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Circuit -- Qubit, CBit, Operation, QGate, QCircuit, QProg ​

API reference for quantum circuit construction in pyqpanda3. These classes form the core building blocks for describing quantum computations: qubit references, operations, gates, circuits, and programs.

Qubit ​

Represents a quantum bit (qubit) identified by a numeric address. Qubit objects serve as lightweight handles used when constructing gates and circuits.

Signature ​

python
Qubit(qubit: int)

Parameters ​

ParameterTypeDescription
qubitintThe integer address (index) of the qubit.

Methods ​

MethodReturn TypeDescription
get_qubit_addr()intReturns the address (index) of this qubit.

Special Methods ​

Examples ​

python
from pyqpanda3.core import Qubit

q0 = Qubit(0)
q1 = Qubit(1)

print(q0)               # Qubit(0)
print(int(q0))          # 0
print(q0.get_qubit_addr())  # 0

Output:

Qubit(0)
0
0

See Also ​

  • CBit -- Classical bit class.
  • QCircuit -- Circuits operate on qubit indices.

CBit ​

Represents a classical bit used to store measurement outcomes. Like Qubit, it is a lightweight handle identified by a numeric address.

Signature ​

python
CBit(addr: int)

Note: The parameter is positional only — keyword calling CBit(addr=0) is not supported.

Parameters ​

ParameterTypeDescription
addrintThe integer address (index) of the classical bit.

Methods ​

MethodReturn TypeDescription
get_cbit_addr()intReturns the address (index) of this classical bit.

Special Methods ​

Examples ​

python
from pyqpanda3.core import CBit

c0 = CBit(0)
c1 = CBit(1)

print(c0)               # CBit(0)
print(int(c0))          # 0
print(c0.get_cbit_addr())  # 0

Output:

CBit(0)
0
0

See Also ​

  • Qubit -- Quantum bit class.
  • measure -- Measurement operations map qubits to classical bits.

Operation ​

Base class for all operations in a quantum program. QGate inherits from Operation. An Operation carries metadata about its type, target qubits, control qubits, and associated classical bits (for measurement operations).

Signature ​

python
Operation()

Attributes ​

AttributeTypeDescription
m_operation_typeOpTypeThe type of this operation (Gate, Measure, etc.).
m_target_qubitslist[int]Indices of target qubits.
m_control_qubitslist[int]Indices of control qubits.
m_measure_cbitslist[int]Classical bit indices associated with measurement.

Methods ​

MethodReturn TypeDescription
is_controlled()boolReturns True if this operation has at least one control qubit.

Examples ​

python
from pyqpanda3.core import H, CNOT, RX

# H is a single-qubit gate (Operation subclass)
h_gate = H(0)
print(h_gate.m_operation_type)    # OpType.Gate
print(h_gate.m_target_qubits)     # [0]
print(h_gate.is_controlled())      # False

# CNOT is a two-qubit gate
cnot = CNOT(0, 1)
print(cnot.m_control_qubits)      # []
print(cnot.m_target_qubits)       # [0, 1]
print(cnot.is_controlled())        # False

Output:

OpType.Gate
[0]
False
[]
[0, 1]
False

See Also ​

  • QGate -- Quantum gate class, inherits from Operation.
  • OpType -- Enumeration of operation types.

QGate ​

Represents a quantum gate operation. QGate inherits from Operation and adds gate-specific functionality such as matrix representation, gate type, parameters, dagger and power operations, and control qubit management.

Signature ​

QGate instances are created through the module-level gate factory functions (e.g. H, X, CNOT, RX, etc.), not by directly calling the QGate constructor.

python
# Typical construction via factory functions
gate = H(0)                    # single-qubit gate
gate = CNOT(0, 1)              # two-qubit gate
gate = RX(0, 3.14)             # parameterized gate

Methods ​

qubits_num ​

python
qubits_num() -> int

Returns the total number of qubits this gate acts on (both target and control qubits).

qubits ​

python
qubits() -> list[int]

Returns all qubit indices used by this gate (both target and control qubits).

control_qubits ​

python
control_qubits() -> list[int]

Returns the control qubit indices for this gate.

target_qubits ​

python
target_qubits() -> list[int]

Returns the target qubit indices.

dagger ​

python
dagger() -> QGate

Returns a new QGate that is the Hermitian conjugate (adjoint) of this gate. The original gate is not modified.

is_dagger ​

python
is_dagger() -> bool

Returns True if this gate is in its dagger (adjoint) form.

power ​

python
power(k: float) -> QGate

Returns a new gate representing this gate raised to the power k.

