### 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.

## Testing locally with Traefik

You can easily run the experiment locally with a stripped path prefix using <a href="https://docs.traefik.io/" class="external-link" target="_blank">Traefik</a>.

<a href="https://github.com/containous/traefik/releases" class="external-link" target="_blank">Download Traefik</a>, it's a single binary, you can extract the compressed file and run it directly from the terminal.

# First Steps

The simplest FastAPI file could look like this:

```Python
{!../../../docs_src/first_steps/tutorial001.py!}
```

Copy that to a file `main.py`.

Run the live server:

<div class="termy">

```console
$ <font color="#4E9A06">fastapi</font> dev <u style="text-decoration-style:single">main.py</u>
<font color="#3465A4">INFO    </font> Using path <font color="#3465A4">main.py</font>

  "devDependencies": {
    "@hey-api/openapi-ts": "^0.27.38",
    "typescript": "^4.6.2"
  }
}
```

After having that NPM `generate-client` script there, you can run it with:

<div class="termy">

```console
$ npm run generate-client

frontend-app@1.0.0 generate-client /home/user/code/frontend-app
> openapi-ts --input http://localhost:8000/openapi.json --output ./src/client --client axios
```

### Separate Program

To achieve this, you will normally have a **separate program** that would make sure your application is run on startup. And in many cases, it would also make sure other components or applications are also run, for example, a database.

### Example Tools to Run at Startup

Some examples of the tools that can do this job are:

* Docker
* Kubernetes
* Docker Compose
* Docker in Swarm Mode

    logging.info("Setting up GitHub Actions git user")
    subprocess.run(["git", "config", "user.name", "github-actions"], check=True)
    subprocess.run(
        ["git", "config", "user.email", "******@****.***"], check=True
    )
    branch_name = "fastapi-people"
    logging.info(f"Creating a new branch {branch_name}")
    subprocess.run(["git", "checkout", "-b", branch_name], check=True)

# (2)
WORKDIR /tmp

# (3)
RUN pip install poetry

# (4)
COPY ./pyproject.toml ./poetry.lock* /tmp/

# (5)
RUN poetry export -f requirements.txt --output requirements.txt --without-hashes

# (6)
FROM python:3.9

# (7)
WORKDIR /code

# (8)
COPY --from=requirements-stage /tmp/requirements.txt /code/requirements.txt

# (9)

$ python ./scripts/docs.py serve

Warning: this is a very simple server. For development, use mkdocs serve instead.
This is here only to preview a site with translations already built.
Make sure you run the build-all command first.
Serving at: http://127.0.0.1:8008
```

</div>

## 💯

📤 ✍ 👈 👆 💪 🏃 🌐 💯 🌐 📟 &amp; 🏗 💰 📄 🕸:

<div class="termy">

```console

It is the recommended server for Starlette and **FastAPI**.

!!! check "**FastAPI** recommends it as"
    The main web server to run **FastAPI** applications.

    You can combine it with Gunicorn, to have an asynchronous multi-process server.

    Check more details in the [Deployment](deployment/index.md){.internal-link target=_blank} section.

Nesse caso, seu `Dockerfile` poderia parecer assim:

```Dockerfile
FROM python:3.7

RUN pip install fastapi uvicorn

EXPOSE 80

COPY ./app /app

CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "80"]
```

### Crie o código **FastAPI**