This may help you better understand and contribute to Gradle.

### Debugging Gradle

You can debug Gradle by adding `-Dorg.gradle.debug=true` to the command-line. Gradle will wait for you to attach a debugger at `localhost:5005` by default.

If you made changes to build logic in the `build-logic` included build, you can run its tests by executing `./gradlew :build-logic:check`.

But you still want to be able to filter and convert the data you return with a `response_model`.

For those cases, you can use a `Response` parameter.

## Use a `Response` parameter

You can declare a parameter of type `Response` in your *path operation function* (as you can do for cookies and headers).

And then you can set the `status_code` in that *temporal* response object.

```Python hl_lines="1  9  12"

If you want to use your APIs' function names as `operationId`s, you can iterate over all of them and override each *path operation's* `operation_id` using their `APIRoute.name`.

You should do it after adding all your *path operations*.

```Python hl_lines="2  12-21  24"
{!../../../docs_src/path_operation_advanced_configuration/tutorial002.py!}
```

!!! tip

If your application is **simple**, this will probably **not be a problem**, and you might not need to specify hard memory limits. But if you are **using a lot of memory** (for example with **machine learning** models), you should check how much memory you are consuming and adjust the **number of containers** that runs in **each machine** (and maybe add more machines to your cluster).

   4. Redistribution. You may reproduce and distribute copies of the
      Work or Derivative Works thereof in any medium, with or without
      modifications, and in Source or Object form, provided that You
      meet the following conditions:

      (a) You must give any other recipients of the Work or
          Derivative Works a copy of this License; and

      (b) You must cause any modified files to carry prominent notices

Here I'll show you how to use <a href="https://gunicorn.org/" class="external-link" target="_blank">**Gunicorn**</a> with **Uvicorn worker processes**.

!!! info
    If you are using containers, for example with Docker or Kubernetes, I'll tell you more about that in the next chapter: [FastAPI in Containers - Docker](docker.md){.internal-link target=_blank}.

* Give you the received data in the parameter `item`.
    * As you declared it in the function to be of type `Item`, you will also have all the editor support (completion, etc) for all of the attributes and their types.
* Generate <a href="https://json-schema.org" class="external-link" target="_blank">JSON Schema</a> definitions for your model, you can also use them anywhere else you like if it makes sense for your project.

    And many teams use only `PUT`, even for partial updates.

    You are **free** to use them however you want, **FastAPI** doesn't impose any restrictions.

    But this guide shows you, more or less, how they are intended to be used.

### Using Pydantic's `exclude_unset` parameter

If you want to receive partial updates, it's very useful to use the parameter `exclude_unset` in Pydantic's model's `.model_dump()`.

Let's say you have a custom exception `UnicornException` that you (or a library you use) might `raise`.

And you want to handle this exception globally with FastAPI.

You could add a custom exception handler with `@app.exception_handler()`:

```Python hl_lines="5-7  13-18  24"
{!../../../docs_src/handling_errors/tutorial003.py!}
```

object browser built into MinIO Server. Point a web browser running on the host machine to <http://127.0.0.1:9000> and log in with the
root credentials. You can use the Browser to create buckets, upload objects, and browse the contents of the MinIO server.