Python - best practices
summary
Benchmarks and small scripts demonstrate concrete tradeoffs: prefer builtins for speed and clarity, fail‑fast shows ~0.005ms vs 0.013ms (≈50% faster), and deferred imports (e.g., numpy, urllib) avoid the import delay ~264ms cost when rarely needed. Memoize expensive pure functions — an LRU cache collapses recursive Fibonacci time to near‑zero. For loops vs listcomp vs map: list comprehensions win raw time, map wins readability at scale. Use ''.join over + for concatenation and generators to cut memory. Repository with code is provided.
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chapters (11)
- 0:00Python best practices intro
- 1:40Built-in methods for efficiency
- 3:27Fail fast for performance
- 5:34Import libraries only when needed
- 7:21Caching method outputs
- 9:28Loops vs list comprehensions vs map
- 11:33String join vs plus
- 12:56Dictionary get method
- 15:41Generators vs lists for memory
- 17:03Faster condition checks with 'in'
- 18:28Conclusion and repo
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