meal-scheduler VS data_engineering_on_gcp_book

I use Minizinc in a personal toy project (https://gitlab.com/dustin-space/meal-scheduler), and GECODE or Google's ortools solver at the backend. It's used for meal planning. Unfortunately it's way way slower than I'd hope. I suspect I just have the domain not modeled efficiently. Maybe if I had a few days to put into it, and learn how to properly debug the CSP solver step by step, it might help...

That sounds like a fun application, both the usage and the implementation.

I wonder if you have any interesting example data-files that could be used with the model, preferable both something small and something larger? Would be fun to test the model locally to see how it behaves.

Notes: I'm assuming here that https://gitlab.com/dustin-space/meal-scheduler/-/blob/master... is the model used.

This book will walk you through setting up a complete data engineering stack on GCP: https://github.com/Nunie123/data_engineering_on_gcp_book

As for resources, this book goes over a lot of these: https://github.com/Nunie123/data_engineering_on_gcp_book. However, this goes over the 'how', not the 'why'. The only method I know for understanding the 'why' is experience. Whether at work or personal projects.

Here's a good book to follow along to introduce you to common tooling and design patterns: https://github.com/Nunie123/data_engineering_on_gcp_book

I'm not sure if this is exactly what you're looking for, but here's a book on GitHub that talks about the tools and steps for building data pipelines into a data warehouse: https://github.com/Nunie123/data_engineering_on_gcp_book

Check out this book: https://github.com/Nunie123/data_engineering_on_gcp_book

If you're interested in example of how to build a complete data engineering infrastructure, you should check out this book: https://github.com/Nunie123/data_engineering_on_gcp_book

If you want to try Airflow without the setup headache, you can try Composer on GCP, which is a hosted version of Airflow. I wrote some info on how to do that here: https://github.com/Nunie123/data_engineering_on_gcp_book/blob/master/ch_2_orchestration.md

This book might be a good resource for you: https://github.com/Nunie123/data_engineering_on_gcp_book

If you want a place to start on personal projects you can check out this book, https://github.com/Nunie123/data_engineering_on_gcp_book, which will walk you through the basics of setting up a full data engineering stack.

If you are interested in tooling, here's a free book on setting up a basic data engineering tech stack on GCP: https://github.com/Nunie123/data_engineering_on_gcp_book