ParameterTypeDescription
kfloatThe exponent.

clear_control ​

python
clear_control() -> None

Removes all control qubits from this gate.

control ​

python
control(qubit: int) -> QGate
control(qubits: list[int]) -> QGate

Adds one or more control qubits to this gate. Returns a new QGate with the control qubits added. The original gate is not modified.

ParameterTypeDescription
qubitintA single control qubit index to add.
qubitslist[int]A list of control qubit indices to add.

matrix ​

python
matrix(expanded: bool = False) -> numpy.ndarray

Returns the matrix representation of this gate. When expanded is True, the matrix is expanded to the full qubit space including control qubits.

ParameterTypeDescription
expandedboolWhether to return the expanded matrix (default False).

gate_type ​

python
gate_type() -> GateType

Returns the GateType enum value for this gate.

remap ​

python
remap(mapping: dict[int, int]) -> QGate
remap(mapping: list[int]) -> QGate

Returns a new gate with qubit indices remapped according to the provided mapping.

ParameterTypeDescription
mappingdict[int, int] or list[int]A dictionary mapping old qubit indices to new ones, or a list where position i gives the new index for qubit i.

parameters ​

python
parameters() -> list[float]

Returns the list of parameters for this gate (empty for non-parameterized gates).

set_parameters ​

python
set_parameters(params: list[float]) -> None

Sets the parameters for this gate.

ParameterTypeDescription
paramslist[float]The new parameter values.

name ​

python
name() -> str

Returns the name of this gate.

Examples ​

python
from pyqpanda3.core import H, X, RX, CNOT

# Basic gate properties
h = H(0)
print(h.gate_type())    # GateType.H
print(h.qubits())       # [0]
print(h.qubits_num())   # 1
print(h.name())         # "H"

# Parameterized gate
rx = RX(0, 1.57)
print(rx.parameters())  # [1.57]
rx.set_parameters([3.14])
print(rx.parameters())  # [3.14]

# Dagger (adjoint)
h_dag = h.dagger()
print(h_dag.is_dagger())  # True

# Power
rx_squared = rx.power(2)

# Control qubits
cnot = CNOT(0, 1)
print(cnot.control_qubits())  # [] (control is encoded in the gate type)
print(cnot.target_qubits())   # [0, 1]

# Add control to a single-qubit gate
controlled_h = H(0).control(2)
print(controlled_h.control_qubits())  # [2]

# Add multiple controls
controlled_x = X(0).control([2, 3])
print(controlled_x.control_qubits())  # [2, 3]

# Clear controls
controlled_x.clear_control()
print(controlled_x.control_qubits())  # []

# Matrix representation
mat = H(0).matrix()
print(mat.shape)  # (2, 2)

Output:

GateType.H
[0]
1
H
[1.57]
[3.14]
True
[]
[0, 1]
[2]
[2, 3]
[]
(2, 2)

See Also ​

QCircuit ​

Represents a quantum circuit: an ordered sequence of quantum gate operations. Circuits can be composed using the << operator and support operations such as dagger, control, depth analysis, and matrix computation.

Signature ​

python
QCircuit()                    # empty circuit
QCircuit(qubits_num: int)     # circuit with a specified register size
QCircuit(circuit: QCircuit)   # copy constructor

Parameters ​

ParameterTypeDescription
qubits_numintNumber of qubits to allocate in the circuit register.
circuitQCircuitAn existing circuit to copy.

