u6b21\u5f00\u53d1\u3002\u901a\u8fc7\u8fd9\u4e9bAPI\u63a5\u53e3\uff0c\u7528\u6237\u53ef\u4ee5\u6307\u5b9a\u5173\u952e\u8bcd\u3001\u4f5c\u8005\u3001\u51fa\u7248\u5e74\u4efd\u7b49\u53c2\u6570\u6765\u7cbe\u786e\u5730\u68c0\u7d22\u6587\u732e\uff0c\u5e76\u83b7\u53d6\u5305\u62ec\u6587\u7ae0\u6807\u9898\u3001\u6458\u8981\u3001\u4f5c\u8005\u3001\u51fa\u7248\u7269\u3001DOI\u7b49\u4fe1\u606f\u7684\u7ed3\u679c\u3002\u6b64\u5916\uff0c\u5229\u7528API\u63a5\u53e3\u8fd8\u53ef\u4ee5\u5b9e\u73b0\u6279\u91cf\u6587\u732e\u4e0b\u8f7d\uff0c\u5927\u5927\u63d0\u9ad8\u5de5\u4f5c\u6548\u7387\u3002<\/p>\n<\/p>\n

\n

\u4e00\u3001\u5229\u7528API\u8bbf\u95ee\u5b66\u672f\u6570\u636e\u5e93<\/h3>\n<\/p>\n

\u4f7f\u7528API\u8bbf\u95ee\u5b66\u672f\u6570\u636e\u5e93\u662f\u5bfb\u627e\u6587\u732e\u7684\u6709\u6548\u9014\u5f84\uff0c\u56e0\u4e3a\u5b83\u63d0\u4f9b\u4e86\u7ed3\u6784\u5316\u6570\u636e\u5e76\u652f\u6301\u9ad8\u6548\u68c0\u7d22\u3002<\/p>\n<\/p>\n

1.1 \u83b7\u53d6API\u8bbf\u95ee\u6743\u9650<\/h4>\n<\/p>\n

\u5927\u591a\u6570\u5b66\u672f\u6570\u636e\u5e93\u63d0\u4f9bAPI\u63a5\u53e3\uff0c\u4f46\u901a\u5e38\u9700\u8981\u6ce8\u518c\u5f00\u53d1\u8005\u8d26\u53f7\u5e76\u7533\u8bf7\u8bbf\u95ee\u6743\u9650\u3002\u4ee5PubMed\u4e3a\u4f8b\uff0c\u7528\u6237\u53ef\u4ee5\u901a\u8fc7Entrez Programming Utilities (E-utilities) API\u8bbf\u95ee\u5176\u6570\u636e\u5e93\u3002\u5728\u4f7f\u7528API\u4e4b\u524d\uff0c\u9700\u8981\u5148\u4e86\u89e3API\u7684\u6587\u6863\u548c\u4f7f\u7528\u9650\u5236\uff0c\u5982\u6bcf\u79d2\u8bf7\u6c42\u6b21\u6570\u3001\u6570\u636e\u683c\u5f0f\u7b49\u3002<\/p>\n<\/p>\n

1.2 \u6784\u5efaAPI\u8bf7\u6c42<\/h4>\n<\/p>\n

\u4f7f\u7528Python\u7684requests<\/code>\u5e93\u53ef\u4ee5\u8f7b\u677e\u53d1\u9001HTTP\u8bf7\u6c42\u3002\u6784\u5efaAPI\u8bf7\u6c42\u65f6\uff0c\u9700\u8981\u6839\u636eAPI\u6587\u6863\u6307\u5b9a\u8bf7\u6c42\u53c2\u6570\u3002\u4f8b\u5982\uff0c\u68c0\u7d22\u7279\u5b9a\u4e3b\u9898\u7684\u6587\u732e\u65f6\uff0c\u53ef\u4ee5\u8bbe\u7f6e\u5173\u952e\u8bcd\u3001\u51fa\u7248\u5e74\u4efd\u3001\u671f\u520a\u540d\u79f0\u7b49\u53c2\u6570\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u8bf7\u6c42\u793a\u4f8b\uff1a<\/p>\n<\/p>\n

