Recursion is a programming technique where a function calls itself to solve a problem. In this article, we will focus on implementing recursion in Python to find the sum of integers in a list, as well as other common recursive applications.
Suppose we have a function, listSum, that takes a list of integers and returns their sum. Here's its basic recursive implementation:
<code class="python">def listSum(ls): # Base condition: if the list is empty, return 0 if not ls: return 0 # Recursive call with the rest of the list return ls[0] + listSum(ls[1:])</code>
To optimize the above recursion, we can use tail call recursion. This involves passing the current result along with the list to the recursive call:
<code class="python">def listSum(ls, result): if not ls: return result return listSum(ls[1:], result + ls[0])</code>
To avoid creating intermediate lists, we can pass the index of the current element to the recursive call:
<code class="python">def listSum(ls, index, result): if index == len(ls): return result return listSum(ls, index + 1, result + ls[index])</code>
If you prefer a more encapsulated approach, you can define an inner function within listSum to handle the recursive logic:
<code class="python">def listSum(ls): def recursion(index, result): if index == len(ls): return result return recursion(index + 1, result + ls[index]) return recursion(0, 0)</code>
For convenience, you can use default parameters to simplify the function call:
<code class="python">def listSum(ls, index=0, result=0): if index == len(ls): return result return listSum(ls, index + 1, result + ls[index])</code>
Recursion can also be applied to calculate powers. Consider the power function that takes a base and exponent:
<code class="python">def power(base, exponent): if exponent <= 1: return base return base * power(base, exponent - 1)</code>
To optimize power using tail call recursion:
<code class="python">def power(base, exponent, result=1): if exponent <= 0: return result return power(base, exponent - 1, result * base)</code>
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