input: []byte(`id,time,num,num2,text
1,2010-01-01T,7867786,4565.908123
2,2017-01-02T03:04Z,-5, 0.765111,Some some
`),
			// Since we are doing offset, no headers are used.
			wantResult: `{"id":"1","time":"2010-01-01T","num":"7867786","num2":"4565.908123"}
{"id":"2","time":"2017-01-02T03:04Z","num":"-5","num2":" 0.765111","text":"Some some"}`,
			wantErr: false,
			requestXML: []byte(`<?xml version="1.0" encoding="UTF-8"?>

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

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

## Forbid Extra Form Fields { #forbid-extra-form-fields }

In some special use cases (probably not very common), you might want to **restrict** the form fields to only those declared in the Pydantic model. And **forbid** any **extra** fields.

/// note

   * documentation for {@link Collection}:
   *
   * <blockquote>
   *
   * "Some collection implementations have restrictions on the elements that they may contain. For
   * example, some implementations prohibit null elements, and some have restrictions on the types
   * of their elements."
   *
   * </blockquote>
   */
  RESTRICTS_ELEMENTS,

  /**

// about HTTP headers, Set should be used instead of
// http.Header.Set(...). Otherwise, some S3 clients will not
// able to extract the ETag.
func Set(etag ETag, h http.Header) {
	// Some (broken) S3 clients expect the ETag header to
	// literally "ETag" - not "Etag". Further, some clients
	// expect an ETag in double quotes. Therefore, we set the
	// ETag directly as map entry instead of using http.Header.Set

{* ../../docs_src/cookie_param_models/tutorial002_an_py310.py hl[10] *}

If a client tries to send some **extra cookies**, they will receive an **error** response.

Poor cookie banners with all their effort to get your consent for the <abbr title="This is another joke. Don't pay attention to me. Have some coffee for your cookie. ☕">API to reject it</abbr>. 🍪

## Bodies of arbitrary `dict`s { #bodies-of-arbitrary-dicts }

You can also declare a body as a `dict` with keys of some type and values of some other type.

This way, you don't have to know beforehand what the valid field/attribute names are (as would be the case with Pydantic models).

            }
            // Simulate some encoding activity on the buffer
            dst.enc_ndr_long(123);
        }

        @Override
        public void decode(NdrBuffer src) throws NdrException {
            if (throwOnDecode) {
                throw new NdrException("Failed to decode");
            }
            // Simulate some decoding activity on the buffer
            src.dec_ndr_long();

That would refer to some package above `app/`, with its own file `__init__.py`, etc. But we don't have that. So, that would throw an error in our example. 🚨

But now you know how it works, so you can use relative imports in your own apps no matter how complex they are. 🤓

### Add some custom `tags`, `responses`, and `dependencies` { #add-some-custom-tags-responses-and-dependencies }

    for (StandardSystemProperty property : StandardSystemProperty.values()) {
      // Even though the contract in System.getProperties() specifies that a value will exist for
      // all of the listed keys, for some reason the "java.compiler" key returns null in some JVMs.
      if (property == JAVA_COMPILER) {
        continue;
      }
      // Removed in Java 9:

        return this.profilePath;
    }

    /**
     * Returns the user's home directory path.
     * @return the home directory path
     */
    public String getHomeDirectory() {
        return this.homeDirectory;
    }

    /**
     * Returns the user's home drive letter.
     * @return the home drive
     */
    public String getHomeDrive() {
        return this.homeDrive;
    }