{"id":1123725,"date":"2025-01-08T19:35:03","date_gmt":"2025-01-08T11:35:03","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1123725.html"},"modified":"2025-01-08T19:35:07","modified_gmt":"2025-01-08T11:35:07","slug":"python%e5%a6%82%e4%bd%95%e5%af%b9%e6%af%94%e4%b8%8d%e5%90%8c%e7%bd%91%e7%ab%99%e5%95%86%e5%93%81%e4%bb%b7%e6%a0%bc","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1123725.html","title":{"rendered":"python\u5982\u4f55\u5bf9\u6bd4\u4e0d\u540c\u7f51\u7ad9\u5546\u54c1\u4ef7\u683c"},"content":{"rendered":"

\"python\u5982\u4f55\u5bf9\u6bd4\u4e0d\u540c\u7f51\u7ad9\u5546\u54c1\u4ef7\u683c\"<\/p>\n

Python\u5bf9\u6bd4\u4e0d\u540c\u7f51\u7ad9\u5546\u54c1\u4ef7\u683c\u7684\u65b9\u6cd5<\/strong>\u5305\u62ec\u4f7f\u7528Web Scraping\u5de5\u5177\u3001\u5229\u7528API\u3001\u6570\u636e\u6e05\u6d17\u4e0e\u5904\u7406\u3001\u6570\u636e\u53ef\u89c6\u5316<\/strong>\u7b49\u3002\u672c\u6587\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528Python\u4ece\u4e0d\u540c\u7f51\u7ad9\u83b7\u53d6\u5546\u54c1\u4ef7\u683c\uff0c\u5e76\u8fdb\u884c\u5bf9\u6bd4\u5206\u6790\u3002\u91cd\u70b9\u5c06\u653e\u5728Web Scraping\u5de5\u5177\u7684\u9009\u62e9\u548c\u4f7f\u7528<\/strong>\u4e0a\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u4f7f\u7528Web Scraping\u5de5\u5177<\/h3>\n<\/p>\n

Web Scraping\u662f\u4ece\u7f51\u9875\u4e2d\u63d0\u53d6\u6570\u636e\u7684\u8fc7\u7a0b\u3002Python\u6709\u5f88\u591a\u5f3a\u5927\u7684\u5e93\u53ef\u4ee5\u8fdb\u884cWeb Scraping\uff0c\u5305\u62ecBeautifulSoup<\/code>\u3001Scrapy<\/code>\u548cSelenium<\/code>\u7b49\u3002\u4ee5\u4e0b\u662f\u8be6\u7ec6\u4ecb\u7ecd\uff1a<\/p>\n<\/p>\n

1\u3001BeautifulSoup<\/h4>\n<\/p>\n

BeautifulSoup<\/code>\u662f\u4e00\u4e2a\u7528\u4e8e\u89e3\u6790HTML\u548cXML\u6587\u6863\u7684Python\u5e93\u3002\u5b83\u5c06\u590d\u6742\u7684HTML\u6587\u6863\u8f6c\u6362\u6210\u4e00\u4e2a\u590d\u6742\u7684\u6811\u5f62\u7ed3\u6784\uff0c\u5305\u62ec\u6240\u6709HTML\u6807\u7b7e\u3001\u5c5e\u6027\u4ee5\u53ca\u5185\u5bb9\u3002<\/p>\n<\/p>\n