import requests<\/p>\n
url = "https:\/\/eutils.ncbi.nlm.nih.gov\/entrez\/eutils\/esearch.fcgi"<\/p>\n
params = {<\/p>\n
    "db": "pubmed",<\/p>\n
    "term": "python programming",<\/p>\n
    "retmax": 10,<\/p>\n
    "retmode": "json"<\/p>\n
}<\/p>\n
response = requests.get(url, params=params)<\/p>\n
data = response.json()<\/p>\n
print(data)<\/p>\n
<\/code><\/pre>\n<\/p>\n
1.3 \u89e3\u6790\u548c\u5904\u7406\u6570\u636e<\/h4>\n<\/p>\n
API\u8fd4\u56de\u7684\u6570\u636e\u901a\u5e38\u4e3aJSON\u6216XML\u683c\u5f0f\u3002\u4f7f\u7528Python\u7684\u5185\u7f6e\u5e93\u6216json<\/code>\u3001xml.etree.ElementTree<\/code>\u5e93\uff0c\u53ef\u4ee5\u65b9\u4fbf\u5730\u89e3\u6790\u8fd9\u4e9b\u6570\u636e\u683c\u5f0f\u3002\u83b7\u53d6\u5230\u7684\u6587\u732e\u4fe1\u606f\u53ef\u4ee5\u5b58\u50a8\u5728\u672c\u5730\u6587\u4ef6\u4e2d\uff0c\u6216\u8fdb\u4e00\u6b65\u8fdb\u884c\u6570\u636e\u5206\u6790\u548c\u53ef\u89c6\u5316\u3002<\/p>\n<\/p>\n
\u4e8c\u3001\u5229\u7528\u722c\u866b\u6280\u672f\u6293\u53d6\u7f51\u9875\u4fe1\u606f<\/h3>\n<\/p>\n
\u5bf9\u4e8e\u6ca1\u6709API\u63a5\u53e3\u7684\u5b66\u672f\u8d44\u6e90\uff0c\u53ef\u4ee5\u5229\u7528\u722c\u866b\u6280\u672f\u6293\u53d6\u7f51\u9875\u4fe1\u606f\u3002<\/p>\n<\/p>\n
2.1 \u786e\u5b9a\u76ee\u6807\u7f51\u7ad9\u548c\u722c\u53d6\u8303\u56f4<\/h4>\n<\/p>\n
\u5728\u4f7f\u7528\u722c\u866b\u6280\u672f\u65f6\uff0c\u9996\u5148\u8981\u9009\u62e9\u76ee\u6807\u7f51\u7ad9\u5e76\u786e\u5b9a\u722c\u53d6\u8303\u56f4\u3002\u9700\u8981\u6ce8\u610f\u7684\u662f\uff0c\u722c\u866b\u884c\u4e3a\u5e94\u9075\u5faa\u7f51\u7ad9\u7684robots.txt\u534f\u8bae\uff0c\u5e76\u907f\u514d\u5bf9\u7f51\u7ad9\u9020\u6210\u8d1f\u62c5\u3002\u6bd4\u5982\uff0c\u5728Google Scholar\u4e0a\uff0c\u7528\u6237\u53ef\u4ee5\u901a\u8fc7\u624b\u52a8\u641c\u7d22\u83b7\u53d6\u67d0\u4e2a\u5173\u952e\u8bcd\u7684\u7ed3\u679c\u9875\u9762\uff0c\u7136\u540e\u4f7f\u7528\u722c\u866b\u6293\u53d6\u8fd9\u4e9b\u9875\u9762\u3002<\/p>\n<\/p>\n
2.2 \u7f16\u5199\u722c\u866b\u811a\u672c<\/h4>\n<\/p>\n
\u4f7f\u7528Python\u7684BeautifulSoup<\/code>\u548crequests<\/code>\u5e93\u53ef\u4ee5\u8f7b\u677e\u7f16\u5199\u722c\u866b\u811a\u672c\u3002\u9996\u5148\u53d1\u9001HTTP\u8bf7\u6c42\u83b7\u53d6\u7f51\u9875\u5185\u5bb9\uff0c\u7136\u540e\u5229\u7528BeautifulSoup<\/code>\u89e3\u6790HTML\u7ed3\u6784\uff0c\u63d0\u53d6\u6240\u9700\u7684\u6587\u732e\u4fe1\u606f\uff0c\u5982\u6807\u9898\u3001\u4f5c\u8005\u3001\u6458\u8981\u7b49\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u722c\u866b\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
