Fibonacci Series using Dynamic Programming

Author: OmkarPathak

Dynamic Programming/P01_Fibonnaci.py

@@ -0,0 +1,39 @@
+# Author: OMKAR PATHAK
+
+# recursive fibonacci solution has a time complexity of O(2 ^ n).
+# To reduce this we can use dynamic programming. Dictionary data structure is used to drastically reduce
+# the time complexity to O(n)
+
+import time
+
+# improved fibonacci function
+def fibonacci(number):
+    if myList[number] == None:
+        myList[number] = fibonacci(number - 1) + fibonacci(number - 2)
+    return myList[number]
+
+# traditional recursive fibonacci function
+def fibonacciRec(number):
+    if number <= 1:
+        return number
+    else:
+        return (fibonacciRec(number - 1) + fibonacciRec(number - 2))
+
+if __name__ == '__main__':
+    userInput = int(input('Enter the number: '))
+
+    myList = [None for _ in range(userInput + 1)]
+
+    # base cases
+    myList[0] = 0
+    myList[1] = 1
+
+    startTime = time.time()
+    result = fibonacci(userInput)
+    stopTime = time.time()
+    print('Time:', (stopTime - startTime), 'Result:', result)
+
+    startTime = time.time()
+    result = fibonacciRec(userInput)
+    stopTime = time.time()
+    print('Time:', (stopTime - startTime), 'Result:', result)