python从入门到精通（十八）：python爬虫的练习案列集合

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 xlwt


class Spider(object):
	"""  
    天气数据爬虫类  
    """  
    # 定义类变量，用于正则表达式
    datatime_pattern = re.compile(r'
(.*?)
')
    wendu_pattern = re.compile(r'
(.*?)
')

    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 = url
        self.headers = headers
        self.datalist = []  # 存储日期的列表  
        self.mwen = []      # 存储最高温度的列表  
        self.iwen = []     	# 存储最低温度的列表  
        self.tq = []		# 存储天气状况的列表  
        self.fx = []		# 存储风向的列表 
        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()  # 如果HTTP请求返回了不成功的状态码，则引发HTTPError异常
            return response.text
        except requests.RequestException as e:
            print(f"Error downloading page: {e}")
            return None

    def 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')
        # print(soup)
        for item in soup.find_all('ul', class_='thrui'):
            item_str = str(item)
            # print(item)
             # 使用正则表达式提取日期数据  
            dates = re.findall(self.datatime_pattern, item_str)
            self.datalist.extend(dates)
            # print(dates)
			 # 使用正则表达式提取温度数据  
            temperatures = re.findall(self.wendu_pattern, item_str)
            print(temperatures)
           # 假设每组温度数据包含4个部分：最高温度、最低温度、天气状况、风向  
            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):  # 这里设定只是下载2023年的
            for month in range(1, 2):  # 这里设定只是下载2023年的1月的
                # base_url = self.url  
                page_url = f"{self.url}20{year:02d}{month:02d}.html" # 这里设定不够两位补0
                print(page_url)
                html = self.download_page(page_url)
                # print(html)
                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)
		 # 写入表头 
        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)
		 # 写入数据  
        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 xlwt

datatime = re.compile('
(.*?)
')
wendu = re.compile('
(.*?)
')

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)
            # print(html)
            soup = BeautifulSoup(html, 'html.parser')
            for item in soup.find_all('ul',class_='thrui'):
                # print(item)
                item = str(item)

                riqi = re.findall(datatime,item)
                for item1 in riqi:
                    datalist.append(item1)
                # print(datalist)
                zb_all = re.findall(wendu,item)
                # print(zb_all)
                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])
                # print(mwen,'\n',iwen,'\n',tq,'\n',fx)
    return datalist,mwen,iwen,tq,fx

def 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.text
    return html
    # print(html)




if __name__ == '__main__':
    url = 'http://lishi.tianqi.com/beijing/'
    # down_page(url)
    down_allpage(url)
    datalist,mwen,iwen,tq,fx = down_allpage(url)
    print(datalist)
    save_xls(datalist,mwen,iwen,tq,fx)