this.attributes = attributes;
            this.creationTime = creationTime;
            this.lastAccessTime = lastAccessTime;
        }

        /**
         * Check if this file info matches the given attributes
         *
         * @param otherSize size to compare
         * @param otherLastModified last modified time to compare
         * @param otherAttributes attributes to compare

/// warning

Notice that `Field` is imported directly from `pydantic`, not from `fastapi` as are all the rest (`Query`, `Path`, `Body`, etc).

///

## Declare model attributes { #declare-model-attributes }

You can then use `Field` with model attributes:

{* ../../docs_src/body_fields/tutorial001_an_py310.py hl[11:14] *}

`Field` works the same way as `Query`, `Path` and `Body`, it has all the same parameters, etc.

     */
    public int getAttributes() throws SmbException {
        if (getUncPath0().length() == 1) {
            return 0;
        }
        exists();
        return attributes & ATTR_GET_MASK;
    }

    /**
     * Set the attributes of this file. Attributes are composed into a
     * bitset by bitwise ORing the {@code ATTR_*} constants. Setting the

        long lastModified = System.currentTimeMillis();
        boolean isDirectory = false;
        long attributes = 0x20; // FILE_ATTRIBUTE_ARCHIVE
        long creationTime = System.currentTimeMillis() - 10000;
        long lastAccessTime = System.currentTimeMillis() - 5000;

        entry.updateChild(childName, size, lastModified, isDirectory, attributes, creationTime, lastAccessTime);

        assertTrue(entry.hasChild(childName));

            div.innerHTML = `<span ${this._attributes(line)}>${line.value || ''}</span>`;

            return div.firstElementChild;
        });
    }

    /**
     * Helper function for generating attributes string.
     *
     * @param {Object} line - Line data object.
     * @returns {string} - String of attributes.
     */
    _attributes(line) {
        let attrs = '';

Then you declare your data model as a class that inherits from `BaseModel`.

Use standard Python types for all the attributes:

{* ../../docs_src/body/tutorial001_py310.py hl[5:9] *}


The same as when declaring query parameters, when a model attribute has a default value, it is not required. Otherwise, it is required. Use `None` to make it just optional.

    /**
     * Permission to append data to the file.
     */
    int FILE_APPEND_DATA = 0x00000004; // 3
    /**
     * Permission to read extended attributes.
     */
    int FILE_READ_EA = 0x00000008; // 4
    /**
     * Permission to write extended attributes.
     */
    int FILE_WRITE_EA = 0x00000010; // 5
    /**
     * Permission to execute the file.
     */
    int FILE_EXECUTE = 0x00000020; // 6

///

/// note

Notice that the input model is still validated.

So, if you want to receive partial updates that can omit all the attributes, you need to have a model with all the attributes marked as optional (with default values or `None`).

    /**
     * Mask for attributes that can be retrieved from the server
     */
    protected static final int ATTR_GET_MASK = 0x7FFF;
    /**
     * Mask for attributes that can be set on the server
     */
    protected static final int ATTR_SET_MASK = 0x30A7;
    /**
     * Default expiration period for cached attributes in milliseconds
     */

{* ../../docs_src/body_nested_models/tutorial005_py310.py hl[2,8] *}

The string will be checked to be a valid URL, and documented in JSON Schema / OpenAPI as such.

## Attributes with lists of submodels { #attributes-with-lists-of-submodels }

You can also use Pydantic models as subtypes of `list`, `set`, etc.:

{* ../../docs_src/body_nested_models/tutorial006_py310.py hl[18] *}