Handling JSON Serialization implementing Nested Custom Classes in FastAPI
I need help solving I'm refactoring my project and I'm collaborating on a project where I'm updating my dependencies and I'm stuck on something that should probably be simple..... I'm stuck on something that should probably be simple. I'm working on a FastAPI application where I need to return a JSON response containing nested custom class instances. I've defined a couple of classes and a Pydantic model for serialization, but I keep running into a `TypeError: Object of type MyClass is not JSON serializable` behavior when I try to return the response. Here's a simplified version of my code: ```python from fastapi import FastAPI from pydantic import BaseModel app = FastAPI() class MyClass: def __init__(self, name: str, value: int): self.name = name self.value = value class MyResponse(BaseModel): name: str value: int class Config: orm_mode = True @app.get("/items/{item_id}", response_model=MyResponse) async def read_item(item_id: int): item = MyClass(name="Sample Item", value=item_id) # MyClass instance return item # This line throws the TypeError ``` I tried using `jsonable_encoder` from FastAPI to convert the response before returning it, but it doesn't seem to help. Here's how I tried implementing it: ```python from fastapi.encoders import jsonable_encoder @app.get("/items/{item_id}", response_model=MyResponse) async def read_item(item_id: int): item = MyClass(name="Sample Item", value=item_id) return jsonable_encoder(item) ``` However, I'm still working with issues because `jsonable_encoder` is not properly serializing my custom class. My goal is to convert `MyClass` into a structure compatible with the Pydantic model. Should I implement a custom method for this, or is there a more elegant solution? Any insights would be greatly appreciated! For context: I'm using Python on Ubuntu. My development environment is macOS. Thanks in advance! I'd really appreciate any guidance on this. For context: I'm using Python on Ubuntu. Is this even possible? I'd love to hear your thoughts on this. Any ideas what could be causing this?