input: Write a function to extract the latest stock prices from specific websites given a list of stock identifiers using web scraping techniques in Python. The function should return a dictionary where the keys are the stock identifiers and the values are their respective current prices.
  
  def get_stock_prices(stock_identifiers):
      import requests
      from bs4 import BeautifulSoup
      prices = {}
      for stock in stock_identifiers:
          url = f"https://finance.yahoo.com/quote/{stock}"
          response = requests.get(url)
          soup = BeautifulSoup(response.text, 'html.parser')
          price = soup.find('div', {'class': 'My(6px) Pos(r) smartphone_Mt(6px)'}).find('span').text
          prices[stock] = price
      return prices
  
  assert get_stock_prices(["AAPL", "MSFT"]) == {"AAPL": "150.00", "MSFT": "300.00"}
  assert get_stock_prices([]) == {}
  assert get_stock_prices(["FB"]) == {"FB": "350.00"}
output: def get_stock_prices(stock_identifiers):
      import requests
      from bs4 import BeautifulSoup
      prices = {}
      for stock in stock_identifiers:
          url = f"https://finance.yahoo.com/quote/{stock}"
          response = requests.get(url)
          soup = BeautifulSoup(response.text, 'html.parser')
          price = soup.find('div', {'class': 'My(6px) Pos(r) smartphone_Mt(6px)'}).find('span').text
          prices[stock] = price
      return prices