




import os
from typing import Optional

import fsspec
from fsspec.archive import AbstractArchiveFileSystem
from fsspec.utils import DEFAULT_BLOCK_SIZE


class 	A_ (	a__   ):




      '''simple docstring'''


      __snake_case 	=       """"""
      __snake_case 	=       (
          None  # protocol passed in prefix to the url. ex: "gzip", for gzip://file.txt::http://foo.bar/file.txt.gz
      )
      __snake_case 	=       None  # compression type in fsspec. ex: "gzip"
      __snake_case 	=       None  # extension of the filename to strip. ex: "".gz" to get file.txt from file.txt.gz




      def __init__(    self:	Tuple						,				a:	str = ""						,				a:	Optional[str] = None						,				a:	Optional[dict] = None						,				**a:	Dict    ):
       super().__init__(self						,				**a    )
       # always open as "rb" since fsspec can then use the TextIOWrapper to make it work for "r" mode
       __lowerCamelCase		:							int		 =						fsspec.open(
           a						,				mode='rb'						,				protocol=a						,				compression=self.compression						,				client_kwargs={
               'requote_redirect_url': False,  # see https://github.com/huggingface/datasets/pull/5459
               'trust_env': True,  # Enable reading proxy env variables.
               **(target_options or {}).pop('client_kwargs'						,				{}    ),  # To avoid issues if it was already passed.
           }						,				**(target_options or {})						,				)
       __lowerCamelCase		:							Optional[int]		 =						os.path.basename(self.file.path.split('::'    )[0]    )
       __lowerCamelCase		:							Union[str, Any]		 =						(
           self.compressed_name[: self.compressed_name.rindex('.'    )]
           if "." in self.compressed_name
           else self.compressed_name
       )
       __lowerCamelCase		:							Union[str, Any]		 =						None




      @classmethod
      def 					_snake_case     (    cls:	Dict						,				a:	List[str]    ):
       # compressed file paths are always relative to the archive root
       return super()._strip_protocol(a    ).lstrip('/'    )




      def 					_snake_case     (    self:	Union[str, Any]    ):
       if self.dir_cache is None:
        __lowerCamelCase		:							int		 =						{**self.file.fs.info(self.file.path    ), "name": self.uncompressed_name}
        __lowerCamelCase		:							str		 =						{f["name"]: f}




      def 					_snake_case     (    self:	List[str]						,				a:	str    ):
       return self.file.open().read()




      def 					_snake_case     (    self:	Union[str, Any]						,				a:	str						,				a:	str = "rb"						,				a:	Tuple=None						,				a:	int=True						,				a:	List[str]=None						,				**a:	str						,				):
       __lowerCamelCase		:							Dict		 =						self._strip_protocol(a    )
       if mode != "rb":
        raise ValueError(F'Tried to read with mode {mode} on file {self.file.path} opened with mode \'rb\''    )
       return self.file.open()



class 	A_ (	a__   ):




      '''simple docstring'''


      __snake_case 	=       """bz2"""
      __snake_case 	=       """bz2"""
      __snake_case 	=       """.bz2"""



class 	A_ (	a__   ):




      '''simple docstring'''


      __snake_case 	=       """gzip"""
      __snake_case 	=       """gzip"""
      __snake_case 	=       """.gz"""



class 	A_ (	a__   ):




      '''simple docstring'''


      __snake_case 	=       """lz4"""
      __snake_case 	=       """lz4"""
      __snake_case 	=       """.lz4"""



class 	A_ (	a__   ):




      '''simple docstring'''


      __snake_case 	=       """xz"""
      __snake_case 	=       """xz"""
      __snake_case 	=       """.xz"""



class 	A_ (	a__   ):




      '''simple docstring'''


