Isso vem a seguir....

const crossDomainXML = `<?xml version="1.0"?><!DOCTYPE cross-domain-policy SYSTEM "http://www.adobe.com/xml/dtds/cross-domain-policy.dtd"><cross-domain-policy><allow-access-from domain="*" secure="false" /></cross-domain-policy>`

// Standard path where an app would find cross domain policy information.
const crossDomainXMLEntity = "/crossdomain.xml"

/// info | Información

Ten en cuenta que los dataclasses no pueden hacer todo lo que los modelos de Pydantic pueden hacer.

Así que, podrías necesitar seguir usando modelos de Pydantic.

Pero si tienes un montón de dataclasses por ahí, este es un buen truco para usarlos para potenciar una API web usando FastAPI. 🤓

///

## Dataclasses en `response_model`

- name: authx
  html_url: https://github.com/yezz123/authx
  stars: 978
  owner_login: yezz123
  owner_html_url: https://github.com/yezz123
- name: secure
  html_url: https://github.com/TypeError/secure
  stars: 942
  owner_login: TypeError
  owner_html_url: https://github.com/TypeError
- name: titiler
  html_url: https://github.com/developmentseed/titiler
  stars: 940

        ref = u.getRef();
        if (ref != null) {
            path += '#' + ref;
        }
        port = u.getPort();
        if (port == -1) {
            port = getDefaultPort();
        }
        setURL(u, "smb", u.getHost(), port, u.getAuthority(), u.getUserInfo(), path, u.getQuery(), null);
    }

        byte[] hash1 = md5_1.digest(data);
        byte[] hash2 = md5_2.digest(data);

        // Then
        assertArrayEquals(hash1, hash2);
    }

    @Test
    @DisplayName("Should generate secure random bytes")
    void testSecureRandomGeneration() throws java.security.NoSuchAlgorithmException {
        // Given
        int length = 16;

        // When
        byte[] random1 = new byte[length];

	github.com/prometheus/procfs v0.16.1
	github.com/puzpuzpuz/xsync/v3 v3.5.1
	github.com/rabbitmq/amqp091-go v1.10.0
	github.com/rcrowley/go-metrics v0.0.0-20250401214520-65e299d6c5c9
	github.com/rs/cors v1.11.1
	github.com/secure-io/sio-go v0.3.1
	github.com/shirou/gopsutil/v3 v3.24.5
	github.com/tinylib/msgp v1.2.5
	github.com/valyala/bytebufferpool v1.0.0
	github.com/xdg/scram v1.0.5
	github.com/zeebo/xxh3 v1.0.2
	go.etcd.io/etcd/api/v3 v3.5.21

```Python
if not (credentials.username == "stanleyjobson") or not (credentials.password == "swordfish"):
    # Return some error
    ...
```

But by using the `secrets.compare_digest()` it will be secure against a type of attacks called "timing attacks".

### Timing Attacks { #timing-attacks }

But what's a "timing attack"?

Let's imagine some attackers are trying to guess the username and password.

        Repository repo = new Repository();

        repo.setId(profileXmlRepo.getId());
        repo.setLayout(profileXmlRepo.getLayout());
        repo.setName(profileXmlRepo.getName());
        repo.setUrl(profileXmlRepo.getUrl());

        if (profileXmlRepo.getSnapshots() != null) {
            repo.setSnapshots(convertRepositoryPolicy(profileXmlRepo.getSnapshots()));
        }

- **Pre-Authentication Integrity**: SMB 3.1.1 PAI for preventing downgrade attacks
- **Automatic Detection**: Encryption automatically enabled when servers require it
- **Secure Key Management**: Proper key derivation and nonce generation

### Core Features
- **Per-context configuration**: No global state, each context encapsulates configuration