Dockerize Python Environment for FastAPI with Poetry

Dockerizing a Python environment for FastAPI with Poetry allows you to easily manage dependencies, ensure consistency across different environments, and deploy your applications conveniently. Combining FastAPI with Docker offers a scalable and reproducible environment for deploying web applications. In this tutorial, we'll explore how to dockerize a Python environment for FastAPI while using Poetry for package management and version control.

Step 1: Setup your FastAPI project with Poetry

First, ensure you have Poetry installed on your local machine. If not, you can install it via pip:

$ pip install poetry

Now initialize a new Poetry project:

$ poetry init

Follow the prompts to initialize your project. Once done, you can start adding dependencies, including FastAPI:

$ poetry add fastapi uvicorn

Create a new Python file for your FastAPI application, for example,, and define your FastAPI app:

from fastapi import FastAPI

app = FastAPI()

async def root():
    return {"message": "Hello, World!"}

Step 2: Write a Dockerfile

Create a new file named Dockerfile in your project directory. This file will contain instructions for building your Docker image:

FROM python:3.11


COPY pyproject.toml poetry.lock /app/

RUN pip install poetry && poetry install --no-root --no-dev

COPY . /app


CMD ["uvicorn", "main:app", "--host", "", "--port", "8000"]

Step 3: Build and run the Docker image

Now that we have defined our Dockerfile, we can build the Docker image:

$ docker build -t my_fastapi_app .

Once the image is built successfully, you can run your FastAPI application using Docker:

$ docker run -d -p 8000:8000 my_fastapi_app

Your FastAPI application should now be running inside a Docker container. You can access it by navigating to http://localhost:8000 in your web browser.