- 5.1 Function Definitions
- 5.2 Default Arguments
- 5.3 Variadic Arguments
- 5.4 Keyword Arguments
- 5.5 Variadic Keyword Arguments
- 5.6 Functions Accepting All Inputs
- 5.7 Positional-Only Arguments
- 5.8 Names, Documentation Strings, and Type Hints
- 5.9 Function Application and Parameter Passing
- 5.10 Return Values
- 5.11 Error Handling
- 5.12 Scoping Rules
- 5.13 Recursion
- 5.14 The lambda Expression
- 5.15 Higher-Order Functions
- 5.16 Argument Passing in Callback Functions
- 5.17 Returning Results from Callbacks
- 5.18 Decorators
- 5.19 Map, Filter, and Reduce
- 5.20 Function Introspection, Attributes, and Signatures
- 5.21 Environment Inspection
- 5.22 Dynamic Code Execution and Creation
- 5.23 Asynchronous Functions and await
- 5.24 Final Words: Thoughts on Functions and Composition
This chapter is from the book
This chapter is from the book
This chapter is from the book
5.13 Recursion
Python supports recursive functions. For example:
def sumn(n):
if n == 0:
return 0
else:
return n + sumn(n-1)
However, there is a limit on the depth of recursive function calls. The function sys.getrecursionlimit() returns the current maximum recursion depth, and the function sys.setrecursionlimit() can be used to change the value. The default value is 1000. Although it is possible to increase the value, programs are still limited by the stack size enforced by the host operating system. When the recursion depth limit is exceeded, a RuntimeError exception is raised. If the limit is increased too much, Python might crash with a segmentation fault or another operating system error.
In practice, issues with the recursion limit only arise when you work with deeply nested recursive data structures such as trees and graphs. Many algorithms involving trees naturally lend themselves to recursive solutions—and, if your data structure is too large, you might blow the stack limit. However, there are some clever workarounds; see Chapter 6 on generators for an example.