Books:
- Python Data Science Handbook https://jakevdp.github.io/PythonDataScienceHandbook/
2)O'reilly
• Architecture Patterns with Python (how to structure larger projects sanely)
• Test-Driven Development with Python (how to know your code will run reliably, and how to prove it to seasoned devs) Designing Data Intensive Applications (reduces workload when it's obvious that performance will be strained, solves common problems for you)
• Python for Devops (the stuff in here seriously makes life/workflow easier if you let it, but if you don't think you need it then you don't)
3)Not O'reilly and not in Python, but honorable mentions:
• Domain Driven Design Eric Evans (how to keep code from becoming a ball of mud)
• Design Patterns gang of 4 (how to say a thousand words to another developer in under 6 seconds)
• Clean Code Robert Martin (why your code sucks and what to do about it)
4)Asha's Book
5)Automate the Boring Stuff with Python, 2nd Edition (Al Sweigart)
Goal:
- Learn 30 mins + Daily
- Write Notes for each book