
import math
import os
import sys





def   _lowerCAmelCase				(   UpperCamelCase__:     str						) ->   Optional[int]:





	"""simple docstring"""







	A								=				""
	try:
		with open(__lowerCAmelCase							,					"""rb"""						) as binary_file:
			A								=				binary_file.read()
		for dat in data:
			A								=				f'{dat:08b}'
			result += curr_byte
		return result
	except OSError:
		print("""File not accessible"""						)
		sys.exit()





def   _lowerCAmelCase				(   UpperCamelCase__:     int							,					UpperCamelCase__:     Any							,					UpperCamelCase__:     Any							,					UpperCamelCase__:     Any						) ->   List[str]:





	"""simple docstring"""







	lexicon.pop(__lowerCAmelCase						)
	A								=				last_match_id

	if math.loga(__lowerCAmelCase						).is_integer():
		for curr_key in lexicon:
			A								=				"0" + lexicon[curr_key]

	A								=				bin(__lowerCAmelCase						)[2:]





def   _lowerCAmelCase				(   UpperCamelCase__:     Optional[Any]						) ->   Optional[Any]:





	"""simple docstring"""







	A								=				{"0": "0", "1": "1"}
	A								=				"", ""
	A								=				len(__lowerCAmelCase						)

	for i in range(len(__lowerCAmelCase						)						):
		curr_string += data_bits[i]
		if curr_string not in lexicon:
			continue

		A								=				lexicon[curr_string]
		result += last_match_id
		add_key_to_lexicon(__lowerCAmelCase							,					__lowerCAmelCase							,					__lowerCAmelCase							,					__lowerCAmelCase						)
		index += 1
		A								=				""

	while curr_string != "" and curr_string not in lexicon:
		curr_string += "0"

	if curr_string != "":
		A								=				lexicon[curr_string]
		result += last_match_id

	return result





def   _lowerCAmelCase				(   UpperCamelCase__:     str							,					UpperCamelCase__:     str						) ->   Optional[int]:





	"""simple docstring"""







	A								=				os.path.getsize(__lowerCAmelCase						)
	A								=				bin(__lowerCAmelCase						)[2:]
	A								=				len(__lowerCAmelCase						)

	return "0" * (length_length - 1) + file_length_binary + compressed





def   _lowerCAmelCase				(   UpperCamelCase__:     List[str]							,					UpperCamelCase__:     Optional[int]						) ->   Optional[int]:





	"""simple docstring"""







	A								=				8
	try:
		with open(__lowerCAmelCase							,					"""wb"""						) as opened_file:
			A								=				[
			    to_write[i : i + byte_length]
			    for i in range(0							,					len(__lowerCAmelCase						)							,					__lowerCAmelCase						)
			]

			if len(result_byte_array[-1]						) % byte_length == 0:
				result_byte_array.append("""10000000"""						)
			else:
				result_byte_array[-1] += "1" + "0" * (
				    byte_length - len(result_byte_array[-1]						) - 1
				)

			for elem in result_byte_array:
				opened_file.write(int(__lowerCAmelCase							,					2						).to_bytes(1							,					byteorder="""big"""						)						)
	except OSError:
		print("""File not accessible"""						)
		sys.exit()





def   _lowerCAmelCase				(   UpperCamelCase__:     List[Any]							,					UpperCamelCase__:     Tuple						) ->   int:





	"""simple docstring"""







	A								=				read_file_binary(__lowerCAmelCase						)
	A								=				compress_data(__lowerCAmelCase						)
	A								=				add_file_length(__lowerCAmelCase							,					__lowerCAmelCase						)
	write_file_binary(__lowerCAmelCase							,					__lowerCAmelCase						)


if __name__ == "__main__":
				compress(sys.argv[1], sys.argv[2])







import timeit

import numpy as np

import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD





def   _lowerCAmelCase				(   UpperCamelCase__:     Any						) ->   Tuple:





	"""simple docstring"""







	def wrapper(*UpperCamelCase__:     Union[str, Any]							,					**UpperCamelCase__:     List[str]						):
		A								=				timeit.default_timer()
		A								=				func(*UpperCamelCase__							,					**UpperCamelCase__						)
		A								=				timeit.default_timer() - starttime
		return delta

	A								=				func.__name__

	return wrapper





def   _lowerCAmelCase				(   UpperCamelCase__:     dict							,					UpperCamelCase__:     List[str]=1_00							,					UpperCamelCase__:     int=None						) ->   Any:





	"""simple docstring"""







	A								=				[]
	A								=				seq_shapes or {}
	for i in range(UpperCamelCase__						):
		A								=				{}
		for col_id, (k, v) in enumerate(features.items()						):
			if isinstance(UpperCamelCase__							,					_ArrayXD						):
				A								=				np.random.rand(*v.shape						).astype(v.dtype						)
			elif isinstance(UpperCamelCase__							,					datasets.Value						):
				if v.dtype == "string":
					A								=				"""The small grey turtle was surprisingly fast when challenged."""
				else:
					A								=				np.random.randint(10							,					size=1						).astype(v.dtype						).item()
			elif isinstance(UpperCamelCase__							,					datasets.Sequence						):
				while isinstance(UpperCamelCase__							,					datasets.Sequence						):
					A								=				v.feature
				A								=				seq_shapes[k]
				A								=				np.random.rand(*UpperCamelCase__						).astype(v.dtype						)
			A								=				data

		dummy_data.append((i, example)						)

	return dummy_data





def   _lowerCAmelCase				(   UpperCamelCase__:     int							,					UpperCamelCase__:     Union[str, Any]							,					UpperCamelCase__:     List[str]=1_00							,					UpperCamelCase__:     str=None						) ->   Optional[int]:





	"""simple docstring"""







	A								=				generate_examples(UpperCamelCase__							,					num_examples=UpperCamelCase__							,					seq_shapes=UpperCamelCase__						)

	with ArrowWriter(features=UpperCamelCase__							,					path=UpperCamelCase__						) as writer:
		for key, record in dummy_data:
			A								=				features.encode_example(UpperCamelCase__						)
			writer.write(UpperCamelCase__						)

		A					,			A								=				writer.finalize()

	if not num_final_examples == num_examples:
		raise ValueError(
		    f'Error writing the dataset, wrote {num_final_examples} examples but should have written {num_examples}.'						)

	A								=				datasets.Dataset.from_file(filename=UpperCamelCase__							,					info=datasets.DatasetInfo(features=UpperCamelCase__						)						)

	return dataset