Methods ​

size ​

python
size() -> int

Returns the number of operations in the circuit.

append ​

python
append(gate: QGate) -> None
append(circuit: QCircuit) -> None

Appends a gate or another circuit to this circuit.

ParameterTypeDescription
gateQGateA quantum gate to append.
circuitQCircuitA circuit to append.

clear ​

python
clear() -> None

Removes all operations from this circuit.

matrix ​

python
matrix() -> numpy.ndarray

Returns the unitary matrix representation of the entire circuit.

qubits ​

python
qubits() -> list[int]

Returns the list of qubit indices used in this circuit.

target_qubits ​

python
target_qubits() -> list[int]

Returns the target qubit indices used in this circuit.

control_qubits ​

python
control_qubits() -> list[int]

Returns the control qubit indices used in this circuit.

dagger ​

python
dagger() -> QCircuit

Returns a new QCircuit where every gate is replaced by its Hermitian conjugate. The original circuit is not modified.

control ​

python
control(qubit: int) -> QCircuit
control(qubits: list[int]) -> QCircuit

Adds one or more control qubits to the entire circuit. Returns a new QCircuit. The original circuit is not modified.

ParameterTypeDescription
qubitintA single control qubit index to add.
qubitslist[int]A list of control qubit indices to add.

clear_control ​

python
clear_control() -> None

Removes all control qubits from this circuit.

set_name ​

python
set_name(name: str) -> None

Sets a custom name for the circuit.

ParameterTypeDescription
namestrThe name to assign.

name ​

python
name() -> str

Returns the name of the circuit.

operations ​

python
operations() -> list

Returns all operations in the circuit as a list (may contain QGate and nested QCircuit objects).

gate_operations ​

python
gate_operations(only_q2: bool = False) -> list[QGate]

Returns all gate-level operations, flattening nested circuits. When only_q2 is True, only two-qubit gates are returned.

ParameterTypeDescription
only_q2boolIf True, return only two-qubit gates (default False).

num_2q_gate ​

python
num_2q_gate() -> int

Returns the count of two-qubit gates in the circuit.

depth ​

python
depth(only_q2: bool = False) -> int

Returns the circuit depth (number of sequential gate layers). When only_q2 is True, only two-qubit gates are considered.

ParameterTypeDescription
only_q2boolIf True, compute depth using only two-qubit gates (default False).

count_ops ​

python
count_ops(only_q2: bool = False) -> dict[str, int]

Returns a dictionary mapping gate names to their occurrence counts.

ParameterTypeDescription
only_q2boolIf True, count only two-qubit gates (default False).

get_register_size ​

python
get_register_size() -> int

Returns the size of the qubit register allocated for this circuit.

expand ​

python
expand() -> QCircuit

Returns a new circuit with all nested sub-circuits expanded into a flat gate sequence.

originir ​

python
originir(precision: int = 8) -> str

Returns the OriginIR string representation of the circuit.

ParameterTypeDescription
precisionintFloating-point precision for parameter values (default 8).

remap ​

python
remap(mapping: list[int]) -> QCircuit
remap(mapping: dict[int, int]) -> QCircuit

Returns a new circuit with qubit indices remapped according to the provided mapping.

ParameterTypeDescription
mappinglist[int] or dict[int, int]A list or dictionary mapping old qubit indices to new ones.

Operators ​

<< (left shift) ​

Appends a gate or circuit. Returns the circuit itself, enabling chaining.

python
c = QCircuit()
c << H(0)
c << CNOT(0, 1)  # append gates to QCircuit

Special Methods ​

  • __str__() -- Returns a text-based circuit diagram.
  • __lshift__() -- Implements the << operator for appending gates and circuits.

