FastAPI + Docker: Complete Steps for Containerized Deployment
This article introduces the method of containerizing a FastAPI application using Docker to solve the environment inconsistency issue in development and deployment. First, create a FastAPI application: write `main.py` (including root path and parameterized interfaces), install dependencies `fastapi` and `uvicorn`, and generate `requirements.txt`. Next, package it through a Dockerfile: base on the Python 3.9-slim image, set the working directory to `/app`, copy dependency files and install them, copy the code, and finally start the service with `uvicorn` (port 8000). Execute `docker build -t my-fastapi-app .` to build the image, then run the container with `docker run -p 8000:8000 my-fastapi-app`. For testing, access `http://localhost:8000` or the API documentation at `http://localhost:8000/docs`. Common issues like port conflicts require changing the port or stopping the program; code modifications need rebuilding the image and restarting the container. The advantages of containerization include environment consistency, rapid migration, and dependency isolation. Future optimizations can include Docker Compose, reverse proxies, etc.
Read MoreFastAPI + Uvicorn: Basic Configuration for Local Development and Deployment
This article introduces the web development and deployment process using FastAPI with Uvicorn. FastAPI is a high-performance Python framework supporting asynchronous operations and automatic API documentation. Uvicorn, as an ASGI server, is the recommended deployment tool for FastAPI, and their combination enables efficient development. **Environment Installation**: First, create a virtual environment (e.g., `python -m venv venv`), activate it, and then install dependencies with `pip install fastapi uvicorn`. **Development Configuration**: Write `main.py`, define routes (e.g., root route `/` and parameterized route `/items/{item_id}`), and start the server with `uvicorn main:app --reload` for auto-reloading in development mode. Verify the interface by accessing `http://127.0.0.1:8000`. **Production Deployment**: Use the basic command `uvicorn main:app --host 0.0.0.0 --port 8000`. Specify the number of worker processes with `--workers` for multi-processing. Ensure the deployment server opens the port and manage processes via `nohup` or `systemd`. **Common Issues**: For port conflicts, change the port. If the service is unreachable, confirm `--host 0.0.0.0` and firewall settings. If installation fails, update pip or check Python version compatibility.
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