{"id":1104526,"date":"2025-01-08T16:21:37","date_gmt":"2025-01-08T08:21:37","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1104526.html"},"modified":"2025-01-08T16:21:41","modified_gmt":"2025-01-08T08:21:41","slug":"%e5%a6%82%e4%bd%95%e5%86%99python%e7%88%ac%e5%8f%96%e8%b4%a2%e6%8a%a5%e6%95%b0%e6%8d%ae","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1104526.html","title":{"rendered":"\u5982\u4f55\u5199python\u722c\u53d6\u8d22\u62a5\u6570\u636e"},"content":{"rendered":"

\"\u5982\u4f55\u5199python\u722c\u53d6\u8d22\u62a5\u6570\u636e\"<\/p>\n

\u8981\u5199Python\u722c\u53d6\u8d22\u62a5\u6570\u636e\uff0c\u53ef\u4ee5\u4f7f\u7528\u7f51\u7edc\u722c\u866b\u3001API\u63a5\u53e3\u83b7\u53d6\u6570\u636e\u3001\u6570\u636e\u89e3\u6790\u4e0e\u6e05\u6d17<\/strong>\u3002\u672c\u6587\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528Python\u722c\u53d6\u8d22\u62a5\u6570\u636e\uff0c\u5e76\u5206\u6b65\u8bb2\u89e3\u6bcf\u4e2a\u73af\u8282\u7684\u5177\u4f53\u64cd\u4f5c\u65b9\u6cd5\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u7f51\u7edc\u722c\u866b<\/p>\n<\/p>\n

\u4f7f\u7528\u7f51\u7edc\u722c\u866b\u662f\u83b7\u53d6\u8d22\u62a5\u6570\u636e\u7684\u5e38\u7528\u65b9\u6cd5\u4e4b\u4e00\u3002\u722c\u866b\u901a\u8fc7\u6a21\u62df\u6d4f\u89c8\u5668\u7684\u884c\u4e3a\uff0c\u81ea\u52a8\u8bbf\u95ee\u7f51\u9875\u5e76\u63d0\u53d6\u6240\u9700\u7684\u4fe1\u606f\u3002\u4ee5\u4e0b\u662f\u4f7f\u7528Python\u722c\u53d6\u8d22\u62a5\u6570\u636e\u7684\u5177\u4f53\u6b65\u9aa4\uff1a<\/p>\n<\/p>\n

\u5b89\u88c5\u5fc5\u8981\u7684\u5e93<\/h3>\n<\/p>\n

\u9996\u5148\uff0c\u6211\u4eec\u9700\u8981\u5b89\u88c5\u4e00\u4e9b\u5fc5\u8981\u7684\u5e93\uff0c\u5982requests<\/code>\u548cBeautifulSoup<\/code>\u3002requests<\/code>\u7528\u4e8e\u53d1\u9001HTTP\u8bf7\u6c42\uff0cBeautifulSoup<\/code>\u7528\u4e8e\u89e3\u6790HTML\u6587\u6863\u3002<\/p>\n<\/p>\n

pip install requests<\/p>\n
pip install beautifulsoup4<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u53d1\u9001HTTP\u8bf7\u6c42\u5e76\u83b7\u53d6\u7f51\u9875\u5185\u5bb9<\/h3>\n<\/p>\n
\u901a\u8fc7requests<\/code>\u5e93\u53d1\u9001HTTP\u8bf7\u6c42\uff0c\u83b7\u53d6\u7f51\u9875\u5185\u5bb9\u3002<\/p>\n<\/p>\n
import requests<\/p>\n
from bs4 import BeautifulSoup<\/p>\n
url = 'https:\/\/example.com\/financial-reports'<\/p>\n
response = requests.get(url)<\/p>\n
html_content = response.content<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u89e3\u6790HTML\u6587\u6863<\/h3>\n<\/p>\n
\u4f7f\u7528BeautifulSoup<\/code>\u89e3\u6790HTML\u6587\u6863\uff0c\u63d0\u53d6\u8d22\u62a5\u6570\u636e\u3002<\/p>\n<\/p>\n
soup = BeautifulSoup(html_content, 'html.parser')<\/p>\n
financial_reports = soup.find_all('div', class_='financial-report')<\/p>\n
