Build a Data Pipeline Using Python | Setup Project and Read Table List | Data Engineering

In this session, you'll follow along with a live demonstration of building a complete data pipeline using Python. We'll cover everything from setting up the project and connecting to databases to extracting, transforming, and loading data. This isn't just about the code; we'll dive into the essential nuts and bolts that ensure your pipeline is robust, efficient, and scalable!** *Topics Covered:* * What are the prerequisites for building a data pipeline? (Source & target databases, VMs, Docker setup) * How to setup initial project for data pipeline? (requirements.txt and its significance.) * SQLAlchemy vs Direct Connections, what's best? (Discussion on when to use SQL Alchemy) * How to initialize a Git repository and manage code versioning? (git init, .gitignore, commit messages, branching basics) * How to read a table list from a file and load only specific tables? (using pandas) * How to externalize database properties for different environments? (config.py, OS environment variables, runtime configurations) * How to use the OS library to externalize database properties? (runtime configurations) * What are the best practices for creating clean and maintainable code? (Avoiding print statements, proper commenting) * Copy Command for bulk insert, when to use? (Incremental load or full load?) * When we should avoid database joins? (Join table for the performance issue, how to improve?) Timestamps: 00:00:00 — Introduction to Apache Spark - Setup Data Engineering Project 00:02:20 — Setting up the Project in PyCharm 00:39:56 — Using Git and GitHub for Version Control 00:53:53 — Creating a File with List of Tables to Load 00:59:34 — Reading Table List with Pandas This video is part of a comprehensive series on building data pipelines with Python. Be sure to check out the complete playlist for a step-by-step guide to mastering ETL processes and data engineering techniques. Full Playlist: https://www.youtube.com/playlist?list=PLf0swTFhTI8pRV9DDzae2o1m-cqe5PtJ2 Next Video: https://youtube.com/live/czJ0j-9FK08 🤔 Are you currently or have you ever built a Data Pipeline using these methods? Share your story in the comments! 👇 👍 Like & Subscribe for more data engineering tutorials and Python programming tips! #Python #ETL #MySQL #PostgreSQL #DataEngineering #Database #DataScience #Coding #Tutorial #TechCareer