{* ../../docs_src/sub_applications/tutorial001.py hl[11, 14:16] *}

### Mount the sub-application { #mount-the-sub-application }

In your top-level application, `app`, mount the sub-application, `subapi`.

In this case, it will be mounted at the path `/subapi`:

{* ../../docs_src/sub_applications/tutorial001.py hl[11, 19] *}

# Including WSGI - Flask, Django, others { #including-wsgi-flask-django-others }

You can mount WSGI applications as you saw with [Sub Applications - Mounts](sub-applications.md){.internal-link target=_blank}, [Behind a Proxy](behind-a-proxy.md){.internal-link target=_blank}.

For that, you can use the `WSGIMiddleware` and use it to wrap your WSGI application, for example, Flask, Django, etc.

## Using `WSGIMiddleware` { #using-wsgimiddleware }

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And multiple processes normally **don't share any memory**. This means that each running process has its own things, variables, and memory. And if you are consuming a large amount of memory in your code, **each process** will consume an equivalent amount of memory.

### Server Memory { #server-memory }

    }

    /**
     * Test validation of excessive negotiate context count.
     */
    @Test
    public void testExcessiveNegotiateContextCount() {
        byte[] buffer = createBasicNegotiateResponseBuffer();
        // Set SMB 3.1.1 dialect
        SMBUtil.writeInt2(0x0311, buffer, 4);
        // Set excessive negotiate context count (should be limited to 100)
        SMBUtil.writeInt2(1000, buffer, 6);

you will have a more or less well-defined, stable, and limited amount of memory consumed by each of those containers (more than one if they are replicated).

And then you can set those same memory limits and requirements in your configurations for your container management system (for example in **Kubernetes**). That way it will be able to **replicate the containers** in the **available machines** taking into account the amount of memory needed by them, and the amount available in the machines...

# Static Files { #static-files }

You can serve static files automatically from a directory using `StaticFiles`.

## Use `StaticFiles` { #use-staticfiles }

* Import `StaticFiles`.
* "Mount" a `StaticFiles()` instance in a specific path.

{* ../../docs_src/static_files/tutorial001.py hl[2,6] *}

/// note | Technical Details

You could also use `from starlette.staticfiles import StaticFiles`.