code: import numpy as np
  import qiskit
  
  
  
  
  
  
  def   __lowerCamelCase	(       lowerCamelCase__		:	str     ,       lowerCamelCase__		:	int			):
  
  
  
  
  
  			'''simple docstring'''
  
  
  
  
  			lowerCamelCase								=     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								=     np.random.randint(1     ,       2**num_qubits			)
  						# Next, format 'b' as a binary string of length 'n', padded with zeros:
  						lowerCamelCase								=     format(lowerCamelCase__     ,       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(lowerCamelCase__			):
  									if bit == "1":
  												oracle_qc.x(lowerCamelCase__			)
          # Do the controlled-NOT gates for each qubit, using the output qubit
          # as the target:
  						for index in range(lowerCamelCase__			):
  									oracle_qc.cx(lowerCamelCase__     ,       lowerCamelCase__			)
  						# Next, place the final X-gates
  						for index, bit in enumerate(lowerCamelCase__			):
  									if bit == "1":
  												oracle_qc.x(lowerCamelCase__			)
  
      # 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								=     np.random.randint(2			)
  						if output == 1:
  									oracle_qc.x(lowerCamelCase__			)
  
  			lowerCamelCase								=     oracle_qc.to_gate()
  			lowerCamelCase								=     """Oracle"""  # To show when we display the circuit
  			return oracle_gate
  
  
  
  
  
  
  def   __lowerCamelCase	(       lowerCamelCase__		:	qiskit.QuantumCircuit     ,       lowerCamelCase__		:	int			):
  
  
  
  
  
  			'''simple docstring'''
  
  
  
  
  			lowerCamelCase								=     qiskit.QuantumCircuit(num_qubits + 1     ,       lowerCamelCase__			)
  			# Set up the output qubit:
  			dj_circuit.x(lowerCamelCase__			)
  			dj_circuit.h(lowerCamelCase__			)
  			# And set up the input register:
  			for qubit in range(lowerCamelCase__			):
  						dj_circuit.h(lowerCamelCase__			)
  			# Let's append the oracle gate to our circuit:
  			dj_circuit.append(lowerCamelCase__     ,       range(num_qubits + 1			)			)
  			# Finally, perform the H-gates again and measure:
  			for qubit in range(lowerCamelCase__			):
  						dj_circuit.h(lowerCamelCase__			)
  
  			for i in range(lowerCamelCase__			):
  						dj_circuit.measure(lowerCamelCase__     ,       lowerCamelCase__			)
  
  			return dj_circuit
  
  
  
  
  
  
  def   __lowerCamelCase	(       lowerCamelCase__		:	str     ,       lowerCamelCase__		:	int			):
  
  
  
  
  
  			'''simple docstring'''
  
  
  
  
  			lowerCamelCase								=     qiskit.Aer.get_backend("""aer_simulator"""			)
  
  			lowerCamelCase								=     dj_oracle(lowerCamelCase__     ,       lowerCamelCase__			)
  			lowerCamelCase								=     dj_algorithm(lowerCamelCase__     ,       lowerCamelCase__			)
  
  			# Execute the circuit on the simulator
  			lowerCamelCase								=     qiskit.execute(lowerCamelCase__     ,       lowerCamelCase__     ,       shots=1000			)
  
  			# Return the histogram data of the results of the experiment.
  			return job.result().get_counts(lowerCamelCase__			)
  
  
  if __name__ == "__main__":
  		print(f"""Deutsch Jozsa - Constant Oracle: {deutsch_jozsa("constant", 3)}""")
  		print(f"""Deutsch Jozsa - Balanced Oracle: {deutsch_jozsa("balanced", 3)}""")
  
  
style_context: 
  
  
  import abc
  import copy
  import dataclasses
  from dataclasses import dataclass
  from typing import ClassVar, Dict, Type, TypeVar
  
  from ..features import Features
  
  
  UpperCAmelCase      :						List[Any]    =		TypeVar("T", bound="TaskTemplate")
  
  
  
  
  
  
  
  @dataclass(frozen=a_     )
  class 					__lowercase					(       abc.ABC     ):
  
  
  
  		"""simple docstring"""
  
  		UpperCamelCase    :				str
  		UpperCamelCase    :				ClassVar[Features]
  		UpperCamelCase    :				ClassVar[Features]
  
  
  
  
  
  
  
  		def 				__A      (   self		,			A  )     ->   T:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					return copy.deepcopy(self  )
  
  
  
  
  
  
  
  		@property
  		def 				__A      (   self  )     ->   Features:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					return Features(**self.input_schema		,			**self.label_schema  )
  
  
  
  
  
  
  
  		@property
  		@abc.abstractmethod
  		def 				__A      (   self  )     ->   Dict[str, str]:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					raise NotImplementedError
  
  
  
  
  
  
  
  		@classmethod
  		def 				__A      (   cls		,			A  )     ->   T:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					lowerCamelCase								=     {f.name for f in dataclasses.fields(cls  )}
  					return cls(**{k: v for k, v in template_dict.items() if k in field_names}  )
  
  