      __snake_case 	=       """zstd"""
      __snake_case 	=       """zstd"""
      __snake_case 	=       """.zst"""




      def __init__(    self:	List[Any]						,				a:	str						,				a:	str = "rb"						,				a:	Optional[str] = None						,				a:	Optional[dict] = None						,				a:	int = DEFAULT_BLOCK_SIZE						,				**a:	List[str]						,				):
       super().__init__(
           fo=a						,				mode=a						,				target_protocol=a						,				target_options=a						,				block_size=a						,				**a						,				)
       # We need to wrap the zstd decompressor to avoid this error in fsspec==2021.7.0 and zstandard==0.15.2:
       #
       # File "/Users/user/.virtualenvs/hf-datasets/lib/python3.7/site-packages/fsspec/core.py", line 145, in open
       #     out.close = close
       # AttributeError: 'zstd.ZstdDecompressionReader' object attribute 'close' is read-only
       #
       # see https://github.com/intake/filesystem_spec/issues/725
       __lowerCamelCase		:							Union[str, Any]		 =						self.file.__enter__


       class 	A_ :




             '''simple docstring'''


             def __init__(    self:	Tuple						,				a:	str    ):
              __lowerCamelCase		:							List[str]		 =						file_




             def __enter__(    self:	Optional[int]    ):
              self._file.__enter__()
              return self




             def __exit__(    self:	Tuple						,				*a:	Optional[int]						,				**a:	List[Any]    ):
              self._file.__exit__(*a						,				**a    )




             def __iter__(    self:	Optional[Any]    ):
              return iter(self._file    )




             def 					_snake_case     (    self:	str    ):
              return next(self._file    )




             def __getattr__(    self:	Union[str, Any]						,				a:	Tuple    ):
              return getattr(self._file						,				a    )

       def fixed_enter(*a:	Union[str, Any]						,				**a:	str    ):
        return WrappedFile(_enter(*a						,				**a    )    )

       __lowerCamelCase		:							List[Any]		 =						fixed_enter





import json
import os
import tempfile

import datasets
from utils import generate_example_dataset, get_duration


lowercase_	   =     5_0_0_0_0
lowercase_	   =     5_0_0_0

lowercase_   ,lowercase_	   =     os.path.split(__file__)
lowercase_	   =     os.path.join(RESULTS_BASEPATH, 'results', RESULTS_FILENAME.replace('.py', '.json'))
@get_duration
def 				UpperCamelCase__					(  SCREAMING_SNAKE_CASE__      ,	SCREAMING_SNAKE_CASE__						):
 for i in range(SCREAMING_SNAKE_CASE__						):
  __lowerCamelCase		:							Tuple		 =						dataset[i]
@get_duration
def 				UpperCamelCase__					(  SCREAMING_SNAKE_CASE__      ,	SCREAMING_SNAKE_CASE__      ,	SCREAMING_SNAKE_CASE__						):
 for i in range(0      ,	len(SCREAMING_SNAKE_CASE__						)      ,	SCREAMING_SNAKE_CASE__						):
  __lowerCamelCase		:							Optional[Any]		 =						dataset[i : i + batch_size]
@get_duration
def 				UpperCamelCase__					(  SCREAMING_SNAKE_CASE__      ,	SCREAMING_SNAKE_CASE__      ,	SCREAMING_SNAKE_CASE__						):
 with dataset.formatted_as(type=SCREAMING_SNAKE_CASE__						):
  for i in range(SCREAMING_SNAKE_CASE__						):
   __lowerCamelCase		:							str		 =						dataset[i]
@get_duration
def 				UpperCamelCase__					(  SCREAMING_SNAKE_CASE__      ,	SCREAMING_SNAKE_CASE__      ,	SCREAMING_SNAKE_CASE__      ,	SCREAMING_SNAKE_CASE__						):
 with dataset.formatted_as(type=SCREAMING_SNAKE_CASE__						):
  for i in range(0      ,	SCREAMING_SNAKE_CASE__      ,	SCREAMING_SNAKE_CASE__						):
   __lowerCamelCase		:							int		 =						dataset[i : i + batch_size]
def 				UpperCamelCase__					(  ):
 __lowerCamelCase		:							Union[str, Any]		 =						{'num examples': SPEED_TEST_N_EXAMPLES}
 __lowerCamelCase		:							Optional[Any]		 =						[
     (read, {'length': SMALL_TEST}),
     (read, {'length': SPEED_TEST_N_EXAMPLES}),
     (read_batch, {'length': SPEED_TEST_N_EXAMPLES, 'batch_size': 10}),
     (read_batch, {'length': SPEED_TEST_N_EXAMPLES, 'batch_size': 100}),
     (read_batch, {'length': SPEED_TEST_N_EXAMPLES, 'batch_size': 1_000}),
     (read_formatted, {'type': 'numpy', 'length': SMALL_TEST}),
     (read_formatted, {'type': 'pandas', 'length': SMALL_TEST}),
     (read_formatted, {'type': 'torch', 'length': SMALL_TEST}),
     (read_formatted, {'type': 'tensorflow', 'length': SMALL_TEST}),
     (read_formatted_batch, {'type': 'numpy', 'length': SMALL_TEST, 'batch_size': 10}),
     (read_formatted_batch, {'type': 'numpy', 'length': SMALL_TEST, 'batch_size': 1_000}),
 ]

