Understanding Python Higher‑Order Functions: map, filter, sorted, reduce and Practical Examples

In Python, a higher‑order function is a function that can take another function as an argument or return a function as a result. Examples include map , filter , sorted and reduce .

1. map – mapping function

def func1(x, y, f): return f(x) + f(y) num = func1(-10, 2, abs) print(num)

The map function applies a given function to each item of one or more iterables and returns an iterator. Example:

lst = [1,2,3,4,5,6,7] lst2 = [10,100,1000,10000] def f1(x, y): return x + y print(list(map(f1, lst, lst2))) print(list(map(lambda x, y: x + y, lst, lst2)))

Convert a list of integers to strings using map :

lst = [1,2,3,4,5] print(list(map(str, lst)))

2. filter – filtering function

print(list(filter(lambda x: x % 2, [1,2,3,4,5,6,7,8,9])))

Filter a list to keep only truthy values after stripping whitespace and removing falsy elements:

lst = ['A','', 'B', None, 'C',' ', 'a', 1, 0] print(list(filter(lambda x: x and str(x).strip(), lst)))

3. sorted – sorting function

Sort a list of strings case‑insensitively:

list1 = ['bob', 'about', 'Zoo', 'Credit'] print(sorted(list1, key=lambda x: x.lower())) print(sorted(list1, key=str.lower))

Sort a dictionary by its values:

d1 = {"a":3, "b":4, "c":2, "d":5} print(dict(sorted(d1.items(), key=lambda x: x[1])))

4. reduce – cumulative reduction

Concatenate a list of numbers into a single integer:

from functools import reduce s = [1,3,5,7,9] print(reduce(lambda x, y: x*10 + y, s))

Calculate the factorial of a number using reduce :

from functools import reduce n = [1,2,3,4,5,6,7] print(reduce(lambda x, y: x*y, n))

5. Practice exercises

Use map to validate usernames against a regular expression, then filter the valid ones:

lst = ["username","a123","Y_78ju","23hu","was23_67hu"] import re def func1(x): if re.findall(r"^[a-zA-Z_][0-9a-zA-Z_]{5,17}$", x): return f"{x}符合规范" else: return f"{x}不符合规范" print(list(map(func1, lst))) print(list(filter(lambda x: re.findall(r"^[a-zA-Z_][0-9a-zA-Z_]{5,17}$", x), lst)))

Find numbers from 1 to 100 divisible by 3:

print(list(filter(lambda x: x % 3 == 0, range(1, 101))))

Compute squares of numbers 1‑10 using map :

print(list(map(lambda x: x*x, range(1, 11))))

Convert a list of digits into a concatenated string using reduce :

print(reduce(lambda x, y: str(x)+str(y), [1,4,5,9]))

Sort a mixed list of positive and negative integers so that positives appear first, then negatives ordered by absolute value:

list1 = [7, -8, 5, 4, 0, -2, -5] print(sorted(list1, key=lambda x: (x <= 0, abs(x)))) print(sorted(list1, key=lambda x: max(list1)-x+1 if x <= 0 else x))

Custom string sorting where the order is: lowercase < uppercase < odd digit < even digit:

s = 'asdf234GDSdsf23' s2 = "".join(sorted(s, key=lambda x: (x.isdigit(), x.isdigit() and int(x) % 2 == 0, x.isupper(), x))) print(s2)

These examples illustrate how higher‑order functions enable concise, functional‑style data processing in Python.