for report in financial_reports:<\/p>\n
    report_date = report.find('span', class_='date').text<\/p>\n
    report_link = report.find('a')['href']<\/p>\n
    print(f'Report Date: {report_date}, Report Link: {report_link}')<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e8c\u3001API\u63a5\u53e3\u83b7\u53d6\u6570\u636e<\/p>\n<\/p>\n
\u5f88\u591a\u7f51\u7ad9\u63d0\u4f9bAPI\u63a5\u53e3\u4f9b\u7528\u6237\u83b7\u53d6\u6570\u636e\u3002\u901a\u8fc7API\u63a5\u53e3\u83b7\u53d6\u6570\u636e\uff0c\u901a\u5e38\u6bd4\u4f7f\u7528\u7f51\u7edc\u722c\u866b\u66f4\u4e3a\u7b80\u4fbf\u548c\u9ad8\u6548\u3002\u4ee5\u4e0b\u662f\u4f7f\u7528API\u63a5\u53e3\u83b7\u53d6\u8d22\u62a5\u6570\u636e\u7684\u5177\u4f53\u6b65\u9aa4\uff1a<\/p>\n<\/p>\n
\u83b7\u53d6API\u5bc6\u94a5<\/h3>\n<\/p>\n
\u9996\u5148\uff0c\u6211\u4eec\u9700\u8981\u6ce8\u518c\u5e76\u83b7\u53d6API\u5bc6\u94a5\u3002\u4ee5\u67d0\u4e2a\u8d22\u62a5\u6570\u636eAPI\u4e3a\u4f8b\uff0c\u6ce8\u518c\u5e76\u83b7\u53d6API\u5bc6\u94a5\u540e\uff0c\u53ef\u4ee5\u901a\u8fc7API\u63a5\u53e3\u83b7\u53d6\u6570\u636e\u3002<\/p>\n<\/p>\n
\u53d1\u9001API\u8bf7\u6c42\u5e76\u83b7\u53d6\u6570\u636e<\/h3>\n<\/p>\n
\u901a\u8fc7requests<\/code>\u5e93\u53d1\u9001API\u8bf7\u6c42\uff0c\u83b7\u53d6\u8d22\u62a5\u6570\u636e\u3002<\/p>\n<\/p>\n
import requests<\/p>\n
api_key = 'your_api_key'<\/p>\n
url = f'https:\/\/api.example.com\/financial-reports?api_key={api_key}'<\/p>\n
response = requests.get(url)<\/p>\n
data = response.json()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u89e3\u6790\u5e76\u5904\u7406\u6570\u636e<\/h3>\n<\/p>\n
\u89e3\u6790API\u8fd4\u56de\u7684JSON\u6570\u636e\uff0c\u5e76\u8fdb\u884c\u5904\u7406\u3002<\/p>\n<\/p>\n
for report in data['financial_reports']:<\/p>\n
    report_date = report['date']<\/p>\n
    report_link = report['link']<\/p>\n
    print(f'Report Date: {report_date}, Report Link: {report_link}')<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e09\u3001\u6570\u636e\u89e3\u6790\u4e0e\u6e05\u6d17<\/p>\n<\/p>\n
\u83b7\u53d6\u5230\u8d22\u62a5\u6570\u636e\u540e\uff0c\u6211\u4eec\u901a\u5e38\u9700\u8981\u5bf9\u6570\u636e\u8fdb\u884c\u89e3\u6790\u4e0e\u6e05\u6d17\u3002\u4ee5\u4e0b\u662f\u6570\u636e\u89e3\u6790\u4e0e\u6e05\u6d17\u7684\u5177\u4f53\u6b65\u9aa4\uff1a<\/p>\n<\/p>\n
\u89e3\u6790HTML\u6216JSON\u6570\u636e<\/h3>\n<\/p>\n
\u6839\u636e\u83b7\u53d6\u6570\u636e\u7684\u65b9\u5f0f\u4e0d\u540c\uff0c\u6211\u4eec\u9700\u8981\u89e3\u6790HTML\u6216JSON\u6570\u636e\u3002\u5bf9\u4e8eHTML\u6570\u636e\uff0c\u53ef\u4ee5\u4f7f\u7528BeautifulSoup<\/code>\u8fdb\u884c\u89e3\u6790\uff1b\u5bf9\u4e8eJSON\u6570\u636e\uff0c\u76f4\u63a5\u4f7f\u7528Python\u7684\u5185\u7f6e\u6a21\u5757\u8fdb\u884c\u89e3\u6790\u3002<\/p>\n<\/p>\n
\u6570\u636e\u6e05\u6d17<\/h3>\n<\/p>\n
\u6570\u636e\u6e05\u6d17\u662f\u6307\u5bf9\u6570\u636e\u8fdb\u884c\u6574\u7406\u548c\u8f6c\u6362\uff0c\u4ee5\u4fbf\u540e\u7eed\u5206\u6790\u3002\u5e38\u89c1\u7684\u6570\u636e\u6e05\u6d17\u64cd\u4f5c\u5305\u62ec\u53bb\u9664\u7a7a\u503c\u3001\u683c\u5f0f\u5316\u65e5\u671f\u3001\u5904\u7406\u5f02\u5e38\u503c\u7b49\u3002<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
\u793a\u4f8b\u6570\u636e<\/strong><\/h2>\n
data = [<\/p>\n
    {'date': '2023-01-01', 'link': 'https:\/\/example.com\/report1', 'value': 100},<\/p>\n
    {'date': '2023-02-01', 'link': 'https:\/\/example.com\/report2', 'value': None},<\/p>\n
    {'date': '2023-03-01', 'link': 'https:\/\/example.com\/report3', 'value': 200},<\/p>\n
]<\/p>\n
df = pd.DataFrame(data)<\/p>\n
\u53bb\u9664\u7a7a\u503c<\/strong><\/h2>\n
df.dropna(inplace=True)<\/p>\n
\u683c\u5f0f\u5316\u65e5\u671f<\/strong><\/h2>\n
df['date'] = pd.to_datetime(df['date'])<\/p>\n
\u5904\u7406\u5f02\u5e38\u503c<\/strong><\/h2>\n
df = df[df['value'] > 0]<\/p>\n
print(df)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56db\u3001\u4fdd\u5b58\u6570\u636e<\/p>\n<\/p>\n
\u5728\u6570\u636e\u6e05\u6d17\u5b8c\u6bd5\u540e\uff0c\u6211\u4eec\u901a\u5e38\u9700\u8981\u5c06\u6570\u636e\u4fdd\u5b58\u5230\u6587\u4ef6\u6216\u6570\u636e\u5e93\u4e2d\u3002\u4ee5\u4e0b\u662f\u4fdd\u5b58\u6570\u636e\u7684\u5177\u4f53\u6b65\u9aa4\uff1a<\/p>\n<\/p>\n
\u4fdd\u5b58\u5230CSV\u6587\u4ef6<\/h3>\n<\/p>\n
\u4f7f\u7528pandas<\/code>\u5e93\u5c06\u6570\u636e\u4fdd\u5b58\u5230CSV\u6587\u4ef6\u3002<\/p>\n<\/p>\n
df.to_csv('financial_reports.csv', index=False)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4fdd\u5b58\u5230\u6570\u636e\u5e93<\/h3>\n<\/p>\n
\u4f7f\u7528SQLAlchemy<\/code>\u5e93\u5c06\u6570\u636e\u4fdd\u5b58\u5230\u6570\u636e\u5e93\u3002<\/p>\n<\/p>\n
from sqlalchemy import create_engine<\/p>\n
engine = create_engine('sqlite:\/\/\/financial_reports.db')<\/p>\n
df.to_sql('financial_reports', engine, index=False, if_exists='replace')<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e94\u3001\u81ea\u52a8\u5316\u6570\u636e\u722c\u53d6<\/p>\n<\/p>\n
\u4e3a\u4e86\u5b9e\u73b0\u6570\u636e\u7684\u81ea\u52a8\u5316\u722c\u53d6\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528schedule<\/code>\u5e93\u5b9a\u65f6\u8fd0\u884c\u722c\u866b\u811a\u672c\u3002\u4ee5\u4e0b\u662f\u81ea\u52a8\u5316\u6570\u636e\u722c\u53d6\u7684\u5177\u4f53\u6b65\u9aa4\uff1a<\/p>\n<\/p>\n
\u5b89\u88c5schedule<\/code>\u5e93<\/h3>\n<\/p>\n
\u9996\u5148\uff0c\u6211\u4eec\u9700\u8981\u5b89\u88c5schedule<\/code>\u5e93\u3002<\/p>\n<\/p>\n
pip install schedule<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5b9a\u4e49\u722c\u866b\u4efb\u52a1<\/h3>\n<\/p>\n
\u5b9a\u4e49\u4e00\u4e2a\u51fd\u6570\uff0c\u7528\u4e8e\u6267\u884c\u722c\u866b\u4efb\u52a1\u3002<\/p>\n<\/p>\n
import schedule<\/p>\n
import time<\/p>\n
def job():<\/p>\n
    # \u722c\u53d6\u6570\u636e\u7684\u4ee3\u7801<\/p>\n
    print('Crawling data...')<\/p>\n
schedule.every().day.at('10:00').do(job)<\/p>\n
while True:<\/p>\n
    schedule.run_pending()<\/p>\n
    time.sleep(1)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8fd0\u884c\u722c\u866b\u4efb\u52a1<\/h3>\n<\/p>\n
\u542f\u52a8\u811a\u672c\uff0c\u5b9a\u65f6\u8fd0\u884c\u722c\u866b\u4efb\u52a1\u3002<\/p>\n<\/p>\n
\u516d\u3001\u5f02\u5e38\u5904\u7406<\/p>\n<\/p>\n
\u5728\u722c\u53d6\u8d22\u62a5\u6570\u636e\u7684\u8fc7\u7a0b\u4e2d\uff0c\u6211\u4eec\u53ef\u80fd\u4f1a\u9047\u5230\u5404\u79cd\u5f02\u5e38\u60c5\u51b5\uff0c\u5982\u7f51\u7edc\u8fde\u63a5\u5931\u8d25\u3001\u9875\u9762\u7ed3\u6784\u53d1\u751f\u53d8\u5316\u7b49\u3002\u4e3a\u4e86\u4fdd\u8bc1\u722c\u866b\u7684\u7a33\u5b9a\u6027\u548c\u5065\u58ee\u6027\uff0c\u6211\u4eec\u9700\u8981\u8fdb\u884c\u5f02\u5e38\u5904\u7406\u3002\u4ee5\u4e0b\u662f\u5f02\u5e38\u5904\u7406\u7684\u5177\u4f53\u6b65\u9aa4\uff1a<\/p>\n<\/p>\n
\u6355\u83b7\u5f02\u5e38<\/h3>\n<\/p>\n
\u4f7f\u7528try-except<\/code>\u8bed\u53e5\u6355\u83b7\u5f02\u5e38\uff0c\u5e76\u8fdb\u884c\u76f8\u5e94\u5904\u7406\u3002<\/p>\n<\/p>\n
try:<\/p>\n
    response = requests.get(url)<\/p>\n
    response.rAI<\/a>se_for_status()<\/p>\n
    html_content = response.content<\/p>\n
except requests.exceptions.RequestException as e:<\/p>\n
    print(f'Error: {e}')<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u91cd\u8bd5\u673a\u5236<\/h3>\n<\/p>\n
\u5bf9\u4e8e\u67d0\u4e9b\u4e34\u65f6\u6027\u9519\u8bef\uff0c\u53ef\u4ee5\u4f7f\u7528\u91cd\u8bd5\u673a\u5236\u3002\u5728\u9047\u5230\u9519\u8bef\u65f6\uff0c\u7b49\u5f85\u4e00\u6bb5\u65f6\u95f4\u540e\u91cd\u65b0\u5c1d\u8bd5\u3002<\/p>\n<\/p>\n
import time<\/p>\n
max_retries = 3<\/p>\n
retry_delay = 5<\/p>\n
for attempt in range(max_retries):<\/p>\n
    try:<\/p>\n
        response = requests.get(url)<\/p>\n
        response.raise_for_status()<\/p>\n
        html_content = response.content<\/p>\n
        break<\/p>\n
    except requests.exceptions.RequestException as e:<\/p>\n
        print(f'Error: {e}, retrying in {retry_delay} seconds...')<\/p>\n
        time.sleep(retry_delay)<\/p>\n
else:<\/p>\n
    print('Max retries exceeded.')<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e03\u3001\u65e5\u5fd7\u8bb0\u5f55<\/p>\n<\/p>\n
