qbraid.runtime.schemas.DeviceData
- class DeviceData(**data)[source]
Represents metadata and capabilities of a quantum device.
- provider
The entity that manufactures the quantum hardware or maintains the simulator software.
- Type:
str
- vendor
The entity that hosts or provides access to the quantum device for end users.
- Type:
str
- name
The name of the quantum device.
- Type:
str
- paradigm
The quantum computing paradigm (e.g., gate-model, AHS).
- Type:
str
- status
The current status of the device (e.g., ONLINE, OFFLINE).
- Type:
str
- is_available
Indicates whether the device is available for jobs.
- Type:
bool
- queue_depth
The depth of the job queue, or None if not applicable.
- Type:
int, optional
- device_type
The type of device (e.g., Simulator, QPU).
- Type:
str
- num_qubits
The number of qubits supported by the device.
- Type:
int
- run_input_types
The software packages / program type alises that can be used to specify quantum programs in jobs submitted to the device (e.g. [‘qasm2’]).
- Type:
list[str]
- device_id
The qBraid-specific device identifier.
- Type:
str
- noise_models
A list of supported noise models. Defaults to None.
- Type:
list[str], optional
- pricing
The pricing structure for using the device, in qBraid credits.
- Type:
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_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)Attributes
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.