import requests<\/p>\n
from bs4 import BeautifulSoup<\/p>\n
url = "https:\/\/scholar.google.com\/scholar?q=python+programming"<\/p>\n
response = requests.get(url)<\/p>\n
soup = BeautifulSoup(response.text, 'html.parser')<\/p>\n
for item in soup.find_all('h3', class_='gs_rt'):<\/p>\n
    print(item.text)<\/p>\n
<\/code><\/pre>\n<\/p>\n
2.3 \u6570\u636e\u6e05\u6d17\u548c\u5b58\u50a8<\/h4>\n<\/p>\n
\u83b7\u53d6\u5230\u7684\u7f51\u9875\u6570\u636e\u901a\u5e38\u5305\u542b\u5927\u91cf\u5197\u4f59\u4fe1\u606f\uff0c\u9700\u8981\u8fdb\u884c\u6570\u636e\u6e05\u6d17\u3002\u53ef\u4ee5\u4f7f\u7528\u6b63\u5219\u8868\u8fbe\u5f0f\u6216\u5b57\u7b26\u4e32\u64cd\u4f5c\u53bb\u9664\u591a\u4f59\u7684\u6807\u7b7e\u548c\u5b57\u7b26\uff0c\u5c06\u6587\u732e\u4fe1\u606f\u5b58\u50a8\u5230\u7ed3\u6784\u5316\u7684\u683c\u5f0f\u4e2d\uff0c\u5982CSV\u3001JSON\u7b49\u3002<\/p>\n<\/p>\n
\u4e09\u3001\u901a\u8fc7Python\u5e93\u8fdb\u884c\u6570\u636e\u5904\u7406\u4e0e\u5206\u6790<\/h3>\n<\/p>\n
\u5728\u83b7\u53d6\u5230\u6587\u732e\u4fe1\u606f\u540e\uff0c\u901a\u8fc7Python\u7684\u5f3a\u5927\u6570\u636e\u5904\u7406\u5e93\uff0c\u53ef\u4ee5\u5bf9\u6570\u636e\u8fdb\u884c\u6df1\u5165\u5206\u6790\u3002<\/p>\n<\/p>\n
3.1 \u4f7f\u7528Pandas\u8fdb\u884c\u6570\u636e\u5904\u7406<\/h4>\n<\/p>\n
Pandas<\/code>\u5e93\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684\u6570\u636e\u5904\u7406\u529f\u80fd\uff0c\u53ef\u4ee5\u7528\u4e8e\u5bf9\u6587\u732e\u6570\u636e\u8fdb\u884c\u6e05\u6d17\u3001\u7b5b\u9009\u548c\u7edf\u8ba1\u5206\u6790\u3002\u901a\u8fc7DataFrame<\/code>\u5bf9\u8c61\uff0c\u7528\u6237\u53ef\u4ee5\u65b9\u4fbf\u5730\u5bf9\u6587\u732e\u4fe1\u606f\u8fdb\u884c\u6392\u5e8f\u3001\u5206\u7ec4\u3001\u805a\u5408\u7b49\u64cd\u4f5c\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u6570\u636e\u5904\u7406\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
data = {<\/p>\n
    'Title': ['Title1', 'Title2'],<\/p>\n
    'Author': ['Author1', 'Author2'],<\/p>\n
    'Year': [2020, 2021]<\/p>\n
}<\/p>\n
df = pd.DataFrame(data)<\/p>\n
print(df)<\/p>\n
<\/code><\/pre>\n<\/p>\n
3.2 \u6570\u636e\u53ef\u89c6\u5316<\/h4>\n<\/p>\n
