RestFull Flask Backend

This is a simple Flask-API boilerplate to help you quickly get started with setting up and deploying your python project. Here are some of the features of the setup:

Docker Ready
Kubernetes Ready
Deployment Ready

Prerequisites:

i) Install Git

ii) Install Docker

iii) Install docker-compose

STEP 1: Clone Project

To clone the project, run this command:

git clone git@github.com:GeoffMahugu/flask-backend.git

cd into project directory:

cd flask-backend

STEP 2: Setup Environment

There are 2 states the app can run:

i) DevConfig: Has debug congigurations set on

ii) ProdConfig: This configuration has debug set off

To set the environments run this(This sets the environment variable in memmory - Do same in prod server):

ENV_CONFIG: being either DevConfig or ProdConfig

export APP_ENV=<ENV_CONFIG>

STEP 3: Run Project

To run the project:

Using Docker

i. Build

docker-compose -f "docker-compose.yaml" up -d --build

ii. Run app

docker-compose up

To read more on docker: (link ☞)[README_Docker.md]

NOTE: During development, remember to build the image before runing the image. (That might just be the reason you are not seeing your upates)

Using PipEnv

i. Install PipEnv

Check version to make sure you are running python3

python --version

Proceed to install PipEnv

pip3 install pipenv

ii. Activate the Env

To activate the environment, run this command: PS: Will auto pick the configs from the (requirements.txt)[./requirements.txt] file.

pipenv shell

iii. Install dependancies

pipenv install

iv. Run project

python3 app.py

PROJECT SETUP

✦ /api This directory contains configurations for setting up the business logic Contains configurations for setting up API's

✦ /config Contains Global application configurations

✦ /models Contains configurations for modeling Database/iGraph. Do all ORM here.

✦ /static Contains any sattic files that needs to be served

✦ /tasks Contains configurations for any messaging process e.g Celery

API DOCUMENATION

i. Test Get-Request

url: http://127.0.0.1:5000/api/test-get

protocol: GET

response:

	{
	  "You are task home": "API 1 Done"
	}

ii. Test POST-Request

url: http://127.0.0.1:5000/api/test-igraph

protocol: POST

request:

	{
	  "name": "John Doe",
		"uuid": "=_ueyJhbGciOiJSUzI1NiIsImtp="
	}

response:

	{
	  "name": "John Doe",
	  "uuid": "=_ueyJhbGciOiJSUzI1NiIsImtp=",
	  "message": "Data has been processed"
	}

RESOURCES

This is a ist of usefull resources:

Conclusion

Feel free to use the project as a boilerplate to get you up and running quickly.

Any Pull Requests to improve the project and help other Python developers will be much appreciated 😀

With from the creator ❤️