Hey Pythonista,

We don't often talk about design patterns, because:

• usually, the Python Standard Library has you covered (and you might not even realize it) 😍

• some design patterns stemming from other languages (e.g. Java) are not considered Pythonic 🤔

But sometimes they can make your code more awesome.

Which brings us to Juanjo's new blog article about the Pipeline Pattern, which offers a flexible way to chain data processing steps, perfect for web scraping, data cleaning, and more.

👉 Why it matters: The Pipeline Pattern makes it easy to handle complex sequences of operations. Think of it as a conveyor belt for your data—each function does its job, then passes the data along. 🚀

In his article you’ll learn:

• How to use functools.reduce and partial to build a powerful pipeline.

• Real-world application with BeautifulSoup to parse and transform HTML tables.

• Key techniques to structure data efficiently into a DataFrame.

Go deeper here: https://pybit.es/articles/a-practical-example-of-the-pipeline-pattern-in-python/

Continue the discussion: https://pybites.circle.so/c/open-discussion/first-post-on-pybit-es

Have a great week!

Bob & Julian

P.S. Bigger apps require deeper design thinking. It's hard to get this from tutorials and study alone.

That's why we've created our PDI and PDM coaching programs where you can work on real world apps.

Building bigger, more complex apps with the help of an experienced coach is the most effective way to really grasp software design.

Check out the coaching and certifications here: https://pybit.es