


Scalable Python backend: Building a containerized FastAPI Application with uv, Docker, and pre-commit: a step-by-step guide
In today's containerized world, efficient backend application deployment is crucial. FastAPI, a popular Python framework, excels at creating fast, high-performance APIs. We'll use uv
, a package manager, to streamline dependency management.
uv
Assuming you've installed uv
and Docker, let's create our app: uv init simple-app
. This generates:
<code>simple-app/ ├── .python-version ├── README.md ├── hello.py └── pyproject.toml</code>
pyproject.toml
holds project metadata:
[project] name = "simple-app" version = "0.1.0" description = "Add your description here" readme = "README.md" requires-python = ">=3.11" dependencies = []
Add project dependencies to pyproject.toml
:
dependencies = [ "fastapi[standard]=0.114.2", "python-multipart=0.0.7", "email-validator=2.1.0", "pydantic>2.0", "SQLAlchemy>2.0", "alembic=1.12.1", ] [tool.uv] dev-dependencies = [ "pytest=7.4.3", "mypy=1.8.0", "ruff=0.2.2", "pre-commit=4.0.0", ]
The [tool.uv]
section defines development dependencies excluded during deployment. Run uv sync
to:
- Create
uv.lock
. - Create a virtual environment (
.venv
).uv
downloads a Python interpreter if needed. - Install dependencies.
FastAPI
Create the FastAPI application structure:
<code>recipe-app/ ├── app/ │ ├── main.py │ ├── __init__.py │ └── ... ├── .python-version ├── README.md └── pyproject.toml</code>
In app/main.py
:
from fastapi import FastAPI from pydantic import BaseModel app = FastAPI() class Hello(BaseModel): message: str @app.get("/", response_model=Hello) async def hello() -> Hello: return Hello(message="Hi, I am using FastAPI")
Run with: uv run fastapi dev app/main.py
. You'll see output similar to:
Access it at https://www.php.cn/link/c099034308f2a231c24281de338726c1.
Docker
Let's Dockerize. We'll develop within containers. Add a Dockerfile
:
FROM python:3.11-slim ENV PYTHONUNBUFFERED=1 COPY --from=ghcr.io/astral-sh/uv:0.5.11 /uv /uvx /bin/ ENV UV_COMPILE_BYTE=1 ENV UV_LINK_MODE=copy WORKDIR /app ENV PATH="/app/.venv/bin:$PATH" COPY ./pyproject.toml ./uv.lock ./.python-version /app/ RUN --mount=type=cache,target=/root/.cache/uv \ --mount=type=bind,source=uv.lock,target=uv.lock \ --mount=type=bind,source=pyproject.toml,target=pyproject.toml \ uv sync --frozen --no-install-project --no-dev COPY ./app /app/app RUN --mount=type=cache,target=/root/.cache/uv \ uv sync --frozen --no-dev CMD ["fastapi", "dev", "app/main.py", "--host", "0.0.0.0"]
For easier container management, use docker-compose.yaml
:
services: app: build: context: . dockerfile: Dockerfile working_dir: /app volumes: - ./app:/app/app ports: - "${APP_PORT:-8000}:8000" environment: - DATABASE_URL=${DATABASE_URL} depends_on: - postgres postgres: image: postgres:15 environment: POSTGRES_DB: ${POSTGRES_DB} POSTGRES_USER: ${POSTGRES_USER} POSTGRES_PASSWORD: ${POSTGRES_PASSWORD} volumes: - postgres_data:/var/lib/postgresql/data volumes: postgres_data: {}
Create a .env
file with environment variables. Run with: docker compose up --build
.
[tool.uv]
and Development Tools
The [tool.uv]
section in pyproject.toml
lists development tools:
- pytest: Testing framework (out of scope here).
- mypy: Static type checker. Run manually:
uv run mypy app
. - ruff: Fast linter (replaces multiple tools).
- pre-commit: Manages pre-commit hooks. Create
.pre-commit-config.yaml
:
repos: - repo: https://github.com/pre-commit/pre-commit-hooks rev: v4.4.0 hooks: - id: check-added-large-files - id: check-toml - id: check-yaml args: - --unsafe - id: end-of-file-fixer - id: trailing-whitespace - repo: https://github.com/astral-sh/ruff-pre-commit rev: v0.8.6 hooks: - id: ruff args: [--fix] - id: ruff-format
Add pyproject.toml
configurations for mypy
and ruff
(example provided in the original text). Install a VS Code Ruff extension for real-time linting. This setup ensures consistent code style, type checking, and pre-commit checks for a streamlined workflow.
The above is the detailed content of Scalable Python backend: Building a containerized FastAPI Application with uv, Docker, and pre-commit: a step-by-step guide. For more information, please follow other related articles on the PHP Chinese website!

Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Hot Topics

Solution to permission issues when viewing Python version in Linux terminal When you try to view Python version in Linux terminal, enter python...

How to avoid being detected when using FiddlerEverywhere for man-in-the-middle readings When you use FiddlerEverywhere...

When using Python's pandas library, how to copy whole columns between two DataFrames with different structures is a common problem. Suppose we have two Dats...

How to teach computer novice programming basics within 10 hours? If you only have 10 hours to teach computer novice some programming knowledge, what would you choose to teach...

How does Uvicorn continuously listen for HTTP requests? Uvicorn is a lightweight web server based on ASGI. One of its core functions is to listen for HTTP requests and proceed...

Using python in Linux terminal...

Fastapi ...

Understanding the anti-crawling strategy of Investing.com Many people often try to crawl news data from Investing.com (https://cn.investing.com/news/latest-news)...
