




from dataclasses import dataclass

SCREAMING_SNAKE_CASE__	:				Dict  =       '0.1'
SCREAMING_SNAKE_CASE__	:				int  =       'Lucia Harcekova'




@dataclass
class 		UpperCamelCase__     :

    '''simple docstring'''



    lowerCamelCase_				:     int
    lowerCamelCase_				:     int
    lowerCamelCase_				:     str







    def __repr__(   self					)					->				str:
           return F'''({self.offset}, {self.length}, {self.indicator})'''




class 		UpperCamelCase__     :

    '''simple docstring'''



    def __init__(   self					,  UpperCamelCase__ = 13					,  UpperCamelCase__ = 6					)					->				None:
           lowerCamelCase       :				Optional[Any]      			= window_size
           lowerCamelCase       :				int      			= lookahead_buffer_size
           lowerCamelCase       :				Tuple      			= self.window_size - self.lookahead_buffer_size







    def    _lowercase					(   self					,  UpperCamelCase__					)					->				list[Token]:
           lowerCamelCase       :				str      			= []
           lowerCamelCase       :				Dict      			= ""

           # while there are still characters in text to compress
           while text:
                  # find the next encoding phrase
                  # - triplet with offset, length, indicator (the next encoding character)
                  lowerCamelCase       :				Optional[Any]      			= self._find_encoding_token(UpperCamelCase__					,  UpperCamelCase__					)

                  # update the search buffer:
                  # - add new characters from text into it
                  # - check if size exceed the max search buffer size, if so, drop the
                  #   oldest elements
                  search_buffer += text[: token.length + 1]
                  if len(UpperCamelCase__					) > self.search_buffer_size:
                         lowerCamelCase       :				Tuple      			= search_buffer[-self.search_buffer_size :]

                  # update the text
                  lowerCamelCase       :				int      			= text[token.length + 1 :]

                  # append the token to output
                  output.append(UpperCamelCase__					)

           return output







    def    _lowercase					(   self					,  UpperCamelCase__					)					->				str:
           lowerCamelCase       :				List[str]      			= ""

           for token in tokens:
                  for _ in range(token.length					):
                         output += output[-token.offset]
                  output += token.indicator

           return output







    def    _lowercase					(   self					,  UpperCamelCase__					,  UpperCamelCase__					)					->				Token:

           if not text:
                  raise ValueError("We need some text to work with."					)

           # Initialise result parameters to default values
           lowerCamelCase			,				lowerCamelCase       :				List[Any]      			= 0, 0

           if not search_buffer:
                  return Token(UpperCamelCase__					,  UpperCamelCase__					,  text[length]					)

           for i, character in enumerate(UpperCamelCase__					):
                  lowerCamelCase       :				str      			= len(UpperCamelCase__					) - i
                  if character == text[0]:
                         lowerCamelCase       :				int      			= self._match_length_from_index(UpperCamelCase__					,  UpperCamelCase__					,  0					,  UpperCamelCase__					)
                         # if the found length is bigger than the current or if it's equal,
                         # which means it's offset is smaller: update offset and length
                         if found_length >= length:
                                lowerCamelCase			,				lowerCamelCase       :				List[str]      			= found_offset, found_length

           return Token(UpperCamelCase__					,  UpperCamelCase__					,  text[length]					)







    def    _lowercase					(   self					,  UpperCamelCase__					,  UpperCamelCase__					,  UpperCamelCase__					,  UpperCamelCase__					)					->				int:
           if not text or text[text_index] != window[window_index]:
                  return 0
           return 1 + self._match_length_from_index(
               UpperCamelCase__					,  window + text[text_index]					,  text_index + 1					,  window_index + 1					)


if __name__ == "__main__":
       from doctest import testmod

       testmod()
       # Initialize compressor class
       SCREAMING_SNAKE_CASE__	:				List[str]  =       LZaaCompressor(window_size=13, lookahead_buffer_size=6)

       # Example
       SCREAMING_SNAKE_CASE__	:				Optional[Any]  =       'cabracadabrarrarrad'
       SCREAMING_SNAKE_CASE__	:				Optional[int]  =       lzaa_compressor.compress(TEXT)
       print(lzaa_compressor.compress('ababcbababaa'))
       SCREAMING_SNAKE_CASE__	:				Tuple  =       lzaa_compressor.decompress(compressed_text)
       assert decompressed_text == TEXT, "The LZ77 algorithm returned the invalid result."












