有时候我们想查询一个地方的历史气温用来预测今年的气温,自己去互联网查询又太麻烦,闲来无事写了个查询代码
第一步,运行一次下面的代码,用于获取地区对应的代码,会自动保存为 “city_data.csv” 文件,用于第二步的文件调用
- import os
- import csv
- import requests
- from lxml import etree
-
- # 目标主网址
- main_url = "https://lishi.tianqi.com/"
-
- # 设置请求头
- headers = {
- 'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/127.0.0.0 Safari/537.36 Edg/127.0.0.0',
- }
-
- if not os.path.exists('city_data.csv'):
- # 获取不同城市对应的网址
- try:
- response = requests.get(url=main_url, headers=headers)
- html = etree.HTML(response.text)
-
- city_name_list = html.xpath("//td/ul/li/a/text()")
- city_url_list = html.xpath("//td/ul/li/a/@href")
-
- with open('city_data.csv', mode='w', encoding='utf-8-sig', newline='') as f:
- writer = csv.writer(f)
- writer.writerow(['城市', '代码'])
- for n, u in zip(city_name_list, city_url_list):
- writer.writerow([n, u.split('/')[0]])
- print(n, u.split('/')[0])
- except Exception as e:
- print(e)
-
- else:
- print('城市数据已存在')
第二步:输入地区名和日期,开始查询
代码运行结束之后,会在同目录下生成一个html文件,在浏览器打开即可看见折线图
- import requests
- import csv
- import re
- import os
- from lxml import etree
- import pyecharts.options as opts
- from pyecharts.charts import Line
-
- # 设置请求头
- headers= {
- 'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/127.0.0.0 Safari/537.36 Edg/127.0.0.0',
- }
- def input_data():
- """输入地点,时间"""
- city = input("请输入查询城市:")
- month = input("请输入查询月份(格式:202307):")
- return city, month
-
- def get_date_url(city, month):
- """获取当月日期地址"""
- if os.path.exists('city_data.csv'):
- with open('city_data.csv', mode='r', encoding='utf-8') as f:
- reader = csv.reader(f)
- for row in reader:
- if city == row[0]:
- city_id = row[1]
- month_url = f"https://lishi.tianqi.com/{city_id}/{month}.html"
- return month_url
-
- def extract_numbers(string):
- """提取字符串中的数字"""
- numbers = re.findall(r'\d+', string)[0]
- return float(numbers)
-
- def spider_weather(date_url, city, month):
- try:
- response = requests.get(url=date_url, headers=headers)
- html = etree.HTML(response.text)
- tree = html.xpath('/html/body/div[7]/div[1]/div[4]/ul/li')
- date_name_list = []
- high_temperatures = []
- low_temperatures = []
- weathers = []
- for i in tree:
- date = i.xpath('./div[1]/text()')[0].split(' ')[0]
- high_temperature = extract_numbers(i.xpath('./div[2]/text()')[0])
- low_temperature = extract_numbers(i.xpath('./div[3]/text()')[0])
- weather = i.xpath('./div[4]/text()')[0]
- wind = i.xpath('./div[5]/text()')[0]
- print(date, high_temperature, low_temperature, weather, wind)
- date_name_list.append(date)
- high_temperatures.append(high_temperature)
- low_temperatures.append(low_temperature)
- weathers.append(weather)
-
- line = (
- Line(init_opts=opts.InitOpts(width="1200px", height="600px",page_title='月份气温折线图'))
- .add_xaxis(xaxis_data=date_name_list)
- .add_yaxis(
- series_name="最高气温",
- y_axis=high_temperatures,
- markpoint_opts=opts.MarkPointOpts(
- data=[
- opts.MarkPointItem(type_="max", name="最大值"),
- ]
- ),
- markline_opts=opts.MarkLineOpts(
- data=[opts.MarkLineItem(type_="average", name="平均值")]
- ),
- )
- .add_yaxis(
- series_name="最低气温",
- y_axis=low_temperatures,
- markpoint_opts=opts.MarkPointOpts(
- data=[opts.MarkPointItem(type_="min", name="最小值")]
- ),
- markline_opts=opts.MarkLineOpts(
- data=[
- opts.MarkLineItem(type_="average", name="平均值"),
- ]
- ),
- )
- .set_global_opts(
- # 设置主副标题
- title_opts=opts.TitleOpts(title=f"{city}地区{month[0:4]}年{month[4:]}月气温走势折线图", subtitle=f"{city}"),
- tooltip_opts=opts.TooltipOpts(trigger="axis"),
- toolbox_opts=opts.ToolboxOpts(is_show=True, feature=opts.ToolBoxFeatureOpts(save_as_image=opts.ToolBoxFeatureSaveAsImageOpts(pixel_ratio=3, type_='jpg', background_color='#fff'))),
- xaxis_opts=opts.AxisOpts(type_="category", boundary_gap=False, name='日期', min_=0, max_=len(date_name_list), axisline_opts=opts.AxisLineOpts(symbol=['none', 'arrow'])),
- datazoom_opts=opts.AxisLineOpts(),
-
- )
-
- )
- line.render(f"{city}地区{month[0:4]}年{month[4:]}月气温走势折线图.html")
- except Exception as e:
- print(e)
-
- def main():
- city, month = input_data()
- month_url = get_date_url(city, month)
- spider_weather(month_url, city, month)
-
- if __name__ == '__main__':
- main()
效果图如下