Python-DTO

Simple implementation of Data Transfer Object (DTO) in Python.

With Python-DTO you can make Immutable/Mutable (or partially mutable - i.e. attribute level control) DTO classes and parse JSON string and dictionaries to them.

Python-DTO classes support validation of both type and value.

Example:

from typing import Optional
from pydto import DTO
from datetime import datetime

class CarDTO(DTO, partial=True):
    year = int, {"validator": lambda value: value > 1980}
    license = str,

class AddressDTO(DTO):
    city = str,

class UserDTO(DTO):
    first_name = str,
    middle_name = str,
    last_name = str,
    birth_date = datetime, {"coerce": lambda value: datetime.strptime(value, '%Y-%m-%d')}
    car = CarDTO,
    address = AddressDTO,
    email = str, {"immutable": False}
    salary = Optional[float],

json_string = '{"salary": null, "middle_name": "kurt", "address": {"city": "scranton"}, "first_name": "dwight", ' \
              '"email": "dshrute@schrutefarms.com", "car": {"license": "4018 JXT", "year": 1987, "color": "red"}, ' \
              '"last_name": "schrute", "birth_date": "1974-01-20"}'

user_dto = UserDTO.from_json(json_string)

Notes:

1. DTO classes attributes can be other DTOs or type object (e.g. int, float, string).
2. by default DTO object/attributes are immutable. You can change this by adding {"immutable": False} to DTO attribute definition tuple.
3. You can add custom value validator (callable object) to a DTO attribute by adding dictionary key validator the DTO attribute definition tuple e.g. {"validator": lambda x: x>0}.
4. by default all attributes of a DTO should be observed in the JSON/dictionary. Partial DTOs (with partial=False in their class definition) can be part of a JSON/dictionary
5. You can define a specific parser for a DTO attribute by adding the dictionary key coerce to DTO definition tuple e.g. {"coerce": lambda value: datetime.strptime(value, '%Y-%m-%d')}