{"id":1026856,"date":"2024-12-31T10:46:11","date_gmt":"2024-12-31T02:46:11","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1026856.html"},"modified":"2024-12-31T10:46:13","modified_gmt":"2024-12-31T02:46:13","slug":"python%e7%ae%80%e8%bf%b0%e5%a6%82%e4%bd%95%e6%94%b6%e9%9b%86%e7%bb%9f%e8%ae%a1%e6%95%b0%e6%8d%ae","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1026856.html","title":{"rendered":"python\u7b80\u8ff0\u5982\u4f55\u6536\u96c6\u7edf\u8ba1\u6570\u636e"},"content":{"rendered":"

\"python\u7b80\u8ff0\u5982\u4f55\u6536\u96c6\u7edf\u8ba1\u6570\u636e\"<\/p>\n

\u901a\u8fc7Python\u6536\u96c6\u7edf\u8ba1\u6570\u636e\u7684\u4e3b\u8981\u65b9\u6cd5\u5305\u62ec\uff1a\u4f7f\u7528\u7f51\u7edc\u722c\u866b\u6536\u96c6\u6570\u636e\u3001\u8c03\u7528API\u63a5\u53e3\u83b7\u53d6\u6570\u636e\u3001\u4f7f\u7528\u6570\u636e\u5e93\u67e5\u8be2\u3001\u8bfb\u53d6\u6587\u4ef6\u6570\u636e<\/strong>\u3002\u5728\u8fd9\u4e9b\u65b9\u6cd5\u4e2d\uff0c\u6700\u5e38\u7528\u4e14\u6709\u6548\u7684\u65b9\u6cd5\u662f\u4f7f\u7528\u7f51\u7edc\u722c\u866b\u6536\u96c6\u6570\u636e\u3002\u7f51\u7edc\u722c\u866b\u662f\u4e00\u79cd\u81ea\u52a8\u5316\u7a0b\u5e8f\uff0c\u53ef\u4ee5\u8bbf\u95ee\u7f51\u9875\u5e76\u63d0\u53d6\u6240\u9700\u7684\u4fe1\u606f\u3002\u8fd9\u79cd\u65b9\u6cd5\u7279\u522b\u9002\u7528\u4e8e\u9700\u8981\u4ece\u591a\u4e2a\u7f51\u7ad9\u6536\u96c6\u5927\u91cf\u6570\u636e\u7684\u60c5\u51b5\u3002\u4e0b\u9762\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528\u7f51\u7edc\u722c\u866b\u6765\u6536\u96c6\u7edf\u8ba1\u6570\u636e\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u7f51\u7edc\u722c\u866b\u6536\u96c6\u6570\u636e<\/p>\n<\/p>\n

\u7f51\u7edc\u722c\u866b\u662f\u4e00\u79cd\u81ea\u52a8\u5316\u7a0b\u5e8f\uff0c\u7528\u4e8e\u6d4f\u89c8\u4e92\u8054\u7f51\u5e76\u63d0\u53d6\u6240\u9700\u7684\u4fe1\u606f\u3002Python\u4e2d\u5e38\u7528\u7684\u7f51\u7edc\u722c\u866b\u5e93\u5305\u62ecBeautifulSoup\u3001Scrapy\u548cSelenium\u3002<\/p>\n<\/p>\n

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

BeautifulSoup\u662f\u4e00\u4e2a\u7528\u4e8e\u89e3\u6790HTML\u548cXML\u6587\u6863\u7684Python\u5e93\u3002\u5b83\u521b\u5efa\u4e00\u4e2a\u89e3\u6790\u6811\uff0c\u7528\u4e8e\u5e2e\u52a9\u5f00\u53d1\u4eba\u5458\u4ee5\u66f4\u76f4\u89c2\u7684\u65b9\u5f0f\u63d0\u53d6\u6570\u636e\u3002<\/p>\n<\/p>\n

from bs4 import BeautifulSoup<\/p>\n
import requests<\/p>\n
url = "http:\/\/example.com"<\/p>\n
response = requests.get(url)<\/p>\n
soup = BeautifulSoup(response.content, 'html.parser')<\/p>\n
\u67e5\u627e\u6240\u6709\u7684\u6807\u9898<\/strong><\/h2>\n
