If you’re working with recursive functions in Python, like tree traversal, backtracking, or graph problems, you might have seen the RecursionError: maximum recursion depth exceeded. This error can be confusing if you’re not sure whether it’s a bug or just a language limitation. Here’s what’s really going on and how to fix it.
Description of the Problem
If you are working on a Python project, or have worked on some previously, you must have noticed this kind of error message when trying recursion in Python.
RecursionError: maximum recursion depth exceededThis often pops up when you’re trying to solve a problem using recursion and Python hits its internal limit on how many times a function can call itself.
Why This Happens
Python is designed to prevent programs from crashing due to infinite recursion. The general limit for recursions in Python is set to 1000 levels deep. However it can change for different versions and platforms.
You’ll run into this error if:
| Cause | Explanation |
| Function goes too deep | Happens when working with large structures like trees or graphs, where the recursion can easily exceed the default limit. |
| Missing or incorrect base case | If the base case is missing or not properly written, the function keeps calling itself and never stops. |
| Recursion used instead of a loop | Sometimes recursion is used where a simple loop would be more efficient and safer, leading to unnecessary depth. |
Best Practices to avoid this:
- Always define clear and correct base cases
- Rewrite recursive logic using loops when feasible
- Only increase recursion limits when absolutely necessary
- Be cautious, deep recursion isn’t always the best design choice in Python
Steps to Resolve the “maximum recursion depth exceeded” error in Python
Step 1: Check for a Missing or Faulty Base Case
Most recursion problems need a base case to exit the recursion.
Incorrect example (missing base case):
def countdown(n): print(n) return countdown(n - 1)
countdown(5)This runs forever.
Corrected Version
def countdown(n): if n <= 0: return print(n) return countdown(n - 1)
countdown(5)Step 2: Refactor to Use Iteration (If Possible)
If your recursion depth goes too high, consider rewriting it using loops.
Recursive factorial (can hit limit at high N):
def factorial(n): return 1 if n == 0 else n * factorial(n - 1)Iterative version (safe for large N):
def factorial(n): result = 1 for i in range(2, n + 1): result *= i return resultStep 3: Increase the Recursion Limit (With Caution)
If you’re sure your code is correct and just needs deeper recursion (e.g., parsing a large tree), you can raise the recursion limit:
import sys
sys.setrecursionlimit(3000)Warning: Increasing the recursion limit too much can cause your program to crash with a segmentation fault or stack overflow. Do this only if you’re confident your code is not stuck in infinite recursion.
Step 4: Use Tail Recursion Optimization (Not Native in Python)
Python does not support tail-call optimization like some other languages. If you rely on deeply recursive logic, try to rewrite the logic iteratively, or use a language like Scheme or Scala for such cases.
However, libraries like stackless Python or third-party approaches may offer alternatives if recursion is essential.
Quick Recap: Best Practices for Avoiding maximum recursion depth Problem
The RecursionError: maximum recursion depth exceeded occurs when a recursive function exceeds Python’s internal call stack limit. This is often due to missing base cases or excessive recursion.
Best Practices:
- Always define clear and correct base cases
- Rewrite recursive logic using loops when feasible
- Only increase recursion limits when absolutely necessary
- Be cautious — deep recursion isn’t always the best design choice in Python
Conclusion
Deep recursion can trigger errors fast in Python if you’re not careful with how the function exits. If your project involves complex recursive logic, it might be smarter to hire Python developers who can help you avoid these traps and write cleaner, more efficient code.
