






from collections import namedtuple

import requests
from lxml import html  # type: ignore

A_		:		int		     =			namedtuple('covid_data', 'cases deaths recovered')

def   snake_case (UpperCAmelCase__ = "https://www.worldometers.info/coronavirus/"  )	->    covid_data:
  UpperCamelCase_: Union[str, Any]   				=    '//div[@class = "maincounter-number"]/span/text()'
  return covid_data(*html.fromstring(requests.get(UpperCAmelCase__  ).content  ).xpath(UpperCAmelCase__  )  )


A_		:		str		     =			'Total COVID-19 cases in the world: {}\nTotal deaths due to COVID-19 in the world: {}\nTotal COVID-19 patients recovered in the world: {}'
print(fmt.format(*covid_stats()))







# A Bipartite Graph is a graph whose vertices can be divided into two independent sets,
# U and V such that every edge (u, v) either connects a vertex from U to V or a vertex
# from V to U. In other words, for every edge (u, v), either u belongs to U and v to V,
# or u belongs to V and v to U. We can also say that there is no edge that connects
# vertices of same set.

def   snake_case (UpperCAmelCase__  )	->    List[str]:
  UpperCamelCase_: int   				=    [False] * len(UpperCAmelCase__  )
  UpperCamelCase_: Any   				=    [-1] * len(UpperCAmelCase__  )

  def dfs(UpperCAmelCase__     ,   UpperCAmelCase__  ):
    UpperCamelCase_: Tuple   				=    True
    UpperCamelCase_: Optional[int]   				=    c
    for u in graph[v]:
      if not visited[u]:
        dfs(UpperCAmelCase__     ,   1 - c  )

  for i in range(len(UpperCAmelCase__  )  ):
    if not visited[i]:
      dfs(UpperCAmelCase__     ,   0  )

  for i in range(len(UpperCAmelCase__  )  ):
    for j in graph[i]:
      if color[i] == color[j]:
        return False

  return True


# Adjacency list of graph
A_		:		Dict		     =			{0: [1, 3], 1: [0, 2], 2: [1, 3], 3: [0, 2], 4: []}
print(check_bipartite_dfs(graph))