Examples ​

Basic circuit construction ​

python
from pyqpanda3.core import QCircuit, H, X, CNOT, T

# Create an empty circuit
circ = QCircuit()

# Append gates using <<
circ << H(0) << CNOT(0, 1)

print(circ.size())   # 2
print(circ.qubits()) # [0, 1]

Output:

2
[0, 1]

Circuit with register size ​

python
from pyqpanda3.core import QCircuit, H, CNOT, X

circ = QCircuit(3)
circ << H(0) << CNOT(0, 1) << X(2)

print(circ.get_register_size())  # 3
print(circ.size())               # 3

Output:

3
3

Composing circuits ​

python
from pyqpanda3.core import QCircuit, H, CNOT, T, S

# Sub-circuit A
sub_a = QCircuit()
sub_a << H(0) << CNOT(0, 1)

# Sub-circuit B
sub_b = QCircuit()
sub_b << T(0) << S(1)

# Combine using <<
full = QCircuit()
full << sub_a << sub_b

print(full.size())  # 2 (two nested sub-circuits)

Output:

2

Analysis: depth and gate count ​

python
from pyqpanda3.core import QCircuit, H, CNOT, T

circ = QCircuit()
circ << H(0) << H(1) << CNOT(0, 1) << T(0) << T(1)

print(circ.depth())          # 3 (H layer, CNOT layer, T layer)
print(circ.depth(only_q2=True))  # 1 (only the CNOT layer)
print(circ.num_2q_gate())    # 1
print(circ.count_ops())      # {'CNOT': 1, 'H': 2, 'T': 2}

Output:

3
1
1
{'CNOT': 1, 'H': 2, 'T': 2}

Dagger and control ​

python
from pyqpanda3.core import QCircuit, H, CNOT, RX

circ = QCircuit()
circ << H(0) << CNOT(0, 1) << RX(1, 1.57)

# Dagger of the entire circuit
circ_dag = circ.dagger()

# Add a control qubit to the entire circuit
ctrl_circ = QCircuit()
ctrl_circ << H(0) << CNOT(0, 1)
ctrl_circ = ctrl_circ.control([2])

print(ctrl_circ.control_qubits())  # [2]

Output:

[2]

Matrix representation ​

python
from pyqpanda3.core import QCircuit, H, X

circ = QCircuit()
circ << H(0) << X(1)

mat = circ.matrix()
print(mat.shape)  # (4, 4)

Output:

(4, 4)

OriginIR output ​

python
from pyqpanda3.core import QCircuit, H, CNOT, RX

circ = QCircuit()
circ << H(0) << CNOT(0, 1) << RX(1, 1.57)

print(circ.originir())

Output:

QINIT 2
CREG 1
H q[0]
CNOT q[0],q[1]
RX q[1],(1.57000000)

Remap qubits ​

python
from pyqpanda3.core import QCircuit, H, CNOT

circ = QCircuit()
circ << H(0) << CNOT(0, 1)

# Remap: qubit 0 -> 2, qubit 1 -> 3
remapped = circ.remap([2, 3])
print(remapped.qubits())  # [2, 3]

Output:

[2, 3]

See Also ​

  • QProg -- Quantum program (circuits plus measurements and control flow).
  • QGate -- Quantum gate class.
  • Gates -- Full list of gate factory functions.
  • OriginIR -- OriginIR intermediate representation.

QProg ​

Represents a quantum program: a complete quantum computation that may include gates, circuits, measurements, and dynamic control flow (classical conditional branches and loops). QProg is the top-level container used when submitting programs to simulators or quantum hardware.

Signature ​

python
QProg()                                       # empty program
QProg(qubits_num: int)                        # program with a specified number of qubits
QProg(prog: QProg)                            # copy constructor
QProg(originir_src: str, is_file: bool = False)  # from OriginIR source or file
QProg(node: QCircuit)                         # from a QCircuit

Parameters ​

ParameterTypeDescription
qubits_numintNumber of qubits to allocate.
progQProgAn existing program to copy.
originir_srcstrOriginIR source string or file path.
is_fileboolIf True, originir_src is treated as a file path (default False).
nodeQCircuitA circuit to initialize the program with.

Methods ​

qubits_num ​

python
qubits_num() -> int

Returns the number of qubits used in the program.

cbits_num ​

python
cbits_num() -> int

Returns the number of classical bits used in the program.

qubits ​

python
qubits() -> list[int]

Returns the qubit indices used in the program.

cbits ​

python
cbits() -> list[int]

Returns the classical bit indices used in the program.

operations ​

python
operations() -> list

Returns all operations in the program (gates, measurements, sub-programs, etc.).

gate_operations ​

python
gate_operations(only_q2: bool = False) -> list[QGate]

Returns all gate-level operations, flattening nested structures. When only_q2 is True, only two-qubit gates are returned.

