pymodelio 0.1.0

A simple Python module for defining domain models and performing validations against them

pymodelio

A simple Python module for defining domain models and performing validations against them.

What is this module for?

Have you ever needed to validate a user input, the body of a request, re data obtained from a service like a database or an external api? Well, that's for pymodelio is built for, simplicity when defining your domain models and the restrictions arround them.

How to install the module

Installing the module is simple as running the following script on your terminal:

pip install pymodelio

How to use the module

Declaring the models

Models can be declared using the pymodelio_model decorator or by inheriting from BaseModel. In the example below, the decorator way it's used for not complicating the inheritance tree, but it would be the same if instead of using the decorator in each model, we just declare Component class as class Component(BaseModel).

import uuid
from typing import List

from pymodelio import pymodelio_model, Attribute, UNDEFINED
from pymodelio.validators import Validator, IntValidator, IterableValidator


@pymodelio_model
class Component:
    __serial_no: Attribute[str](default_factory=lambda: uuid.uuid4().__str__())

    @property
    def serial_no(self) -> str:
        return self.__serial_no


@pymodelio_model
class CPU(Component):
    frequency: Attribute[int](validator=IntValidator())
    cores: Attribute[int](validator=IntValidator())

    @staticmethod
    def from_dict(data: dict, auto_validate: bool = True) -> 'CPU':
        return CPU(
            frequency=data.get('frequency'),
            cores=data.get('cores'),
            auto_validate=auto_validate
        )


@pymodelio_model
class RAM(Component):
    frequency: Attribute[int](validator=IntValidator())
    size: Attribute[int](validator=IntValidator())

    @staticmethod
    def from_dict(data: dict, auto_validate: bool = True) -> 'RAM':
        return RAM(
            frequency=data.get('frequency'),
            size=data.get('size'),
            auto_validate=auto_validate
        )


@pymodelio_model
class Disk(Component):
    size: Attribute[int](validator=IntValidator())

    @staticmethod
    def from_dict(data: dict, auto_validate: bool = True) -> 'Disk':
        return Disk(
            size=data.get('size'),
            auto_validate=auto_validate
        )


@pymodelio_model
class Computer(Component):
    _cpu: Attribute[CPU](validator=Validator(expected_type=CPU))
    _rams: Attribute[List[RAM]](validator=IterableValidator(elements_type=RAM))
    _disks: Attribute[List[Disk]](validator=IterableValidator(elements_type=Disk))

    @property
    def cpu(self) -> CPU:
        return self._cpu

    @property
    def rams(self) -> List[RAM]:
        return self._rams

    @property
    def disks(self) -> List[Disk]:
        return self._disks

    @staticmethod
    def from_dict(data: dict, auto_validate: bool = True) -> 'Computer':
        return Computer(
            serial_no=data.get('serial_no') if 'serial_no' in data else UNDEFINED,
            cpu=CPU.from_dict(data.get('cpu'), auto_validate=False),
            rams=[RAM.from_dict(x, auto_validate=False) for x in data.get('rams')],
            disks=[Disk.from_dict(x, auto_validate=False) for x in data.get('disks')],
            auto_validate=auto_validate
        )

Using these specific models

computer = Computer.from_dict({
    'serial_no': '123e4567-e89b-12d3-a456-426614174000',
    'cpu': {
        'frequency': 3500,
        'cores': 8
    },
    'rams': [
        {
            'frequency': 1600,
            'size': 8
        },
        {
            'frequency': 1800,
            'size': 16
        }
    ],
    'disks': [
        {
            'size': 1024
        },
        {
            'size': 512
        }
    ]
})

Customizing the model's initialization workflow

@pymodelio_model
class Model:
    model_attr: Attribute[str]

    @classmethod
    def __before_init__(cls, *args, **kwargs) -> None:
        # This method is called before everything when the model constructor is called
        # It receives the same parameters the constructor gets
        pass

    @classmethod
    def __before_validate__(cls) -> None:
        # This method is called after initializing the model attributes but just before
        # performing the model validations (it will be executed even if 
        # auto_validate = False)
        pass

    @classmethod
    def __once_validated__(cls) -> None:
        # This method is called just after performing the model validations initializing
        # the model attributes but before performing the model validations (it will be
        # executed even if auto_validate = False)
        pass

Non initable attributes

@pymodelio_model
class Model:
    non_initable_model_attr: Attribute[str](initable=False, default_factory=lambda: 'Non initable default value')


# WARNING: This will raise a NameError('non_initable_model_attr attribute is not
#          initable for class Model')
Model(non_initable_model_attr='custom value')

Considerations

When instantiating a model specifying auto_validate = False, the model won't be automatically validated during initialization.

