DEV Community

📝 How to Dockerize a FastAPI Application (A Beginner's Guide)

Have you ever heard a developer say, "But it works on my machine!" That is the exact problem Docker was built to solve. If you are building a FastAPI application, you need a way to package it with all its dependencies, environment variables, and OS libraries so it runs exactly the same way on your laptop, your teammate's laptop, and the production server. Here is how to Dockerize a FastAPI app in three simple steps. Step 1: Create your requirements.txt First, make sure your project has a requirements.txt file listing all your Python packages. fastapi==0.100.0
uvicorn==0.23.2
Step 2: Write the Dockerfile A Dockerfile is a text document that contains all the commands a user could call on the command line to assemble an image. Create a file named Dockerfile in the root of your project (no file extension). # Use the official lightweight Python image
FROM python:3.10-slim

Set the working directory in the container

WORKDIR /code

Copy the requirements file first (this helps with caching)

COPY ./requirements.txt /code/requirements.txt

Install the dependencies

RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt

Copy the rest of the application code

COPY ./app /code/app

Command to run the application using Uvicorn

CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "80"]
Step 3: Build and Run Now that you have your Dockerfile, you can build the image and run the container. Open your terminal and run: docker build -t my-fastapi-app .
docker run -d --name my-running-app -p 8080:80 my-fastapi-app
- -d runs the container in the background. · -p 8080:80 maps port 8080 on your machine to port 80 inside the container. Why this is a game-changer If you look closely at the Dockerfile, the --host 0.0.0.0 flag is crucial. If you leave it as 127.0.0.1, the server will only listen to traffic inside the container, and your browser won't be able to reach it. Once you start using Docker, you never have to worry about dependency conflicts again. Have you started using Docker for your Python projects yet? Let me know!

Powered by Readybot.io