ParameterTypeDescription
only_q2boolIf True, return only two-qubit gates (default False).

name ​

python
name() -> str

Returns the name of the program.

get_measure_nodes ​

python
get_measure_nodes() -> list

Returns all measurement nodes in the program.

flatten ​

python
flatten() -> QProg

Returns a new program with all nested sub-programs expanded into a flat sequence.

to_circuit ​

python
to_circuit() -> QCircuit

Converts the program to a QCircuit (excluding measurement operations).

count_ops ​

python
count_ops(only_q2: bool = False) -> dict[str, int]

Returns a dictionary mapping operation names to their counts.

ParameterTypeDescription
only_q2boolIf True, count only two-qubit gates (default False).

depth ​

python
depth(only_q2: bool = False) -> int

Returns the program depth (number of sequential gate layers).

ParameterTypeDescription
only_q2boolIf True, compute depth using only two-qubit gates (default False).

clear ​

python
clear() -> None

Removes all operations from the program.

append ​

python
append(gate: QGate) -> None
append(circuit: QCircuit) -> None
append(prog: QProg) -> None
append(measure: MeasureNode) -> None
append(karus: Karus) -> None
append(karus_list: list[Karus]) -> None

Appends an operation to the program. Accepts gates, circuits, programs, measurement nodes, and Kraus noise operators.

ParameterTypeDescription
gateQGateA quantum gate to append.
circuitQCircuitA circuit to append.
progQProgA program to append.
measureMeasureNodeA measurement node to append.
karusKarusA single Kraus noise operator to append (e.g. depolarizing_error(0.01).error_karus([0])).
karus_listlist[Karus]A list of Kraus noise operators to append.

remap ​

python
remap(remap_qubits: list[int], remap_cbits: list[int]) -> QProg
remap(remap_qubits: dict[int, int], remap_cbits: dict[int, int] = {}) -> QProg

Returns a new program with qubit and classical bit indices remapped.

ParameterTypeDescription
remap_qubitslist[int] or dict[int, int]Mapping for qubit indices.
remap_cbitslist[int] or dict[int, int]Mapping for classical bit indices. Defaults to an empty mapping, which (since 0.5.0) leaves classical bit indices unchanged instead of dropping them.

originir ​

python
originir(precision: int = 8) -> str

Returns the OriginIR string representation of the program.

ParameterTypeDescription
precisionintFloating-point precision for parameter values (default 8).

originbis ​

Deprecated: Use Utils.convert_qprog_to_originbis instead.

python
originbis() -> bytes

Returns the OriginBIS binary serialization of the program.

from_originbis ​

Deprecated: Use Utils.convert_originbis_to_qprog instead.

python
from_originbis(data: bytes) -> None

Deserializes the program from OriginBIS binary data.

ParameterTypeDescription
databytesOriginBIS binary data.

to_instruction ​

python
to_instruction(backend: ChipBackend, offset: int = 1, is_scheduling: bool = False, compensate_pulse: bool = True) -> str

Converts the program into a JSON instruction string compatible with the specified chip backend.

ParameterTypeDescription
backendChipBackendThe chip backend configuration object (from pyqpanda3.transpilation).
offsetintQubit index offset (default 1).
is_schedulingboolWhether to include scheduling information (default False).
compensate_pulseboolWhether to apply CZ virtual-Z phase compensation from the backend (default True).

