# Body - Fields

The same way you can declare additional validation and metadata in *path operation function* parameters with `Query`, `Path` and `Body`, you can declare validation and metadata inside of Pydantic models using Pydantic's `Field`.

## Import `Field`

First, you have to import it:

{* ../../docs_src/body_fields/tutorial001_an_py310.py hl[4] *}


/// warning

        MoreObjects.toStringHelper(new TestClass())
            .add("field1", "This is string.")
            .add("field2", Arrays.asList("abc", "def", "ghi"))
            .add("field3", map)
            .toString();
    final String expected =
        "TestClass{"
            + "field1=This is string., field2=[abc, def, ghi], field3={abc=1, def=2, ghi=3}}";

    assertEquals(expected, toTest);
  }

          <association>
            <type>Reporting</type>
          </association>
        </field>
      </fields>
    </class>
    <class>
      <name>PluginContainer</name>
      <version>3.0.0+</version>
      <description>Contains the plugins information for the project.</description>
      <fields>
        <field>
          <name>plugins</name>
          <version>4.0.0+</version>

        </field>
        <field>
          <name>exists</name>
          <version>1.0.0+</version>
          <type>String</type>
          <description>
            The name of the file that should exist to activate a profile. Please note, that missing and exists
            fields cannot be used together. Only one of them should be used at any one time.
          </description>
        </field>
      </fields>
    </class>

            field.field_info.annotation
        ) and not isinstance(field.field_info, params.Body)

    def is_sequence_field(field: ModelField) -> bool:
        return field_annotation_is_sequence(field.field_info.annotation)

    def is_scalar_sequence_field(field: ModelField) -> bool:
        return field_annotation_is_scalar_sequence(field.field_info.annotation)

    def is_bytes_field(field: ModelField) -> bool:

    # fields but it's the same one, so count them by name
    body_param_names_set = {field.name for field in fields}
    # A top level field has to be a single field, not multiple
    if len(body_param_names_set) > 1:
        return True
    first_field = fields[0]
    # If it explicitly specifies it is embedded, it has to be embedded

and <code>T</code> itself may not be
a pointer type. The unqualified type name acts as the field name.
</p>

<pre>
// A struct with four embedded fields of types T1, *T2, P.T3 and *P.T4
struct {
	T1        // field name is T1
	*T2       // field name is T2
	P.T3      // field name is T3
	*P.T4     // field name is T4
	x, y int  // field names are x and y
}
</pre>

<p>

                if (q instanceof BooleanQuery) {
                    queryList.addAll(getTermQueryList(q, fields));
                } else if (q instanceof final TermQuery termQuery) {
                    for (final String field : fields) {
                        if (field.equals(termQuery.getTerm().field())) {
                            queryList.add(termQuery);
                        }
                    }

                "Configure " + dispatcherMeta.displayName());
        context.addInHeader("");

        for (DispatcherMeta.Field field : dispatcherMeta.fields()) {
            String fieldKey = field.getKey();
            String fieldDescription = "Configure " + fieldKey + ": " + field.getDescription();
            if (field.getOptions().isPresent()) {
                // list options
                ListPromptBuilder listPromptBuilder =

The `HeroUpdate` *data model* is somewhat special, it has **all the same fields** that would be needed to create a new hero, but all the fields are **optional** (they all have a default value). This way, when you update a hero, you can send just the fields that you want to update.

Because all the **fields actually change** (the type now includes `None` and they now have a default value of `None`), we need to **re-declare** them.