Python中怎么爬取天气数据

bar = pygal.Line() # 创建折线图 bar.add('最低气温', lows) #添加两线的数据序列 bar.add('最高气温', highs) #注意lows和highs是int型的列表 bar.x_labels = daytimes bar.x_labels_major = daytimes[::30] bar.x_label_rotation = 45 bar.title = cityname+'未来七天气温走向图' #设置图形标题 bar.x_title = '日期' #x轴标题 bar.y_title = '气温(摄氏度)' # y轴标题 bar.legend_at_bottom = True bar.show_x_guides = False bar.show_y_guides = True bar.render_to_file('temperate1.svg') # 将图像保存为SVG文件，可通过浏览器

import csv import sys import urllib.request from bs4 import BeautifulSoup # 解析页面模块 import pygal import cityinfo cityname = input("请输入你想要查询天气的城市:") if cityname in cityinfo.city: citycode = cityinfo.city[cityname] else: sys.exit() url = '非常抱歉，网页无法访问' + citycode + '.shtml' header = ("User-Agent","Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/76.0.3809.132 Safari/537.36") # 设置头部信息 http_handler = urllib.request.HTTPHandler() opener = urllib.request.build_opener(http_handler) # 修改头部信息 opener.addheaders = [header] request = urllib.request.Request(url) # 制作请求 response = opener.open(request) # 得到应答包 html = response.read() # 读取应答包 html = html.decode('utf-8') # 设置编码，否则会乱码 # 根据得到的页面信息进行初步筛选过滤 final = [] # 初始化一个列表保存数据 bs = BeautifulSoup(html, "html.parser") # 创建BeautifulSoup对象 body = bs.body data = body.find('div', {'id': '7d'}) print(type(data)) ul = data.find('ul') li = ul.find_all('li') # 爬取自己需要的数据 i = 0 # 控制爬取的天数 lows = [] # 保存低温 highs = [] # 保存高温 daytimes = [] # 保存日期 weathers = [] # 保存天气 for day in li: # 便利找到的每一个li if i < 7: temp = [] # 临时存放每天的数据 date = day.find('h2').string # 得到日期 #print(date) temp.append(date) daytimes.append(date) inf = day.find_all('p') # 遍历li下面的p标签有多个p需要使用find_all 而不是find #print(inf[0].string) # 提取第一个p标签的值，即天气 temp.append(inf[0].string) weathers.append(inf[0].string) temlow = inf[1].find('i').string # 最低气温 if inf[1].find('span') is None: # 天气预报可能没有最高气温 temhigh = None temperate = temlow else: temhigh = inf[1].find('span').string # 最高气温 temhigh = temhigh.replace('℃', '') temperate = temhigh + '/' + temlow # temp.append(temhigh) # temp.append(temlow) lowStr = "" lowStr = lowStr.join(temlow.string) lows.append(int(lowStr[:-1])) # 以上三行将低温NavigableString转成int类型并存入低温列表 if temhigh is None: highs.append(int(lowStr[:-1])) highStr = "" highStr = highStr.join(temhigh) highs.append(int(highStr)) # 以上三行将高温NavigableString转成int类型并存入高温列表 temp.append(temperate) final.append(temp) i = i + 1 # 将最终的获取的天气写入csv文件 with open('weather.csv', 'a', errors='ignore', newline='') as f: f_csv = csv.writer(f) f_csv.writerows([cityname]) f_csv.writerows(final) # 绘图 bar = pygal.Line() # 创建折线图 bar.add('最低气温', lows) bar.add('最高气温', highs) bar.x_labels = daytimes bar.x_labels_major = daytimes[::30] # bar.show_minor_x_labels = False # 不显示X轴最小刻度 bar.x_label_rotation = 45 bar.title = cityname+'未来七天气温走向图' bar.x_title = '日期' bar.y_title = '气温(摄氏度)' bar.legend_at_bottom = True bar.show_x_guides = False bar.show_y_guides = True bar.render_to_file('temperate.svg')

import requests from bs4 import BeautifulSoup from pyecharts import Bar ALL_DATA = [] def send_parse_urls(start_urls): headers = { "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/81.0.4044.122 Safari/537.36" } for start_url in start_urls: response = requests.get(start_url,headers=headers) # 编码问题的解决 response = response.text.encode("raw_unicode_escape").decode("utf-8") soup = BeautifulSoup(response,"html5lib") #lxml解析器：性能比较好，html5lib：适合页面结构比较混乱的 div_tatall = soup.find("div",class_="conMidtab") #find() 找符合要求的第一个元素 tables = div_tatall.find_all("table") #find_all() 找到符合要求的所有元素的列表 for table in tables: trs = table.find_all("tr") info_trs = trs[2:] for index,info_tr in enumerate(info_trs): # 枚举函数，可以获得索引 # print(index,info_tr) # print("="*30) city_td = info_tr.find_all("td")[0] temp_td = info_tr.find_all("td")[6] # if的判断的index的特殊情况应该在一般情况的后面，把之前的数据覆盖 if index==0: city_td = info_tr.find_all("td")[1] temp_td = info_tr.find_all("td")[7] city=list(city_td.stripped_strings)[0] temp=list(temp_td.stripped_strings)[0] ALL_DATA.append({"city":city,"temp":temp}) return ALL_DATA def get_start_urls(): start_urls = [ "http://www.weather.com.cn/textFC/hb.shtml", "http://www.weather.com.cn/textFC/db.shtml", "http://www.weather.com.cn/textFC/hd.shtml", "http://www.weather.com.cn/textFC/hz.shtml", "http://www.weather.com.cn/textFC/hn.shtml", "http://www.weather.com.cn/textFC/xb.shtml", "http://www.weather.com.cn/textFC/xn.shtml", "http://www.weather.com.cn/textFC/gat.shtml", ] return start_urls def main(): """ 主程序逻辑展示全国实时温度最低的十个城市气温排行榜的柱状图 """ # 1 获取所有起始url start_urls = get_start_urls() # 2 发送请求获取响应、解析页面 data = send_parse_urls(start_urls) # print(data) # 4 数据可视化 #1排序 data.sort(key=lambda data:int(data["temp"])) #2切片，选择出温度最低的十个城市和温度值 show_data = data[:10] #3分出城市和温度 city = list(map(lambda data:data["city"],show_data)) temp = list(map(lambda data:int(data["temp"]),show_data)) #4创建柱状图、生成目标图 chart = Bar("中国最低气温排行榜") #需要安装pyechart模块 chart.add("",city,temp) chart.render("tempture.html") if __name__ == '__main__': main()

使用pygal绘图，使用该模块前需先安装pip install pygal，然后导入import pygal

完整代码

Python爬取天气数据实例扩展：

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