functionality. Syntax is `mc support inspect ALIAS/path/to/files`. This can for example be used to collect `xl.meta` from objects that are misbehaving. To collect `xl.meta` from a specific object, for example placed at `ALIAS/bucket/path/to/file.txt` append `/xl.meta`, for instance `mc support inspect ALIAS/bucket/path/to/file.txt/xl.meta`. All files can be collected, so this can also be used to retrieve `part.*` files, etc.

Wildcards can be used, for example `mc support inspect ALIAS/bucket/path/**/xl.meta`...

# Response Headers

## Use a `Response` parameter

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

And then you can set headers in that *temporal* response object.

```Python hl_lines="1  7-8"
{!../../docs_src/response_headers/tutorial002.py!}
```

And then you can return any object you need, as you normally would (a `dict`, a database model, etc).

   * occur when using {@link CacheBuilder#weakKeys}, {@link CacheBuilder#weakValues}, or {@link
   * CacheBuilder#softValues}.
   */
  COLLECTED {
    @Override
    boolean wasEvicted() {
      return true;
    }
  },

  /**
   * The entry's expiration timestamp has passed. This can occur when using {@link

Therefore, if you run a `tf.train.Server` in your network, anybody with access
to the network can execute arbitrary code with the privileges of the user
running the `tf.train.Server`.

## Untrusted inputs during training and prediction

TensorFlow supports a wide range of input data formats. For example it can
process images, audio, videos, and text. There are several modules specialized

### Read Heroes

We can **read** `Hero`s from the database using a `select()`. We can include a `limit` and `offset` to paginate the results.

{* ../../docs_src/sql_databases/tutorial001_an_py310.py ln[48:55] hl[51:52,54] *}

### Read One Hero

We can **read** a single `Hero`.

{* ../../docs_src/sql_databases/tutorial001_an_py310.py ln[58:63] hl[60] *}

### Delete a Hero

We can also **delete** a `Hero`.

# 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.

As all these methods are `async` methods, you need to "await" them.

For example, inside of an `async` *path operation function* you can get the contents with:

```Python
contents = await myfile.read()
```

If you are inside of a normal `def` *path operation function*, you can access the `UploadFile.file` directly, for example:

```Python
contents = myfile.file.read()
```

You can override any of them by setting a different value in the argument `swagger_ui_parameters`.

For example, to disable `deepLinking` you could pass these settings to `swagger_ui_parameters`:

{* ../../docs_src/configure_swagger_ui/tutorial003.py hl[3] *}

## Other Swagger UI Parameters

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. 😊

## Overview

MinIO supports two storage classes, Reduced Redundancy class and Standard class. These classes can be defined using environment variables
set before starting MinIO server. After the data and parity drives for each storage class are defined using environment variables,
you can set the storage class of an object via request metadata field `x-amz-storage-class`. MinIO server then honors the storage class by