* {@link ValueGraph}, and {@link Network}):
 *
 * {@snippet :
 * someGraphAlgorithm(startNode, graph);
 * }
 *
 * This works because those types each implement {@code PredecessorsFunction}. It will also work
 * with any other implementation of this interface.
 *
 * <p>If you have your own graph implementation based around a custom node type {@code MyNode},

 * {@link ValueGraph}, and {@link Network}):
 *
 * {@snippet :
 * someGraphAlgorithm(startNode, graph);
 * }
 *
 * This works because those types each implement {@code SuccessorsFunction}. It will also work with
 * any other implementation of this interface.
 *
 * <p>If you have your own graph implementation based around a custom node type {@code MyNode},

# Server Workers - Uvicorn with Workers { #server-workers-uvicorn-with-workers }

Let's check back those deployment concepts from before:

* Security - HTTPS
* Running on startup
* Restarts
* **Replication (the number of processes running)**
* Memory
* Previous steps before starting

     * from any repository but are present among the set of specified projects will not cause an exception. Instead,
     * those unresolved artifacts will be returned in the result set, allowing the caller to take special care of
     * artifacts that haven't been build yet.
     *
     * @param projects The projects whose dependencies should be resolved, may be {@code null}.

So, you will want to have a **single process** to perform those **previous steps**, before starting the application.

If you added the return type annotation, tools and editors would complain with a (correct) error telling you that your function is returning a type (e.g. a dict) that is different from what you declared (e.g. a Pydantic model).

In those cases, you can use the *path operation decorator* parameter `response_model` instead of the return type.

You can use the `response_model` parameter in any of the *path operations*:

* `@app.get()`
* `@app.post()`

        forEach(rootDir, null, handler);
    }

    /**
     * Traverses resources contained in the file system.
     * <p>

`Body` also returns objects of a subclass of `FieldInfo` directly. And there are others you will see later that are subclasses of the `Body` class.

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

///

/// tip

your code interacts with the filesystem, network, etc. and uses checkpointed
variables as part of those interactions (ex: using a string variable to build a
filesystem path), a maliciously created checkpoint might be able to change the
targets of those operations, which could result in arbitrary
read/write/executions.

### Running a TensorFlow server

 * file system (those projects are usually about to be built) or from the local repository
 * (they are usually downloaded during dependency collection). Those projects are loaded
 * from a Project Object Model (POM).</p>
 *
 * <p><dfn>Project Object Model</dfn> or <dfn>POM</dfn> refers to the information describing
 * all the information needed to build or consume a project. Those are usually loaded from