\u5b89\u88c5BeautifulSoup<\/h5>\n<\/p>\n

pip install beautifulsoup4<\/p>\n
pip install requests<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4f7f\u7528BeautifulSoup\u8fdb\u884cWeb Scraping<\/h5>\n<\/p>\n
\u4e0b\u9762\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u793a\u4f8b\uff0c\u5c55\u793a\u5982\u4f55\u4f7f\u7528BeautifulSoup\u4ece\u4e00\u4e2a\u7f51\u9875\u4e2d\u63d0\u53d6\u5546\u54c1\u4ef7\u683c\uff1a<\/p>\n<\/p>\n
import requests<\/p>\n
from bs4 import BeautifulSoup<\/p>\n
url = 'https:\/\/example.com\/product-page'<\/p>\n
response = requests.get(url)<\/p>\n
soup = BeautifulSoup(response.text, 'html.parser')<\/p>\n
price = soup.find('span', {'class': 'product-price'}).text<\/p>\n
print(price)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8fd9\u4e2a\u793a\u4f8b\u5c55\u793a\u4e86\u5982\u4f55\u4ece\u4e00\u4e2a\u7f51\u9875\u4e2d\u63d0\u53d6\u5546\u54c1\u4ef7\u683c\u3002\u9996\u5148\uff0c\u4f7f\u7528requests<\/code>\u5e93\u83b7\u53d6\u7f51\u9875\u5185\u5bb9\uff0c\u7136\u540e\u7528BeautifulSoup<\/code>\u89e3\u6790HTML\u6587\u6863\uff0c\u6700\u540e\u63d0\u53d6\u4ef7\u683c\u4fe1\u606f\u3002<\/p>\n<\/p>\n
2\u3001Scrapy<\/h4>\n<\/p>\n
Scrapy<\/code>\u662f\u4e00\u4e2a\u66f4\u52a0\u9ad8\u7ea7\u548c\u529f\u80fd\u4e30\u5bcc\u7684Web Scraping\u6846\u67b6\uff0c\u9002\u5408\u4e8e\u66f4\u590d\u6742\u7684Scraping\u4efb\u52a1\u3002<\/p>\n<\/p>\n
\u5b89\u88c5Scrapy<\/h5>\n<\/p>\n
pip install scrapy<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4f7f\u7528Scrapy\u8fdb\u884cWeb Scraping<\/h5>\n<\/p>\n
Scrapy\u7684\u4f7f\u7528\u6bd4BeautifulSoup\u590d\u6742\u4e00\u4e9b\uff0c\u4f46\u5b83\u63d0\u4f9b\u4e86\u66f4\u591a\u7684\u529f\u80fd\u548c\u66f4\u9ad8\u7684\u6027\u80fd\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684Scrapy\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
import scrapy<\/p>\n
class PriceSpider(scrapy.Spider):<\/p>\n
    name = 'price_spider'<\/p>\n
    start_urls = ['https:\/\/example.com\/product-page']<\/p>\n
    def parse(self, response):<\/p>\n
        price = response.css('span.product-price::text').get()<\/p>\n
        yield {'price': price}<\/p>\n
<\/code><\/pre>\n<\/p>\n
3\u3001Selenium<\/h4>\n<\/p>\n
Selenium<\/code>\u662f\u4e00\u4e2a\u7528\u4e8e\u81ea\u52a8\u5316Web\u6d4f\u89c8\u7684\u5de5\u5177\uff0c\u9002\u7528\u4e8e\u9700\u8981\u4e0eJavaScript\u52a8\u6001\u751f\u6210\u5185\u5bb9\u8fdb\u884c\u4ea4\u4e92\u7684\u60c5\u51b5\u3002<\/p>\n<\/p>\n
\u5b89\u88c5Selenium<\/h5>\n<\/p>\n
pip install selenium<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4f7f\u7528Selenium\u8fdb\u884cWeb Scraping<\/h5>\n<\/p>\n
\u4e0b\u9762\u662f\u4e00\u4e2a\u7b80\u5355\u7684Selenium\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
from selenium import webdriver<\/p>\n
driver = webdriver.Chrome()<\/p>\n
driver.get('https:\/\/example.com\/product-page')<\/p>\n
price = driver.find_element_by_css_selector('span.product-price').text<\/p>\n
print(price)<\/p>\n
driver.quit()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e8c\u3001\u5229\u7528API<\/h3>\n<\/p>\n
