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Functional Programming

6 Topics
1

Pure Functions

Understanding pure functions — deterministic outputs, no side effects, referential transparency, and their role in testable, predictable code.

Core functional programming concept — interviewers value candidates who understand side effects and write predictable code.
2

Immutability

Immutable data patterns in Python — using tuples, frozensets, NamedTuples, and functional update patterns to avoid mutation bugs.

Shows understanding of defensive programming and functional design principles.
3

functools Module

The functools standard library — partial application, reduce, lru_cache memoization, singledispatch, and wraps for building composable functional utilities.

reduce, partial, and lru_cache are common interview topics — shows mastery of Python functional tools.
4

Currying and Partial Application

Transforming multi-argument functions into chains of single-argument functions, and freezing arguments with partial application.

Advanced functional concept — shows understanding of function transformation and composability.
5

Function Composition

Combining simple functions into complex pipelines — compose, pipe, and building reusable data transformation chains.

Functional design pattern — shows ability to build complex logic from simple, testable pieces.
6

Monads in Python

Monad-like patterns in Python — Optional/Maybe, Result/Either, and the pipeline operator pattern for safer error handling without exceptions.

Advanced pattern — shows knowledge of functional error handling and type-safe design.
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