///

## Run your code with your debugger { #run-your-code-with-your-debugger }

Because you are running the Uvicorn server directly from your code, you can call your Python program (your FastAPI application) directly from the debugger.

---

For example, in Visual Studio Code, you can:

* Go to the "Debug" panel.
* "Add configuration...".
* Select "Python"

ideally referring to a person with the responsibility to complete the note.

If your CL addresses an accepted proposal, mention the proposal issue number in
your release note in the form `/issue/NUMBER`. A link to the issue in the text
will have this form (see below). If you don't want to mention the issue in the
text, add it as a comment:
```
<!-- go.dev/issue/12345 -->
```

You could **call** that same function in **other places** without FastAPI, and it would **work as expected**. If there's a **required** parameter (without a default value), your **editor** will let you know with an error, **Python** will also complain if you run it without passing the required parameter.

This way you can add correct type annotations to your functions even when you are returning a type different than the response model, to be used by the editor and tools like mypy. And still you can have FastAPI do the data validation, documentation, etc. using the `response_model`.

Now, let's see the module at `app/main.py`.

Here's where you import and use the class `FastAPI`.

This will be the main file in your application that ties everything together.

And as most of your logic will now live in its own specific module, the main file will be quite simple.

### Import `FastAPI` { #import-fastapi }

You import and create a `FastAPI` class as normally.

The same way you use `Body`, `Query`, etc. with your *path operation function* parameters, use `Depends` with a new parameter:

{* ../../docs_src/dependencies/tutorial001_an_py310.py hl[13,18] *}

Although you use `Depends` in the parameters of your function the same way you use `Body`, `Query`, etc, `Depends` works a bit differently.

You only give `Depends` a single parameter.

In most cases, when you create a web API, you want it to be **always running**, uninterrupted, so that your clients can always access it. This is of course, unless you have a specific reason why you want it to run only in certain situations, but most of the time you want it constantly running and **available**.

### In a Remote Server { #in-a-remote-server }

    # - - - - - - - - - -/

    # /- - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    # o extendedDBFluteInitializerClass: (NotRequired - Default null)
    #  If you want to extend the embedded DBFlute initializer,
    #  specify the class name of your original initializer
    #  that extends the embedded one.
    #  *Basically for fixed DBFluteConfig settings
    #

# Request Body { #request-body }

When you need to send data from a client (let's say, a browser) to your API, you send it as a **request body**.

A **request** body is data sent by the client to your API. A **response** body is the data your API sends to the client.

#### Running sanity check

If you have Docker installed on your system, you can perform a sanity check on
your changes by running the command:

```bash
tensorflow/tools/ci_build/ci_build.sh CPU tensorflow/tools/ci_build/ci_sanity.sh
```

This will catch most license, Python coding style and BUILD file issues that
may exist in your changes.

#### Running unit tests