titles = soup.find_all('h1')<\/p>\n
for title in titles:<\/p>\n
    print(title.get_text())<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001Scrapy<\/p>\n<\/p>\n
Scrapy\u662f\u4e00\u4e2a\u529f\u80fd\u5f3a\u5927\u7684\u7f51\u7edc\u722c\u866b\u6846\u67b6\uff0c\u9002\u7528\u4e8e\u5927\u89c4\u6a21\u6570\u636e\u6293\u53d6\u548c\u5904\u7406\u3002\u5b83\u63d0\u4f9b\u4e86\u66f4\u591a\u7684\u529f\u80fd\u548c\u66f4\u9ad8\u7684\u7075\u6d3b\u6027\u3002<\/p>\n<\/p>\n
import scrapy<\/p>\n
class QuotesSpider(scrapy.Spider):<\/p>\n
    name = "quotes"<\/p>\n
    start_urls = ['http:\/\/quotes.toscrape.com\/']<\/p>\n
    def parse(self, response):<\/p>\n
        for quote in response.css('div.quote'):<\/p>\n
            yield {<\/p>\n
                'text': quote.css('span.text::text').get(),<\/p>\n
                'author': quote.css('span small::text').get(),<\/p>\n
                'tags': quote.css('div.tags a.tag::text').getall(),<\/p>\n
            }<\/p>\n
<\/code><\/pre>\n<\/p>\n
3\u3001Selenium<\/p>\n<\/p>\n
Selenium\u662f\u4e00\u4e2a\u7528\u4e8e\u81ea\u52a8\u5316Web\u6d4f\u89c8\u5668\u7684\u5de5\u5177\u3002\u5b83\u80fd\u591f\u5904\u7406JavaScript\u52a0\u8f7d\u7684\u5185\u5bb9\uff0c\u8fd9\u4f7f\u5f97\u5b83\u5728\u5904\u7406\u52a8\u6001\u7f51\u9875\u65f6\u975e\u5e38\u6709\u7528\u3002<\/p>\n<\/p>\n
from selenium import webdriver<\/p>\n
driver = webdriver.Chrome(executable_path='\/path\/to\/chromedriver')<\/p>\n
driver.get('http:\/\/example.com')<\/p>\n
\u67e5\u627e\u6240\u6709\u7684\u6807\u9898<\/strong><\/h2>\n
titles = driver.find_elements_by_tag_name('h1')<\/p>\n
for title in titles:<\/p>\n
    print(title.text)<\/p>\n
driver.quit()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e8c\u3001\u8c03\u7528API\u63a5\u53e3\u83b7\u53d6\u6570\u636e<\/p>\n<\/p>\n
\u8bb8\u591a\u7f51\u7ad9\u548c\u5728\u7ebf\u670d\u52a1\u63d0\u4f9bAPI\u63a5\u53e3\uff0c\u4f9b\u5f00\u53d1\u4eba\u5458\u83b7\u53d6\u6570\u636e\u3002\u4f7f\u7528API\u63a5\u53e3\u662f\u4e00\u79cd\u65b9\u4fbf\u4e14\u9ad8\u6548\u7684\u65b9\u6cd5\uff0c\u53ef\u4ee5\u76f4\u63a5\u83b7\u53d6\u7ed3\u6784\u5316\u6570\u636e\u3002<\/p>\n<\/p>\n
import requests<\/p>\n
url = "http:\/\/api.example.com\/data"<\/p>\n
response = requests.get(url)<\/p>\n
data = response.json()<\/p>\n
\u5904\u7406\u6570\u636e<\/strong><\/h2>\n
for item in data:<\/p>\n
    print(item['name'], item['value'])<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e09\u3001\u4f7f\u7528\u6570\u636e\u5e93\u67e5\u8be2<\/p>\n<\/p>\n
\u5982\u679c\u6570\u636e\u5b58\u50a8\u5728\u6570\u636e\u5e93\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528SQL\u67e5\u8be2\u6765\u83b7\u53d6\u6570\u636e\u3002Python\u4e2d\u5e38\u7528\u7684\u6570\u636e\u5e93\u5e93\u5305\u62ecSQLite\u3001MySQL\u548cPostgreSQL\u3002<\/p>\n<\/p>\n
import sqlite3<\/p>\n
conn = sqlite3.connect('example.db')<\/p>\n
cursor = conn.cursor()<\/p>\n
cursor.execute("SELECT name, value FROM data")<\/p>\n
rows = cursor.fetchall()<\/p>\n
for row in rows:<\/p>\n
    print(row[0], row[1])<\/p>\n
conn.close()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56db\u3001\u8bfb\u53d6\u6587\u4ef6\u6570\u636e<\/p>\n<\/p>\n
\u8bb8\u591a\u7edf\u8ba1\u6570\u636e\u5b58\u50a8\u5728\u6587\u4ef6\u4e2d\uff0c\u4f8b\u5982CSV\u3001Excel\u548cJSON\u6587\u4ef6\u3002Python\u63d0\u4f9b\u4e86\u591a\u4e2a\u5e93\u6765\u8bfb\u53d6\u548c\u5904\u7406\u8fd9\u4e9b\u6587\u4ef6\u3002<\/p>\n<\/p>\n
1\u3001\u8bfb\u53d6CSV\u6587\u4ef6<\/p>\n<\/p>\n
import csv<\/p>\n
with open('data.csv', newline='') as csvfile:<\/p>\n
    reader = csv.DictReader(csvfile)<\/p>\n
    for row in reader:<\/p>\n
        print(row['name'], row['value'])<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u8bfb\u53d6Excel\u6587\u4ef6<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
df = pd.read_excel('data.xlsx')<\/p>\n
for index, row in df.iterrows():<\/p>\n
    print(row['name'], row['value'])<\/p>\n
<\/code><\/pre>\n<\/p>\n
3\u3001\u8bfb\u53d6JSON\u6587\u4ef6<\/p>\n<\/p>\n
import json<\/p>\n
with open('data.json') as jsonfile:<\/p>\n
    data = json.load(jsonfile)<\/p>\n
    for item in data:<\/p>\n
        print(item['name'], item['value'])<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e94\u3001\u6570\u636e\u5904\u7406\u548c\u6e05\u6d17<\/p>\n<\/p>\n
\u5728\u83b7\u53d6\u6570\u636e\u540e\uff0c\u901a\u5e38\u9700\u8981\u8fdb\u884c\u6570\u636e\u5904\u7406\u548c\u6e05\u6d17\u3002Python\u63d0\u4f9b\u4e86\u591a\u4e2a\u5e93\u6765\u5e2e\u52a9\u5904\u7406\u6570\u636e\uff0c\u4f8b\u5982Pandas\u3001NumPy\u548cScikit-learn\u3002<\/p>\n<\/p>\n
1\u3001\u4f7f\u7528Pandas\u8fdb\u884c\u6570\u636e\u5904\u7406<\/p>\n<\/p>\n
Pandas\u662f\u4e00\u4e2a\u529f\u80fd\u5f3a\u5927\u7684\u6570\u636e\u5904\u7406\u5e93\uff0c\u63d0\u4f9b\u4e86\u6570\u636e\u6846\uff08DataFrame\uff09\u548c\u7cfb\u5217\uff08Series\uff09\u4e24\u79cd\u6570\u636e\u7ed3\u6784\u3002<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
df = pd.read_csv('data.csv')<\/p>\n
\u5904\u7406\u7f3a\u5931\u503c<\/strong><\/h2>\n
df.fillna(0, inplace=True)<\/p>\n
\u6570\u636e\u8f6c\u6362<\/strong><\/h2>\n
df['value'] = df['value'].astype(float)<\/p>\n
\u6570\u636e\u8fc7\u6ee4<\/strong><\/h2>\n
filtered_df = df[df['value'] > 10]<\/p>\n
print(filtered_df)<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u4f7f\u7528NumPy\u8fdb\u884c\u6570\u503c\u8ba1\u7b97<\/p>\n<\/p>\n
NumPy\u662f\u4e00\u4e2a\u7528\u4e8e\u6570\u503c\u8ba1\u7b97\u7684\u5e93\uff0c\u63d0\u4f9b\u4e86\u591a\u7ef4\u6570\u7ec4\u5bf9\u8c61\u548c\u4e30\u5bcc\u7684\u6570\u5b66\u51fd\u6570\u3002<\/p>\n<\/p>\n
import numpy as np<\/p>\n
data = np.array([1, 2, 3, 4, 5])<\/p>\n
\u8ba1\u7b97\u5747\u503c<\/strong><\/h2>\n
mean = np.mean(data)<\/p>\n
\u8ba1\u7b97\u6807\u51c6\u5dee<\/strong><\/h2>\n
std = np.std(data)<\/p>\n
print("Mean:", mean)<\/p>\n
print("Standard Deviation:", std)<\/p>\n
<\/code><\/pre>\n<\/p>\n
3\u3001\u4f7f\u7528Scikit-learn\u8fdb\u884c\u6570\u636e\u9884\u5904\u7406<\/p>\n<\/p>\n
Scikit-learn\u662f\u4e00\u4e2a\u7528\u4e8e\u673a\u5668\u5b66\u4e60<\/a>\u7684\u5e93\uff0c\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u6570\u636e\u9884\u5904\u7406\u5de5\u5177\u3002<\/p>\n<\/p>\n
from sklearn.preprocessing import StandardScaler<\/p>\n
data = [[1, 2], [3, 4], [5, 6]]<\/p>\n
scaler = StandardScaler()<\/p>\n
scaled_data = scaler.fit_transform(data)<\/p>\n
print(scaled_data)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u516d\u3001\u6570\u636e\u53ef\u89c6\u5316<\/p>\n<\/p>\n
\u6570\u636e\u53ef\u89c6\u5316\u662f\u6570\u636e\u5206\u6790\u7684\u91cd\u8981\u73af\u8282\uff0c\u53ef\u4ee5\u5e2e\u52a9\u6211\u4eec\u66f4\u76f4\u89c2\u5730\u7406\u89e3\u6570\u636e\u3002Python\u63d0\u4f9b\u4e86\u591a\u4e2a\u53ef\u89c6\u5316\u5e93\uff0c\u4f8b\u5982Matplotlib\u3001Seaborn\u548cPlotly\u3002<\/p>\n<\/p>\n
1\u3001\u4f7f\u7528Matplotlib\u8fdb\u884c\u6570\u636e\u53ef\u89c6\u5316<\/p>\n<\/p>\n
Matplotlib\u662f\u4e00\u4e2a\u57fa\u7840\u7684\u7ed8\u56fe\u5e93\uff0c\u9002\u7528\u4e8e\u521b\u5efa\u7b80\u5355\u7684\u56fe\u8868\u3002<\/p>\n<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
data = [1, 2, 3, 4, 5]<\/p>\n
plt.plot(data)<\/p>\n
plt.xlabel('X-axis')<\/p>\n
plt.ylabel('Y-axis')<\/p>\n
plt.title('Simple Plot')<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u4f7f\u7528Seaborn\u8fdb\u884c\u9ad8\u7ea7\u53ef\u89c6\u5316<\/p>\n<\/p>\n
Seaborn\u662f\u4e00\u4e2a\u57fa\u4e8eMatplotlib\u7684\u9ad8\u7ea7\u7ed8\u56fe\u5e93\uff0c\u63d0\u4f9b\u4e86\u66f4\u7f8e\u89c2\u7684\u56fe\u8868\u548c\u66f4\u591a\u7684\u529f\u80fd\u3002<\/p>\n<\/p>\n
import seaborn as sns<\/p>\n
import pandas as pd<\/p>\n
df = pd.read_csv('data.csv')<\/p>\n
sns.barplot(x='name', y='value', data=df)<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
3\u3001\u4f7f\u7528Plotly\u8fdb\u884c\u4ea4\u4e92\u5f0f\u53ef\u89c6\u5316<\/p>\n<\/p>\n
Plotly\u662f\u4e00\u4e2a\u7528\u4e8e\u521b\u5efa\u4ea4\u4e92\u5f0f\u56fe\u8868\u7684\u5e93\uff0c\u975e\u5e38\u9002\u5408\u521b\u5efa\u590d\u6742\u7684\u53ef\u89c6\u5316\u3002<\/p>\n<\/p>\n
import plotly.express as px<\/p>\n
df = pd.read_csv('data.csv')<\/p>\n
fig = px.bar(df, x='name', y='value')<\/p>\n
fig.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u603b\u7ed3<\/p>\n<\/p>\n
\u901a\u8fc7Python\u6536\u96c6\u548c\u7edf\u8ba1\u6570\u636e\u7684\u65b9\u6cd5\u591a\u79cd\u591a\u6837\uff0c\u5305\u62ec\u4f7f\u7528\u7f51\u7edc\u722c\u866b\u3001\u8c03\u7528API\u63a5\u53e3\u3001\u4f7f\u7528\u6570\u636e\u5e93\u67e5\u8be2\u548c\u8bfb\u53d6\u6587\u4ef6\u6570\u636e\u3002\u6bcf\u79cd\u65b9\u6cd5\u90fd\u6709\u5176\u72ec\u7279\u7684\u4f18\u52bf\u548c\u9002\u7528\u573a\u666f\u3002\u5728\u83b7\u53d6\u6570\u636e\u540e\uff0c\u901a\u5e38\u9700\u8981\u8fdb\u884c\u6570\u636e\u5904\u7406\u548c\u6e05\u6d17\uff0c\u5e76\u6700\u7ec8\u8fdb\u884c\u6570\u636e\u53ef\u89c6\u5316\uff0c\u4ee5\u4fbf\u66f4\u76f4\u89c2\u5730\u7406\u89e3\u6570\u636e\u3002Python\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u5e93\u548c\u5de5\u5177\uff0c\u53ef\u4ee5\u5e2e\u52a9\u6211\u4eec\u9ad8\u6548\u5730\u5b8c\u6210\u8fd9\u4e00\u7cfb\u5217\u4efb\u52a1\u3002\u901a\u8fc7\u4e0d\u65ad\u5b9e\u8df5\u548c\u5b66\u4e60\uff0c\u53ef\u4ee5\u63d0\u9ad8\u6570\u636e\u6536\u96c6\u548c\u5206\u6790\u7684\u80fd\u529b\uff0c\u4e3a\u6570\u636e\u9a71\u52a8\u7684\u51b3\u7b56\u63d0\u4f9b\u6709\u529b\u652f\u6301\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
 \u5982\u4f55\u4f7f\u7528Python\u6536\u96c6\u7edf\u8ba1\u6570\u636e\uff1f<\/strong>
\u4f7f\u7528Python\u6536\u96c6\u7edf\u8ba1\u6570\u636e\u53ef\u4ee5\u901a\u8fc7\u591a\u79cd\u65b9\u5f0f\u5b9e\u73b0\u3002\u4f60\u53ef\u4ee5\u4f7f\u7528Python\u7684\u5185\u7f6e\u5e93\uff0c\u5982pandas<\/code>\u548cnumpy<\/code>\uff0c\u6765\u5904\u7406\u548c\u5206\u6790\u6570\u636e\u3002\u901a\u8fc7\u7f51\u7edc\u722c\u866b\u5de5\u5177\uff0c\u5982BeautifulSoup<\/code>\u548cScrapy<\/code>\uff0c\u53ef\u4ee5\u4ece\u7f51\u9875\u4e0a\u63d0\u53d6\u6570\u636e\u3002\u6b64\u5916\uff0cAPI\u63a5\u53e3\u4e5f\u662f\u4e00\u4e2a\u91cd\u8981\u7684\u6570\u636e\u6536\u96c6\u6e20\u9053\uff0c\u4f7f\u7528requests<\/code>\u5e93\u53ef\u4ee5\u8f7b\u677e\u5730\u83b7\u53d6\u5728\u7ebf\u6570\u636e\u3002<\/p>\n
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