}

type wrapperConnPool struct {
	db     *sql.DB
	got    []string
	expect []string
}

func (c *wrapperConnPool) Ping() error {
	return c.db.Ping()
}

// If you use BeginTx returned *sql.Tx as shown below then you can't record queries in a transaction.
//
//	func (c *wrapperConnPool) BeginTx(ctx context.Context, opts *sql.TxOptions) (*sql.Tx, error) {
//		 return c.db.BeginTx(ctx, opts)
//	}
//

{* ../../docs_src/additional_responses/tutorial003_py39.py hl[20:31] *}

It will all be combined and included in your OpenAPI, and shown in the API docs:

<img src="/img/tutorial/additional-responses/image01.png">

## Combine predefined responses and custom ones { #combine-predefined-responses-and-custom-ones }

mc: Encrypted file data successfully downloaded as inspect.ad2b43d8.enc
mc: Decryption key: ad2b43d847fdb14e54c5836200177f7158b3f745433525f5d23c0e0208e50c9948540b54

mc: The decryption key will ONLY be shown here. It cannot be recovered.
mc: The encrypted file can safely be shared without the decryption key.
mc: Even with the decryption key, data stored with encryption cannot be accessed.
```

## Automatic docs { #automatic-docs }

The JSON Schemas of your models will be part of your OpenAPI generated schema, and will be shown in the interactive API docs:

<img src="/img/tutorial/body/image01.png">

And will also be used in the API docs inside each *path operation* that needs them:

<img src="/img/tutorial/body/image02.png">

<img src="/img/tutorial/generate-clients/image01.png">

You can see those schemas because they were declared with the models in the app.

That information is available in the app's **OpenAPI schema**, and then shown in the API docs.

That same information from the models that is included in OpenAPI is what can be used to **generate the client code**.

### Hey API { #hey-api }

All these dependencies, while declaring their requirements, also add parameters, validations, etc. to your *path operations*.

Each specific example `dict` in the `examples` can contain:

* `summary`: Short description for the example.
* `description`: A long description that can contain Markdown text.
* `value`: This is the actual example shown, e.g. a `dict`.
* `externalValue`: alternative to `value`, a URL pointing to the example. Although this might not be supported by as many tools as `value`.

You can use it like this:

'(string|function)',\n  sanitize: 'boolean',\n  sanitizeFn: '(null|function)',\n  whiteList: 'object',\n  popperConfig: '(null|object)'\n}\n\nconst Event = {\n  HIDE: `hide${EVENT_KEY}`,\n  HIDDEN: `hidden${EVENT_KEY}`,\n  SHOW: `show${EVENT_KEY}`,\n  SHOWN: `shown${EVENT_KEY}`,\n  INSERTED: `inserted${EVENT_KEY}`,\n  CLICK: `click${EVENT_KEY}`,\n  FOCUSIN: `focusin${EVENT_KEY}`,\n  FOCUSOUT: `focusout${EVENT_KEY}`,\n  MOUSEENTER: `mouseenter${EVENT_KEY}`,\n  MOUSELEAVE: `mouseleave${EVENT_KEY}`\n}\n\n/**\n...

ciphertext  := sealed_chunk_0   ||       sealed_chunk_1   ||       sealed_chunk_2   ||       ...
```

In case of a S3 multi-part operation each part is en/decrypted with the scheme shown in Figure 1. However, for each part a unique secret key is derived from the OEK and the part number using a PRF. So in case of multi-part not the OEK but the output of `PRF(OEK, part_id)` is used as secret key.

## Custom Validation { #custom-validation }

There could be cases where you need to do some **custom validation** that can't be done with the parameters shown above.

In those cases, you can use a **custom validator function** that is applied after the normal validation (e.g. after validating that the value is a `str`).