> You have to clean a big, dirty house.

*Yep, that's the whole story*.

---

There's no waiting 🕙 anywhere, just a lot of work to be done, on multiple places of the house.

You could have turns as in the burgers example, first the living room, then the kitchen, but as you are not waiting 🕙 for anything, just cleaning and cleaning, the turns wouldn't affect anything.

**Spoiler alert**: the tutorial - user guide includes:

* Declaration of **parameters** from other different places as: **headers**, **cookies**, **form fields** and **files**.
* How to set **validation constraints** as `maximum_length` or `regex`.

### Create the SQLAlchemy `engine`

The first step is to create a SQLAlchemy "engine".

We will later use this `engine` in other places.

```Python hl_lines="8-10"
{!../../../docs_src/sql_databases/sql_app/database.py!}
```

#### Note

The argument:

```Python
connect_args={"check_same_thread": False}
```

		UserAgent:    r.UserAgent(),
		Host:         handlers.GetSourceIP(r),
	})
}

// PutBucketObjectLockConfigHandler - PUT Bucket object lock configuration.
// ----------
// Places an Object Lock configuration on the specified bucket. The rule
// specified in the Object Lock configuration will be applied by default
// to every new object placed in the specified bucket.

    * `alias_priority`
    * `validation_alias`
    * `serialization_alias`
    * `discriminator`
    * `strict`
    * `multiple_of`
    * `allow_inf_nan`
    * `max_digits`
    * `decimal_places`
    * `json_schema_extra`

...you can read about them in the Pydantic docs.

* The parameter `regex` has been deprecated and replaced by `pattern`.

            calling this op is typically not necessary, as it is automatically
            used when computing the gradient of `tf.sparse.segment_sum`.
    *   Renaming of tensorflow::int64 to int_64_t in numerous places (the former
        is an alias for the latter) which could result in needing to regenerate
        selective op registration headers else execution would fail with
        unregistered kernels error.