qbraid.runtime.schemas.RuntimeJobModel

class RuntimeJobModel(**data)[source]

Represents a runtime job in the qBraid platform.

job_id

The unique identifier for the job.

Type:

str

device_id

The identifier of the quantum device used.

Type:

str

status

The current status of the job.

Type:

JobStatus

shots

The number of shots for the quantum experiment.

Type:

Optional[int]

experiment_type

The type of experiment conducted.

Type:

str

metadata

Metadata associated with the experiment.

Type:

Union[QbraidExperimentMetadata, ExperimentMetadata]

time_stamps

Time-related information about the job.

Type:

TimeStamps

tags

Custom tags associated with the job.

Type:

dict[str, str]

cost

The cost of the job in qBraid credits.

Type:

Credits, optional

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Methods

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

construct([_fields_set])

copy(*[, include, exclude, update, deep])

Returns a copy of the model.

dict(*[, include, exclude, by_alias, ...])

from_dict(job_data)

Creates a RuntimeJobModel instance from a dictionary of job data.

from_orm(obj)

json(*[, include, exclude, by_alias, ...])

model_construct([_fields_set])

Creates a new instance of the Model class with validated data.

model_copy(*[, update, deep])

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy

model_dump(*[, mode, include, exclude, ...])

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump

model_dump_json(*[, indent, include, ...])

Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json

model_json_schema([by_alias, ref_template, ...])

Generates a JSON schema for a model class.

model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

model_post_init(_BaseModel__context)

Override this method to perform additional initialization after __init__ and model_construct.

model_rebuild(*[, force, raise_errors, ...])

Try to rebuild the pydantic-core schema for the model.

model_validate(obj, *[, strict, ...])

Validate a pydantic model instance.

model_validate_json(json_data, *[, strict, ...])

Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing

model_validate_strings(obj, *[, strict, context])

Validate the given object with string data against the Pydantic model.

parse_file(path, *[, content_type, ...])

parse_obj(obj)

parse_raw(b, *[, content_type, encoding, ...])

schema([by_alias, ref_template])

schema_json(*[, by_alias, ref_template])

update_forward_refs(**localns)

validate(value)

validate_experiment_type(value)

Ensure the experiment_type is a valid ExperimentType enum value.

validate_header()

Validates that the header is correctly set up during instantiation.

validate_status(value)

Ensure the status is a valid JobStatus enum value.

Attributes

VERSION

header

Computes the schema header based on the module name and class version.

model_computed_fields

model_config

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_extra

Get extra fields set during validation.

model_fields

model_fields_set

Returns the set of fields that have been explicitly set on this model instance.

job_id

device_id

status

status_text

shots

experiment_type

metadata

time_stamps

tags

cost