# Fix: "RecursionError: maximum recursion depth exceeded" in Python

## Introduction

Python is known for its simplicity and readability. Although, even in Python, you may occasionally stumble upon errors that don't make a lot of sense at first glance. One of those errors is the `RecursionError: maximum recursion depth exceeded`

.

This Byte aims to help you understand what this error is, why it occurs, and how you can fix it. A basic understanding of Python programming, particularly functions, is recommended.

## Recursion in Python

Recursion is a fundamental concept in computer science where a function calls itself in its definition. It's a powerful concept that can simplify code for the right problem, making it cleaner and more readable. However, it can also lead to some tricky errors if not handled carefully.

Let's take a look at a simple recursive function in Python:

```
def factorial(n):
"""Calculate the factorial of a number using recursion"""
if n == 1:
return 1
else:
return n * factorial(n-1)
print(factorial(5))
```

When you run this code, it will prints `120`

, which is the factorial of 5. The function `factorial`

calls itself with a different argument each time until it reaches the base case (n == 1), at which point it starts returning the results back up the call stack.

## The RecursionError

So what happens if a recursive function doesn't have a proper base case or the base case is never reached? Let's modify the above function to find out:

```
def endless_recursion(n):
"""A recursive function without a proper base case"""
return n * endless_recursion(n-1)
print(endless_recursion(5))
# RecursionError: maximum recursion depth exceeded
```

When you run this code, you'll encounter the `RecursionError: maximum recursion depth exceeded`

. But why does this happen?

**Note:** Python has a limit on the depth of recursion to prevent a stack overflow. The maximum depth is platform-dependent but is typically around 1000. If you exceed this limit, Python raises a `RecursionError`

.

## Causes of RecursionError

The `RecursionError: maximum recursion depth exceeded`

is a safety mechanism in Python. It prevents your program from entering an infinite loop and using up all the stack space. This error usually occurs when:

- The base case of a recursive function is not defined correctly, or
- The recursive function doesn't reach the base case within the maximum recursion depth.

In the `endless_recursion`

function above, there is no base case, which causes the function to call itself indefinitely and eventually exceed the maximum recursion depth.

## Fixing the RecursionError

When you get a `RecursionError`

, you probably now understand that your code has gone too deep into recursion. So, how do we fix this?

First and foremost, you'll need to review your code and understand why it's causing infinite recursion. Often, the problem lies in the base case of your recursive function. Make sure that your function has a condition that stops the recursion.

Going back to our previous example that causes a `RecursionError`

:

```
def endless_recursion(n):
"""A recursive function without a proper base case"""
return n * endless_recursion(n-1)
endless_recursion(5)
```

To fix this, we need to add a base case that stops the recursion when `n`

is less than or equal to 0:

```
def endless_recursion(n):
if n <= 0:
return n
return n * endless_recursion(n-1)
endless_recursion(5)
```

Sometimes, despite having a base case, you might still exceed the maximum recursion depth. This can happen when you're dealing with large inputs. In such cases, you can increase the recursion limit using `sys.setrecursionlimit()`

.

```
import sys
sys.setrecursionlimit(3000)
def recursive_function(n):
if n <= 0:
return n
return recursive_function(n-1)
recursive_function(2500)
```

**Warning:** Be cautious when changing the recursion limit. Setting it too high can lead to a stack overflow and crash your program. Always balance the need for deeper recursion against the available system resources.

## Maximum Recursion Depth in Python

Python's `sys`

module allows us to access the default maximum recursion depth. You can find out the current setting with the `getrecursionlimit()`

function. Here's how you can check it:

```
import sys
print(sys.getrecursionlimit())
```

This will typically output `1000`

, although it may vary depending on the platform.

### Modifying the Maximum Recursion Depth

We briefly touched on this earlier, but it's worth going in a bit more depth. While it's generally not recommended, you can modify the maximum recursion depth using the `setrecursionlimit()`

function from the `sys`

module.

```
import sys
sys.setrecursionlimit(2000)
```

This sets the recursion limit to 2000 calls, allowing for deeper recursion.

Increasing the recursion depth allows your recursive functions to make more calls, which can be useful for algorithms that naturally require deep recursion. However, this comes at the cost of increased memory usage and potential system instability.

Reducing the recursion depth can make your program more conservative in terms of resource usage, but it can also make it more prone to `RecursionError`

even when the recursion is logically correct.

### Using Recursion Depth in Debugging

One way to debug these kinds of issues is to print the current depth of each recursive call. This can help you see if your function is approaching the maximum limit or if the recursion isn't making progress toward the base case as expected.

```
def factorial(n, depth=1):
print(f"Current recursion depth: {depth}")
if n == 1:
return 1
else:
return n * factorial(n-1, depth + 1)
print(factorial(5))
```

In this example, the `depth`

argument is used to keep track of the current recursion depth. This kind of debug output can be really useful when trying to understand why a `RecursionError`

is occurring.

Using this along with `getrecursionlimit()`

can help you track exactly how close you are to the limit when profiling your code.

## Conclusion

In this Byte, we've looked into the `RecursionError: maximum recursion depth exceeded`

in Python. We've explored how to fix this error and shared tips on avoiding it in the future. We've also talked the Python stack and the concept of recursion depth.