Part 9- Data Testing Automation Framework | Run test cases from excel using pytest (1)
Description-
🚀 What You’ll Learn in This Project
In this video, you’ll learn how to build a complete data automation framework using Python, Pandas, Supabase (Postgresql) and Pytest — from scratch!
We’ll start by downloading a CSV dataset from Kaggle, upload it into Supabase as a table, and then automate various data validation test cases using Pytest. You’ll see how to connect Supabase to Python, perform count and transformation checks, and finally generate a professional HTML test report.
By the end of this project, you’ll have a fully working data testing automation framework that’s scalable, modular, and easy to extend for real-world projects.
Topics-
Read test cases from an excel file as parameters through Pytest
Run each test cases one by one
Validate source (csv) results vs target (Postgres)
💡 Tech Stack: Python | Pytest | Supabase (Postgres) | Pandas
📊 Source: CSV dataset from Kaggle
Link to Download Kaggle Data Set- https://www.kaggle.com/datasets/vivek...
Full Code GitHub Link- https://github.com/Jyoti13394/datates...
Link to Download PyCharm- https://www.jetbrains.com/pycharm/dow...
Link to create a free account in Supabase- • Part 3- Data Testing Automation Framework ...
Link to video to fetch Postgres Connection Details- • Part 6- Data Testing Automation Framework ...
#DataTesting #Pytest #Postgres #PythonAutomation #ETLTesting #DataQA #AutomationFramework #DataEngineering #Pandas #SDET