///

We can also use this same approach to access the request body in an exception handler.

All we need to do is handle the request inside a `try`/`except` block:

{* ../../docs_src/custom_request_and_route/tutorial002.py hl[13,15] *}

If an exception occurs, the`Request` instance will still be in scope, so we can read and make use of the request body when handling the error:

## Testing locally with Traefik { #testing-locally-with-traefik }

You can easily run the experiment locally with a stripped path prefix using <a href="https://docs.traefik.io/" class="external-link" target="_blank">Traefik</a>.

<a href="https://github.com/containous/traefik/releases" class="external-link" target="_blank">Download Traefik</a>, it's a single binary, you can extract the compressed file and run it directly from the terminal.

		expectedQuery string
	}{
		{"", ""},
		{
			"?Action=AssumeRoleWithLDAPIdentity&LDAPUsername=myusername&LDAPPassword=can+youreadthis%3F&Version=2011-06-15",
			"?Action=AssumeRoleWithLDAPIdentity&LDAPUsername=myusername&LDAPPassword=*REDACTED*&Version=2011-06-15",
		},
		{
			"LDAPPassword=can+youreadthis%3F&Version=2011-06-15&?Action=AssumeRoleWithLDAPIdentity&LDAPUsername=myusername",

                Arguments.of(WinError.ERROR_ACCESS_DENIED, "Access is denied."),
                Arguments.of(WinError.ERROR_REQ_NOT_ACCEP,
                        "No more connections can be made to this remote computer at this time because there are already as many connections as the computer can accept."),
                Arguments.of(WinError.ERROR_BAD_PIPE, "The pipe state is invalid."),
                Arguments.of(WinError.ERROR_PIPE_BUSY, "All pipe instances are busy."),

   
   Apparently, your CPU model does not support AVX instruction sets. You can still use TensorFlow with the alternatives given below:
   
      * Try Google Colab to use TensorFlow.
         * The easiest way to use TF will be to switch to [google colab](https://colab.sandbox.google.com/notebooks/welcome.ipynb#recent=true). You get pre-installed latest stable TF version. Also you can use ```pip install```  to install any other preferred TF version.

# Background Tasks - `BackgroundTasks`

You can declare a parameter in a *path operation function* or dependency function with the type `BackgroundTasks`, and then you can use it to schedule the execution of background tasks after the response is sent.

You can import it directly from `fastapi`:

```python
from fastapi import BackgroundTasks
```

 *       block or a {@link ListenableFuture}.
 *   <li>Each other step is derived from one or more input steps. At each step, zero or more objects
 *       can be captured for later closing.
 *   <li>There is one last step (the root of the tree), from which you can extract the final result
 *       of the computation. After that result is available (or the computation fails), all objects

1. The id_token is an identifier that is hard to guess. For example, a randomly generated string of sufficient length, that the server handling the protected resource can use to lookup the associated authorization information.
2. The id_token self-contains the authorization information in a manner that can be verified. For example, by encoding authorization information along with a signature into the token.

```JSON
{
  "detail": "Item not found"
}
```

/// tip

When raising an `HTTPException`, you can pass any value that can be converted to JSON as the parameter `detail`, not only `str`.

You could pass a `dict`, a `list`, etc.

They are handled automatically by **FastAPI** and converted to JSON.

///

For example, in one of the ways the OAuth2 specification can be used (called "password flow") it is required to send a `username` and `password` as form fields.

The <abbr title="specification">spec</abbr> requires the fields to be exactly named `username` and `password`, and to be sent as form fields, not JSON.