Enumerations

This page documents the enumerations used across the qcloud module for job status, data formats, noise models, and logging.

JobStatus

Represents the lifecycle status of a quantum cloud job.

Value	Description
WAITING	The job is waiting to be processed
COMPUTING	The job is currently being executed on the backend
FINISHED	The job has completed successfully
FAILED	The job has failed during execution
QUEUING	The job is queued and waiting for available resources

FAILED is terminal; since 0.5.1, QCloudJob.result() returns server-reported failures as results instead of raising.

Example

from pyqpanda3.qcloud import JobStatus

# JobStatus is the value QCloudJob.status() reports.
status = JobStatus.FINISHED
if status == JobStatus.FINISHED:
    print("Job finished")
elif status == JobStatus.FAILED:
    print("Job failed")

DataFormat

Specifies the data format used for quantum circuit export and communication with cloud backends.

NOTE

DataFormat is exported from pyqpanda3.qcloud via from pyqpanda3.qcloud import DataFormat.

Value	Description
DEFAULT	Default format; behavior depends on the context or backend implementation
BINARY	Compact binary format for efficient transmission and storage
INSTRUCTION_SET	Explicit sequence of instructions or gate operations

DataBase

Specifies the numeric base used for representing quantum measurement results.

Value	Description
Binary	Base-2 (binary) representation, e.g., "0010"
Hex	Base-16 (hexadecimal) representation, e.g., "0x2"

Example

from pyqpanda3.qcloud import DataBase

# DataBase selects the key format of QCloudResult.get_probs():
#   DataBase.Binary -> keys like '00', '11'
#   DataBase.Hex    -> keys like '0x0', '0x3'
for base in (DataBase.Binary, DataBase.Hex):
    print(base.name, base.value)

NOISE_MODEL

Defines the types of quantum noise models available for cloud-based noisy simulations.

Value	Description
BITFLIP_KRAUS_OPERATOR	Bit-flip noise model (X error with probability p)
BIT_PHASE_FLIP_OPERATOR	Bit-phase flip noise model (Y error with probability p)
DAMPING_KRAUS_OPERATOR	Amplitude damping noise model (energy dissipation)
DECOHERENCE_KRAUS_OPERATOR	Combined decoherence noise model (T1 and T2 relaxation)
DEPHASING_KRAUS_OPERATOR	Phase damping noise model (loss of phase coherence)
DEPOLARIZING_KRAUS_OPERATOR	Depolarizing noise model (uniform error on all Pauli axes)
PHASE_DAMPING_OPERATOR	Phase damping noise model (pure dephasing)

Example

from pyqpanda3.qcloud import QCloudNoiseModel, NOISE_MODEL

# Create a decoherence noise model
# Note: QCloudNoiseModel accepts positional arguments only
# DECOHERENCE_KRAUS_OPERATOR requires exactly 3 elements each
noise = QCloudNoiseModel(
    NOISE_MODEL.DECOHERENCE_KRAUS_OPERATOR,
    [0.001, 0.002, 0.003],
    [0.01, 0.02, 0.03]
)

LogLevel

Defines logging verbosity levels for the cloud service.

Value	Description
CLOUD_INFO	Informational messages about normal operations
CLOUD_DEBUG	Detailed debug messages for troubleshooting
CLOUD_WARNING	Warning messages about potential issues
CLOUD_ERROR	Error messages about failures

Example

from pyqpanda3.qcloud import LogLevel

# LogLevel values define verbosity levels for cloud service logging
print(LogLevel.CLOUD_INFO)
print(LogLevel.CLOUD_DEBUG)
print(LogLevel.CLOUD_WARNING)
print(LogLevel.CLOUD_ERROR)

Output:

LogLevel.CLOUD_INFO
LogLevel.CLOUD_DEBUG
LogLevel.CLOUD_WARNING
LogLevel.CLOUD_ERROR

LogOutput

Specifies the destination for log output from the cloud service.

Value	Description
CONSOLE	Log messages are printed to the console (standard output)
FILE	Log messages are written to a file

Example

from pyqpanda3.qcloud import QCloudService, LogOutput

service = QCloudService(api_key="your_api_key")
service.setup_logging(output=LogOutput.FILE, file_path="qcloud_debug.log")

See Also

• QCloudService -- Main cloud service class
• QCloudNoiseModel -- Noise model configuration using NOISE_MODEL
• QCloudResult -- Result class using DataBase for output format