Flask-CRUD-RestFul API with Testcases(pytest)

Features

• Authentication: Users can log in using JWT (JSON Web Tokens) for secure authentication.
• Inject Sensor data: Authenticate user can inject data in batch.
• Filter and Update: Sensor data can be fetched by filtering parameters.
• Analysys: Get informative insignts from sensor data using analysis api.

Setup Instructions

Clone the Repository

To get started, clone the repository to your local machine:

git clone https://github.com/Faizgeeky/CoulombAI-Task.git
cd CoulombAI-Task

Setting Up the Django WebSocket Server

1. Install the required dependencies:

   pip install -r requirements.txt

2. Setup Env varibales:

   export FLASK_APP=app.py
   export FLASK_DEBUG=1

3. Config env variable [Currently it is defined in confg.py that can be use din env var]

   export SECRET_KEY = 'jkbkjbvc-bkjbjkb-jka-kjbjkbkbda'
   export JWT_SECRET_KEY = 'kjbjkaebk-kjbjba-kjbajb'  

🚀🚀 Ready to launch your server

4. Run flask server:

   flask run

API's

   /auth/register
   /auth/login

   /v1/data/ // POST & GET Sensor data injection and filtering 
   /v1/data/<sensor_id> // Retrive Sensor data by sensor_id
   /v1/data/<id> // PUT update sensor data
   /v1/data/aggregate // GET - all you want to know about sensor data

🚀🚀 Test all API's using pytest

5. Run API testing :

   pytest -s 

   pytest 

   pytest {filename}

Postman Collection

A CoulombAI.postman_collection.json file is included for easy testing of the API endpoints with Postman. Simply import this file into Postman to get started.

File strcuture

  |-app.py  (entry point and regiterd all blueprints)
  |-config.py  (configurations and env variables - can be stored in env for better security)
  |-requirements.txt  
  |-extension.py  (to keep all 3rd party modeuls at one place)
  |-instance
     |-app.db (database)
  |-api
     |-model.py (User and Sensor database model defined)
     |-route 
        |- auth.py (auth routes)
        |- sensor.py (sensor routes)
        |- views.py (bussiness logic)
     |-schema (used marsmallow seriaizers)
        |- user.py
        |-sensor.py

API Postman collection

• It has all the api's endpoint with request and response
• You can import it in postman and use it to test the api's

NOTE

There are some filters might be missing in collection but you can add in filters for example

```sh
/v1/data/?sensor_id=1&start_date=2022-01

   //  You can pass many filters here as per task like start_date, end_date, aggregate =['hourly','daily'] , pressure, temperature

Enhancement

1. Handling large data injest asynly while storing
2. Data analysis - can get more details about sensor like , predictive analysis , correlation over time , increment or decrement by month , year , etc