sqlmodel/docs/tutorial/fastapi/update.md

Update Data with FastAPI

Now let's see how to update data in the database with a FastAPI path operation.

HeroUpdate Model

We want clients to be able to udpate the name, the secret_name, and the age of a hero.

But we don't want them to have to include all the data again just to update a single field.

So, we need to have all those fields marked as optional.

And because the HeroBase has some of them as required and not optional, we will need to create a new model.

!!! tip Here is one of those cases where it probably makes sense to use an independent model instead of trying to come up with a complex tree of models inheriting from each other.

Because each field is **actually different** (we just change it to `Optional`, but that's already making it different), it makes sense to have them in their own model.

So, let's create this new HeroUpdate model:

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This is almost the same as HeroBase, but all the fields are optional, so we can't simply inherit from HeroBase.

Create the Update Path Operation

Now let's use this model in the path operation to update a hero.

We will use a PATCH HTTP operation. This is used to partially update data, which is what we are doing.

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We also read the hero_id from the path parameter an the request body, a HeroUpdate.

Read the Existing Hero

We take a hero_id with the ID of the hero we want to update.

So, we need to read the hero from the database, with the same logic we used to read a single hero, checking if it exists, possibly raising an error for the client if it doesn't exist, etc.

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Get the New Data

The HeroUpdate model has all the fields with default values, because they all have defaults, they are all optional, which is what we want.

But that also means that if we just call hero.dict() we will get a dictionary that could potentially have several or all of those values with their defaults, for example:

{
    "name": None,
    "secret_name": None,
    "age": None,
}

And then if we update the hero in the database with this data, we would be removing any existing values, and that's probably not what the client intended.

But fortunately Pydantic models (and so SQLModel models) have a parameter we can pass to the .dict() method for that: exclude_unset=True.

This tells Pydantic to not include the values that were not sent by the client. Saying it another way, it would only include the values that were sent by the client.

So, if the client sent a JSON with no values:

{}

Then the dictionary we would get in Python using hero.dict(exclude_unset=True) would be:

{}

But if the client sent a JSON with:

{
    "name": "Deadpuddle"
}

Then the dictionary we would get in Python using hero.dict(exclude_unset=True) would be:

{
    "name": "Deadpuddle"
}

Then we use that to get the data that was actually sent by the client:

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Update the Hero in the Database

Now that we have a dictionary with the data sent by the client, we can iterate for each one of the keys and the values, and then we set them in the database hero model db_hero using setattr().

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If you are not familiar with that setattr(), it takes an object, like the db_hero, then an attribute name (key), that in our case could be "name", and a value (value). And then it sets the attribute with that name to the value.

So, if key was "name" and value was "Deadpuddle", then this code:

setattr(db_hero, key, value)

...would be more or less equivalent to:

db_hero.name = "Deadpuddle"

Remove Fields

Here's a bonus. 🎁

When getting the dictionary of data sent by the client, we only include what the client actually sent.

This sounds simple, but it has some additional nuances that become nice features. ✨

We are not simply omitting the data that has the default values.

And we are not simply omitting anything that is None.

This means that, if a model in the database has a value different than the default, the client could reset it to the same value as the default, or even None, and we would still notice it and update it accordingly. 🤯🚀

So, if the client wanted to intentionally remove the age of a hero, they could just send a JSON with:

{
    "age": null
}

And when getting the data with hero.dict(exclude_unset=True), we would get:

{
    "age": None
}

So, we would use that value and upate the age to None in the database, just as the client intended.

Notice that age here is None, and we still detected it.

Also that name was not even sent, and we don't accidentaly set it to None or something, we just didn't touch it, because the client didn't sent it, so we are pefectly fine, even in these corner cases. ✨

These are some of the advantages of Pydantic, that we can use with SQLModel. 🎉

Recap

Using .dict(exclude_unset=True) in SQLModel models (and Pydantic models) we can easily update data correctly, even in the edge cases. 😎