Pipeline stage compose functions left to right in Python

Compose multiple functions into a left-to-right pipeline so each stage receives the output of the previous one.

Easy Python 3.9+ Aug 9, 2026 Data pipelines & processing 16 views 0 copies

composition pipeline functional closures

Python code

22 lines

Python 3.9+

def compose(*funcs):
    """Compose functions left to right: compose(f, g, h)(x) == h(g(f(x)))"""
    def composed(arg):
        result = arg
        for func in funcs:
            result = func(result)
        return result
    return composed

if __name__ == "__main__":
    def add_one(x):
        return x + 1

    def double(x):
        return x * 2

    def square(x):
        return x ** 2

    pipeline = compose(add_one, double, square)
    result = pipeline(3)
    print(f"Result: {result}")  # ((3 + 1) * 2) ** 2 = 64

Output

stdout

Result: 64

How it works

The compose function returns a new function that chains the input functions in the order they were passed. When called, it starts with the initial argument and passes it through each function sequentially, updating the result at every step. The left-to-right order matches the way data flows through a pipeline: compose(f, g, h)(x) is equivalent to h(g(f(x))). This differs from the traditional mathematical compose in many libraries, which applies functions right-to-left. The implementation uses a closure over funcs so the composed callable remembers its stages, and it gracefully handles a single stage or even an empty list by returning the input unchanged.

Common mistakes

Confusing left-to-right composition with the right-to-left order used by functools.reduce or math-style compose
Assuming the pipeline is applied in reverse order when reading `compose(f, g, h)`
Forgetting that each function must accept exactly one argument since the pipeline passes a single value through
Mutating shared state inside stage functions, which can break reusability of the composed pipeline

Variations

Use `functools.reduce(lambda acc, f: lambda x: f(acc(x)), funcs, lambda x: x)` for a functional one-liner
Create an async version with `await` between stages for I/O-heavy pipelines

Real-world use cases

Chaining data transformation stages like parsing, cleaning, and normalizing records in an ETL job.
Building a request processing pipeline where each middleware stage enriches or validates the payload.
Composing image processing steps such as resize, filter, and watermark in a batch media workflow.

Pipeline stage compose functions left to right in Python

Python code

Output

How it works

Common mistakes

Variations

Real-world use cases

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Real-world use cases

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