return cycles == 1
	}
	return uint32(xxhash.Sum64String(string(h)))%cycles == cycle%cycles
}

// modAlt returns true if the hash mod cycles == cycle.
// This is out of sync with mod.
// If cycles is 0 false is always returned.
// If cycles is 1 true is always returned (as expected).
func (h dataUsageHash) modAlt(cycle uint32, cycles uint32) bool {
	if cycles <= 1 {
		return cycles == 1
	}

				objectName:  path.Base(entName),
				debug:       f.dataUsageScannerDebug,
				lifeCycle:   activeLifeCycle,
				replication: replicationCfg,
			}

			item.heal.enabled = thisHash.modAlt(f.oldCache.Info.NextCycle/folder.objectHealProbDiv, f.healObjectSelect/folder.objectHealProbDiv) && f.shouldHeal()
			item.heal.bitrot = f.scanMode == madmin.HealDeepScan

			sz, err := f.getSize(item)

# Extra Models { #extra-models }

Continuing with the previous example, it will be common to have more than one related model.

This is especially the case for user models, because:

* The **input model** needs to be able to have a password.
* The **output model** should not have a password.
* The **database model** would probably need to have a hashed password.

/// danger

# Cookie Parameter Models { #cookie-parameter-models }

If you have a group of **cookies** that are related, you can create a **Pydantic model** to declare them. 🍪

This would allow you to **re-use the model** in **multiple places** and also to declare validations and metadata for all the parameters at once. 😎

/// note

This is supported since FastAPI version `0.115.0`. 🤓

///

/// tip

## Nested Models { #nested-models }

Each attribute of a Pydantic model has a type.

But that type can itself be another Pydantic model.

So, you can declare deeply nested JSON "objects" with specific attribute names, types and validations.

All that, arbitrarily nested.

### Define a submodel { #define-a-submodel }

For example, we can define an `Image` model:

			<url url="${repo.url}/${module.groupId}/${module.name.prefix}${module.name}/${module.version}/${module.name.prefix}${module.name}-${module.zip.version}.zip" />
		</get>
		<unzip dest="${modules.dir}/${module.name}" src="${target.dir}/${module.name.prefix}${module.name}-${module.zip.version}.zip">
			<patternset>
				<include name="**" />
			</patternset>
			<cutdirsmapper dirs="1" />
		</unzip>
	</target>

	<target name="remove.jars" if="with.fess">

# Query Parameter Models { #query-parameter-models }

If you have a group of **query parameters** that are related, you can create a **Pydantic model** to declare them.

This would allow you to **re-use the model** in **multiple places** and also to declare validations and metadata for all the parameters at once. 😎

/// note

This is supported since FastAPI version `0.115.0`. 🤓

///

## See it in the docs { #see-it-in-the-docs }

When you see the automatic docs, you can check that the input model and output model will both have their own JSON Schema:

<img src="/img/tutorial/response-model/image01.png">

And both models will be used for the interactive API documentation:

<img src="/img/tutorial/response-model/image02.png">

## Other Return Type Annotations { #other-return-type-annotations }

# Header Parameter Models { #header-parameter-models }

If you have a group of related **header parameters**, you can create a **Pydantic model** to declare them.

This would allow you to **re-use the model** in **multiple places** and also to declare validations and metadata for all the parameters at once. 😎

/// note

This is supported since FastAPI version `0.115.0`. 🤓

///

# Form Models { #form-models }

You can use **Pydantic models** to declare **form fields** in FastAPI.

/// info

To use forms, first install <a href="https://github.com/Kludex/python-multipart" class="external-link" target="_blank">`python-multipart`</a>.

Make sure you create a [virtual environment](../virtual-environments.md){.internal-link target=_blank}, activate it, and then install it, for example:

```console
$ pip install python-multipart
```