// to the given dividend, so that we don't have half of our divisions being
  // trivial because the divisor is bigger than the dividend.
  // Using remainder here does not give us a uniform distribution but it should
  // not have a big impact on the measurement.
  private static long randomDivisor(long dividend) {
    long r = randomSource.nextLong();
    if (dividend == -1) {
      return r;

    }

    /**
     * Creates a string with all location details for the specified model problem. If the project identifier is
     * provided, the generated location will omit the model id and source information and only give line/column
     * information for problems originating directly from this POM.
     *
     * @param problem The problem whose location should be formatted, must not be {@code null}.

{* ../../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`:

<div class="screenshot">

        // Referral flags (2 bytes)
        SMBUtil.writeInt2(0, buffer, 14);

        // Proximity (2 bytes for v3)
        SMBUtil.writeInt2(0, buffer, 16);

        // Time to live (2 bytes for v3)
        SMBUtil.writeInt2(300, buffer, 18);

        // DFS path offset (2 bytes) - points to string data
        SMBUtil.writeInt2(stringDataStart - 8, buffer, 20); // Offset from start of referral

  // to the given dividend, so that we don't have half of our divisions being
  // trivial because the divisor is bigger than the dividend.
  // Using remainder here does not give us a uniform distribution but it should
  // not have a big impact on the measurement.
  private static long randomDivisor(long dividend) {
    long r = randomSource.nextLong();
    if (dividend == -1) {
      return r;

   * compatible with HTML. Specifically, it does not perform entity replacement (symbolic or
   * numeric), so it does not replace non-ASCII code points with character references. This escaper
   * escapes only the following five ASCII characters: {@code '"&<>}.
   */
  public static Escaper htmlEscaper() {
    return HTML_ESCAPER;
  }

  // For each xxxEscaper() method, please add links to external reference pages

{* ../../docs_src/security/tutorial001_an_py39.py hl[12] *}

But that is still not that useful.

Let's make it give us the current user.

## Create a user model { #create-a-user-model }

First, let's create a Pydantic user model.

The same way we use Pydantic to declare bodies, we can use it anywhere else:

            @Throws(IOException::class)
            override fun authenticate(route: Route?, response: Response): Request? {
              if (response.request.header("Authorization") != null) {
                return null // Give up, we've already attempted to authenticate.
              }

              println("Authenticating for response: $response")
              println("Challenges: ${response.challenges()}")

- Click `Create subproject` button at the bottom of the "Subprojects" region of [this page](https://builds.gradle.org/admin/editProject.html?projectId=Gradle&tab=projectGeneralTab)
  - Select `Manually`.
  - Give it a name. The name will be displayed on TeamCity web UI. We highly recommend it be capitalized from the branch name, i.e. `MyTestBranch`.

{* ../../docs_src/cookie_param_models/tutorial001_an_py310.py hl[9:12,16] *}

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

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

You can see the defined cookies in the docs UI at `/docs`:

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