\u4e3a\u4e86\u4fbf\u4e8e\u8c03\u8bd5\u548c\u76d1\u63a7\u722c\u866b\u7684\u8fd0\u884c\u72b6\u6001\uff0c\u6211\u4eec\u9700\u8981\u8bb0\u5f55\u65e5\u5fd7\u3002\u4ee5\u4e0b\u662f\u65e5\u5fd7\u8bb0\u5f55\u7684\u5177\u4f53\u6b65\u9aa4\uff1a<\/p>\n<\/p>\n
\u914d\u7f6e\u65e5\u5fd7\u8bb0\u5f55<\/h3>\n<\/p>\n
\u4f7f\u7528logging<\/code>\u5e93\u914d\u7f6e\u65e5\u5fd7\u8bb0\u5f55\u3002<\/p>\n<\/p>\n
import logging<\/p>\n
logging.basicConfig(level=logging.INFO,<\/p>\n
                    format='%(asctime)s - %(levelname)s - %(message)s',<\/p>\n
                    filename='crawler.log',<\/p>\n
                    filemode='w')<\/p>\n
logger = logging.getLogger(__name__)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8bb0\u5f55\u65e5\u5fd7<\/h3>\n<\/p>\n
\u5728\u722c\u866b\u4ee3\u7801\u4e2d\u8bb0\u5f55\u5173\u952e\u4fe1\u606f\u548c\u5f02\u5e38\u60c5\u51b5\u3002<\/p>\n<\/p>\n
try:<\/p>\n
    response = requests.get(url)<\/p>\n
    response.raise_for_status()<\/p>\n
    html_content = response.content<\/p>\n
    logger.info('Successfully fetched data.')<\/p>\n
except requests.exceptions.RequestException as e:<\/p>\n
    logger.error(f'Error: {e}')<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u516b\u3001\u6570\u636e\u5206\u6790\u4e0e\u53ef\u89c6\u5316<\/p>\n<\/p>\n
\u83b7\u53d6\u548c\u6e05\u6d17\u8d22\u62a5\u6570\u636e\u540e\uff0c\u6211\u4eec\u53ef\u4ee5\u5bf9\u6570\u636e\u8fdb\u884c\u5206\u6790\u4e0e\u53ef\u89c6\u5316\u3002\u4ee5\u4e0b\u662f\u6570\u636e\u5206\u6790\u4e0e\u53ef\u89c6\u5316\u7684\u5177\u4f53\u6b65\u9aa4\uff1a<\/p>\n<\/p>\n
\u6570\u636e\u5206\u6790<\/h3>\n<\/p>\n
\u4f7f\u7528pandas<\/code>\u5e93\u8fdb\u884c\u6570\u636e\u5206\u6790\u3002<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
\u793a\u4f8b\u6570\u636e<\/strong><\/h2>\n
data = [<\/p>\n
    {'date': '2023-01-01', 'value': 100},<\/p>\n
    {'date': '2023-02-01', 'value': 150},<\/p>\n
    {'date': '2023-03-01', 'value': 200},<\/p>\n
]<\/p>\n
df = pd.DataFrame(data)<\/p>\n
\u8ba1\u7b97\u8d22\u62a5\u6570\u636e\u7684\u5e73\u5747\u503c<\/strong><\/h2>\n
average_value = df['value'].mean()<\/p>\n
print(f'Average Value: {average_value}')<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u6570\u636e\u53ef\u89c6\u5316<\/h3>\n<\/p>\n
\u4f7f\u7528matplotlib<\/code>\u5e93\u8fdb\u884c\u6570\u636e\u53ef\u89c6\u5316\u3002<\/p>\n<\/p>\n
import matplotlib.pyplot as plt<\/p>\n
\u7ed8\u5236\u8d22\u62a5\u6570\u636e\u7684\u6298\u7ebf\u56fe<\/strong><\/h2>\n
df['date'] = pd.to_datetime(df['date'])<\/p>\n
df.set_index('date', inplace=True)<\/p>\n
df['value'].plot()<\/p>\n
plt.xlabel('Date')<\/p>\n
plt.ylabel('Value')<\/p>\n
plt.title('Financial Report Values Over Time')<\/p>\n
plt.show()<\/p>\n
<\/code><\/pre>\n<\/p>\n
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