Flask Application Structure with MongoDB

This application aims to serve as a template for APIs that intend to use mongoengine and flask-restx. One of the advantages of this application is to generate swagger documentation through schemas.

The general structure of the application can be seen below:

app_name
 |--api
    |--middleware
    |--resources
    |--schemas
 |--models
 |--logs

Requirements to run with Docker

• Docker
  • https://docs.docker.com/get-docker/
• Docker Compose
  • https://docs.docker.com/compose/install/

Requirements to run without Docker

• Python 3.8
  • https://www.anaconda.com/distribution
• MongoDB (> v.4)
  • https://www.mongodb.com/download-center/community

Configuration

Configuration is handled by environment variables, for development purpose you just need to update / add entries in .env file.

It's filled by default with following content:

# FLASK
ENV=(development | production)
SECRET_KEY=FLASK_SECRET_KEY
PORT=8000 # app port

# MongoDB
MONGO_DB=app_name
MONGO_HOST=localhost
MONGO_PORT=27017
MONGO_USER=
MONGO_PASS=

• If ENV=development, the application will be automatically reloaded when any change happens in the source files.

Execute with Docker

Initially it is necessary to build the image, which contains the application and the Postgres database

docker-compose --build

The command line below activates the application's container.

docker-compose up

Navigate to http://localhost:8000/api to see all routes on swagger.

Execute without Docker

First create the environment in Anaconda

conda create -n MYENV python=3.8

Activate the environment in the terminal

conda activate MYENV 

Import the libraries

pip install -r ./app_name/requirements.txt

Run the application

python index.py

Navigate to http://localhost:8000/api to see all routes on swagger.

Running pylint

To execute the code quality test with Pylint.

pylint ./app_name

Author & Help

• Tiago Franco

License

This project is licensed under the MIT License - see the LICENSE file for details