### Server Memory { #server-memory }

For example, if your code loads a Machine Learning model with **1 GB in size**, when you run one process with your API, it will consume at least 1 GB of RAM. And if you start **4 processes** (4 workers), each will consume 1 GB of RAM. So in total, your API will consume **4 GB of RAM**.

 * License as published by the Free Software Foundation; either
 * version 2.1 of the License, or (at your option) any later version.
 *
 * This library is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
 * Lesser General Public License for more details.
 *

    void testWriteSetupWireFormatPreservesBuffer() {
        notifyChange = new NtTransNotifyChange(mockConfig, 0x1234, FILE_NOTIFY_CHANGE_FILE_NAME, false);
        byte[] dst = new byte[20];

        // Fill buffer with test pattern
        for (int i = 0; i < dst.length; i++) {
            dst[i] = (byte) (i & 0xFF);
        }

        int startIndex = 5;

   * {@code view} returned by this method will be invalidated, and will throw {@code
   * IllegalStateException} if it is accessed in any way, with the following exceptions:
   *
   * <ul>
   *   <li>{@code view.equals(view)} evaluates to {@code true} (but any other {@code equals()}
   *       expression involving {@code view} will throw)
   *   <li>{@code hashCode()} does not throw

Those parameters are what **FastAPI** will use to "solve" the dependency.

In both cases, it will have:

* An optional `q` query parameter that is a `str`.
* A `skip` query parameter that is an `int`, with a default of `0`.
* A `limit` query parameter that is an `int`, with a default of `100`.

In both cases the data will be converted, validated, documented on the OpenAPI schema, etc.

So, the prefix in this case is `/items`.

We can also add a list of `tags` and extra `responses` that will be applied to all the *path operations* included in this router.

And we can add a list of `dependencies` that will be added to all the *path operations* in the router and will be executed/solved for each request made to them.

/// tip

---> 100%
```

</div>

It will install all the dependencies and your local FastAPI in your local environment.

### Using your local FastAPI

If you create a Python file that imports and uses FastAPI, and run it with the Python from your local environment, it will use your cloned local FastAPI source code.

And if you update that local FastAPI source code when you run that Python file again, it will use the fresh version of FastAPI you just edited.

   * captured by the returned {@link ClosingFuture}).
   *
   * <p>If this {@code ClosingFuture} succeeds, the derived one will be equivalent to the one
   * returned by the function.
   *
   * <p>If this {@code ClosingFuture} fails, the function will not be called, and the derived {@code
   * ClosingFuture} will be equivalent to this one.
   *
   * <p>If the function throws an exception, that exception is used as the result of the derived

    * This will be done by sending a POST request (from *your API*) to some *external API* provided by that external developer (this is the "callback").

## The normal **FastAPI** app { #the-normal-fastapi-app }

Let's first see how the normal API app would look like before adding the callback.

It will have a *path operation* that will receive an `Invoice` body, and a query parameter `callback_url` that will contain the URL for the callback.

   *
   * <p>Exceptions thrown by a listener will be propagated up to the executor. Any exception thrown
   * during {@code Executor.execute} (e.g., a {@code RejectedExecutionException} or an exception
   * thrown by {@linkplain MoreExecutors#directExecutor direct execution}) will be caught and
   * logged.
   *
   * <p>Note: If your listener is lightweight -- and will not cause stack overflow by completing