Writing parallel code in a readable way

This article discusses a Python-based approach to writing parallel code that remains readable and easy to debug, particularly for embarrassingly parallel problems. The author introduces a custom tool using a 'delayed' decorator and a 'Parallel' object that allows developers to write map/reduce-style code with list comprehensions, making it look like standard procedural code. Key features include a simple switch to run code serially (n_jobs=1) for debugging, automatic pickling checks to avoid errors, and a uniform API that can encapsulate various fork/join-based parallel libraries. The tool evolved into the joblib project. This is relevant to IT/technology as it covers parallel computing, Python programming, and software development best practices.