kefahi / fastapi

Python/FastApi pre-configured skeleton project

FastApi Skeleton

A python Fastapi skeleton that is crafted to fit specific needs: Building a simple api-only backend.

Features

• Using json_logging and FastApi middleware to create jsonl (JSON Lines) log file
  • Easy to view and query using tools like jq
  • Captures errors/exception with stacktrace
  • Produces a log entry for every api call with extensible details
• Settings setup to feed from dotenv style (File or Environment variables)
  • Port/Listen address
  • Database connection string
  • Log file path (jsonl)
• Database configuration using SQLAlchemy
• Suggested code structure
  • api folder: apis are broken into api-sets, each Api set is served from a separate directory and can be mounted arbitrarily on the main api route. e.g. /my1stapiset, /2ndapiset ...etc.
  • utils folder: contains common code like settings, db models ...etc.
• Optimized / small footprint container image based on barebone Alpine 3.15. The skeleton image size containing the code + python + depdedent python modules (the file fastapi-backend.tar.gz below) is only 23MB. This also makes it ideal for air-gapped deployements (copying the image to a server that doesn't have internet access).
• Templated json/xml api requests using jinja2
• Basic external api mocking using requests_mock

Install / usage

Requirements

• git
• python 3
• pip

Optional:

• podman
• gzip

Clone the code

git clone https://github.com/kefahi/fastapi.git
cd fastapi

Local / Direct Setup

pip install -r backend/requirements.txt

# Create logs folder (path can be configured in sample.env)
mkdir ../logs/

cd backend 

cp sample.env secrets.env
source env.sh

# Unit test
python tests.py

# pytest
pytest

# To run:
python main.py
# or 
./run.sh

# Invoke sample apis using curl
./curl.sh

Using Podman/Container

# Build
podman rmi fastapi-backend
podman build -t fastapi-backend .

# Run 
podman run --name fastapi-backend --rm \
  -e DATABASE_URL="postgresql://MYDBUSER:MYPASS@DBSERVERIP/DB" \
  -p 127.0.0.1:8080:8080/tcp \
  -it fastapi-backend \
  /home/backend/run.sh
  
# Command line access inside the container
podman exec -it fastapi-backend ash

# The image can be saved to a file for off-line deployement
podman save --quiet fastapi-backend | gzip > fastapi-backend.tar.gz

# Then loaded at the target system
podman load -i fastapi-backend.tar.gz