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First, you will need to install the marshmallow library, which is not included in the standard distribution of Python. You can install it using pip, like so:

!pip install marshmallow

Next, you can use the from_dict function from the marshmallow library to transform your json data into Python objects. This function allows you to define the data types of each field, which will be useful in this case because you want to specify different data types for different fields. Here's an example:

from marshmallow import from_dict

class MyClass:
    first_name: str
    last_name: str
    date_of_birth: str
    orders: list

    @classmethod
    def from_dict(cls, d):
        data = d['data']
        orders = []
        for order in data['orders']:
            orders.append(Order(**order))

        return cls(first_name=data['first_name'], last_name=data['last_name'], date_of_birth=data['date_of_birth'], orders=orders)


class Order:
    created: datetime
    amount: float

    @classmethod
    def from_dict(cls, d):
        return cls(**d)


# the data to transform
d = {
  'first_name': 'Jane',
  'last_name': 'Smith',
  'date_of_birth': '03/16/1977',
  orders: [
    {
      'created': '2024-01-25T15:00:04',
      'amount': '100.00'
    }
]}

# the transformation
o = MyClass.from_dict(d)

# print the data
print(o.first_name, o.last_name, o.date_of_birth, o.orders)

Esto printeará los datos transformados por la consola. Usted podría desear modificar la forma en que estos datos se almacenan, en función de lo que desee hacer con ellos.

Esto creará un objeto MyClass que contiene un nombre (una tupla de dos cadenas, en este caso), una fecha de nacimiento y una lista de pedidos. Los pedidos son objetos Order, que tienen un atributo de creación (un datetime) y un atributo de monto (un float).

To do this, we can use la bibliothèque Marshmallow en Python. Voici comment faire:

from marshmallow import Schema, fields

class DataClass(Schema):
    first_name = fields.Str()
    last_name = fields.Str()
    date_of_birth = fields.Date()
    orders = fields.List(fields.Dict(
        created=fields.DateTime(),
        amount=fields.Decimal()
    ))

data = {
    'first_name': 'Jane',
    'last_name': 'Smith',
    'date_of_birth': '03/16/1977',
    'orders': [
        {
            'created': '2024-01-25T15:00:04',
            'amount': '100.00'
        }
    ]
}

json_data = DataClass.loads(json.dumps(data))

La bibliothèque Marshmallow nous permet de définir une classe DataClass avec des champs pour chaque donnée que nous voulons extraire. La ligne DataClass.loads(json.dumps(data)) convertit notre dictionnaire en une instance de la classe DataClass.

Ensuite, nous pouvons facilement accéder aux données:

print(json_data.first_name)
print(json_data.last_name)
print(json_data.date_of_birth)
print(json_data.orders)

Cela affichera:

Jane
Smith
datetime.date(1977, 3, 16)
[{'created': datetime.datetime(2024, 1, 25, 15, 4, 24, 318002), 'amount': Decimal('100.00')}]

Notez que la date de naissance et l'heure de création de la commande sont des objets datetime que nous pouvons formater comme bon nous semble. Par exemple, si nous voulons obtenir la date de naissance au format 'dd/mm/yyyy', nous pouvons faire:

date_of_birth = json_data.date_of_birth.strftime('%m/%d/%Y')
print(date_of_birth)

Cela affichera:

03/16/1977

You can represent this JSON using a Dataclasses in python.

Dataclasses are a standard part of python 3.7. Ellas permiten representar un dato en término de sus atributos.

In this caso, tu representación podría ser un dataclass de una persona con atributos 'first_name' (nombre), 'last_name' (apellido), 'date_of_birth' (fecha de nacimiento), y una lista de orders.

Además, necesitas agregar las importaciones necesarias en la parte superior de tu programa python:

from datetime import datetime
from typing import List, Dict

Entonces puedes define tu dataclass y una función para convertir un Dict a una Person (la instancia de la dataclass):

from dataclasses import dataclass
from typing import List


@dataclass
class Order:
    created: datetime
    amount: float


@dataclass
class Person:
    first_name: str
    last_name: str
    date_of_birth: datetime
    orders: List[Order]


def dict_to_Person(d: Dict) -> Person:
    return Person(first_name=d["first_name"], last_name=d["last_name"], date_of_birth=datetime.strptime(d["date_of_birth"], "%m/%d/%Y"), orders=[Order(created=datetime.strptime(o["created"], "%Y-%m-%dT%H:%M:%S"), amount=o["amount"]) for o in d["orders"]])

Y a continuación, un ejemplo de cómo convertir un Dict a la Person:

def example():
    d = {
        "first_name": "Jane",
        "last_name": "Smith",
        "date_of_birth": "03/16/1977",
        "orders": [
            {
                "created": "2024-01-25T15:00:04",
                "amount": "100.00"
            }
        ]
    }

p = dict_to_Person(d)
print(p)  # Prints: Person(first_name='Jane', last_name='Smith', date_of_birth=datetime.datetime(1977, 3, 16, 0, 0), orders=[Order(created=datetime.datetime(2024, 1, 25, 15, 0, 4), amount=100.0)])