<function-class>org.codelibs.fess.taglib.FessFunctions</function-class>
    <function-signature>java.lang.String mltForm()</function-signature>
    <example>
      ${fe:mltForm()}
    </example>
  </function>

  <function>
    <description>
      Returns a hidden form for Geo.
    </description>
    <name>geoForm</name>
    <function-class>org.codelibs.fess.taglib.FessFunctions</function-class>

We are not restricted to having only one dependency that can return that type of data.

///

## Other models { #other-models }

You can now get the current user directly in the *path operation functions* and deal with the security mechanisms at the **Dependency Injection** level, using `Depends`.

And you can use any model or data for the security requirements (in this case, a Pydantic model `User`).

    return {"fresh_value": fresh_value}
```

////

## Recap { #recap }

Apart from all the fancy words used here, the **Dependency Injection** system is quite simple.

Just functions that look the same as the *path operation functions*.

But still, it is very powerful, and allows you to declare arbitrarily deeply nested dependency "graphs" (trees).

/// tip

All this might not seem as useful with these simple examples.

Maybe you need to start a new version, or you just got tired of running it. 🤷

///

### Lifespan function { #lifespan-function }

The first thing to notice, is that we are defining an async function with `yield`. This is very similar to Dependencies with `yield`.

{* ../../docs_src/events/tutorial003.py hl[14:19] *}

The first part of the function, before the `yield`, will be executed **before** the application starts.

        boolQuery.filter(roleQuery);
    }

    /**
     * Builds boost query functions to modify document scoring based on various factors.
     * This method adds field value factors, key matching boosts, and custom boost functions.
     *
     * @param queryContext the query context to add boost functions to
     */
    protected void buildBoostQuery(final QueryContext queryContext) {

   * generated by applying the specified functions. If multiple inputs are mapped to the same row
   * and column pair, they will be combined with the specified merging function in encounter order.
   *
   * <p>The returned {@code Collector} will throw a {@code NullPointerException} at collection time
   * if the row, column, value, or merging functions return null on any input.
   *

   * generated by applying the specified functions.
   *
   * <p>The returned {@code Collector} will throw a {@code NullPointerException} at collection time
   * if the row, column, or value functions return null on any input.
   *
   * @since 21.0
   */
  public static <T extends @Nullable Object, R, C, V>
      Collector<T, ?, ImmutableTable<R, C, V>> toImmutableTable(
          Function<? super T, ? extends R> rowFunction,

Remember that when you import `Query`, `Path`, and others from `fastapi`, those are actually functions that return special classes.

///

/// tip

Notice how each model's attribute with a type, default value and `Field` has the same structure as a *path operation function's* parameter, with `Field` instead of `Path`, `Query` and `Body`.

///

## Add extra information { #add-extra-information }

## ¿Con prisa?

<abbr title="too long; didn't read"><strong>TL;DR:</strong></abbr>

Si estás usando paquetes de terceros que te dicen que los llames con `await`, como:

```Python
results = await some_library()
```

Entonces, declara tus *path operation functions* con `async def` así:

/**
 * Functional interface for boolean functions.
 * Represents a function that accepts one argument and produces a boolean result.
 * @param <T> the type of the input to the function
 */
@FunctionalInterface
public interface BooleanFunction<T> {
    /**
     * Applies this function to the given argument.
     * @param t the function argument
     * @return the function result
     */
    boolean apply(T t);