Python is a really useful tool whilst developing data engineering pipelines. Working in VS Code gives you access to a heap of plugins which can automatically format your code to make it easier to read and even identify your errors. I'll be using PyLint.

Why use PyLint?

1. Prevents Bugs in Data Pipelines

ETL scripts often involve numerous variables, file paths, and transformations. A single typo or forgotten import can break an entire pipeline. PyLint helps by catching these errors before you even run your code.

2. Improves Code Readability

Readable code is easier to debug and maintain. By suggesting better variable names, flagging overly complex functions, and pointing out missing docstrings, PyLint ensures your code remains understandable.

3. Encourages Best Practices

PyLint identifies anti-patterns and suggests improvements. For example, it might warn you about accessing variables before initialization.

How do I get going with PyLint?

I'm going to assume that if you're reading this you are already using Python in VS Code.

1. Open the Extensions menu and search for PyLint
2. Install PyLint
3. Go to the VS Code settings by selecting the cog in the bottom left hand corner and selecting settings
4. Find the default formatter setting and select PyLint

May all you code be pretty 💖 (and light mode is better)