Instruction export behavior ​

  • Empty programs are exported as [].
  • offset is added to every qubit label in the exported JSON. With the default offset=1, logical qubit 0 is emitted as physical label 1.
  • When is_scheduling=True, timestamps are generated from backend timing information such as single_gate_timing, double_gate_timing, and gate-pattern rules.
  • compensate_pulse=True asks the exporter to fold backend CZ compensation data into the instruction stream. Use compensate_pulse=False when you want the raw phases preserved.

instruction_to_qprog ​

python
instruction_to_qprog(
    instruction_json: str,
    qubit_offset: int = -1,
    insert_barrier: bool = True,
) -> QProg | list[QProg]

Converts an instruction JSON stream back into a QProg (or a list of programs). The return type is adaptive to the input:

  • A single stream such as [{...}] or a wrapped [[{...}]] returns one QProg.
  • A multi-stream payload such as [[{...}], [{...}]] returns list[QProg], one program per stream.
ParameterTypeDescription
instruction_jsonstrJSON instruction stream produced by QProg.to_instruction() or a compatible instruction array.
qubit_offsetintQubit label offset used by the JSON encoding, default -1. Pass qubit_offset=1 when reading the standard QProg.to_instruction() output (whose offset defaults to 1). The legacy offset keyword from 0.4.0 was removed in 0.4.1 (passing it raises TypeError); only qubit_offset is accepted.
insert_barrierboolWhether to insert BARRIER operations between timestamp layers. Defaults to True.

Instruction round-trip example ​

python
import json

from pyqpanda3.core import instruction_to_qprog

single_stream = [
    {"RPhi": [1, 90.0, 0.0, 0]},
    {"CZ": [1, 2, 40]},
    {"Measure": [[2, 1], 120]},
]

prog = instruction_to_qprog(json.dumps(single_stream), qubit_offset=1)
programs = instruction_to_qprog(
    json.dumps([single_stream, single_stream]),
    qubit_offset=1,
    insert_barrier=False,
)

print(type(prog).__name__)
print(type(programs).__name__, len(programs))

Expected output:

text
QProg
list 2

Operators ​

<< (left shift) ​

Appends a gate, circuit, program, measurement node, or Kraus noise operator. Returns the program itself, enabling chaining.

python
prog << gate          # append a QGate
prog << circuit       # append a QCircuit
prog << other_prog    # append a QProg
prog << measure_node  # append a MeasureNode
prog << karus         # append a single Karus noise operator
prog << karus_list    # append a list of Karus noise operators

Special Methods ​

  • __str__() -- Returns a text-based circuit diagram of the program.

Examples ​

Basic program with measurements ​

python
from pyqpanda3.core import QProg, H, CNOT, measure

prog = QProg()
prog << H(0) << CNOT(0, 1) << measure(0, 0) << measure(1, 1)

print(prog.qubits_num())  # 2
print(prog.cbits_num())   # 2
print(prog.qubits())      # [0, 1]
print(prog.cbits())       # [0, 1]

Output:

2
2
[0, 1]
[0, 1]

Program from OriginIR ​

python
from pyqpanda3.core import QProg

# From an OriginIR string
ir_source = """
QINIT 2
CREG 2
H q[0]
CNOT q[0],q[1]
MEASURE q[0],c[0]
MEASURE q[1],c[1]
"""
prog = QProg(ir_source)
print(prog.originir())

Output:

QINIT 2
CREG 2
H q[0]
CNOT q[0],q[1]
MEASURE q[0],c[0]
MEASURE q[1],c[1]

Program from a QCircuit ​

python
from pyqpanda3.core import QProg, QCircuit, H, CNOT, measure

circ = QCircuit()
circ << H(0) << CNOT(0, 1)

prog = QProg(circ)
prog << measure(0, 0) << measure(1, 1)

Analysis: depth and gate counts ​

python
from pyqpanda3.core import QProg, H, CNOT, RX, T

prog = QProg()
prog << H(0) << H(1) << CNOT(0, 1) << RX(1, 0.5) << T(0)

print(prog.depth())          # 3
print(prog.depth(only_q2=True))  # 1
print(prog.count_ops())      # {'RX': 1, 'CNOT': 1, 'H': 2, 'T': 1}

Output:

