This is a note quoted from ‘Mastering Machine Learning with Python in Six Steps’ by data scientist Manohar
1. Beautiful is better than ugly — be consistent.
2. Complex is better than complicated — use existing libraries.
3. Simple is better than complex — keep it simple and stupid (KISS).
4. Flat is better than nested — avoid nested ifs.
5. Explicit is better than implicit — be clear.
6. Sparse is better than dense — separate code into modules.
7. Readability counts — indenting for easy readability.
8. Special cases aren’t special enough to break the rules — everything is an object.
9. Errors should never pass silently — good exception handler.
10. Although practicality beats purity — if required, break the rules.
11. Unless explicitly silenced — error logging and traceability.
12. In ambiguity, refuse the temptation to guess — Python syntax is simpler; however, many times we might take a longer time to decipher it.
13. Although that way may not be obvious at first unless you’re Dutch — there is not only one of way of achieving something.
14. There should be preferably only one obvious way to do it — use existing libraries.
15. If the implementation is hard to explain, it’s a bad idea — if you can’t explain in simple terms then you don’t understand it well enough.
16. Now is better than never — there are quick/dirty ways to get the job done rather than trying too much to optimize.
17. Although never is often better than *right* now — although there is a quick/dirty way, don’t head in the path that will not allow a graceful way back.
18. Namespaces are one honking great idea, so let’s do more of those! — be specific.
19. If the implementation is easy to explain, it may be a good idea — simplicity.