Further Reading: Recursion

Foundational Texts

Abelson, H. & Sussman, G. J. (1996). Structure and Interpretation of Computer Programs (SICP), 2nd Ed. MIT Press. (Tier 1) The gold standard for learning recursive thinking. Its Chapter 1 builds recursive functions from first principles in Scheme. MIT Press hosts the full text free online at mitp-content-server.mit.edu/books/content/sectbyfn/books_pres_0/6515/sicp.zip/full-text/book/book.html. Even if you never write Scheme, the recursive thinking exercises will permanently change how you approach problems.
Downey, A. (2024). Think Python, 3rd Edition. O'Reilly Media. (Tier 1) Its Chapter 5, "Conditionals and Recursion," covers recursion with a practical, Python-focused approach, including stack diagrams for recursive calls. Good as a second perspective if the presentation in this chapter didn't fully click. Available free online at allendowney.github.io/ThinkPython.

Roberts, E. (2006). Thinking Recursively with Java. Wiley. (Tier 1) Despite the Java title, this is one of the best books ever written on developing recursive thinking skills (it's the 20th-anniversary update of Roberts's 1986 Thinking Recursively). The emphasis is on the "leap of faith" approach -- trusting the recursive call -- rather than tracing executions. The examples translate directly to Python.
Friedman, D. P. & Felleisen, M. (1996). The Little Schemer, 4th Ed. MIT Press. (Tier 1) A unique, dialogue-style book that teaches recursion through a series of questions and answers. Builds recursive thinking from absolute zero to surprisingly sophisticated concepts in just over 200 pages. A cult classic for a reason.

Bhargava, A. (2016). Grokking Algorithms. Manning. (Tier 1) Its Chapter 3 covers recursion with excellent visual explanations, and Chapter 9 introduces dynamic programming, the technique that grows out of memoization. (A second edition appeared in 2024.) The illustrations of call stacks and recursive trees are some of the best in any introductory text.
Python documentation: functools.lru_cache and functools.cache. (Tier 1) docs.python.org/3/library/functools.html Official documentation for Python's built-in memoization decorators. Includes usage examples, performance notes, and the difference between @cache (unbounded) and @lru_cache (bounded by size).

Mandelbrot, B. (1982). The Fractal Geometry of Nature. W.H. Freeman. (Tier 2) The foundational text on fractal geometry by the mathematician who coined the term. Dense but fascinating. Demonstrates how recursive self-similarity appears throughout nature.
Shiffman, D. The Nature of Code, Chapter 8: Fractals. (Tier 1) Available free at natureofcode.com/fractals. A beautifully illustrated, code-heavy introduction to fractals. The examples are in Processing/p5.js but translate easily to Python's turtle module.

Van Rossum, G. (2009). "Tail Recursion Elimination." Neopythonic blog. (Tier 1) Python's creator explains why Python doesn't do tail call optimization: lost tracebacks, code that would break on implementations without it, and his view that recursion shouldn't be the basis of all programming. Short and essential for understanding Python's design philosophy around recursion. neopythonic.blogspot.com/2009/04/tail-recursion-elimination.html
Python documentation: os.walk(). (Tier 1) docs.python.org/3/library/os.html#os.walk The standard library function for traversing directory trees. Through Python 3.11 it was a recursive generator; since 3.12 it keeps an explicit stack of directories instead, so very deep trees can't trigger RecursionError. Comparing the two versions of its source is a great lesson in turning recursion into iteration.

Pythontutor.com — Recursion visualizations. (Tier 1) pythontutor.com Paste any recursive Python function and watch the call stack build and unwind step by step. Invaluable for developing intuition about how recursive calls work.
Computerphile (YouTube): "What on Earth is Recursion?" and "The Most Difficult Program to Compute?" (2014). (Tier 2) Professor David Brailsford explains recursion, then the Ackermann function, a recursive function whose values grow so explosively that it can't be computed with simple counted loops alone. Good for building appreciation of recursion's theoretical significance.

Hofstadter, D. (1979). Gödel, Escher, Bach: An Eternal Golden Braid. Basic Books. (Tier 2) A Pulitzer Prize-winning exploration of self-reference, recursion, and consciousness through the lens of mathematics, art, and music. Not a programming book, but it will permanently deepen your appreciation for recursive structures. A challenging but rewarding read.