pyrot.eye_modelling.datamodels.validators

Data validation and field descriptors for pyROT data models.

Exceptions

ValidationError

Exception raised when a validation error occurs.

Classes

RayOcularField	A descriptor class that provides validation for a RayOcular field.
Vector3	Three-dimensional vector with components of a given type.

Functions

dataclass(→ Callable[Ellipsis, T])	Validate dataclasses.
positive_float(→ float)	Validate positive floats.
vector3(→ Callable[[Any], Vector3[T]])	Validate Vector3 objects.
literal(→ Callable[[Any], T])	Validate literal values.
optional(→ Callable[[Any], T | None])	Validate optional values.

Module Contents

exception pyrot.eye_modelling.datamodels.validators.ValidationError(value: Any, field_name: str)

Bases: Exception

Exception raised when a validation error occurs.

class pyrot.eye_modelling.datamodels.validators.RayOcularField(validator: Callable[[Any], Value], name: str, *, default: Value = ...)

Bases: ValidatedField[Value]

A descriptor class that provides validation for a RayOcular field.

Parameters

validatorCallable[[Any], Value]

A callable object that performs the validation.

namestr

The RayOcular name of the field. This is used for serialization and deserialization to RayOcular.

defaultValue, optional

The default value for the field. If not provided, the field will be required and must be set explicitly.

Attributes

public_namestr

The public name of the field.

private_namestr

The private name of the field.

Methods

__get__(self, instance: Instance, owner: type[Instance] | None = None) -> Value:

Retrieves the value of the field.

__set__(self, instance: Instance, value: Value):

Sets the value of the field after validating it.

validate(self, value):

Validates the given value using the provided validator.

Raises

ValueError

If the validation fails.

Notes

Define a ValidatedField descriptor for a class attribute and provide a validator function. The validator function should take a single argument and return the validated value.

Examples

>>> class Person:
...     age = ValidatedField(int)
...
...     def __init__(self, age):
...         self.age = age

pyrot.eye_modelling.datamodels.validators.dataclass(cls: type[T]) → Callable[Ellipsis, T]

Validate dataclasses.

Checks if the value is an instance of the dataclass or a dict that can be used to create an instance of the dataclass.

Parameters

clstype[T]

The dataclass type to validate against.

Returns

Callable[…, T]

A validator function that can be used to validate instances of the dataclass.

pyrot.eye_modelling.datamodels.validators.positive_float(value: Any) → float

Validate positive floats.

Parameters

valueAny

The value to validate.

Returns

float

The validated positive float value.

Raises

ValueError

If the value is not a positive float.

class pyrot.eye_modelling.datamodels.validators.Vector3

Bases: Generic[T]

Three-dimensional vector with components of a given type.

Attributes

xT

X component of the vector.

yT

Y component of the vector.

zT

Z component of the vector.

pyrot.eye_modelling.datamodels.validators.vector3(item_validator: Callable[Ellipsis, T]) → Callable[[Any], Vector3[T]]

Validate Vector3 objects.

Parameters

item_validatorCallable[…, T]

A validator function for the individual components of the vector.

Returns

Callable[[Any], Vector3[T]]

A validator function that can be used to validate Vector3 objects.

pyrot.eye_modelling.datamodels.validators.literal(type_: type[T]) → Callable[[Any], T]

Validate literal values.

Parameters

type_type[T]

The type containing the allowed literal values.

Returns

Callable[[Any], T]

A validator function that can be used to validate literal values.

pyrot.eye_modelling.datamodels.validators.optional(inner: Callable[Ellipsis, T]) → Callable[[Any], T | None]

Validate optional values.

Parameters

innerCallable[…, T]

The validator function for the non-optional value.

Returns

Callable[[Any], T | None]

A validator function to validate optional values.