\u67d0\u4e9b\u7f51\u7ad9\u63d0\u4f9bAPI\u63a5\u53e3\uff0c\u53ef\u4ee5\u901a\u8fc7API\u76f4\u63a5\u83b7\u53d6\u5546\u54c1\u4ef7\u683c\u4fe1\u606f\u3002\u8fd9\u79cd\u65b9\u6cd5\u901a\u5e38\u6bd4Web Scraping\u66f4\u7a33\u5b9a\u548c\u53ef\u9760\u3002<\/p>\n<\/p>\n
1\u3001\u627e\u5230API<\/h4>\n<\/p>\n
\u9996\u5148\uff0c\u9700\u8981\u627e\u5230\u76ee\u6807\u7f51\u7ad9\u63d0\u4f9b\u7684API\u6587\u6863\uff0c\u4e86\u89e3\u5982\u4f55\u8fdb\u884cAPI\u8bf7\u6c42\u3002<\/p>\n<\/p>\n
2\u3001\u4f7f\u7528requests\u5e93\u8fdb\u884cAPI\u8bf7\u6c42<\/h4>\n<\/p>\n
\u4f7f\u7528Python\u7684requests<\/code>\u5e93\u53ef\u4ee5\u65b9\u4fbf\u5730\u8fdb\u884cAPI\u8bf7\u6c42\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
import requests<\/p>\n
url = 'https:\/\/api.example.com\/product'<\/p>\n
params = {'id': '12345'}<\/p>\n
response = requests.get(url, params=params)<\/p>\n
data = response.json()<\/p>\n
price = data['price']<\/p>\n
print(price)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e09\u3001\u6570\u636e\u6e05\u6d17\u4e0e\u5904\u7406<\/h3>\n<\/p>\n
\u83b7\u53d6\u6570\u636e\u540e\uff0c\u9700\u8981\u5bf9\u6570\u636e\u8fdb\u884c\u6e05\u6d17\u548c\u5904\u7406\uff0c\u4ee5\u4fbf\u540e\u7eed\u5206\u6790\u3002<\/p>\n<\/p>\n
1\u3001\u6570\u636e\u6e05\u6d17<\/h4>\n<\/p>\n
\u6570\u636e\u6e05\u6d17\u5305\u62ec\u53bb\u9664\u65e0\u6548\u6570\u636e\u3001\u5904\u7406\u7f3a\u5931\u503c\u548c\u91cd\u590d\u503c\u7b49\u3002\u53ef\u4ee5\u4f7f\u7528pandas<\/code>\u5e93\u8fdb\u884c\u6570\u636e\u6e05\u6d17\u3002<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
\u5047\u8bbedata\u662f\u4e00\u4e2a\u5305\u542b\u4ef7\u683c\u4fe1\u606f\u7684\u5217\u8868<\/strong><\/h2>\n
data = [{'price': 100}, {'price': 200}, {'price': None}, {'price': 150}, {'price': 100}]<\/p>\n
df = pd.DataFrame(data)<\/p>\n
\u53bb\u9664\u7f3a\u5931\u503c<\/strong><\/h2>\n
df.dropna(inplace=True)<\/p>\n
\u53bb\u9664\u91cd\u590d\u503c<\/strong><\/h2>\n
df.drop_duplicates(inplace=True)<\/p>\n
print(df)<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u6570\u636e\u5904\u7406<\/h4>\n<\/p>\n
\u53ef\u4ee5\u5bf9\u6570\u636e\u8fdb\u884c\u8fdb\u4e00\u6b65\u5904\u7406\uff0c\u5982\u5f52\u4e00\u5316\u3001\u6807\u51c6\u5316\u7b49\u3002<\/p>\n<\/p>\n
from sklearn.preprocessing import StandardScaler<\/p>\n
scaler = StandardScaler()<\/p>\n
df['price'] = scaler.fit_transform(df[['price']])<\/p>\n
print(df)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56db\u3001\u6570\u636e\u53ef\u89c6\u5316<\/h3>\n<\/p>\n
\u6700\u540e\uff0c\u53ef\u4ee5\u4f7f\u7528\u6570\u636e\u53ef\u89c6\u5316\u5de5\u5177\u5c06\u6570\u636e\u8fdb\u884c\u53ef\u89c6\u5316\uff0c\u5e2e\u52a9\u66f4\u76f4\u89c2\u5730\u8fdb\u884c\u4ef7\u683c\u5bf9\u6bd4\u3002<\/p>\n<\/p>\n
1\u3001\u4f7f\u7528Matplotlib\u8fdb\u884c\u6570\u636e\u53ef\u89c6\u5316<\/h4>\n<\/p>\n
Matplotlib<\/code>\u662fPython\u4e2d\u6700\u5e38\u7528\u7684\u6570\u636e\u53ef\u89c6\u5316\u5e93\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
\u5047\u8bbeprices\u662f\u4e00\u4e2a\u5305\u542b\u4ef7\u683c\u4fe1\u606f\u7684\u5217\u8868<\/strong><\/h2>\n
prices = [100, 200, 150, 100]<\/p>\n
plt.plot(prices)<\/p>\n
plt.ylabel('Price')<\/p>\n
plt.xlabel('Product')<\/p>\n
