Functional Programming in Python
summary
Functional Python emphasizes concrete techniques: using map and filter, list comprehensions, generators and lambdas to transform sequences; leveraging functools partial to build reusable predicates like an evens function; preferring iterator-based streaming with itertools takewhile/dropwhile to avoid large memory use; using reduce/fold and unfold patterns for aggregation and generation; noting recursion depth limits and when a manual loop is clearer; and applying map‑reduce style parallelism when side‑effect‑free computation yields performance.
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chapters (11)
- 0:00Functional programming intro
- 3:31What is FP
- 7:06Functions as first-class objects
- 10:12Lambda expressions
- 13:45List comprehensions
- 17:12Filter and predicates
- 20:43Partial function application
- 22:09Mapping sequences
- 24:17Folding sequences
- 27:24Functional programming in web frameworks like Django
- 28:58Resources & closing
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