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You can use the marshmallow library to convert your JSON to dataclasses by following these steps:

1. Install the required libraries:

pip install dataclasses marshmallow core

Note: If you are using Python 3.6+ you don't need to install dataclasses, as it is built-in. For Python 3.5, you will need to install dataclasses separately.

1. Create the dataclasses for your input data:

from dataclasses import dataclass, field
from typing import List, Dict

import datetime
from dateutil.parser import parse
from decimal import Decimal

@dataclass
class Person:
    first_name: str
    last_name: str
    date_of_birth: datetime.date

@dataclass
class Order:
    created: datetime.datetime
    amount: Decimal

@dataclass
class Main:
    person: Person
    orders: List[Order]

1. Create a marshmallow schema that matches your dataclasses:

from datetime import datetime
from marshmallow import Schema, fields, post_load, pre_dump, EXCLUDE
from decimal import Decimal

class PersonSchema(Schema):
    first_name = fields.Str()
    last_name = fields.Str()
    date_of_birth = fields.Date(format='%m/%d/%Y')

    @post_load
    def make_person(self, data, **kwargs):
        return Person(**data)


class OrderSchema(Schema):
    created = fields.DateTime()
    amount = fields.Decimal()

    @post_load
    def make_order(self, data, **kwargs):
        return Order(**data)


class MainSchema(Schema):
    person = PersonSchema()
    orders = fields.Nested(OrderSchema, many=True, unknown=EXCLUDE)

    @post_dump
    def remove_none(self, data, **kwargs):
        return {k: v for (k, v) in data.items() if v is not None}

    @pre_dump
    def make_main(self, person, orders, **kwargs):
        return {"person": person, "orders": orders}

    @post_load
    def make_main(self, data, **kwargs):
        return Main(**data)

1. Convert JSON to Python object using your schema:

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

result_data = MainSchema().load(json_data)
print(result_data)
# Output: Main(person=Person(first_name='Jane', last_name='Smith', date_of_birth=datetime.date(1977, 3, 16)), orders=[Order(created=datetime.datetime(2024, 1, 25, 15, 0, 4), amount=Decimal('100.00'))])

This will create a Main dataclass with an instance of Person and a list of Order instances as attributes, reflecting the original JSON input.

You can achieve this by defining your dataclasses using dataclasses.dataclass decorator, dataclasses_json. Let's start by installing it using pip:

pip install dataclasses-json

After the installation, here is how you can define your classes using the dataclasses and dataclasses_json Python libraries:

import dataclasses
from dataclasses_json import dataclass_json
from datetime import datetime
from decimal import Decimal

@dataclass_json
@dataclasses.dataclass
class Order:
    created: datetime
    amount: Decimal

@dataclass_json
@dataclasses.dataclass
class Person:
    first_name: str
    last_name: str
    date_of_birth: datetime.date
    orders: [Order]

In this code, the Order dataclass has created field which is a datetime object and amount field which is a Decimal. Similarly, the Person class has a date_of_birth field which is a datetime.date object and orders field which is a list of Order instances.

The dataclass_json decorator automatically infers the JSON schema from the dataclass and takes care of (de)serialization.

The JSON data can now be converted to/from these dataclasses using the methods provided by dataclasses_json.

To generate the dataclasses from the given JSON using the marshmallow library in Python, you will first need to install the marshmallow library if you haven't already. You can install it using pip:

pip install marshmallow

Now, you can create the dataclasses for the given JSON and use marshmallow to serialize and deserialize the data. Here's a Python script that demonstrates how to do this:

import dataclasses
from typing import List
import datetime
from decimal import Decimal
from marshmallow import Schema, fields

# Define the data classes
@dataclasses.dataclass
class Person:
    first_name: str
    last_name: str
    date_of_birth: datetime.date

@dataclasses.dataclass
class Order:
    created: datetime.datetime
    amount: Decimal

@dataclasses.dataclass
class Customer:
    person: Person
    orders: List[Order]

# Define marshmallow Schemas
class PersonSchema(Schema):
    first_name = fields.Str()
    last_name = fields.Str()
    date_of_birth = fields.Date(format='%m/%d/%Y')

class OrderSchema(Schema):
    created = fields.DateTime()
    amount = fields.Decimal()

class CustomerSchema(Schema):
    person = fields.Nested(PersonSchema(many=False))
    orders = fields.List(fields.Nested(OrderSchema))

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

# Deserialize the JSON data into a Customer object
loaded_data = CustomerSchema().loads(input_json)

# Print the deserialized data
print(f"Name: {loaded_data['person']['first_name']} {loaded_data['person']['last_name']}")
print(f"Birth Date: {loaded_data['person']['date_of_birth']}")
for order in loaded_data['orders']:
    print(f"Order Created: {order['created']}")
    print(f"Order Amount: {order['amount']}")

This script defines the dataclasses and marshmallow schemas for the given JSON, and then deserializes the JSON data into a Customer object. The deserialized data is then printed to the console.