python爬取天气数据的实例详解

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('h1').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()