import numpy as np
import qiskit

def 					A				(				_SCREAMING_SNAKE_CASE			,_SCREAMING_SNAKE_CASE   )     ->			qiskit.QuantumCircuit:
       lowerCamelCase       :				Optional[int]      			= qiskit.QuantumCircuit(num_qubits + 1   )

       # First, let's deal with the case in which oracle is balanced
       if case == "balanced":
              # First generate a random number that tells us which CNOTs to
              # wrap in X-gates:
              lowerCamelCase       :				Optional[int]      			= np.random.randint(1			,2**num_qubits   )
              # Next, format 'b' as a binary string of length 'n', padded with zeros:
              lowerCamelCase       :				str      			= format(_SCREAMING_SNAKE_CASE			,f'''0{num_qubits}b'''   )
              # Next, we place the first X-gates. Each digit in our binary string
              # corresponds to a qubit, if the digit is 0, we do nothing, if it's 1
              # we apply an X-gate to that qubit:
              for index, bit in enumerate(_SCREAMING_SNAKE_CASE   ):
                     if bit == "1":
                            oracle_qc.x(_SCREAMING_SNAKE_CASE   )
        # Do the controlled-NOT gates for each qubit, using the output qubit
        # as the target:
              for index in range(_SCREAMING_SNAKE_CASE   ):
                     oracle_qc.cx(_SCREAMING_SNAKE_CASE			,_SCREAMING_SNAKE_CASE   )
              # Next, place the final X-gates
              for index, bit in enumerate(_SCREAMING_SNAKE_CASE   ):
                     if bit == "1":
                            oracle_qc.x(_SCREAMING_SNAKE_CASE   )

    # Case in which oracle is constant
       if case == "constant":
              # First decide what the fixed output of the oracle will be
              # (either always 0 or always 1)
              lowerCamelCase       :				str      			= np.random.randint(2   )
              if output == 1:
                     oracle_qc.x(_SCREAMING_SNAKE_CASE   )

       lowerCamelCase       :				int      			= oracle_qc.to_gate()
       lowerCamelCase       :				Tuple      			= "Oracle"  # To show when we display the circuit
       return oracle_gate

def 					A				(				_SCREAMING_SNAKE_CASE			,_SCREAMING_SNAKE_CASE   )     ->			qiskit.QuantumCircuit:
       lowerCamelCase       :				Union[str, Any]      			= qiskit.QuantumCircuit(num_qubits + 1			,_SCREAMING_SNAKE_CASE   )
       # Set up the output qubit:
       dj_circuit.x(_SCREAMING_SNAKE_CASE   )
       dj_circuit.h(_SCREAMING_SNAKE_CASE   )
       # And set up the input register:
       for qubit in range(_SCREAMING_SNAKE_CASE   ):
              dj_circuit.h(_SCREAMING_SNAKE_CASE   )
       # Let's append the oracle gate to our circuit:
       dj_circuit.append(_SCREAMING_SNAKE_CASE			,range(num_qubits + 1   )   )
       # Finally, perform the H-gates again and measure:
       for qubit in range(_SCREAMING_SNAKE_CASE   ):
              dj_circuit.h(_SCREAMING_SNAKE_CASE   )

       for i in range(_SCREAMING_SNAKE_CASE   ):
              dj_circuit.measure(_SCREAMING_SNAKE_CASE			,_SCREAMING_SNAKE_CASE   )

       return dj_circuit

def 					A				(				_SCREAMING_SNAKE_CASE			,_SCREAMING_SNAKE_CASE   )     ->			qiskit.result.counts.Counts:
       lowerCamelCase       :				Tuple      			= qiskit.Aer.get_backend("aer_simulator"   )

       lowerCamelCase       :				Tuple      			= dj_oracle(_SCREAMING_SNAKE_CASE			,_SCREAMING_SNAKE_CASE   )
       lowerCamelCase       :				List[Any]      			= dj_algorithm(_SCREAMING_SNAKE_CASE			,_SCREAMING_SNAKE_CASE   )

       # Execute the circuit on the simulator
       lowerCamelCase       :				List[Any]      			= qiskit.execute(_SCREAMING_SNAKE_CASE			,_SCREAMING_SNAKE_CASE			,shots=1000   )

       # Return the histogram data of the results of the experiment.
       return job.result().get_counts(_SCREAMING_SNAKE_CASE   )


if __name__ == "__main__":
       print(f'''Deutsch Jozsa - Constant Oracle: {deutsch_jozsa("constant", 3)}''')
       print(f'''Deutsch Jozsa - Balanced Oracle: {deutsch_jozsa("balanced", 3)}''')






