## Dataclasses in Nested Data Structures

You can also combine `dataclasses` with other type annotations to make nested data structures.

In some cases, you might still have to use Pydantic's version of `dataclasses`. For example, if you have errors with the automatically generated API documentation.

In that case, you can simply swap the standard `dataclasses` with `pydantic.dataclasses`, which is a drop-in replacement:

			// If the object you request does not exist,
			// the error Amazon S3 returns depends on
			// whether you also have the s3:ListBucket
			// permission.
			// * If you have the s3:ListBucket permission
			//   on the bucket, Amazon S3 will return an
			//   HTTP status code 404 ("no such key")
			//   error.
			// * if you don’t have the s3:ListBucket
			//   permission, Amazon S3 will return an HTTP

        }

        // After the collection we will have the artifact object in the result but they will not be resolved yet.
        result = artifactCollector.collect(
                artifacts, rootArtifact, managedVersions, collectionRequest, source, collectionFilter, listeners, null);

        // We have metadata retrieval problems, or there are cycles that have been detected

!!! tip
    A file starting with a dot (`.`) is a hidden file in Unix-like systems, like Linux and macOS.

    But a dotenv file doesn't really have to have that exact filename.

        assertNotNull(res.getClasspath(), "null classpath after compile transform");
        assertEquals(3, res.getClasspath().size(), "compile classpath should have 3 entries");
    }

    // ------------------------------------------------------------------------------------------
    @Test
    void testRuntimeClasspathTransform() throws Exception {
        ClasspathContainer res;

then fixing the bug will break that code.
New features can also have similar impacts:
enabling the HTTP/2 use by the HTTP client broke programs
connecting to servers with buggy HTTP/2 implementations.
These kinds of changes are unavoidable and
[permitted by the Go 1 compatibility rules](/doc/go1compat).
Even so, Go provides a mechanism called GODEBUG to
reduce the impact such changes have on Go developers
using newer toolchains to compile old code.

## Another module with `APIRouter`

Let's say you also have the endpoints dedicated to handling "items" from your application in the module at `app/routers/items.py`.

You have *path operations* for:

* `/items/`
* `/items/{item_id}`

It's all the same structure as with `app/routers/users.py`.

And then, that system (in this case **FastAPI**) will take care of doing whatever is needed to provide your code with those needed dependencies ("inject" the dependencies).

This is very useful when you need to:

* Have shared logic (the same code logic again and again).
* Share database connections.
* Enforce security, authentication, role requirements, etc.
* And many other things...

All these, while minimizing code repetition.

		issFromToken, _ = v.(string)
	}

	// Since issFromToken can have `/` characters (it is typically the
	// provider URL), we hash and encode it to base64 here. This is needed
	// because there will be a policy mapping stored on drives whose
	// filename is this parentUser: therefore, it needs to have only valid
	// filename characters and needs to have bounded length.
	{
		h := sha256.New()

* **Replication (the number of processes running)**
* Memory
* Previous steps before starting

Up to this point, with all the tutorials in the docs, you have probably been running a **server program** like Uvicorn, running a **single process**.

When deploying applications you will probably want to have some **replication of processes** to take advantage of **multiple cores** and to be able to handle more requests.