## Custom Validation { #custom-validation }

There could be cases where you need to do some **custom validation** that can't be done with the parameters shown above.

In those cases, you can use a **custom validator function** that is applied after the normal validation (e.g. after validating that the value is a `str`).

        } catch (SMBProtocolDecodingException e) {
            // If exception thrown, validation is working
            assertTrue(e.getMessage().contains("Invalid negotiate context data length") || e.getMessage().contains("Buffer too small")
                    || e.getMessage().contains("negotiate context"), "Validation detected issue: " + e.getMessage());
        }

As these keys may not necessarily be part of the OpenAPI specification, some OpenAPI tools, for example [the OpenAPI validator](https://validator.swagger.io/), may not work with your generated schema.

///

## Recap { #recap }

You can use Pydantic's `Field` to declare extra validations and metadata for model attributes.

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`, and not some random string. This is especially useful for incoming data.

Without a data validation system, you would have to do all the checks by hand, in code.

    @Test
    @DisplayName("Test invalid buffer size validation")
    void testInvalidBufferSize() {
        assertThrows(IllegalArgumentException.class, () -> InputValidator.validateBufferSize(-1, 1000, "test"));
        assertThrows(IllegalArgumentException.class, () -> InputValidator.validateBufferSize(1001, 1000, "test"));
    }

    @Test
    @DisplayName("Test SMB2 buffer size validation")
    void testSmb2BufferSize() {

/// info

To use `EmailStr`, first install <a href="https://github.com/JoshData/python-email-validator" class="external-link" target="_blank">`email-validator`</a>.

Make sure you create a [virtual environment](../virtual-environments.md){.internal-link target=_blank}, activate it, and then install it, for example:

```console
$ pip install email-validator
```

or with:

```console
$ pip install "pydantic[email]"
```

///

import org.slf4j.LoggerFactory;

import jcifs.smb.SmbException;

/**
 * Path validation utility to prevent directory traversal and other path-based attacks.
 *
 * Features:
 * - Directory traversal prevention
 * - Path normalization
 * - Blacklist/whitelist support
 * - UNC path validation
 * - Special character filtering
 * - Length validation
 */
public class PathValidator {

    * If you didn't use FastAPI and used Starlette directly (or another tool, like Sanic, Flask, Responder, etc) you would have to implement all the data validation and serialization yourself. So, your final application would still have...

        byte[] expectedHash = preauthService.getCurrentPreauthHash(sessionId);

        // Validation should pass with correct hash
        assertTrue(preauthService.validatePreauthIntegrity(sessionId, expectedHash));

        // Validation should fail with incorrect hash
        byte[] incorrectHash = new byte[expectedHash.length];
        secureRandom.nextBytes(incorrectHash);

}
```

Again, doing just that declaration, with **FastAPI** you get:

* Editor support (completion, etc.), even for nested models
* Data conversion
* Data validation
* Automatic documentation

## Special types and validation { #special-types-and-validation }

Apart from normal singular types like `str`, `int`, `float`, etc. you can use more complex singular types that inherit from `str`.