And to create `fluffy`, you are "calling" `Cat`.

So, a Python class is also a **callable**.

Then, in **FastAPI**, you could use a Python class as a dependency.

What FastAPI actually checks is that it is a "callable" (function, class or anything else) and the parameters defined.

  }

  /**
   * Test EqualsTester with no equals or not equals objects. This checks proper handling of null,
   * incompatible class and reflexive tests
   */
  public void testTestEqualsEmptyLists() {
    equalsTester.addEqualityGroup(reference);
    equalsTester.testEquals();
  }

  /**
   * Test EqualsTester after populating equalObjects. This checks proper handling of equality and
   * verifies hashCode for valid objects
   */

}

// getImmediate checks that addr represents an immediate constant and returns its value.
func (p *Parser) getImmediate(prog *obj.Prog, op obj.As, addr *obj.Addr) int64 {
	if addr.Type != obj.TYPE_CONST || addr.Name != 0 || addr.Reg != 0 || addr.Index != 0 {
		p.errorf("%s: expected immediate constant; found %s", op, obj.Dconv(prog, addr))
	}
	return addr.Offset
}

In your editor, inside your function you will get type hints and completion everywhere (this wouldn't happen if you received a `dict` instead of a Pydantic model):

<img src="/img/tutorial/body/image03.png">

You also get error checks for incorrect type operations:

<img src="/img/tutorial/body/image04.png">

This is not by chance, the whole framework was built around that design.

But there could be cases where you want to be able to set parameters on the dependency, without having to declare many different functions or classes.

Let's imagine that we want to have a dependency that checks if the query parameter `q` contains some fixed content.

But we want to be able to parameterize that fixed content.

## A "callable" instance

In Python there's a way to make an instance of a class a "callable".

                                                     const TF_DataType* values,
                                                     int num_values);

// Checks the tensorflow::NodeDef built via the methods above to see if it can
// run on device_type.
TF_CAPI_EXPORT extern void TF_AttrBuilderCheckCanRunOnDevice(
    TF_AttrBuilder* builder, const char* device_type, TF_Status* status);

     * @return {@code true} if remote repositories should be re-checked for updated artifacts/metadata, {@code false}
     *         otherwise.
     */
    boolean isForceUpdate();

    /**
     * Enables/disabled forced checks for updated artifacts/metadata on remote repositories.
     *
     * @param forceUpdate {@code true} to forcibly check the remote repositories for updated artifacts/metadata, {@code

			port = "443"
		case "http":
			port = "80"
		default:
			return "", "", errors.New("unable to guess port from scheme")
		}
	}

	return host, port, nil
}

// isLocalHost - checks if the given parameter
// correspond to one of the local IP of the
// current machine
func isLocalHost(host string, port string, localPort string) (bool, error) {
	hostIPs, err := getHostIP(host)
	if err != nil {

import static org.mockito.Mockito.verify;

import java.io.Flushable;
import java.io.IOException;
import junit.framework.TestCase;

/**
 * Unit tests for {@link Flushables}.
 *
 * <p>Checks proper flushing behavior, and ensures that IOExceptions on Flushable.flush() are not
 * propagated out from the {@link Flushables#flush} method if {@code swallowException} is true.
 *
 * @author Michael Lancaster
 */

          NANOSECONDS.timedWait(lock, nanos);
          nanos -= System.nanoTime() - now; // subtract the actual time we waited
        }
      }
    }
  }

  /**
   * Checks if the executor has been shut down and increments the running task count.
   *
   * @throws RejectedExecutionException if the executor has been previously shutdown
   */
  private void startTask() {