The Power of Function Composition
summary
Combinators from SKI calculus become practical tools across Haskell, APL, J, BQN, Jelly, Wewa, Clojure and Python, with concrete demos converting a naive index-and-loop parity check into a single compositional expression; the talk live-codes APL/BQN/J and shows a browser Jello tool that emits Jelly plus Python/C++ libraries (dovekey, blackbird) used to express S combinator and map-adjacent. The takeaway: these operators map directly to map/reduce patterns that are easier to parallelize and accelerate, and the demos all run in web editors shown on screen.
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chapters (14)
- 0:00Function composition intro
- 5:22Combinators and pure functions
- 10:33Elementary combinators
- 15:28Special array problem in Python
- 22:25Haskell’s S combinator
- 27:16Clojure threading macro
- 27:37Array languages and trains
- 29:02Live coding in APL
- 31:50Live coding in BQN
- 33:16Live coding in J
- 35:07Live coding in Jelly
- 37:54Live coding in Weva
- 38:37Composition strategies summary
- 40:02Conclusion
