Dockerize FastAPI with Docker Compose: A Step-by-Step Guide

Added:

Project Setup
Dependencies & Run
Env Configuration
Dockerfile Creation
Manual Build & Run
Compose Introduction
Changes & Rebuild
Bind Mounts & Sync
Live Reload Setup

Project Setup

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  • 1

    Clone the repository and create an app directory for the project.

  • 2

    Create a Python virtual environment and activate it.

  • 3

    Move project files into the root directory and make the app a Python package.

Basic proficiency in Python programming and the fundamentals of the FastAPI framework, including routing and asynchronous endpoints.
Understanding of CRUD (Create, Read, Update, Delete) operations and basic NoSQL database concepts, specifically MongoDB document structures.
Familiarity with using the Command Line Interface (CLI) or terminal for navigating directories and executing scripts.
Fundamental awareness of virtualization concepts and what software containerization aims to solve in software deployment.
Optimizing Docker images for production using multi-stage builds and security best practices, such as running containers as non-root users.
Deploying and scaling containerized applications using orchestration platforms like Kubernetes or AWS ECS.
Configuring automated Continuous Integration and Continuous Deployment (CI/CD) pipelines using platforms like GitHub Actions to build and push Docker images.
Implementing persistent data strategies, system backups, and clustering/replication configurations for MongoDB in a containerized environment.
13.7K views154likes39:47@CodeWithPrinceOriginal Release: 2021-12-03

To dockerize a FastAPI application, create a Dockerfile that installs dependencies before copying application code to leverage Docker's caching system, then use docker-compose to manage the container with port mapping and volume mounts for development. The key steps include: creating a virtual environment and installing requirements, writing a Dockerfile with FROM python:3.9.7, WORKDIR, COPY requirements.txt, RUN pip install, COPY . ., and CMD uvicorn app.main:app --reload, building the image with docker build, and running it with docker run -d -p 8000:8000. For development, use bind mounts (volumes) to automatically reflect code changes without rebuilding the image.