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
- shots
The number of shots for the quantum experiment.
- Type:
Optional[int]
- experiment_type
The type of experiment conducted.
- Type:
str
- queue_position
The position of the job in the queue.
- Type:
Optional[int]
- metadata
Metadata associated with the experiment.
- Type:
Union[QbraidExperimentMetadata, ExperimentMetadata]
- time_stamps
Time-related information about the job.
- Type:
- tags
Custom tags associated with the job.
- Type:
dict[str, str]
- preflight
Flag indicating if the job was run in preflight mode.
- Type:
bool
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
VERSIONheaderComputes the schema header based on the module name and class version.
model_computed_fieldsmodel_configConfiguration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
model_extraGet extra fields set during validation.
model_fieldsmodel_fields_setReturns the set of fields that have been explicitly set on this model instance.
status_text