Here are some examples of when that could make sense:

#### A Simple App

You could want a process manager in the container if your application is **simple enough** that can run it on a **single server**, not a cluster.

#### Docker Compose

```

////

/// info

`Body` also has all the same extra validation and metadata parameters as `Query`,`Path` and others you will see later.

///

## Embed a single body parameter

Let's say you only have a single `item` body parameter from a Pydantic model `Item`.

By default, **FastAPI** will then expect its body directly.

# Bigger Applications - Multiple Files

If you are building an application or a web API, it's rarely the case that you can put everything in a single file.

**FastAPI** provides a convenience tool to structure your application while keeping all the flexibility.

/// info

If you come from Flask, this would be the equivalent of Flask's Blueprints.

///

## An example file structure

Let's say you have a file structure like this:

```

But in most cases, you will want to perform these steps only **once**.

So, you will want to have a **single process** to perform those **previous steps**, before starting the application.

```
Client #1596980209979 left the chat
```

/// tip

The app above is a minimal and simple example to demonstrate how to handle and broadcast messages to several WebSocket connections.

But keep in mind that, as everything is handled in memory, in a single list, it will only work while the process is running, and will only work with a single process.

operations*

Later, when reading about how to structure bigger applications ([Bigger Applications - Multiple Files](../../tutorial/bigger-applications.md){.internal-link target=_blank}), possibly with multiple files, you will learn how to declare a single `dependencies` parameter for a group of *path operations*....

arbitrary customizations.

- Avoid exposing a single subkey of a multi-value field if it would be more flexible to expose the entire field as arbitrary YAML. If the change truly is generally purpose, it is generally preferred to have broader APIs. For example, instead of providing direct access to each of the complex fields in [affinity](https://kubernetes.io/docs/concepts/scheduling-eviction/assign-pod-node/), just providing a single `affinity` field that is passed through as-is to the Kubernetes...

* Keep commits discrete. Avoid including multiple unrelated changes in a single commit.
* Keep commits self-contained. Avoid spreading a single change across multiple commits. A single commit should make sense in isolation.

### Testing changes

After making changes, you can test your code in 2 ways:

1. Run tests.

    ```bash
    bazel test ${flags} //tensorflow/python/...
    ```

    For a single component e.g. softmax op:

    ```bash
    bazel test ${flags} tensorflow/python/kernel_tests/nn_ops:softmax_op_test
    ```

    For a single/parameterized test e.g. `test_capture_variables` in
    `tensorflow/python/saved_model/load_test.py`:

    (Requires `python>=3.7`)

        val applicationStructureChoice = if (descriptor.language === Language.CPP || descriptor.language === Language.SWIFT) "" else """
Select application structure:
  1: Single application project
  2: Application and library project
Enter selection (default: Single application project) [1..2] 1
"""
        val toolChain = when {
            descriptor.language === Language.SWIFT -> {