python爬虫的练习
- 1.爬取天气网的北京城市历史天气数据
- 1.1 第一种使用面向对象OOP编写爬虫
- 1.2 第二种使用面向过程函数编写爬虫
1.爬取天气网的北京城市历史天气数据
1.1 第一种使用面向对象OOP编写爬虫
import re
import requests
from bs4 import BeautifulSoup
import xlwtclass Spider(object):""" 天气数据爬虫类 """ datatime_pattern = re.compile(r'<div class="th200">(.*?)</div>')wendu_pattern = re.compile(r'<div class="th140">(.*?)</div>')def __init__(self, url, headers, filepath):""" 初始化方法 :param url: 基础URL模板 :param headers: HTTP请求头 :param filepath: 输出文件路径 """ self.url = urlself.headers = headersself.datalist = [] self.mwen = [] self.iwen = [] self.tq = [] self.fx = [] self.filepath = filepath def download_page(self,url):""" 下载页面并返回页面内容 :param url: 要下载的页面URL :return: 页面内容或None(如果下载失败)""" try:response = requests.get(url, headers=self.headers)response.raise_for_status() return response.textexcept requests.RequestException as e:print(f"Error downloading page: {e}")return Nonedef parse_page(self, html):""" 解析页面内容,提取日期和温度数据 :param html: 页面内容 """ soup = BeautifulSoup(html, 'html.parser')for item in soup.find_all('ul', class_='thrui'):item_str = str(item)dates = re.findall(self.datatime_pattern, item_str)self.datalist.extend(dates)temperatures = re.findall(self.wendu_pattern, item_str)print(temperatures)for i in range(0, len(temperatures), 4):self.mwen.append(temperatures[i])self.iwen.append(temperatures[i + 1])self.tq.append(temperatures[i + 2])self.fx.append(temperatures[i + 3])def download_and_parse_all_pages(self):""" 下载并解析所有页面 """ for year in range(23, 24): for month in range(1, 2): page_url = f"{self.url}20{year:02d}{month:02d}.html" print(page_url)html = self.download_page(page_url)if html:self.parse_page(html)def save_to_excel(self):""" 将爬取的数据保存到Excel文件中 """ workbook = xlwt.Workbook(encoding='utf-8', style_compression=0)worksheet = workbook.add_sheet('北京历史天气数据', cell_overwrite_ok=True)columns = ("日期", "最高温度", "最低温度", "天气", "风向")for i, col in enumerate(columns):worksheet.write(0, i, col)for i in range(len(self.datalist)):worksheet.write(i + 1, 0, self.datalist[i])worksheet.write(i + 1, 1, self.mwen[i])worksheet.write(i + 1, 2, self.iwen[i])worksheet.write(i + 1, 3, self.tq[i])worksheet.write(i + 1, 4, self.fx[i])workbook.save(self.filepath)print(f"Data saved to {self.filepath}")def run(self):self.download_and_parse_all_pages()self.save_to_excel()if __name__ == '__main__':headers = {'User-Agent': 'Mozilla/5.0(compatible; Baiduspider/2.0; +http://www.baidu.com/search/spider.html)'}url_template = "http://lishi.tianqi.com/beijing/"filepath = "beijing_weather_data.xls"spider = Spider(url_template, headers, filepath)spider.run()
1.2 第二种使用面向过程函数编写爬虫
import requests
from bs4 import BeautifulSoup
import re
import xlwtdatatime = re.compile('<div class="th200">(.*?)</div>')
wendu = re.compile('<div class="th140">(.*?)</div>')def down_allpage(url):datalist = []mwen = []iwen = []tq = []fx = []for i in range(23,24):for j in range(1,2):baseurl = url + '20{}{:0>2d}.html'.format(i, j)html = down_page(baseurl)soup = BeautifulSoup(html, 'html.parser')for item in soup.find_all('ul',class_='thrui'):item = str(item)riqi = re.findall(datatime,item)for item1 in riqi:datalist.append(item1)zb_all = re.findall(wendu,item)for i in range(31):mwen.append(zb_all[i*4+0])iwen.append(zb_all[i*4+1])tq.append(zb_all[i*4+2])fx.append(zb_all[i*4+3])return datalist,mwen,iwen,tq,fxdef save_xls(datalist,mwen,iwen,tq,fx):wb = xlwt.Workbook(encoding='utf-8', style_compression=0)ws = wb.add_sheet('天气数据',cell_overwrite_ok=True)col = ("日期","最高温度","最低温度","天气","风向")for i in range(len(col)):ws.write(0,i,col[i])for i in range(len(datalist)):ws.write(i+1,0,datalist[i])for i in range(len(mwen)):ws.write(i+1,1,mwen[i])for i in range(len(iwen)):ws.write(i+1,2,iwen[i])for i in range(len(tq)):ws.write(i+1,3,tq[i])for i in range(len(fx)):ws.write(i+1,4,fx[i])wb.save(r'D:\天气数据.xls')def down_page(url):headers = {'User-Agent': 'Mozilla/5.0(compatible; Baiduspider/2.0; +http://www.baidu.com/search/spider.html)'}r = requests.get(url, headers=headers)html = r.textreturn htmlif __name__ == '__main__':url = 'http://lishi.tianqi.com/beijing/'down_allpage(url)datalist,mwen,iwen,tq,fx = down_allpage(url)print(datalist)save_xls(datalist,mwen,iwen,tq,fx)