🧮 Map, Filter, Reduce

These three functions are classic tools in functional programming:

• map: transform each element
• filter: keep elements that match a condition
• reduce: combine all elements into one value

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✅ map

Apply a function to every element.

nums = [1, 2, 3]
squares = list(map(lambda x: x * x, nums))
# [1, 4, 9]

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✅ filter

Keep items that satisfy a predicate.

nums = [1, 2, 3, 4, 5]
evens = list(filter(lambda x: x % 2 == 0, nums))
# [2, 4]

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✅ reduce

Reduce combines values into a single result. In Python, it lives in functools.

from functools import reduce
nums = [1, 2, 3, 4]
total = reduce(lambda acc, x: acc + x, nums, 0)
# 10

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✅ Alternatives

Python also offers comprehensions, which are often clearer:

sq = [x * x for x in nums]
ev = [x for x in nums if x % 2 == 0]

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🔍 Key Takeaways

• map transforms, filter selects, reduce aggregates.
• Use lambdas for short logic, named functions for clarity.
• Comprehensions are often more readable in Python.

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Next: Closures