Jose Angel MunozI have followed the 30 first minutes of the freecodecamp training named Dynamic Programing for Beginners – How to Solve Coding Challenges with Memoization and Tabulation.
The first part is about programming efficiency and timing but also about infrastructure resources.
The training shows Javascript examples, but I moved to Python ♥️
The code:
def fib(n):
if n == 0:
return 0
if n == 1:
return 1
return fib(n - 1) + fib(n - 2)
print('The first 50 fibonacci numbers are:')
print(','.join([str(fib(n)) for n in range(50)]))
It takes too many CPU resources and it doesn't even finish:
Moving to:
def fib(n, memo={}):
if n in memo:
return memo[n]
if n == 0:
return 0
if (n <= 2):
return 1
memo[n] = fib(n - 1, memo) + fib(n - 2, memo)
return memo[n]
print('The first 50 fibonacci numbers are:')
print(','.join([str(fib(n)) for n in range(50)]))
Takes less than a second to run and almost no CPU resorces:
real 0m0.156s
user 0m0.075s
sys 0m0.059s
