


'''simple docstring'''




from __future__ import annotations

import json

import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent

__snake_case       		={"""UserAgent""": UserAgent().random}





def       a_   (					lowerCamelCase      :	str							):
   lowerCAmelCase	=     script.contents[0]
   lowerCAmelCase	=     json.loads(data[data.find('{"config"'							) : -1]							)
   return info["entry_data"]["ProfilePage"][0]["graphql"]["user"]

class 						UpperCAmelCase_ :





     def __init__(					self			: Tuple       , UpperCAmelCase__			: int       )							->    Tuple:
        lowerCAmelCase	=     F'''https://www.instagram.com/{username}/'''
        lowerCAmelCase	=     self.get_json()





     def 				__UpperCAmelCase (					self			: Union[str, Any]       )							->    Any:
        lowerCAmelCase	=     requests.get(self.url       , headers=A_       ).text
        lowerCAmelCase	=     BeautifulSoup(A_       , 'html.parser'       ).find_all('script'       )
        try:
           return extract_user_profile(scripts[4]       )
        except (json.decoder.JSONDecodeError, KeyError):
           return extract_user_profile(scripts[3]       )





     def __repr__(					self			: List[Any]       )							->    Optional[Any]:
        return F'''{self.__class__.__name__}(\'{self.username}\')'''





     def __str__(					self			: str       )							->    Union[str, Any]:
        return F'''{self.fullname} ({self.username}) is {self.biography}'''





     @property
     def 				__UpperCAmelCase (					self			: Optional[int]       )							->    Optional[Any]:
        return self.user_data["username"]





     @property
     def 				__UpperCAmelCase (					self			: Optional[Any]       )							->    Optional[int]:
        return self.user_data["full_name"]





     @property
     def 				__UpperCAmelCase (					self			: List[str]       )							->    Optional[int]:
        return self.user_data["biography"]





     @property
     def 				__UpperCAmelCase (					self			: str       )							->    List[Any]:
        return self.user_data["business_email"]





     @property
     def 				__UpperCAmelCase (					self			: Dict       )							->    Dict:
        return self.user_data["external_url"]





     @property
     def 				__UpperCAmelCase (					self			: str       )							->    Any:
        return self.user_data["edge_followed_by"]["count"]





     @property
     def 				__UpperCAmelCase (					self			: Tuple       )							->    List[str]:
        return self.user_data["edge_follow"]["count"]





     @property
     def 				__UpperCAmelCase (					self			: Optional[int]       )							->    List[Any]:
        return self.user_data["edge_owner_to_timeline_media"]["count"]





     @property
     def 				__UpperCAmelCase (					self			: Any       )							->    List[str]:
        return self.user_data["profile_pic_url_hd"]





     @property
     def 				__UpperCAmelCase (					self			: Dict       )							->    Optional[Any]:
        return self.user_data["is_verified"]





     @property
     def 				__UpperCAmelCase (					self			: int       )							->    int:
        return self.user_data["is_private"]





def       a_   (					lowerCamelCase      :	List[Any] = "github"							):
   import os

   if os.environ.get('CI'							):
      return  # test failing on GitHub Actions
   lowerCAmelCase	=     InstagramUser(_lowercase							)
   assert instagram_user.user_data
   assert isinstance(instagram_user.user_data      ,					_lowercase							)
   assert instagram_user.username == username
   if username != "github":
      return
   assert instagram_user.fullname == "GitHub"
   assert instagram_user.biography == "Built for developers."
   assert instagram_user.number_of_posts > 150
   assert instagram_user.number_of_followers > 120000
   assert instagram_user.number_of_followings > 15
   assert instagram_user.email == "support@github.com"
   assert instagram_user.website == "https://github.com/readme"
   assert instagram_user.profile_picture_url.startswith('https://instagram.'							)
   assert instagram_user.is_verified is True
   assert instagram_user.is_private is False


if __name__ == "__main__":
       import doctest

       doctest.testmod()
       __snake_case       		=InstagramUser("""github""")
       print(instagram_user)
       print(F'''{instagram_user.number_of_posts = }''')
       print(F'''{instagram_user.number_of_followers = }''')
       print(F'''{instagram_user.number_of_followings = }''')
       print(F'''{instagram_user.email = }''')
       print(F'''{instagram_user.website = }''')
       print(F'''{instagram_user.profile_picture_url = }''')
       print(F'''{instagram_user.is_verified = }''')
       print(F'''{instagram_user.is_private = }''')