plt.title('Product Price Comparison')<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u4f7f\u7528Seaborn\u8fdb\u884c\u6570\u636e\u53ef\u89c6\u5316<\/h4>\n<\/p>\n
Seaborn<\/code>\u662f\u4e00\u4e2a\u57fa\u4e8eMatplotlib\u7684\u9ad8\u7ea7\u6570\u636e\u53ef\u89c6\u5316\u5e93\uff0c\u63d0\u4f9b\u4e86\u66f4\u9ad8\u7ea7\u548c\u7f8e\u89c2\u7684\u56fe\u8868\u3002<\/p>\n<\/p>\n
import seaborn as sns<\/p>\n
\u5047\u8bbedf\u662f\u4e00\u4e2a\u5305\u542b\u4ef7\u683c\u4fe1\u606f\u7684DataFrame<\/strong><\/h2>\n
sns.barplot(x='product', y='price', data=df)<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u603b\u7ed3<\/h3>\n<\/p>\n
\u901a\u8fc7\u4f7f\u7528Python\u7684Web Scraping\u5de5\u5177\u548cAPI\uff0c\u53ef\u4ee5\u8f7b\u677e\u5730\u4ece\u4e0d\u540c\u7f51\u7ad9\u83b7\u53d6\u5546\u54c1\u4ef7\u683c\u4fe1\u606f\u3002\u6570\u636e\u83b7\u53d6\u540e\uff0c\u53ef\u4ee5\u4f7f\u7528pandas<\/code>\u8fdb\u884c\u6570\u636e\u6e05\u6d17\u548c\u5904\u7406\uff0c\u5e76\u4f7f\u7528Matplotlib<\/code>\u6216Seaborn<\/code>\u8fdb\u884c\u6570\u636e\u53ef\u89c6\u5316\u3002\u65e0\u8bba\u662f\u4f7f\u7528BeautifulSoup<\/code>\u3001Scrapy<\/code>\u8fd8\u662fSelenium<\/code>\uff0c\u90fd\u80fd\u6709\u6548\u5730\u5b8c\u6210\u4ef7\u683c\u5bf9\u6bd4\u5206\u6790\u3002\u5e0c\u671b\u672c\u6587\u5bf9\u4f60\u6709\u6240\u5e2e\u52a9\uff0c\u795d\u4f60\u5728\u6570\u636e\u5206\u6790\u4e4b\u8def\u4e0a\u8d8a\u8d70\u8d8a\u8fdc\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
 \u5982\u4f55\u4f7f\u7528Python\u6293\u53d6\u4e0d\u540c\u7f51\u7ad9\u7684\u5546\u54c1\u4ef7\u683c\uff1f<\/strong>
\u4f7f\u7528Python\u8fdb\u884c\u7f51\u9875\u6293\u53d6\uff0c\u53ef\u4ee5\u4f7f\u7528\u5e93\u5982BeautifulSoup\u548cRequests\u6765\u63d0\u53d6\u5546\u54c1\u4ef7\u683c\u4fe1\u606f\u3002\u9996\u5148\uff0c\u4f7f\u7528Requests\u83b7\u53d6\u7f51\u9875\u7684HTML\u5185\u5bb9\uff0c\u7136\u540e\u5229\u7528BeautifulSoup\u89e3\u6790HTML\u5e76\u5b9a\u4f4d\u5230\u4ef7\u683c\u6807\u7b7e\u3002\u901a\u8fc7\u8fd9\u4e9b\u6b65\u9aa4\uff0c\u60a8\u53ef\u4ee5\u8f7b\u677e\u83b7\u5f97\u4e0d\u540c\u7f51\u7ad9\u4e0a\u7684\u5546\u54c1\u4ef7\u683c\u3002<\/p>\n
\u5bf9\u6bd4\u4e0d\u540c\u7f51\u7ad9\u5546\u54c1\u4ef7\u683c\u65f6\uff0c\u5982\u4f55\u5904\u7406\u7f51\u9875\u7ed3\u6784\u5dee\u5f02\uff1f<\/strong>
\u4e0d\u540c\u7f51\u7ad9\u7684HTML\u7ed3\u6784\u53ef\u80fd\u5b58\u5728\u663e\u8457\u5dee\u5f02\uff0c\u56e0\u6b64\u5728\u6293\u53d6\u4ef7\u683c\u4fe1\u606f\u65f6\uff0c\u9700\u8981\u6839\u636e\u6bcf\u4e2a\u7f51\u7ad9\u7684\u5177\u4f53\u7ed3\u6784\u5b9a\u5236\u89e3\u6790\u89c4\u5219\u3002\u8fd9\u53ef\u4ee5\u901a\u8fc7\u68c0\u67e5\u7f51\u9875\u6e90\u4ee3\u7801\uff0c\u627e\u5230\u5305\u542b\u4ef7\u683c\u7684\u5143\u7d20\u53ca\u5176\u5c5e\u6027\u6765\u5b9e\u73b0\u3002\u4e3a\u63d0\u9ad8\u4ee3\u7801\u7684\u53ef\u7ef4\u62a4\u6027\uff0c\u53ef\u4ee5\u8003\u8651\u4f7f\u7528\u51fd\u6570\u6765\u5904\u7406\u4e0d\u540c\u7f51\u7ad9\u7684\u6293\u53d6\u903b\u8f91\u3002<\/p>\n
\u4f7f\u7528Python\u8fdb\u884c\u5546\u54c1\u4ef7\u683c\u5bf9\u6bd4\u7684\u6700\u4f73\u5b9e\u8df5\u662f\u4ec0\u4e48\uff1f<\/strong>
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