## What makes a dependency { #what-makes-a-dependency }

Up to now you have seen dependencies declared as functions.

But that's not the only way to declare dependencies (although it would probably be the more common).

The key factor is that a dependency should be a "callable".

A "**callable**" in Python is anything that Python can "call" like a function.

      checkArgument(lowerBounds.length <= 1, "Wildcard cannot have more than one lower bounds.");
      if (lowerBounds.length == 1) {
        return supertypeOf(newArrayType(lowerBounds[0]));
      } else {
        Type[] upperBounds = wildcard.getUpperBounds();
        checkArgument(upperBounds.length == 1, "Wildcard should have only one upper bound.");
        return subtypeOf(newArrayType(upperBounds[0]));
      }

In your production system, you probably have a frontend created with a modern framework like React, Vue.js or Angular.

And to communicate using WebSockets with your backend you would probably use your frontend's utilities.

Or you might have a native mobile application that communicates with your WebSocket backend directly, in native code.

Or you might have any other way to communicate with the WebSocket endpoint.

---

  }

  /**
   * A thread-safe cache that contains the mapping from each class to all methods in that class and
   * all super-classes, that are annotated with {@code @Subscribe}. The cache is shared across all
   * instances of this class; this greatly improves performance if multiple EventBus instances are
   * created and objects of the same class are registered on all of them.
   */

        msgs.add("* contains the following plugin(s) that have goals not marked   *");
        msgs.add("* as @threadSafe to support parallel building.                  *");
        msgs.add("* While this /may/ work fine, please look for plugin updates    *");
        msgs.add("* and/or request plugins be made thread-safe.                   *");

	    the same array length.</li>

	<li>Two slice types are identical if they have identical element types.</li>

	<li>Two struct types are identical if they have the same sequence of fields,
	    and if corresponding pairs of fields have the same names, identical types,
	    and identical tags, and are either both embedded or both not embedded.

 that currently we have information about a project scattered across the project.xml and the
 various properties files. What needs to be done is to encapsulate all of this in the POM.

 Typically users parameterize the use of plugins, or have custom values like ${user.name}
 for use in elements like the <developerConnection/>. It would be idea if we

Including external libraries also based on Pydantic, as <abbr title="Object-Relational Mapper">ORM</abbr>s, <abbr title="Object-Document Mapper">ODM</abbr>s for databases.

This also means that in many cases you can pass the same object you get from a request **directly to the database**, as everything is validated automatically.

# Cookie Parameters { #cookie-parameters }

You can define Cookie parameters the same way you define `Query` and `Path` parameters.

## Import `Cookie` { #import-cookie }

First import `Cookie`:

{* ../../docs_src/cookie_params/tutorial001_an_py310.py hl[3] *}

## Declare `Cookie` parameters { #declare-cookie-parameters }

Then declare the cookie parameters using the same structure as with `Path` and `Query`.

And then in our code, we parse that YAML content directly, and then we are again using the same Pydantic model to validate the YAML content:

{* ../../docs_src/path_operation_advanced_configuration/tutorial007_py39.py hl[24:31] *}

/// tip

Here we reuse the same Pydantic model.

But the same way, we could have validated it in some other way.