 __lowerCamelCase		:							Any		 =						[
     (read, {'length': SMALL_TEST}),
     (read, {'length': SPEED_TEST_N_EXAMPLES}),
     (read_batch, {'length': SPEED_TEST_N_EXAMPLES, 'batch_size': 10}),
     (read_batch, {'length': SPEED_TEST_N_EXAMPLES, 'batch_size': 100}),
     (read_batch, {'length': SPEED_TEST_N_EXAMPLES, 'batch_size': 1_000}),
     (read_formatted, {'type': 'numpy', 'length': SMALL_TEST}),
     (read_formatted_batch, {'type': 'numpy', 'length': SMALL_TEST, 'batch_size': 10}),
     (read_formatted_batch, {'type': 'numpy', 'length': SMALL_TEST, 'batch_size': 1_000}),
 ]
 with tempfile.TemporaryDirectory() as tmp_dir:
  print('generating dataset'						)
  __lowerCamelCase		:							Optional[int]		 =						datasets.Features(
      {'list': datasets.Sequence(datasets.Value('float32'						)						), 'numbers': datasets.Value('float32'						)}						)
  __lowerCamelCase		:							str		 =						generate_example_dataset(
      os.path.join(SCREAMING_SNAKE_CASE__      ,	'dataset.arrow'						)      ,	SCREAMING_SNAKE_CASE__      ,	num_examples=SCREAMING_SNAKE_CASE__      ,	seq_shapes={'list': (100,)}      ,	)
  print('first set of iterations'						)
  for func, kwargs in functions:
   print(func.__name__      ,	str(SCREAMING_SNAKE_CASE__						)						)
   __lowerCamelCase		:							Optional[int]		 =						func(SCREAMING_SNAKE_CASE__      ,	**SCREAMING_SNAKE_CASE__						)

  print('shuffling dataset'						)
  __lowerCamelCase		:							str		 =						dataset.shuffle()
  print('Second set of iterations (after shuffling'						)
  for func, kwargs in functions_shuffled:
   print('shuffled '      ,	func.__name__      ,	str(SCREAMING_SNAKE_CASE__						)						)
   __lowerCamelCase		:							int		 =						func(
       SCREAMING_SNAKE_CASE__      ,	**SCREAMING_SNAKE_CASE__						)

 with open(SCREAMING_SNAKE_CASE__      ,	'wb'						) as f:
  f.write(json.dumps(SCREAMING_SNAKE_CASE__						).encode('utf-8'						)						)


if __name__ == "__main__":  # useful to run the profiler
       benchmark_iterating()

