Functions & basics
Reusable building blocks — parameters, returns, scope, and clear function design.
How to Pipe Data Through a List of Transform Functions in Python
Applies a sequence of functions to an initial value using functools.reduce, creating a reusable pipe utility.
from functools import reduce
def pipe(data, *transforms):
return reduce(lambda value, func: func(value), transforms, data)
def double(x):
return x * 2
def add_one(x):
return x + 1
def to_string(x):
return f"Result: {x}"
if __name__ == "__main__":
initial = 5
result = pipe(initial, double, …How to Use functools.reduce in Python
Apply functools.reduce with operator functions and lambda expressions to aggregate lists into sums, products, maximums, and concatenated strings.
from functools import reduce
import operator
# Sum all numbers in a list using reduce
numbers = [1, 2, 3, 4, 5]
sum_result = reduce(operator.add, numbers)
# Find the maximum value using reduce
max_result = reduce(lambda a, b: a if a > b else b, numbers)
# Multiply all numbers using reduce
product_result = reduce(la…Browse by section
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Functions & basics — Python code examples
What you will find here
This page collects functions & basics snippets — short, copy-ready Python you can paste into our free online IDE and run without installing anything. Each sample includes a plain-English explanation and the full source code.
Samples vs tutorials and challenges
Samples are quick reference — one concept per page. For step-by-step teaching, use our Python tutorials. To test yourself, try quizzes or coding challenges. Clean up style with the Python formatter.