Qricle Hotel Management:Framework: Django/DRFServices: AWS(EC2, S3), DockerDatabase/ORM: PostgreSQL/Django ORM-Used DRF viewsets(Modelviewset) and routers to handle CRUD operations for the application that handles user management, Menu, Menu categories, Addon Items, Orders.-Designed and structure database tables with proper ER diagram. -Created endpoints that handles Flat files upload/delete.-Used python QRcode library that can generate qr code for the user to perform mobile login for a particular hotel and its rooms.-Created and deployed docker image and yaml configuration file that can create multiple containers (PostgreSQL and Django DRF api's) at once in AWS server (EC2 instance).-Used AWS S3 service using boto3 python SDK for storing images and qr code.-Integrated Chargebee payment.NextMed:Framework: FastApiServices: AWS(EC2, S3, VPC, AWS Cognito)Database/ORM: Mysql/SqlAlchemy-Created api endpoints that can be consumed at the frontend(React).-Integrated 3 party api's like gogomeds (cloud based pharmacy that provides affordable quality medicines to customers), humhealth services that provides RPM(Remote Patient Monitoring) and CCM(Chronic Care Management) and twilio for sending text messages.-Handled webhooks events while integrating 3rd party api's for api call failure or success status.-Developed Python scripts:To upload csv data file into a secure folder using SFTP protocol.-Used Selenium for automating cover my meds service that covers users medical insurance according to the chosen plan.-Worked on AWS cognito service for user authentication by creating user pools that handles username, email and password.-Hands on AWS VPC and custom S3 bucket policy that can be accessed only if request is coming through specific VPC endpoints.-Implemented logger to ease application debugging.

NoCodeAI:Framework: FlaskService: Celery, RabbitMQ, RedisDatabase/ORM: MySql/SqlAlchemy-Developed Flask endpoints for a web application to manage User Authentication, Roles and Permissions.-Used pandas and pivot tables that facilitates the working of dashboard api for the application.-Worked on Azure services like blob storage for storing images.-Used celery as a background service: a.That handles multiple images deletion process and adding multiple annotations in an image and storing them in azure blob. b.That can submit image annotations. c.Used python library:Resumable upload for huge file upload that uploads files in chunks and keeps the chunks size records in case of upload failure.-Improved api response time by leveraging Redis as database for storing data for faster retrieval.-Used RabbitMQ as Pub-Sub model that sends event data.