The project aim is to develop an END-to-End ETL process. The resulting data will used to apply machine learning models.
PSRA - Property Services Regulatory Authority
├── extract
└────── extract.py
├── transform
├────── tranform_handler.py
└────── transform.py
├── load
└────── load.py
├── aws_handler
└────── aws_notification_handler.py
└────── aws_s3_handler.py
├── schedule_handler
└────── safe_schedule.py
└────── scheduler.py
├── static
└────── css
└────── js
└────── vendor
├── templates
└────── base.html
└────── index.html
├── route.py
├── configuration.py
├── exception.py
├── logconfig.py
├── Dockerfile
├── requirements.txt
└── README.md
Other directories are pytest, output, logs
- Python
- Flask
- AWS - S3, SNS
- Docker
- VSCode Editor
- Postman - Simulation
- Jupyter Notebook
- boto3
- Flask
- Docker
- pandas
- Project Structure
- Project Configuration
- Logging Configuration
- AWS Transaction Handler
- Global Exception Handler
- Extract
- Transform
- Load
- Containerization - DOCKER
- EC2 Deployment using Docker
- S3 Bucket Event Listener
- Enable SNS HTTP endpoint
- CI/CD Pipeline
- Documentation using Sphinx
Docker - Youtube - Channel: SelfTuts