You could also use it to generate code automatically, for clients that communicate with your API. For example, frontend, mobile or IoT applications.

### Deploy your app (optional) { #deploy-your-app-optional }

But then, even though you still don't have your burgers, your work with the cashier is "on pause" ⏸, because you have to wait 🕙 for your burgers to be ready.

But as you go away from the counter and sit at the table with a number for your turn, you can switch 🔀 your attention to your crush, and "work" ⏯ 🤓 on that. Then you are again doing something very "productive" as is flirting with your crush 😍.

### 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**.

---> 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.

In many situations, you would use a **proxy** like Traefik or Nginx in front of your FastAPI app.

These proxies could handle HTTPS certificates and other things.

## Proxy Forwarded Headers { #proxy-forwarded-headers }

If you have improvements to TensorFlow, send us your pull requests! For those
just getting started, GitHub has a
[how-to](https://help.github.com/articles/using-pull-requests/).

TensorFlow team members will be assigned to review your pull requests. Once the
pull requests are approved and pass continuous integration checks, a TensorFlow
team member will apply `ready to pull` label to your change. This means we are

```

### Build the Docker Image { #build-the-docker-image }

Now that all the files are in place, let's build the container image.

* Go to the project directory (in where your `Dockerfile` is, containing your `app` directory).
* Build your FastAPI image:

<div class="termy">

```console
$ docker build -t myimage .

---> 100%
```

</div>

/// tip

pydantic==2.8.0
```

///

## Run Your Program { #run-your-program }

After you activated the virtual environment, you can run your program, and it will use the Python inside of your virtual environment with the packages you installed there.

<div class="termy">

```console
$ python main.py

Hello World
```

</div>

## Configure Your Editor { #configure-your-editor }

You must agree to the terms of [Developer Certificate of Origin](https://developercertificate.org/) by signing off your commits. We automatically verify that all commit messages contain a `Signed-off-by:` line with your email address. We can only accept PRs that have all commits signed off.

If you didn't sign off your commits before creating the pull request, you can fix that after the fact.

To sign off a single commit:

    * **Cookie Sessions**
    * ...and more.

### Deploy your app (optional)

You can optionally deploy your FastAPI app to <a href="https://fastapicloud.com" class="external-link" target="_blank">FastAPI Cloud</a>, go and join the waiting list if you haven't. 🚀

If you already have a **FastAPI Cloud** account (we invited you from the waiting list 😉), you can deploy your application with one command.