Resources

Resources and popular libraries that will help you with development!

1. Caching in Python - Overview
2. Memoization (Video)
3. Multiprocessing in Python (Video)
4. Diagnosing slow Python code. (Video)
5. Numpy Docs
6. SQLite Cheatsheet
7. SQLite Online Viewer

Tips and tricks for optimization:

• Use numpy wherever possible! It uses C behind the scenes, which isn’t slowed down by the Python GIL
• Multiprocessing and caching are your best friends - they are integral to doing operations on so many rows (over 600,000)!
• SQLite is highly optimized with its queries: look into how different queries affect performance