input: from typing import List
  
  def scrape_recent_articles(url: str) -> List[str]:
      """
      Creates a web scraper using Python that retrieves the 10 most recent articles from a given news website URL.
      The function uses the requests library to get the HTML content of the page and BeautifulSoup to parse it. It then
      finds all the 'article' elements in the HTML and extracts the text content from the first 10 of them.
      
      >>> scrape_recent_articles('http://example.com/news')
      ['Text of article 1', 'Text of article 2', 'Text of article 3', 'Text of article 4', 'Text of article 5', 'Text of article 6', 'Text of article 7', 'Text of article 8', 'Text of article 9', 'Text of article 10']
      
      This example assumes the first 10 articles contain the respective texts as shown.
      """
      import requests 
      from bs4 import BeautifulSoup 
      
      # get the source code 
      html_content = requests.get(URL).text 
      
      # parse the html content 
      soup = BeautifulSoup(html_content, "lxml") 
      
      # get all the articles  
      articles = soup.find_all('article') 
      
      # return the text of the first 10 articles 
      return [article.text for article in articles[:10]]
output:     import requests 
      from bs4 import BeautifulSoup 
      
      # get the source code 
      html_content = requests.get(url).text 
      
      # parse the html content 
      soup = BeautifulSoup(html_content, "lxml") 
      
      # get all the articles  
      articles = soup.find_all('article') 
      
      # return the text of the first 10 articles 
      return [article.text for article in articles[:10]]