When a class attribute has the annotation Attribute[<type>], it will be transformed into an instance attribute during the model initialization.

When defining a protected or private model attribute with underscore or double underscore respectively, if that property can be set by the model constructor, it's value will be obtained from an attribute with the same name but without underscores. For instance:

@pymodelio_model
class Component:
    __serial_no: Attribute[str]
    _model_name: Attribute[str]

    @property
    def serial_no(self) -> str:
        return self.__serial_no

    @property
    def model_name(self) -> str:
        return self._model_name


component = Component(serial_no='123e4567-e89b-12d3-a456-426614174000', model_name='ABC123')

print(component.serial_no)  # It will print '123e4567-e89b-12d3-a456-426614174000'
print(component.model_name)  # It will print 'ABC123'

Customizing the validation process

Custom validators can be implemented by inheriting from the Validator class. Even that, there is also other way of performing custom validations that consists on implementing _when_validating_attr method in the defined model. This method is called after the attribute validator is called (if the attribute does not have a validator, this method is called anyway).

def _when_validating_attr(self, internal_attr_name: str, exposed_attr_name: str, attr_value: Any, attr_path: str,
                          parent_path: str, pymodel_attribute: Attribute) -> None:
    pass

Available validators

Validator

A generic validator for any type passed by parameter. It is also capable of validating other models. Validated value must implement validate method in order to be considered a model by this validator. Other validators inherit from this one.

Validator(expected_type: Union[type, List[type]] = None, nullable: bool = False, message: Optional[str] = None)

StringValidator

StringValidator(min_len: Optional[int] = None, max_len: Optional[int] = None, fixed_len: Optional[int] = None, regex:
Optional[str] = None, nullable: bool = False, message: Optional[str] = None)

NumericValidator

NumericValidator(expected_type: type, min_value: Optional[Number] = None, max_value: Optional[
    Number] = None, expected_type: Union[type, List[type]] = None, nullable: bool = False, message: Optional[
    str] = None)

IntValidator

A subclass of NumericValidator specific for integers.

IntValidator(min_value: Optional[int] = None, max_value: Optional[int] = None, nullable: bool = False, message:
Optional[str] = None)

FloatValidator

A subclass of NumericValidator specific for float numbers.

FloatValidator(min_value: Optional[float] = None, max_value: Optional[float] = None, nullable: bool = False, message:
Optional[str] = None)

DatetimeValidator

DatetimeValidator(nullable: bool = False, message: Optional[str] = None)

DictValidator

DictValidator(nullable: bool = False, message: Optional[str] = None)

IterableValidator

A validator for an of any type that allows nested models. Validated children must implement validate method in order to be considered a model by this validator.

IterableValidator(expected_type: Union[type, List[type]] = None, elements_type: Union[
    type, List[type]] = None, allow_empty: bool = True, nullable: bool = False, message: Optional[str] = None)

ListValidator

A subclass of IterableValidator specific for lists.

ListValidator(elements_type: Union[type, List[type]] = None, allow_empty: bool = True, nullable: bool = False, message:
Optional[str] = None)

EmailValidator

EmailValidator(nullable: bool = False, message: Optional[str] = None)

BoolValidator

BoolValidator(nullable: bool = False, message: Optional[str] = None)

Serialization

pymodelio models implement a to_dict() method that serializes the public attributes and properties (defined using the property decorator). For the example at the beginning of this documentation, calling to_dict() method in a computer's instance returns something like:

