///

## Multiple Workers { #multiple-workers }

You can start multiple workers with the `--workers` command line option:

//// tab | `fastapi`

If you use the `fastapi` command:

<div class="termy">

```console

/// tip

Don't worry if some of these items about **containers**, Docker, or Kubernetes don't make a lot of sense yet.

I'll tell you more about container images, Docker, Kubernetes, etc. in a future chapter: [FastAPI in Containers - Docker](docker.md){.internal-link target=_blank}.

///

## Previous Steps Before Starting { #previous-steps-before-starting }

#### Docker Compose { #docker-compose }

You could be deploying to a **single server** (not a cluster) with **Docker Compose**, so you wouldn't have an easy way to manage replication of containers (with Docker Compose) while preserving the shared network and **load balancing**.

Then you could want to have **a single container** with a **process manager** starting **several worker processes** inside.

---

        // Create thread pools
        this.channelExecutor = Executors.newCachedThreadPool(r -> {
            Thread t = new Thread(r, "SMB3-MultiChannel-Worker");
            t.setDaemon(true);
            return t;
        });

        this.healthCheckExecutor = Executors.newScheduledThreadPool(2, r -> {

  html_url: https://github.com/nsidnev/fastapi-realworld-example-app
  stars: 2925
  owner_login: nsidnev
  owner_html_url: https://github.com/nsidnev
- name: uvicorn-gunicorn-fastapi-docker
  html_url: https://github.com/tiangolo/uvicorn-gunicorn-fastapi-docker
  stars: 2796
  owner_login: tiangolo
  owner_html_url: https://github.com/tiangolo
- name: best-of-web-python
  html_url: https://github.com/ml-tooling/best-of-web-python

    - 🦇 Dark mode support.
- 🐋 [Docker Compose](https://www.docker.com) for development and production.
- 🔒 Secure password hashing by default.
- 🔑 JWT token authentication.
- 📫 Email based password recovery.
- ✅ Tests with [Pytest](https://pytest.org).
- 📞 [Traefik](https://traefik.io) as a reverse proxy / load balancer.

ics-vidhya/deploy-machine-learning-models-with-keras-fastapi-redis-and-docker-4940df614ece title: Deploy Machine Learning Models with Keras, FastAPI, Redis and Docker - author: Mandy Gu author_link: https://towardsdatascience.com/@mandygu link: https://towardsdatascience.com/deploying-iris-classifications-with-fastapi-and-docker-7c9b83fdec3a title: 'Towards Data Science: Deploying Iris Classifications with FastAPI and Docker' - author: Michael Herman author_link: https://testdriven.io/authors/herman...

    <img src="https://github.com/fastapi/fastapi/actions/workflows/test.yml/badge.svg?event=push&branch=master" alt="Test">
</a>
<a href="https://coverage-badge.samuelcolvin.workers.dev/redirect/fastapi/fastapi" target="_blank">
    <img src="https://coverage-badge.samuelcolvin.workers.dev/fastapi/fastapi.svg" alt="Coverage">
</a>
<a href="https://pypi.org/project/fastapi" target="_blank">

    <img src="https://github.com/fastapi/fastapi/actions/workflows/test.yml/badge.svg?event=push&branch=master" alt="Test">
</a>
<a href="https://coverage-badge.samuelcolvin.workers.dev/redirect/fastapi/fastapi" target="_blank">
    <img src="https://coverage-badge.samuelcolvin.workers.dev/fastapi/fastapi.svg" alt="Coverage">
</a>
<a href="https://pypi.org/project/fastapi" target="_blank">

## Run it { #run-it }

You can run your tests as usual via:

<div class="termy">

```console
$ pytest

---> 100%
```

</div>

## In Detail { #in-detail }

The marker `@pytest.mark.anyio` tells pytest that this test function should be called asynchronously:

{* ../../docs_src/async_tests/test_main.py hl[7] *}

/// tip