You can help with everything on [Help FastAPI - Get Help](./help-fastapi.md){.internal-link target=_blank} the same ways as external contributors. But additionally, there are some tasks that only you (as part of the team) can perform.

Here are the general instructions for the tasks you can perform.

Thanks a lot for your help. 🙇

## Be Nice

First of all, be nice. 😊

# `Request` class

You can declare a parameter in a *path operation function* or dependency to be of type `Request` and then you can access the raw request object directly, without any validation, etc.

You can import it directly from `fastapi`:

```python
from fastapi import Request
```

/// tip

# Middleware { #middleware }

You can add middleware to **FastAPI** applications.

A "middleware" is a function that works with every **request** before it is processed by any specific *path operation*. And also with every **response** before returning it.

* It takes each **request** that comes to your application.
* It can then do something to that **request** or run any needed code.

But you can return a `JSONResponse` directly from your *path operations*.

It might be useful, for example, to return custom headers or cookies.

## Return a `Response` { #return-a-response }

In fact, you can return any `Response` or any sub-class of it.

/// tip

`JSONResponse` itself is a sub-class of `Response`.

///

# Body - Fields { #body-fields }

The same way you can declare additional validation and metadata in *path operation function* parameters with `Query`, `Path` and `Body`, you can declare validation and metadata inside of Pydantic models using Pydantic's `Field`.

## Import `Field` { #import-field }

First, you have to import it:

{* ../../docs_src/body_fields/tutorial001_an_py310.py hl[4] *}


/// warning

///

## Learn More { #learn-more }

You can learn more about **GraphQL** in the <a href="https://graphql.org/" class="external-link" target="_blank">official GraphQL documentation</a>.

You can use the same type declarations with `str`, `float`, `bool` and many other complex data types.

Several of these are explored in the next chapters of the tutorial.

## Order matters { #order-matters }

When creating *path operations*, you can find situations where you have a fixed path.

These are the exceptions that you can raise to show errors to the client.

When you raise an exception, as would happen with normal Python, the rest of the execution is aborted. This way you can raise these exceptions from anywhere in the code to abort a request and show the error to the client.

You can use:

* `HTTPException`
* `WebSocketException`

These exceptions can be imported directly from `fastapi`:

```python

  scheme: http
  static_configs:
  - targets: ['localhost:9000']
```

##### Node (optional)

Optionally you can also collect per node metrics. This needs to be done on a per server instance.
The scrape configurations should use all the servers under `targets` so that graphing systems like
grafana can visualize them for all the nodes

```yaml
scrape_configs:
- job_name: minio-job
  metrics_path: /minio/v2/metrics/node

```

The command deploys MinIO on the Kubernetes cluster in the default configuration. The [configuration](#configuration) section lists the parameters that can be configured during installation.

### Installing the Chart (toy-setup)

Minimal toy setup for testing purposes can be deployed using:

```bash