script_12.py - List Performance

Code

See script_12.py for full code.

Explanation

Line 8: import time - time module for measuring execution time

Line 9: from collections import deque - deque for performance comparison

Line 11-15: def time_operation(func, *args): - *args captures variable number of arguments as tuple - Function takes another function as parameter (higher-order function)

Line 12: start = time.time() - .time() returns float (seconds since epoch) - High precision timestamp

Line 13: result = func(*args) - *args unpacks tuple into separate arguments - Calls the function passed as parameter - Executes the operation being timed

Line 14: end = time.time() - Second timestamp after operation

Line 15: return result, (end - start) * 1000 - Subtracts timestamps to get duration - * 1000 converts seconds to milliseconds - Returns tuple: (result, time_in_ms)

Line 22: test_list = list(range(n)) - Creates list with n elements - range(n) is 0 to n-1

Line 23: test_deque = deque(range(n)) - Creates deque with same elements - Different internal structure

Line 28: def remove_from_list_front(lst, times): - Function to benchmark list.pop(0)

Line 30: lst.pop(0) - Removes from front of list - O(n) complexity - must shift all remaining elements - Slow for large lists

Line 36: dq.popleft() - Removes from front of deque - O(1) complexity - constant time - Much faster than list.pop(0)

Line 45: return 9999 in lst - in operator for lists - O(n) complexity - must check each element linearly

Line 48: return 9999 in s - in operator for sets - O(1) average complexity - hash lookup - Much faster than list membership test