Functional Programming How To
7 days ago
- #iterators
- #functional-programming
- #python
- Functional programming in Python focuses on decomposing problems into sets of functions that ideally only take inputs and produce outputs without internal state affecting the output.
- Python supports multiple programming paradigms, including procedural, object-oriented, and functional programming, allowing different approaches within the same program.
- Functional programming avoids side effects, meaning functions should not modify internal state or make changes not visible in the function's return value.
- Key advantages of functional programming include formal provability, modularity, composability, and ease of debugging and testing.
- Iterators are a foundational feature for functional-style programming in Python, representing a stream of data that returns elements one at a time.
- Generators simplify the creation of iterators by using the `yield` keyword to produce a stream of values, allowing functions to resume execution where they left off.
- Python's built-in functions like `map()`, `filter()`, and `reduce()` are commonly used in functional programming to process iterables without explicit loops.
- The `itertools` module provides a variety of tools for creating and combining iterators, including functions for infinite sequences, combinatorics, and grouping elements.
- The `functools` module offers higher-order functions, with `partial()` enabling partial function application by fixing certain arguments of a function.
- Lambda expressions can be used to create small anonymous functions, though they are limited to single expressions and may reduce code readability for complex operations.