Pydantic: How to Know Which Class Was Serialized to JSON

Pydantic is a powerful tool for working with data in Python, but have you ever found yourself wondering which class was serialized to JSON? In this article, we’ll dive into the world of Pydantic and explore the different ways to determine which class was serialized to JSON.

What is Pydantic?

Before we dive into the meat of the article, let’s take a quick look at what Pydantic is. Pydantic is a Python library that allows you to define robust, typed, and flexible data models. It’s often used for building APIs, data validation, and data serialization. Pydantic models are defined using Python classes, and they can be used to validate and serialize data to and from various formats, including JSON.

The Problem: Which Class Was Serialized to JSON?

When working with Pydantic, you might find yourself in a situation where you need to know which class was serialized to JSON. This can be useful for a variety of reasons, such as:

• Debugging: You want to know which class was serialized to JSON to debug an issue.
• Data processing: You need to perform different processing steps based on the class that was serialized.
• Data validation: You want to validate the data against the original class schema.

Method 1: Using the __class__ Attribute

One way to determine which class was serialized to JSON is to use the `__class__` attribute. This attribute is available on every Python object and returns the class of the object.

>> from pydantic import BaseModel
>>> class User(BaseModel):
...     name: str
...     age: int
...
>>> user = User(name='John', age=30)
>>> user_json = user.json(exclude_none=True)
>>> print(user_json)
'{"name": "John", "age": 30}'
>>> original_class = user.__class__
>>> print(original_class)
<class '__main__.User'>

In this example, we define a `User` class using Pydantic’s `BaseModel`. We create an instance of the `User` class and serialize it to JSON using the `json` method. Finally, we use the `__class__` attribute to get the original class of the object.

Method 2: Using the __typename__ Attribute

Another way to determine which class was serialized to JSON is to use the `__typename__` attribute. This attribute is available on Pydantic models and returns the name of the model.

>> from pydantic import BaseModel
>>> class User(BaseModel):
...     name: str
...     age: int
...     __typename__: str = 'User'
...
>>> user = User(name='John', age=30)
>>> user_json = user.json(exclude_none=True)
>>> print(user_json)
'{"name": "John", "age": 30, "__typename__": "User"}'
>>> original_class_name = user_json['__typename__']
>>> print(original_class_name)
'User'

In this example, we define a `User` class using Pydantic’s `BaseModel`. We add a `__typename__` attribute to the class to specify its name. When we serialize the object to JSON, the `__typename__` attribute is included in the output. We can then extract the original class name from the JSON output.

Method 3: Using a Custom Encoder

A more advanced approach to determining which class was serialized to JSON is to use a custom encoder. Pydantic provides a `jsonable_encoder` function that can be used to customize the JSON serialization process.

>> from pydantic import BaseModel
>>> from pydantic.json import jsonable_encoder
>>>
>>> class User(BaseModel):
...     name: str
...     age: int
...
>>> class CustomEncoder(jsonable_encoder):
...     def default(self, obj):
...         if isinstance(obj, BaseModel):
...             return {'__class__': obj.__class__.__name__, **obj.dict()}
...         return super().default(obj)
...
>>> user = User(name='John', age=30)
>>> user_json = CustomEncoder().encode(user)
>>> print(user_json)
'{"__class__": "User", "name": "John", "age": 30}'
>>> original_class_name = user_json['__class__']
>>> print(original_class_name)
'User'

In this example, we define a custom encoder class `CustomEncoder` that inherits from Pydantic’s `jsonable_encoder`. We override the `default` method to include the class name in the JSON output. When we encode the `User` object using the custom encoder, the resulting JSON includes the class name.

Method 4: Using a Custom Model with a Type Field

Another approach to determining which class was serialized to JSON is to use a custom model with a type field. This involves defining a base model with a type field and then inheriting from it to create specific models.

>> from pydantic import BaseModel
>>>
>>> class BaseModelWithType(BaseModel):
...     type: str
...
>>> class User(BaseModelWithType):
...     name: str
...     age: int
...     type: str = 'User'
...
>>> user = User(name='John', age=30)
>>> user_json = user.json(exclude_none=True)
>>> print(user_json)
'{"type": "User", "name": "John", "age": 30}'
>>> original_class_name = user_json['type']
>>> print(original_class_name)
'User'

In this example, we define a base model `BaseModelWithType` with a `type` field. We then define a `User` model that inherits from the base model and sets the `type` field to `’User’`. When we serialize the `User` object to JSON, the resulting output includes the type field.

Conclusion

In this article, we’ve explored four different methods for determining which class was serialized to JSON using Pydantic. Each method has its own advantages and disadvantages, and the choice of method depends on the specific use case.

By using the `__class__` attribute, you can get the original class of the object. The `__typename__` attribute provides a way to include the class name in the JSON output. Custom encoders offer a more advanced way to customize the JSON serialization process, while custom models with a type field provide a flexible way to include the class name in the JSON output.

We hope this article has provided you with a comprehensive guide on how to determine which class was serialized to JSON using Pydantic. Happy coding!

Method	Description
Using the __class__ attribute	Gets the original class of the object
Using the __typename__ attribute	Includes the class name in the JSON output
Using a custom encoder	Customizes the JSON serialization process
Using a custom model with a type field	Includes the class name in the JSON output

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2. Pydantic: Advanced Concepts and Techniques
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