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. Chapter 1 builds recursive functions from first principles in Scheme. Available free online at mitpress.mit.edu/sites/default/files/sicp/full-text/book/book.html. Even if you never write Scheme, the recursive thinking exercises will permanently change how you approach problems.
Downey, A. (2015). Think Python, 3rd Edition. O'Reilly Media. (Tier 1) Chapter 5 covers recursion with a practical, Python-focused approach. Good as a second perspective if the presentation in this chapter didn't fully click. Available free online.

Roberts, E. (2006). Thinking Recursively with Java. Wiley. (Tier 1) Despite the Java title, this is the best book ever written on developing recursive thinking skills. 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 under 200 pages. A cult classic for a reason.

Bhargava, A. (2016). Grokking Algorithms. Manning. (Tier 1) Chapter 3 covers recursion with excellent visual explanations, and later chapters introduce dynamic programming (the generalization of memoization). 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. 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 will never have tail call optimization. Essential reading for understanding Python's design philosophy around recursion. Search for "Guido van Rossum tail recursion" to find the blog post.
Python documentation: os.walk(). (Tier 1) docs.python.org/3/library/os.html#os.walk The standard library function for traversing directory trees. Understanding how it works (recursive generator) deepens your understanding of both recursion and generators.

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): "Recursion" and "The Most Difficult Program to Compute?" (Tier 2) Accessible video explanations of recursion and the Ackermann function (a function that grows so fast it can't be expressed with standard mathematical notation). Good for building appreciation of recursion's theoretical significance.

Hofstadter, D. (1979). Godel, 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.