Deploying on Deta" - author: Navule Pavan Kumar Rao author_link: https://www.linkedin.com/in/navule/ link: https://www.tutlinks.com/deploy-fastapi-on-ubuntu-gunicorn-caddy-2/ title: Deploy FastAPI on Ubuntu and Serve using Caddy 2 Web Server - author: Patrick Ladon author_link: https://dev.to/factorlive link: https://dev.to/factorlive/python-facebook-messenger-webhook-with-fastapi-on-glitch-4n90 title: Python Facebook messenger webhook with FastAPI on Glitch - author: Valon Januzaj author_link: https:...

musikisomorphie, Nagy Mostafa, Nayana Thorat, Neil, Niels Ole Salscheider,
Niklas SilfverströM, Niranjan Hasabnis, ocjosen, olramde, Pariksheet Pinjari,
Patrick J. Lopresti, Patrik Gustavsson, per1234, PeterLee, Phan Van Nguyen Duc,
Phillip Kravtsov, Pooya Davoodi, Pranav Marathe, Putra Manggala, Qingqing Cao,
Rajeshwar Reddy T, Ramon ViñAs, Rasmus Diederichsen, Reuben Morais, richardbrks,

    }
    return result;
  }

  // Helpers + main

  private byte runHashFunction(int reps, HashFunction hashFunction) {
    byte result = 0x01;
    // Trick the JVM to prevent it from using the hash function non-polymorphically
    result ^= Hashing.crc32().hashInt(reps).asBytes()[0];
    result ^= Hashing.adler32().hashInt(reps).asBytes()[0];

    }
    return result;
  }

  // Helpers + main

  private byte runHashFunction(int reps, HashFunction hashFunction) {
    byte result = 0x01;
    // Trick the JVM to prevent it from using the hash function non-polymorphically
    result ^= Hashing.crc32().hashInt(reps).asBytes()[0];
    result ^= Hashing.adler32().hashInt(reps).asBytes()[0];

Bedenken Sie, dass Datenklassen nicht alles können, was Pydantic-Modelle können.

Daher müssen Sie möglicherweise weiterhin Pydantic-Modelle verwenden.

Wenn Sie jedoch eine Menge Datenklassen herumliegen haben, ist dies ein guter Trick, um sie für eine Web-API mithilfe von FastAPI zu verwenden. 🤓

///

## Datenklassen als `response_model`

Sie können `dataclasses` auch im Parameter `response_model` verwenden:

```Python hl_lines="1  7-13  19"

/// info

Keep in mind that dataclasses can't do everything Pydantic models can do.

So, you might still need to use Pydantic models.

But if you have a bunch of dataclasses laying around, this is a nice trick to use them to power a web API using FastAPI. 🤓

///

## Dataclasses in `response_model`

You can also use `dataclasses` in the `response_model` parameter:

```

////

## Order the parameters as you need, tricks

/// tip

This is probably not as important or necessary if you use `Annotated`.

///

Here's a **small trick** that can be handy, but you won't need it often.

If you want to:

* declare the `q` query parameter without a `Query` nor any default value
* declare the path parameter `item_id` using `Path`

Dennoch können wir das zu erwartende Schema für den Requestbody deklarieren.

### Benutzerdefinierter OpenAPI-Content-Type

Mit demselben Trick könnten Sie ein Pydantic-Modell verwenden, um das JSON-Schema zu definieren, das dann im benutzerdefinierten Abschnitt des OpenAPI-Schemas für die *Pfadoperation* enthalten ist.

Nevertheless, we can declare the expected schema for the request body.

### Custom OpenAPI content type

Using this same trick, you could use a Pydantic model to define the JSON Schema that is then included in the custom OpenAPI schema section for the *path operation*.

And you could do this even if the data type in the request is not JSON.

import java.util.concurrent.locks.ReentrantLock;
import java.util.concurrent.locks.ReentrantReadWriteLock;
import junit.framework.TestCase;

/**
 * Unittests for {@link CycleDetectingLockFactory}.
 *
 * @author Darick Tong
 */
public class CycleDetectingLockFactoryTest extends TestCase {

  private ReentrantLock lockA;
  private ReentrantLock lockB;
  private ReentrantLock lockC;
  private ReentrantReadWriteLock.ReadLock readLockA;