qunicorn_core.db.models package

Submodules

qunicorn_core.db.models.db_model module

class qunicorn_core.db.models.db_model.DbModel

Bases: object

Dataclass for database model to create a table name and the id column

Attributes:: id (int): Automatically generated id of the database entity

qunicorn_core.db.models.deployment module

class qunicorn_core.db.models.deployment.DeploymentDataclass(id=None, deployed_by=None, programs=None, deployed_at=datetime.datetime(2023, 10, 13, 16, 20, 53, 770495), name=None)

Bases: DbModel

Dataclass for storing deployments

Attributes:: name (str, optional): Optional name for a deployment_api deployed_by (str): The user_id that deployed this Deployment programs (list): A list of quantum programs deployed_at (Date): Date of the creation of a deployment_api

deployed_at: Mapped[datetime]

deployed_by: Mapped[str | None]

id: Mapped[int]

name: Mapped[str | None]

programs: Mapped[List[QuantumProgramDataclass]]

qunicorn_core.db.models.device module

class qunicorn_core.db.models.device.DeviceDataclass(id=None, provider_id=None, num_qubits=-1, name='', is_simulator=False, is_local=False, provider=None)

Bases: DbModel

Dataclass for storing CloudDevices of a provider

Attributes:: provider: The provider of the cloud_service with the needed configurations num_qubits: The amount of qubits that is available at this device name: The name of the device is_simulator: The information whether the device is a simulator (true) or not (false) is_local: The information whether jobs executed on this device are executed local or not provider: The provider of this device

id: Mapped[int]

is_local: Mapped[bool]

is_simulator: Mapped[bool]

name: Mapped[str]

num_qubits: Mapped[int]

provider: Mapped[ProviderDataclass]

provider_id: Mapped[int]

qunicorn_core.db.models.job module

class qunicorn_core.db.models.job.JobDataclass(id=None, results=<factory>, executed_by=None, executed_on_id=None, executed_on=None, deployment_id=None, deployment=None, progress=None, state=None, shots=4000, type=JobType.RUNNER, started_at=datetime.datetime(2023, 10, 13, 16, 20, 53, 776858), finished_at=None, name=None, data=None, parameters=None, provider_specific_id=None, celery_id=None)

Bases: DbModel

Dataclass for storing Jobs

Attributes:

name (str, optional): Optional name for a job executed_by_id (str): A user_id associated to the job, user that wants to execute the job deployment_id (int): A deployment_id associated with the job state (Optional[str], optional): The state of a job, enum JobState started_at (datetime, optional): The moment the job was scheduled.

(default utcnow())

finished_at (Optional[datetime], optional): The moment the job finished successfully or with an error. data (Union[dict, list, str, float, int, bool, None], optional): Mutable JSON-like store for additional

lightweight task data. Default value is empty dict.

results (ResultDataclass, optional): List of results for each quantum program that was executed parameters (str, optional): The parameters for the Job. Job parameters should already be prepared and error

checked before starting the task.

celery_id: Mapped[str | None]

data: Mapped[str | None]

deployment: Mapped[DeploymentDataclass]

deployment_id: Mapped[int]

executed_by: Mapped[str | None]

executed_on: Mapped[DeviceDataclass]

executed_on_id: Mapped[int]

finished_at: Mapped[datetime | None]

id: Mapped[int]

name: Mapped[str | None]

parameters: Mapped[str | None]

progress: Mapped[str]

provider_specific_id: Mapped[str | None]

results: Mapped[List[ResultDataclass] | None]

shots: Mapped[int]

started_at: Mapped[datetime]

state: Mapped[str]

type: Mapped[str]

qunicorn_core.db.models.provider module

class qunicorn_core.db.models.provider.ProviderDataclass(id=None, with_token=None, supported_languages=None, name=None)

Bases: DbModel

Dataclass for storing Providers

Attributes:: with_token (bool): If authentication is needed and can be done by passing a token this attribute true. supported_languages: The programming language that this provider supports. name (ProviderName): Name of the cloud service.

id: Mapped[int]

name: Mapped[str]

supported_languages: Mapped[List[ProviderAssemblerLanguageDataclass]]

with_token: Mapped[bool]

qunicorn_core.db.models.provider_assembler_language module

class qunicorn_core.db.models.provider_assembler_language.ProviderAssemblerLanguageDataclass(id=None, provider_ID=None, supported_language=None)

Bases: DbModel

Dataclass for storing Assembler Languages

Attributes:: provider_ID: the ID of the provider that supports this language supported_language: the AssemblerLanguage (Enum) which is supported

id: Mapped[int]

provider_ID: Mapped[int]

supported_language: Mapped[str]

qunicorn_core.db.models.quantum_program module

class qunicorn_core.db.models.quantum_program.QuantumProgramDataclass(id=None, quantum_circuit=None, assembler_language=None, deployment_id=None, python_file_path=None, python_file_metadata=None, python_file_options=None, python_file_inputs=None)

Bases: DbModel

Dataclass for storing QuantumPrograms

Attributes:: quantum_circuit (str): Quantum code that needs to be executed. assembler_language (enum): Assembler language in which the code should be interpreted deployment_id (int): The deployment where a list of quantum program is used

assembler_language: Mapped[str]

deployment_id: Mapped[int]

id: Mapped[int]

python_file_inputs: Mapped[str]

python_file_metadata: Mapped[str]

python_file_options: Mapped[str]

python_file_path: Mapped[str]

quantum_circuit: Mapped[str]

qunicorn_core.db.models.result module

class qunicorn_core.db.models.result.ResultDataclass(id=None, result_dict=None, job_id=None, circuit=None, meta_data=None, result_type=ResultType.COUNTS)

Bases: DbModel

Dataclass for storing results of a job

Attributes:

result_dict (dict): The results of the job, in the given result_type: For the Runner it should have the keys counts and probabilities The counts and probabilities should be a dict with hexadecimals as quantum-bit-keys

job_id (int): The job_id that was executed circuit (str): The circuit which was executed by the job meta_data (dict): Some other data that was given by ibm result_type (Enum): Result type depending on the Job_Type of the job

circuit: Mapped[str]

id: Mapped[int]

job_id: Mapped[int]

meta_data: Mapped[dict]

result_dict: Mapped[dict]

result_type: Mapped[str]

qunicorn_core.db.models.user module

Module contents

Module containing all SQLalchemy Models.