assertEquals("RESOLVER_WINS", ResolverType.RESOLVER_WINS.name());
        assertEquals("RESOLVER_BCAST", ResolverType.RESOLVER_BCAST.name());
        assertEquals("RESOLVER_DNS", ResolverType.RESOLVER_DNS.name());
        assertEquals("RESOLVER_LMHOSTS", ResolverType.RESOLVER_LMHOSTS.name());
    }

    /**
     * Tests the ordinal values of the enum constants.

Now, if you generate the client again, you will see that it has the improved method names:

<img src="/img/tutorial/generate-clients/image07.png">

As you see, the method names now have the tag and then the function name, now they don't include information from the URL path and the HTTP operation.

### Preprocess the OpenAPI Specification for the Client Generator { #preprocess-the-openapi-specification-for-the-client-generator }

The administrator will associate IAM access policies with each group and if required with the user too. The MinIO server then evaluates applicable policies on a user (these are the policies associated with the groups along with the policy on the user if any) to check if the request should be allowed or denied.

For example, if an attacker were to upload a malicious video file, they could
potentially exploit a vulnerability in the TensorFlow code that handles videos,
which could allow them to execute arbitrary code on the system running
TensorFlow.

It is important to keep TensorFlow up to date with the latest security patches
and follow the sandboxing guideline above to protect against these types of
vulnerabilities.

 * Artifacts matched by this map will be minified to only contain the specified
 * classes and the classes they depend on. The classes are not relocated, they all
 * remain in their original namespace. This reduces the final Gradle distribution
 * size and makes us more conscious of which parts of a library we really need.
 *
 * WARNING: if you decide to do the minification by hand, make sure that you cover all paths of loading classes:

There are some extra features to handle security apart from the ones covered in the [Tutorial - User Guide: Security](../../tutorial/security/index.md){.internal-link target=_blank}.

/// tip

The next sections are **not necessarily "advanced"**.

And it's possible that for your use case, the solution is in one of them.

///

## Read the Tutorial first { #read-the-tutorial-first }

2. For some Python-specific terms like "pickle", "list", "dict" etc, we don't have to translate them.
3. Use the following preferred translations when they apply in documentation prose:

- request (HTTP): 請求
- response (HTTP): 回應
- path operation: 路徑操作
- path operation function: 路徑操作函式

                 * hashes and the other does then they will not be considered equal even
                 * though they may be.
                 */
            }
            return true;
        }
        return false;
    }

    /**
     * Check whether the password hashes are externally supplied.
     *
     * @return whether the hashes are externally supplied
     */

In the previous example, because the classes were different, we had to use the `response_model` parameter. But that also means that we don't get the support from the editor and tools checking the function return type.

{* ../../docs_src/query_param_models/tutorial001_an_py310.py hl[9:13,17] *}

**FastAPI** will **extract** the data for **each field** from the **query parameters** in the request and give you the Pydantic model you defined.

## Check the Docs { #check-the-docs }

You can see the query parameters in the docs UI at `/docs`:

<div class="screenshot">
<img src="/img/tutorial/query-param-models/image01.png">
</div>