{
    'cpu': {
        'cores': 8,
        'frequency': 3500,
        'serial_no': '0f3b6ef1-dea3-4cdd-be53-ef85079731c4'
    },
    'disks': [
        {
            'serial_no': '011639e0-82dd-44c0-ba46-3580482c0add',
            'size': 1024
        },
        {
            'serial_no': 'd76474eb-b854-49d1-a0df-917fe8526621',
            'size': 512
        }
    ],
    'rams': [
        {
            'frequency': 1600,
            'serial_no': '8a2639e0-aa0c-450a-8ee1-8dd536578bb8',
            'size': 8
        },
        {
            'frequency': 1800,
            'serial_no': '49140714-263e-4fbb-b366-06916c4e81f5',
            'size': 16
        }
    ],
    'serial_no': 'computer-001'
}

If a defined model implements to_dict() method, this overridden one will be used instead of the default one. The signature for overriding this method should be:

def to_dict(self) -> dict:
    return {}  # Returns the serialized model

Let's compare the same code using raw python against using pymodelio

Using raw python

class RawPythonChildModel:

    def __int__(self, public_child_attr: int) -> None:
        self.public_child_attr = public_child_attr
        self.validate()

    def validate(self) -> None:
        assert isinstance(self.public_child_attr, int), 'public_child_attr is not a valid int'


class RawPythonModel:
    _PUBLIC_ATTR_MIN_VALUE = 0
    _PUBLIC_ATTR_MAX_VALUE = 0

    _PROTECTED_ATTR_FIXED_LENGTH = 5
    _PROTECTED_ATTR_REGEX = '^[A-Z]+$'  # Only capitalized chars

    def __init__(self, public_attr: int, protected_attr: str, private_attr: datetime,
                 child_model_attr: RawPythonChildModel, children_model_attr: List[RawPythonChildModel],
                 optional_attr: dict = None) -> None:
        self.public_attr = public_attr
        self._protected_attr = protected_attr
        self.__private_attr = private_attr
        self.child_model_attr = child_model_attr
        self.children_model_attr = children_model_attr
        self.optional_attr = {} if optional_attr is None else optional_attr
        self.non_initable_attr = []
        self.validate()

    def validate(self) -> None:
        assert isinstance(self.public_attr, int), 'public_child_attr is not a valid int'
        assert self.public_attr >= self._PUBLIC_ATTR_MIN_VALUE,
        f'public_child_attr is lower than {self._PUBLIC_ATTR_MIN_VALUE}'

    assert self.public_attr <= self._PUBLIC_ATTR_MAX_VALUE,
    f'public_child_attr is greater than {self._PUBLIC_ATTR_MAX_VALUE}'


assert isinstance(self._protected_attr, str), '_protected_attr is not a valid str'
assert len(self._protected_attr) == self._PROTECTED_ATTR_FIXED_LENGTH,
f'_protected_attr length is different than {self._PROTECTED_ATTR_FIXED_LENGTH}'
assert re.compile(self._PROTECTED_ATTR_REGEX).match(self._protected_attr) is not None,
'_protected_attr does not match configured regex'

assert isinstance(self.child_model_attr, RawPythonChildModel),
'child_model_attr is not a valid RawPythonChildModel'
self.child_model_attr.validate()

assert isinstance(self.children_model_attr, list), 'children_model_attr is not a valid list'
for child_model in self.children_model_attr:
    child_model.validate()

assert isinstance(self.__private_attr, datetime), '__private_attr is not a valid datetime'

assert isinstance(self.optional_attr, dict), 'optional_attr is not a valid dict'

Using pymodelio

pymodelio model validation errors also give more information about the full path of nested structures. In case of lists, including the index of the list element where the error occurred.

@pymodelio_model
class PymodelioChildModel:
    public_child_attr: Attribute[int](validator=IntValidator())


@pymodelio_model
class PymodelioModel:
    public_attr: Attribute[int](validator=IntValidator(min_value=0, max_value=10))
    _protected_attr: Attribute[str](validator=StringValidator(fixed_len=5, regex='^[A-Z]+$'))  # Only capitalized chars
    __private_attr: Attribute[datetime](validator=DatetimeValidator())
    child_model_attr: Attribute[PymodelioChildModel](validator=Validator(expected_type=PymodelioChildModel))
    children_model_attr: Attribute[List[PymodelioChildModel]](
        validator=ListValidator(elements_type=PymodelioChildModel))
    optional_attr: Attribute[dict](validator=DictValidator())
    non_initable_attr: Attribute[List[str]](initable=False, default_factory=list)