Function Composition

Concepts covered: pyFunctools

Function composition means combining simple functions to build complex operations. The output of one function becomes the input of the next. This is a core concept in functional programming. Data pipelines are perfect examples of composition. Raw data flows through a series of transformation functions: clean, validate, transform, aggregate, format. Each function does one thing well. Manual Composition The simplest form of composition is calling functions in sequence, where each function takes the previous result: Each function takes text and returns modified text. We chain them together to build the final result. The functions are reusable - you can combine them in different ways. Creating a Compose Function We can create a higher-order function that composes two functions into one new fun

About This Interactive Section

This section is part of the Functional Programming: Advanced lesson on DataDriven, a free data engineering interview prep platform. Each section includes explanations, worked examples, and hands-on code challenges that execute in real time. SQL queries run against a live PostgreSQL database. Python runs in a sandboxed Docker container. Data modeling problems validate against interactive schema canvases. All content is framed around what data engineering interviewers actually test at companies like Meta, Google, Amazon, Netflix, Stripe, and Databricks.

How DataDriven Lessons Work

DataDriven combines four interview rounds (SQL, Python, Data Modeling, Pipeline Architecture) with adaptive difficulty and spaced repetition. Easy problems get harder as you improve. Weak concepts resurface until you master them. Your readiness score tracks progress across every topic interviewers test. Every lesson section ends with problems you solve by writing and running real code, not by picking multiple-choice answers.