This schema definition includes your API paths, the possible parameters they take, etc.

#### Data "schema"

The term "schema" might also refer to the shape of some data, like a JSON content.

In that case, it would mean the JSON attributes, and data types they have, etc.

* Running on startup
* Restarts
* Replication (the number of processes running)
* Memory
* Previous steps before starting

Understanding these ideas and how to apply them should give you the intuition necessary to take any decisions when configuring and tweaking your deployments. 🤓

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    rect rgba(0, 255, 255, .1)
        code ->> function: say_hi(name="Camila")
        function ->> code: return stored result
    end
```

In the case of our dependency `get_settings()`, the function doesn't even take any arguments, so it always returns the same value.

That way, it behaves almost as if it was just a global variable. But as it uses a dependency function, then we can override it easily for testing.

You will see the JSON response as:

```JSON
{"item_id": 5, "q": "somequery"}
```

You already created an API that:

* Receives HTTP requests in the _paths_ `/` and `/items/{item_id}`.
* Both _paths_ take `GET` operations (also known as HTTP _methods_).
* The _path_ `/items/{item_id}` has a _path parameter_ `item_id` that should be an `int`.
* The _path_ `/items/{item_id}` has an optional `str` _query parameter_ `q`.

Downloading and installing the package dependencies **could take minutes**, but using the **cache** would **take seconds** at most.

And as you would be building the container image again and again during development to check that your code changes are working, there's a lot of accumulated time this would save.