Hacks
- Record your findings when testing the time elapsed of the different algorithms.
- I realized that fibonacci code increases a very great amount for an increase in just one
- Constant algorithms only take 0.0s
- Base width increases both space and time complexity greatly
- If it is asked to print a calulation from just random integers it is fast but if it is asked to calculate a number based on an output the time and space complexity is increased greatly
- For i in j is very big
- The time increases exponentially when the data is increased by just a bit
- Makes it even more important to manege complexity
## This takes minutes to execute
def find_duplicates(arr):
duplicates = []
for i in range(len(arr)):
for j in range(i + 1, len(arr)):
if arr[i] == arr[j]:
duplicates.append(arr[i])
return duplicates
arr = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] * 1000000
duplicates = find_duplicates(arr)
print(duplicates)
# This takes 2.1 seconds to execute. This is why its important to manage complexity
def find_duplicates(arr):
duplicates = []
unique_set = set()
for i in arr:
if i not in unique_set:
unique_set.add(i)
else:
duplicates.append(i)
return duplicates
arr = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] * 1000000
duplicates = find_duplicates(arr)
print(duplicates)