model#
Root models for data structures used within the package.
Module Contents#
Classes#
A parent for all data structures. |
Functions#
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Import a python function from a dotted import string (e.g., |
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Import a python class from a dotted import string (e.g., |
- class DataStructure(/, **data: Any)[source]#
Bases:
pydantic.BaseModel
A parent for all data structures.
Data attributes are generated from the class’ type annotations, similarly to dataclasses. If data attributes are JSON-serializable, data structure can be serialized using
json()
method. This string can be deserialized usingparse_raw()
classmethod of a correspondent child class.If required, data fields can be validated, see examples for more information. It is also possible to define custom field types with advanced validation.
This class is a pre-configured pydantic model. See its documentation for details of usage information.
Examples
Initializing a custom data structure:
class ExampleClockResource(DataStructure): """An example clock resource. It has name, frequency and phase. By default phase is zero. Parameters ---------- name Clock name freq Clock frequency [Hz] phase Clock phase, by default 0 [rad]. """ name: str freq: float phase: float = 0 clock = ExampleClockResource(name="q0.01", freq=7e9) print(str(clock)) print(repr(clock))
name='q0.01' freq=7000000000.0 phase=0 ExampleClockResource(name='q0.01', freq=7000000000.0, phase=0)
This data structure can be used within other data structures:
class ExamplePulse(DataStructure): """...""" amplitude: float duration: float clock: ExampleClockResource pulse = ExamplePulse(amplitude=0.1, duration=2e-8, clock=clock) print(str(pulse)) print(repr(pulse))
amplitude=0.1 duration=2e-08 clock=ExampleClockResource(name='q0.01', freq=7000000000.0, phase=0) ExamplePulse(amplitude=0.1, duration=2e-08, clock=ExampleClockResource(name='q0.01', freq=7000000000.0, phase=0))
Serialization, deserialization and comparison are provided from scratch:
pulse_json = pulse.model_dump_json() print(pulse_json) pulse2 = ExamplePulse.model_validate_json(pulse_json) assert pulse == pulse2
{"amplitude":0.1,"duration":2e-8,"clock":{"name":"q0.01","freq":7000000000.0,"phase":0.0}}
User may implement custom validators:
from pydantic import field_validator class ScheduledExamplePulse(DataStructure): """...""" pulse: ExamplePulse start: float @field_validator("start") def _ensure_4ns_grid(cls, value): # pylint: disable=no-self-argument,no-self-use if value % 4e-9 > 1e-12: raise ValueError("Start must be on a 4 ns grid due to hardware limitations") return value # This works fine scheduled_pulse = ScheduledExamplePulse(pulse=pulse, start=8e-9) # This raises a ValidationError scheduled_pulse = ScheduledExamplePulse(pulse=pulse, start=9e-9)
--------------------------------------------------------------------------- ValidationError Traceback (most recent call last) Cell In[5], line 21 19 scheduled_pulse = ScheduledExamplePulse(pulse=pulse, start=8e-9) 20 # This raises a ValidationError ---> 21 scheduled_pulse = ScheduledExamplePulse(pulse=pulse, start=9e-9) File /usr/local/lib/python3.9/site-packages/pydantic/main.py:171, in BaseModel.__init__(self, **data) 169 # `__tracebackhide__` tells pytest and some other tools to omit this function from tracebacks 170 __tracebackhide__ = True --> 171 self.__pydantic_validator__.validate_python(data, self_instance=self) ValidationError: 1 validation error for ScheduledExamplePulse start Value error, Start must be on a 4 ns grid due to hardware limitations [type=value_error, input_value=9e-09, input_type=float] For further information visit https://errors.pydantic.dev/2.6/v/value_error
See pydantic documentation for more usage examples.
- deserialize_function(fun: str) Callable[Ellipsis, Any] [source]#
Import a python function from a dotted import string (e.g., “quantify_scheduler.structure.model.deserialize_function”).
- Parameters:
fun (str) – A dotted import path to a function (e.g., “quantify_scheduler.waveforms.square”), or a function pointer.
- Return type:
Callable[[Any], Any]
- Raises:
ValueError – Raised if the function cannot be imported from path in the string.
- deserialize_class(cls: str) type [source]#
Import a python class from a dotted import string (e.g., “quantify_scheduler.structure.model.DataStructure”).
- Parameters:
cls (str) – A dotted import path to a class (e.g., “quantify_scheduler.structure.model.DataStructure”), or a class pointer.
- Returns:
The type you are trying to import.
- Raises:
ValueError – Raised if the class cannot be imported from path in the string.