So, a Python class is also a **callable**.

Then, in **FastAPI**, you could use a Python class as a dependency.

What FastAPI actually checks is that it is a "callable" (function, class or anything else) and the parameters defined.

If you pass a "callable" as a dependency in **FastAPI**, it will analyze the parameters for that "callable", and process them in the same way as the parameters for a *path operation function*. Including sub-dependencies.

In this case, you would accept any `dict` as long as it has `int` keys with `float` values:

{* ../../docs_src/body_nested_models/tutorial009_py39.py hl[7] *}

/// tip

Keep in mind that JSON only supports `str` as keys.

But Pydantic has automatic data conversion.

        while (authElements.hasMoreElements()) {
            ASN1Sequence authElement = ASN1Util.as(ASN1Sequence.class, authElements);
            ASN1Integer authType = ASN1Util.as(ASN1Integer.class, ASN1Util.as(ASN1TaggedObject.class, authElement, 0));
            DEROctetString authData = ASN1Util.as(DEROctetString.class, ASN1Util.as(ASN1TaggedObject.class, authElement, 1));

* Todas elas incluirão as `responses` predefinidas.
* Todas essas *operações de rota* terão a lista de `dependencies` avaliada/executada antes delas.
    * Se você também declarar dependências em uma *operação de rota* específica, **elas também serão executadas**.

incoming object uploads and metadata changes to source object version. If active-active replication is configured, any incoming uploads and metadata changes to versions created on the target, will sync back to the source and be marked as `REPLICA` on the source. AWS, as well as MinIO do not by default sync metadata changes on a object version marked `REPLICA` back to source. This requires a setting in the replication configuration called [replica modification sync](https://aws.amazon.com/about-aws/what...

The same as we were doing before in the *path operation* directly, our new dependency `get_current_user` will receive a `token` as a `str` from the sub-dependency `oauth2_scheme`:

{* ../../docs_src/security/tutorial002_an_py310.py hl[25] *}

## Get the user { #get-the-user }

`get_current_user` will use a (fake) utility function we created, that takes a token as a `str` and returns our Pydantic `User` model:

blob/master/docs/erasure/README.md#what-is-bit-rot-protection) using [erasure code](https://docs.min.io/community/minio-object-store/operations/concepts/erasure-coding.html). As the minimum drives required for distributed MinIO is 2 (same as minimum drives required for erasure coding), erasure code automatically kicks in as you launch distributed MinIO.

If one or more drives are offline at the start of a PutObject or NewMultipartUpload operation the object will have additional data protection...

**Requests** is a library to *interact* with APIs (as a client), while **FastAPI** is a library to *build* APIs (as a server).

They are, more or less, at opposite ends, complementing each other.

Requests has a very simple and intuitive design, it's very easy to use, with sensible defaults. But at the same time, it's very powerful and customizable.

That's why, as said in the official website:

For this, we use `security_scopes.scopes`, that contains a `list` with all these scopes as `str`.

{* ../../docs_src/security/tutorial005_an_py310.py hl[130:136] *}

## Dependency tree and scopes { #dependency-tree-and-scopes }

Let's review again this dependency tree and the scopes.

/// warning

Notice that `Field` is imported directly from `pydantic`, not from `fastapi` as are all the rest (`Query`, `Path`, `Body`, etc).

///

## Declare model attributes { #declare-model-attributes }

You can then use `Field` with model attributes:

{* ../../docs_src/body_fields/tutorial001_an_py310.py hl[11:14] *}

`Field` works the same way as `Query`, `Path` and `Body`, it has all the same parameters, etc.