Functional Python Programming: Use a functional approach to write succinct, expressive, and efficient Python code

by Steven F. Lott, Ricardo Banffy

“Using this book has propelled my efficiency in solving leetcode challenges.” - Discord user, zizu
Python isn't all about object-oriented programming. Discover a valuable way of thinking about code design through a function-first approach – and learn when you need to use it. Now with detailed exercises at the end of every chapter!
Purchase of the print or Kindle book includes a free eBook in PDF format.

Key FeaturesLearn how, when, and why to adopt functional elements in your projectsExplore the Python modules essential to functional programming, like itertools and functoolsCover examples relevant to mathematical, statistical, and data analysis domainsBook DescriptionNot enough developers understand the benefits of functional programming, or even what it is. Author Steven Lott demystifies the approach, teaching you how to improve the way you code in Python and make gains in memory use and performance. If you’re a leetcoder preparing for coding interviews, this book is for you.
Starting from the fundamentals, this book shows you how to apply functional thinking and techniques in a range of scenarios, with Python 3.10+ examples focused on mathematical and statistical algorithms, data cleaning, and exploratory data analysis. You'll learn how to use generator expressions, list comprehensions, and decorators to your advantage. You don't have to abandon object-oriented design completely, though – you'll also see how Python's native object orientation is used in conjunction with functional programming techniques.
By the end of this book, you'll be well-versed in the essential functional programming features of Python and understand why and when functional thinking helps. You'll also have all the tools you need to pursue any additional functional topics that are not part of the Python language.What you will learnUse Python's libraries to avoid the complexities of state-changing classesLeverage built-in higher-order functions to avoid rewriting common algorithmsWrite generator functions to create lazy processingDesign and implement decorators for functional compositionMake use of Python type annotations to describe parameters and results of functionsApply functional programming to concurrency and web servicesExplore the PyMonad library for stateful simulationsWho this book is forThe functional paradigm is very useful for programmers working in data science or preparing for technical interviews, but any Python developer who wants to create more reliable, succinct, and expressive code will have much to learn from this book.
No prior knowledge of functional programming is required to get started, though Python programming knowledge is assumed. A running Python environment is essential.

Table of ContentsUnderstanding Functional ProgrammingIntroducing Essential Functional ConceptsFunctions, Iterators, and GeneratorsWorking with CollectionsHigher-Order FunctionsRecursions and ReductionsComplex Stateless ObjectsThe Itertools ModuleItertools for Combinatorics – Permutations and CombinationsThe Functools ModuleThe Toolz PackageDecorator Design TechniquesThe PyMonad LibraryThe Multiprocessing, Threa

576 pages, Kindle Edition

Published December 30, 2022

Reviews

[Parsa Parvizi · Rating 5 out of 5]

Steven F. Lott's "Functional Python Programming" is a deep dive into the functional paradigm within the context of Python. While undoubtedly a valuable resource for those seeking a comprehensive understanding of functional programming concepts, it's important to acknowledge that this book is not for the faint of heart.

The book does an excellent job of exploring the theoretical underpinnings of functional programming and demonstrating how they can be applied in Python. Lott's writing style is clear and concise, and he provides numerous examples to illustrate his points. However, the depth and breadth of the material can make it challenging for those who are new to functional programming or Python itself.

One of the strengths of this book is its thorough coverage of advanced topics such as monads, functors, and applicatives. These concepts can be quite abstract, but Lott does a commendable job of making them more accessible. However, the pace of the book can be quite brisk, and readers may find themselves needing to consult additional resources to fully grasp certain concepts.

While I appreciate the book's comprehensive approach, I believe that it would benefit from more introductory material for those who are new to functional programming. Additionally, while the examples are helpful, more practical applications of functional programming could have been included.

Here's where I'd like to add my personal opinion: I found "Functional Python Programming" to be a valuable resource for deepening my understanding of functional programming, but I must admit that it was quite challenging at times. The book assumes a certain level of familiarity with both Python and computer science theory, which may make it difficult for some readers to follow. For those who are just starting out with functional programming or Python, I would recommend exploring more introductory resources before diving into this book.

In conclusion, "Functional Python Programming" is a well-written and informative book that provides a deep dive into the world of functional Python. However, its advanced nature and lack of introductory material may make it challenging for some readers. If you are a seasoned Python programmer looking to expand your knowledge of functional programming, this book is definitely worth considering. However, if you are a beginner, I would suggest starting with a more approachable resource.