we now have a `dict` with the data in the variable `user_dict` (it's a `dict` instead of a Pydantic model object).
And if we call:
```Python
print(user_dict)
```
we would get a Python `dict` with:
```Python
{
'username': 'john',
'password': 'secret',
'email': 'john.doe@example.com',
'full_name': None,
}
```
#### Unwrapping a `dict`
If we take a `dict` like `user_dict` and pass it to a function (or class) with `**user_dict`, Python will "unwrap" it. It will pass the keys and values of the `user_dict` directly as key-value arguments.
So, continuing with the `user_dict` from above, writing:
```Python
UserInDB(**user_dict)
```
Would result in something equivalent to:
```Python
UserInDB(
username="john",
password="secret",
email="john.doe@example.com",
full_name=None,
)
```
Or more exactly, using `user_dict` directly, with whatever contents it might have in the future:
```Python
```Python
UserInDB(
UserInDB(
@ -34,7 +90,28 @@ UserInDB(
)
)
```
```
And then adding the extra `hashed_password=hashed_password`, like in:
#### A Pydantic model from the contents of another
As in the example above we got `user_dict` from `user_in.dict()`, this code:
```Python
user_dict = user_in.dict()
UserInDB(**user_dict)
```
would be equivalent to:
```Python
UserInDB(**user_in.dict())
```
...because `user_in.dict()` is a `dict`, and then we make Python "unwrap" it by passing it to `UserInDB` prepended with `**`.
So, we get a Pydantic model from the data in another Pydantic model.
#### Unrapping a `dict` and extra keywords
And then adding the extra keyword argument `hashed_password=hashed_password`, like in:
@ -65,7 +142,7 @@ And these models are all sharing a lot of the data and duplicating attribute nam
We could do better.
We could do better.
We can declare a `Userbase` model that serves as a base for our other models. And then we can make subclasses of that model that inherit its attributes (type declarations, validation, etc).
We can declare a `UserBase` model that serves as a base for our other models. And then we can make subclasses of that model that inherit its attributes (type declarations, validation, etc).
All the data conversion, validation, documentation, etc. will still work as normally.
All the data conversion, validation, documentation, etc. will still work as normally.
@ -77,4 +154,6 @@ That way, we can declare just the differences between the models (with plaintext
## Recap
## Recap
Use multiple Pydantic models and inherit freely for each case. You don't need to have a single data model per entity if that entity must be able to have different "states". As the case with the user "entity" with a state including `password`, `password_hash` and no password.
Use multiple Pydantic models and inherit freely for each case.
You don't need to have a single data model per entity if that entity must be able to have different "states". As the case with the user "entity" with a state including `password`, `password_hash` and no password.
For a more complete explanation of `**user_dict` check back in <ahref="/tutorial/extra-models/#about-user_indict"target="_blank">the documentation for **Extra Models**</a>.
## Return the token
## Return the token
The response of the `token` endpoint must be a JSON object.
The response of the `token` endpoint must be a JSON object.