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Today, I will talk to you about how python climbs the daily weather chart code of the meteorological station, which may not be well understood by many people. in order to make you understand better, the editor has summarized the following contents for you. I hope you can get something according to this article.

Preface

After the update of the website of the Central Meteorological Observatory, the previous crawler method is not very useful. I studied and found that it is mainly because the page flipping mode of the weather chart on the site has changed from clicking to sliding, and the picture src on the page only shows the current page, so according to the popular method of the network, you can only crawl out one picture. After reading some of the boss's tutorials, I changed a code myself.

1. Install Selenium

Selenium is a Web automation (testing) tool that allows browsers to load pages automatically and get the data they need according to our instructions.

Pip install selenium2. Install chromedriver

Selenium itself does not have the function of a browser. Google's Chrome browser can easily support this function. It is necessary to install its driver Chromedriver.

Download address: http://chromedriver.storage.googleapis.com/index.html

Type 'chrome://version/',' in the address bar of the google browser to view the version information, and download something close to the version.

3. Code

As you can see from the picture, the id corresponding to the forward page turn instruction is' prev'

From selenium import webdriver # # browser driver interface from selenium.webdriver.common.action_chains import ActionChainsfrom selenium.webdriver.support.ui import Selectimport timeimport osimport urllib.requestlevel= for importing selenium ['ground', '925hPa', '850hPa', '700hPa', '500hPa' '100hpa'] chrome_driver = 'path / chromedriver.exe' # chromedriver file location driver = webdriver.Chrome (executable_path = chrome_driver) # load browser driver driver.get (' http://www.nmc.cn/publish/observations/china/dm/weatherchart-h000.htm') # Open page time.sleep (1) # simulate mouse selection height layer for z in level: button1=driver.find_element_by_link_ Text (z) # uses link text to accurately locate the element action = ActionChains (driver). Move_to_element (button1) # Mouse hover over an element action.click (button1). Perform () # Mouse Click time.sleep (1) for p in range (0Power6): # download weather charts for the last six times Str_p=str (p) # simulate mouse selection time button2=driver.find_element_by_id ('prev') # precisely locate the element action = ActionChains (driver). Move_to_element (button2) # mouse over an element action.click (button2). Perform () # mouse click Time.sleep (1) # simulated mouse selection picture elem_pic = driver.find_element_by_id ('imgpath') # precise positioning element action = ActionChains (driver). Move_to_element (elem_pic) # action.context_click (elem_pic). Perform () # right-click filename= str (elem_pic.get_attribute (') Src') .split ('/') [- 1] .split ('?) [0] # get the file name # get the image src src1=elem_pic.get_attribute ('src') if os.path.exists (' save image path /'+ zoned image') is not True: os.makedirs ('save image path /' + zonal image') urllib.request.urlretrieve (src1 'save path /' + z+'/'+filename) print (filename) time.sleep (1)

Then you can easily crawl all the pictures.

After reading the above, do you have any further understanding of how python climbs the daily weather chart code of the meteorological station? If you want to know more knowledge or related content, please follow the industry information channel, thank you for your support.

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