<img class="shadow" src="/img/deployment/concepts/image01.png">

---

Now that we know the difference between the terms **process** and **program**, let's continue talking about deployments.

## Running on Startup

systems is data "<abbr title="also called marshalling, conversion">serialization</abbr>" which is taking data from the code (Python) and converting it into something that can be sent through the network. For example, converting an object containing data from a database into a JSON object. Converting `datetime` objects into strings, etc.

Another big feature needed by APIs is data validation, making sure that the data is valid, given certain parameters. For example, that some field is an `int`,...

<img src="/img/async/concurrent-burgers/concurrent-burgers-05.png" class="illustration">

While waiting and talking to your crush, from time to time, you check the number displayed on the counter to see if it's your turn already.

Then at some point, it finally is your turn. You go to the counter, get your burgers and come back to the table.

This will probably happen for more than one of those tabs.

If you had multiple clients talking to your app exactly at the same time, this is what could happen.

And as your app starts to handle more and more clients at the same time, the waiting time in a single request needs to be shorter and shorter to trigger the error.

### Create the `FastAPI` app

```Python hl_lines="46"
{!../../../docs_src/nosql_databases/tutorial001.py!}
```

### Create the *path operation function*

## Motivation

Let's start with a simple example:

```Python
{!../../../docs_src/python_types/tutorial001.py!}
```

Calling this program outputs:

```
John Doe
```

The function does the following:

* Takes a `first_name` and `last_name`.
* Converts the first letter of each one to upper case with `title()`.

    * PR [#294](https://github.com/tiangolo/fastapi/pull/294).

## 0.28.0

* Implement dependency cache per request.
    * This avoids calling each dependency multiple times for the same request.
    * This is useful while calling external services, performing costly computation, etc.

But at some point, there was no other option than creating something that provided all these features, taking the best ideas from previous tools, and combining them in the best way possible, using language features that weren't even available before (Python 3.6+ type hints).

</blockquote>

## Investigation

    But **FastAPI** will know that it has to solve `query_extractor` first, to pass the results of that to `query_or_cookie_extractor` while calling it.

```mermaid
graph TB

query_extractor(["query_extractor"])
query_or_cookie_extractor(["query_or_cookie_extractor"])

read_query["/items/"]

    ```Python hl_lines="5  22"
    {!> ../../../docs_src/encoder/tutorial001.py!}
    ```

In this example, it would convert the Pydantic model to a `dict`, and the `datetime` to a `str`.

The result of calling it is something that can be encoded with the Python standard <a href="https://docs.python.org/3/library/json.html#json.dumps" class="external-link" target="_blank">`json.dumps()`</a>.