3
1
{'RX': 1, 'CNOT': 1, 'H': 2, 'T': 1}

Flatten and convert to circuit ​

python
from pyqpanda3.core import QProg, QCircuit, H, CNOT

# Nested structure
sub = QCircuit()
sub << H(0) << CNOT(0, 1)

prog = QProg()
prog << sub << H(2)

# Flatten to a linear gate sequence
flat_prog = prog.flatten()

# Convert to a circuit (measurements excluded)
circ = prog.to_circuit()
print(circ.qubits())  # [0, 1, 2]

Output:

[0, 1, 2]

Remap qubits and classical bits ​

python
from pyqpanda3.core import QProg, H, CNOT, measure

prog = QProg()
prog << H(0) << CNOT(0, 1) << measure(0, 0) << measure(1, 1)

# Remap using lists: qubit 0->3, 1->4; cbit 0->5, 1->6
remapped = prog.remap([3, 4], [5, 6])
print(remapped.qubits())  # [3, 4]
print(remapped.cbits())   # [5, 6]

# Remap using dictionaries
remapped2 = prog.remap({0: 3, 1: 4}, {0: 5, 1: 6})

Output:

[3, 4]
[5, 6]

Export to backend instruction ​

python
from pyqpanda3.core import QProg, H, CNOT, measure
from pyqpanda3.transpilation import ChipBackend, Transpiler

prog = QProg()
prog << H(0) << CNOT(0, 1) << measure(0, 0) << measure(1, 1)

# Create and configure a chip backend
cb = ChipBackend()
cb.basic_gates = ['RPHI', 'CZ']

# Transpile to native gates
transpiler = Transpiler()
transpiled = transpiler.transpile(prog, cb)

# Export to JSON instruction string
json_instr = transpiled.to_instruction(cb, offset=1, is_scheduling=False)
print(json_instr)

Get measurement nodes ​

python
from pyqpanda3.core import QProg, H, measure

prog = QProg()
prog << H(0) << measure(0, 0)

measure_nodes = prog.get_measure_nodes()
print(len(measure_nodes))  # 1

Output:

1

See Also ​

draw_qprog ​

Draws a quantum program or circuit as a text diagram or LaTeX source. This function accepts both QProg and QCircuit objects.

Signature ​

python
draw_qprog(qprog: QProg, p: PIC_TYPE = PIC_TYPE.TEXT, expend_map: dict[str, int] = {'all': 1}, param_show: bool = False, with_logo: bool = False, line_length: int = 100, output_file: str = '', encode: str = 'utf-8') -> str
draw_qprog(circuit: QCircuit, p: PIC_TYPE = PIC_TYPE.TEXT, ...) -> str

Parameters ​

ParameterTypeDefaultDescription
qprogQProg—The quantum program to draw
circuitQCircuit—The quantum circuit to draw
pPIC_TYPEPIC_TYPE.TEXTOutput format: PIC_TYPE.TEXT for ASCII text or PIC_TYPE.LATEX for LaTeX
expend_mapdict[str, int]{'all': 1}Map of qubit indices to expand (use {'all': 1} to expand all)
param_showboolFalseWhether to display gate parameter values in the output
with_logoboolFalseWhether to include the pyqpanda3 logo in the output
line_lengthint100Maximum characters per line in the text output
output_filestr''File path to save the output (empty string prints to console)
encodestr'utf-8'Character encoding for the output file

Returns ​

str — The rendered circuit diagram as a string.

Examples ​

python
from pyqpanda3.core import draw_qprog, QProg, H, CNOT, PIC_TYPE

prog = QProg()
prog << H(0) << CNOT(0, 1)

# Draw as text (default)
text_output = draw_qprog(prog)
print(text_output)

# Draw as LaTeX
latex_output = draw_qprog(prog, PIC_TYPE.LATEX)

# Draw with parameter values shown
text_with_params = draw_qprog(prog, param_show=True)

# Save to file
draw_qprog(prog, output_file="circuit.txt")

Output:

          ┌─┐        
q_0:  |0>─┤H├ ───*── 
          └─┘ ┌──┴─┐ 
q_1:  |0>──── ┤CNOT├ 
              └────┘ 
 c :   / ═══════════

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