{* ../../docs_src/request_form_models/tutorial001_an_py310.py hl[9:11,15] *}

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

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

You can verify it in the docs UI at `/docs`:

* `description` : La description de votre API ; elle peut inclure du markdown et sera affichée dans la documentation.
* `routes` : Une liste de routes ; chacune correspond à un *chemin d'accès* enregistré. Elles sont extraites de `app.routes`.

/// info

Le paramètre `summary` est disponible à partir d'OpenAPI 3.1.0, pris en charge par FastAPI 0.99.0 et versions ultérieures.

///

   * typically useful for {@code return} statements. That leaves the code with two options: Either
   * add the suppression to the whole method (which turns off checking for a large section of code),
   * or extract a variable, and put the suppression on that. However, a local variable typically
   * doesn't work: Because nullness analyses typically infer the nullness of local variables,

   * typically useful for {@code return} statements. That leaves the code with two options: Either
   * add the suppression to the whole method (which turns off checking for a large section of code),
   * or extract a variable, and put the suppression on that. However, a local variable typically
   * doesn't work: Because nullness analyses typically infer the nullness of local variables,

 * This form extends CreateForm to include fields necessary for updating existing data config entries,
 * including tracking information for optimistic locking and audit trails.
 * Data configs define how to crawl and extract data from databases, CSV files, and other data sources.
 *
 */
public class EditForm extends CreateForm {

    /**
     * Creates a new EditForm instance.
     */
    public EditForm() {
        super();

        }

        if (tlsVersions.contains(TLS_1_3)) {
          println("TLSv1.3 requires an external command run before first traffic is sent")
          println("Follow instructions at https://github.com/neykov/extract-tls-secrets for TLSv1.3")
          println("Pid: ${ProcessHandle.current().pid()}")

          Thread.sleep(10000)
        }
      }

      CommandLine -> {
        return ProcessBuilder(
          "tshark",

import java.util.List;
import java.util.Map;
import java.util.regex.Pattern;
import java.util.stream.Stream;
import java.util.stream.StreamSupport;
import org.jspecify.annotations.Nullable;

/**
 * Extracts non-overlapping substrings from an input string, typically by recognizing appearances of
 * a <i>separator</i> sequence. This separator can be specified as a single {@linkplain #on(char)

And if you declared a `response_model`, it will still be used to filter and convert the object you returned.

**FastAPI** will use that *temporal* response to extract the cookies (also headers and status code), and will put them in the final response that contains the value you returned, filtered by any `response_model`.

        }
        String url = distributionUrl.substring(idx + 1).trim();

        Matcher m = WRAPPER_VERSION_EXTRACT.matcher(url);
        if (!m.matches()) {
            throw new IllegalStateException("Could not extract wrapper version from distributionUrl: " + url);
        }
        return m.group(1);
    }

    private static void run(String... cmd) throws IOException, InterruptedException, ExecutionException {

Declare the **header parameters** that you need in a **Pydantic model**, and then declare the parameter as `Header`:

{* ../../docs_src/header_param_models/tutorial001_an_py310.py hl[9:14,18] *}

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

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

You can see the required headers in the docs UI at `/docs`: