# FastAPI Response Model via Pydantic

* There are times where you don't want all the data sent back to the user
* This is where you would want to define how the response looks like
* In the <mark style="color:green;">`schemas.py`</mark> we will define the Pydantic model for the response

```python
from pydantic import BaseModel

# Note: This file is used to define Pydantic models
# Used for POST and RESPONSE in FastAPI

# The below code handles the user sending data to us
class PostBase(BaseModel):
    title: str
    content: str
    published: bool = True

class PostCreate(PostBase):
    pass

# The below code handles us sending data back to the user
class PostResponse(BaseModel):
    title: str
    content: str
    published: bool
```

* This will return only the fields specified in the <mark style="color:orange;">`PostResponse`</mark> class
* We will also have to define the <mark style="color:blue;">`response_model`</mark> in the app decorator

```python
@app.post("/posts", status_code=status.HTTP_201_CREATED, response_model=schemas.PostResponse)
def create_posts(post: schemas.PostCreate, db: Session = Depends(get_db)):

    new_post = models.Post(**post.dict())
    db.add(new_post)
    db.commit()
    db.refresh(new_post)

    return new_post
```

* This will still not work fully as our Pydantic model only knows how to work with dictionary's&#x20;
* The issue here is that when we make the query, <mark style="color:blue;">`new_post`</mark> is a SQLAlchemy model
* Pydantic has no idea what to do with that, so the SQLAlchemy model has to be converted to a Pydantic model
* More information about this: [Click here!](https://fastapi.tiangolo.com/tutorial/sql-databases/?h=)
* To do that we will have to pass the following code

```python
class Config:
        orm_mode = True
```

* This will tell Pydantic to convert it, even if it's not a valid dict
* So the new class in <mark style="color:green;">`schemas.py`</mark> should look like this

```python
class PostResponse(BaseModel):
    title: str
    content: str
    published: bool

    class Config:
        orm_mode = True
```

* Now this should work and return our correct response

![](/files/gvwiW7BkxfeDttc2dzkx)

* When retrieving a list, just passing in the normal decorator parameter <mark style="color:purple;">`schemas.PostResponse`</mark> will not work
* We need to convert this to a List with from the typing library
* How it should look: <mark style="color:purple;">`List[schemas.PostResponse]`</mark>

```python
@app.get("/posts", response_model=List[schemas.PostResponse])
def get_posts(db: Session = Depends(get_db)):

    posts = db.query(models.Post).all()

    return posts
```


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.arkannis.net/programming/python/frameworks/fastapi/fastapi-response-model-via-pydantic.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.