How to Compose Two Functions into a Single Callable in Python

Combine two Python functions into a single callable using a compose helper, then apply the chained call.

Easy Python 3.9+ Aug 9, 2026 Functions & basics 13 views 0 copies

functions composition lambda functional

Python code

18 lines
Python 3.9+
Run it 
def add_one(x):
    return x + 1

def double(x):
    return x * 2

def compose(f, g):
    return lambda x: f(g(x))

add_then_double = compose(double, add_one)
double_then_add = compose(add_one, double)

result1 = add_then_double(5)
result2 = double_then_add(5)

print(f"add_one then double(5) = {result1}")
print(f"double then add_one(5) = {result2}")
print(f"Add requires one arg, compose chains two functions: {type(add_then_double).__name__}")

Output

stdout 
add_one then double(5) = 12
double then add_one(5) = 11
Add requires one arg, compose chains two functions: function

How it works

The compose function returns a lambda that applies the second function g first, then passes the result to f. This creates a new callable that behaves like a single function. The order matters: compose(double, add_one) means add_one runs first, then double. The lambda captures the functions f and g from the enclosing scope, allowing the composed callable to be reused. This pattern is a classic way to build pipelines without nesting calls manually.

Common mistakes

  • Reversing the argument order in compose and accidentally calling f before g.
  • Assuming compose mutates the original functions instead of returning a new callable.
  • Forgetting that the composed callable still needs an argument when you call it.

Variations

  1. Use a decorator syntax with `@compose(double, add_one)` for reusable composition.
  2. Chain more than two functions by nesting compose calls, e.g., compose(f, compose(g, h)).

Real-world use cases

  • Building a data transformation pipeline that applies data cleaning then feature scaling.
  • Creating middleware in web frameworks that chains request processing steps.
  • Constructing math functions for functional programming patterns in finance models.

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