#
# This a `torch.distributed` diagnostics script that checks that all GPUs in the cluster (one or
# many nodes) can talk to each other via nccl and allocate gpu memory.
#
# To run first adjust the number of processes and nodes:
#
# python -m torch.distributed.run --nproc_per_node 2 --nnodes 1 torch-distributed-gpu-test.py
#
# You may need to add --master_addr $MASTER_ADDR --master_port $MASTER_PORT if using a custom addr:port
#
# You can also use the rdzv API: --rdzv_endpoint $MASTER_ADDR:$MASTER_PORT --rdzv_backend c10d
#
# use torch.distributed.launch instead of torch.distributed.run for torch < 1.9
#
# If you get a hanging in `barrier` calls you have some network issues, you may try to debug this with:
#
# NCCL_DEBUG=INFO python -m torch.distributed.run --nproc_per_node 2 --nnodes 1 torch-distributed-gpu-test.py
#
# which should tell you what's going on behind the scenes.
#
#
# This script can be run via `srun` in the SLURM environment as well. Here is a SLURM script that
# runs on 2 nodes of 4 gpus per node:
#
# #SBATCH --job-name=test-nodes        # name
# #SBATCH --nodes=2                    # nodes
# #SBATCH --ntasks-per-node=1          # crucial - only 1 task per dist per node!
# #SBATCH --cpus-per-task=10           # number of cores per tasks
# #SBATCH --gres=gpu:4                 # number of gpus
# #SBATCH --time 0:05:00               # maximum execution time (HH:MM:SS)
# #SBATCH --output=%x-%j.out           # output file name
#
# GPUS_PER_NODE=4
# MASTER_ADDR=$(scontrol show hostnames $SLURM_JOB_NODELIST | head -n 1)
# MASTER_PORT=6000
#
# srun --jobid $SLURM_JOBID bash -c 'python -m torch.distributed.run \
# --nproc_per_node $GPUS_PER_NODE --nnodes $SLURM_NNODES --node_rank $SLURM_PROCID \
# --master_addr $MASTER_ADDR --master_port $MASTER_PORT \
# torch-distributed-gpu-test.py'
#

import fcntl
import os
import socket

import torch
import torch.distributed as dist






def 		_A		(		*_lowercase )					-> Tuple:


     """simple docstring"""


     with open(_lowercase					,  'r' ) as fh:
          fcntl.flock(_lowercase					,  fcntl.LOCK_EX )
          try:
               print(*_lowercase )
          finally:
               fcntl.flock(_lowercase					,  fcntl.LOCK_UN )


__snake_case   							=						int(os.environ['''LOCAL_RANK'''])
torch.cuda.set_device(local_rank)
__snake_case   							=						torch.device('''cuda''', local_rank)
__snake_case   							=						socket.gethostname()

__snake_case   							=						f"""[{hostname}-{local_rank}]"""

try:
    # test distributed
    dist.init_process_group('''nccl''')
    dist.all_reduce(torch.ones(1).to(device), op=dist.ReduceOp.SUM)
    dist.barrier()

    # test cuda is available and can allocate memory
    torch.cuda.is_available()
    torch.ones(1).cuda(local_rank)

    # global rank
    __snake_case   							=						dist.get_rank()
    __snake_case   							=						dist.get_world_size()

    printflock(f"""{gpu} is OK (global rank: {rank}/{world_size})""")

    dist.barrier()
    if rank == 0:
        printflock(f"""pt={torch.__version__}, cuda={torch.version.cuda}, nccl={torch.cuda.nccl.version()}""")

except Exception:
    printflock(f"""{gpu} is broken""")
    raise


