Join 📚 Kevin's Highlights
A batch of the best highlights from what Kevin's read, .
[](https://dezyre.gumlet.io/images/blog/real-world-data-engineering-projects-/Data_Engineering_Project_Structure.png?w=700&dpr=1.3%20%22Data%20Engineering%20Project%20Structure%22)
Data Engineering Projects for Beginners
ProjectPro
🌟 Introducing the top 5 Python testing tools that every developer should have in their toolkit 🌟
1️⃣ Pytest:
A powerful and easy-to-use testing framework.
Say goodbye to test classes
and hello to simple test functions! 👋
2️⃣ Unittest:
The classic.
It's built-in, it's reliable, and it's been around for ages.
A true Python staple. 🐍
3️⃣ Mock:
Isolate and rule the world! 🌍
Replace parts of your system under testing with mock objects
and focus on what really matters.
4️⃣ Tox:
Test your code in various Python environments.
Ensure compatibility and make your code versatile! 🌐
5️⃣ Hypothesis:
Property-based testing made easy.
Generate test cases automatically
and put your code through its paces. 🏃
Sarah Floris, MS’ Post
Sarah Floris, MS
I delineate them by the range of changes considered:
**responsible AI** seeks to *make the AI less harmful*,
**ethical AI** *challenges if AI should even be used* in certain applications, and
**just AI** argues that *AI applications must actively challenge oppression* (if this is even possible).
Classification for AI Ethics
@willie_agnew on Twitter
...catch up on these, and many more highlights