\u901a\u8fc7matplotlib<\/code>\u548cseaborn<\/code>\u5e93\uff0c\u53ef\u4ee5\u5bf9\u6587\u732e\u6570\u636e\u8fdb\u884c\u53ef\u89c6\u5316\uff0c\u5e2e\u52a9\u7528\u6237\u76f4\u89c2\u5730\u4e86\u89e3\u6570\u636e\u5206\u5e03\u548c\u8d8b\u52bf\u3002\u4f8b\u5982\uff0c\u53ef\u4ee5\u7ed8\u5236\u6587\u732e\u53d1\u8868\u5e74\u4efd\u7684\u76f4\u65b9\u56fe\uff0c\u5206\u6790\u67d0\u4e2a\u9886\u57df\u7684\u7814\u7a76\u6d3b\u8dc3\u5ea6\u53d8\u5316\u3002<\/p>\n<\/p>\n
\u56db\u3001\u7efc\u5408\u5b9e\u8df5\u4e0e\u5e94\u7528<\/h3>\n<\/p>\n
\u901a\u8fc7\u5c06\u4e0a\u8ff0\u65b9\u6cd5\u7efc\u5408\u5e94\u7528\uff0c\u80fd\u591f\u6709\u6548\u5730\u8fdb\u884c\u5927\u89c4\u6a21\u6587\u732e\u68c0\u7d22\u548c\u5206\u6790\u3002<\/p>\n<\/p>\n
4.1 \u5b9e\u73b0\u81ea\u52a8\u5316\u6587\u732e\u68c0\u7d22\u7cfb\u7edf<\/h4>\n<\/p>\n
\u5c06API\u8bbf\u95ee\u548c\u722c\u866b\u6280\u672f\u7ed3\u5408\uff0c\u6784\u5efa\u4e00\u4e2a\u81ea\u52a8\u5316\u6587\u732e\u68c0\u7d22\u7cfb\u7edf\u3002\u8be5\u7cfb\u7edf\u80fd\u591f\u5b9a\u671f\u66f4\u65b0\u6587\u732e\u6570\u636e\uff0c\u63d0\u4f9b\u7ed9\u7814\u7a76\u4eba\u5458\u5b9e\u65f6\u7684\u53c2\u8003\u4fe1\u606f\u3002<\/p>\n<\/p>\n
4.2 \u6587\u732e\u5206\u6790\u4e0e\u63a8\u8350<\/h4>\n<\/p>\n
\u901a\u8fc7\u5bf9\u5927\u91cf\u6587\u732e\u6570\u636e\u7684\u5206\u6790\uff0c\u53ef\u4ee5\u5b9e\u73b0\u6587\u732e\u63a8\u8350\u7cfb\u7edf\u3002\u5229\u7528\u81ea\u7136\u8bed\u8a00\u5904\u7406\u6280\u672f\uff0c\u53ef\u4ee5\u5206\u6790\u6587\u732e\u7684\u5185\u5bb9\u548c\u5f15\u7528\u5173\u7cfb\uff0c\u4e3a\u7814\u7a76\u4eba\u5458\u63a8\u8350\u76f8\u5173\u6027\u9ad8\u7684\u6587\u732e\u3002<\/p>\n<\/p>\n
4.3 \u673a\u5668\u5b66\u4e60<\/a>\u4e0e\u6587\u732e\u7814\u7a76<\/h4>\n<\/p>\n
\u7ed3\u5408\u673a\u5668\u5b66\u4e60\u6280\u672f\uff0c\u53ef\u4ee5\u5bf9\u6587\u732e\u6570\u636e\u8fdb\u884c\u6df1\u5ea6\u6316\u6398\uff0c\u4f8b\u5982\u4e3b\u9898\u5efa\u6a21\u3001\u60c5\u611f\u5206\u6790\u7b49\uff0c\u4e3a\u79d1\u7814\u63d0\u4f9b\u65b0\u7684\u89c6\u89d2\u548c\u6d1e\u5bdf\u3002<\/p>\n<\/p>\n
\u901a\u8fc7\u4ee5\u4e0a\u65b9\u6cd5\uff0c\u5229\u7528Python\u8fdb\u884c\u6587\u732e\u68c0\u7d22\u548c\u5206\u6790\uff0c\u4e0d\u4ec5\u63d0\u9ad8\u4e86\u6548\u7387\uff0c\u8fd8\u4e3a\u79d1\u7814\u5de5\u4f5c\u63d0\u4f9b\u4e86\u5f3a\u6709\u529b\u7684\u6280\u672f\u652f\u6301\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
 \u5982\u4f55\u4f7f\u7528Python\u81ea\u52a8\u5316\u67e5\u627e\u5b66\u672f\u6587\u732e\uff1f<\/strong>
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