Functional Data I/O and Analysis

This unit teaches practical functional programming techniques for accessing, transforming, and analyzing real-world datasets using Haskell and Python. Students will learn command-line and file I/O, binary data handling, core functional constructs (pattern matching, recursion, mapping, reduction), basic tooling (Jupyter magic, installation testing), and debugging strategies to prepare for higher-level application and performance topics in subsequent units.

Learning Objectives

• Demonstrate how to set up and verify Haskell and Python environments and use the command line and Jupyter magic functions to run scripts and load datasets
• Apply file and binary I/O techniques to locate, open, read, and write datasets and audio/vector data formats using appropriate libraries (e.g., PyAudio, vect, Hascore)
• Analyze and transform data using functional programming constructs—pattern matching, recursion, mapping, reduction, and parameterized types—to implement reproducible data-processing pipelines
• Evaluate and resolve common Haskell- and Python-related errors by applying debugging practices and quick-fix strategies to ensure reliable execution of example code and data analyses