Dict2Model 0.0.22

Dictionary to Model

Dict2Model

The library returns an object with defined attributes in types from an input dictionary, with optional rules about types and more.

The declaration for the object variables and their types uses annotations:

    number: int
    question: bool

The mapping between variable and path inside the input dictionary are inside the source variables, in this format: a string separated by '-' for each inner jump inside the dictionary For example:

    NUMBER_SOURCE = "data-number"           # == dict_input["data"]["number"]
    QUESTION_SOURCE = "data-question"       # == dict_input["data"]["question"]

The optional parameter are:

DISABLE_TYPE_EXCEPTIONS = True
DISABLE_PATH_EXCEPTIONS = True

Type exception indicate to stop the object creation if theirs an error in matching types. The second variable indicate to stop the object creation if a value don't exist in the source path. When disabled variables are true the problematic variables are set to None. The default is DISABLE_TYPE_EXCEPTIONS and DISABLE_PATH_EXCEPTIONS as False.

Full example:

class TestObj:
    number: int
    question: bool
    NUMBER_SOURCE = "data-number"
    QUESTION_SOURCE = "data-question"
    DISABLE_TYPE_EXCEPTIONS = True
    DISABLE_PATH_EXCEPTIONS = True

##Example:

pip install SpecialModel

from src.dict2model import Dict2Model


class TestObj:
    number: int
    question: bool

    NUMBER_SOURCE = "data-number"
    QUESTION_SOURCE = "data-question"
    DISABLE_TYPE_EXCEPTIONS = True
    DISABLE_PATH_EXCEPTIONS = True


dict_input_test = {
    "data": {
        "number": 123,
        "question": True
    }
}

factory = Dict2Model.Dict2Model(TestObj, dict_input_test)
test_obj: TestObj = factory.run()
print(test_obj.number, test_obj.question)
print(type(test_obj.number), type(test_obj.question))