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TASK: Research the Quicksort algorithm and write a robust Python implementation to 'sorting_algo.py'.
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[Agent] Iteration 1/300
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[Agent] Executing 1 tool(s)
[Agent] Spawning researcher agent for: Research the Quicksort algorithm in detail, including its implementation, variations, and best practices.
[parallel] launching spawn_agent
-> Searching web: Quicksort algorithm detailed explanation, implementation, variations, and best practices
[parallel] launching web_search
-> Searching web: Quicksort algorithm detailed explanation, implementation, variations, and best practices
[parallel] launching web_search
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-> Writing file: sorting_algo.py
[parallel] launching write_file
  CHANGES: sorting_algo.py 
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1 - """Robust Quicksort implementation with variations"""  |
2 - import random  |
3 -   |
4 - def quicksort(arr, low=0, high=None, pivot_strategy='last'):  |
5 -  if high is None:  |
6 -  high = len(arr) - 1  |
7 -  if low < high:  |
8 -  # Choose pivot based on strategy  |
9 -  if pivot_strategy == 'random':  |
10 -  pivot_index = random.randint(low, high)  |
11 -  arr[pivot_index], arr[high] = arr[high], arr[pivot_index]  |
12 -  elif pivot_strategy == 'median-of-three':  |
13 -  mid = (low + high) // 2  |
14 -  # Find median of arr[low], arr[mid], arr[high]  |
15 -  s = sorted([(arr[low], low), (arr[mid], mid), (arr[high], high)], key=lambda x: x[0])  |
16 -  median_index = s[1][1]  |
17 -  arr[median_index], arr[high] = arr[high], arr[median_index]  |
18 -  # Partition  |
19 -  p = partition(arr, low, high)  |
20 -  # Recursively sort partitions  |
21 -  quicksort(arr, low, p - 1, pivot_strategy)  |
22 -  quicksort(arr, p + 1, high, pivot_strategy)  |
23 -   |
24 -   |
25 - def partition(arr, low, high):  |
26 -  pivot = arr[high]  |
27 -  i = low - 1  |
28 -  for j in range(low, high):  |
29 -  if arr[j] <= pivot:  |
30 -  i += 1  |
31 -  arr[i], arr[j] = arr[j], arr[i]  |
32 -  arr[i + 1], arr[high] = arr[high], arr[i + 1]  |
33 -  return i + 1  |
34 -   |
35 - # Example usage  |
36 - if __name__ == "__main__":  |
37 -  data = [3, 6, 8, 10, 1, 2, 1, 5, 9, 4]  |
38 -  print("Original data:", data)  |
39 -  quicksort(data, pivot_strategy='median-of-three')  |
40 -  print("Sorted data:", data)  |
| 1 + def quicksort(arr): 
| 2 +  """Recursively sorts an array using the Quicksort algorithm.""" 
| 3 +  if len(arr) <= 1: 
| 4 +  return arr 
| 5 +  pivot = arr[len(arr) // 2] 
| 6 +  left = [x for x in arr if x < pivot] 
| 7 +  middle = [x for x in arr if x == pivot] 
| 8 +  right = [x for x in arr if x > pivot] 
| 9 +  return quicksort(left) + middle + quicksort(right) 
| 10 +  
| 11 +  
| 12 + def quicksort_inplace(arr, low=0, high=None): 
| 13 +  """In-place Quicksort implementation for efficiency.""" 
| 14 +  if high is None: 
| 15 +  high = len(arr) - 1 
| 16 +  if low < high: 
| 17 +  pivot_index = partition(arr, low, high) 
| 18 +  quicksort_inplace(arr, low, pivot_index - 1) 
| 19 +  quicksort_inplace(arr, pivot_index + 1, high) 
| 20 +  
| 21 +  
| 22 + def partition(arr, low, high): 
| 23 +  pivot = arr[high] 
| 24 +  i = low 
| 25 +  for j in range(low, high): 
| 26 +  if arr[j] <= pivot: 
| 27 +  arr[i], arr[j] = arr[j], arr[i] 
| 28 +  i += 1 
| 29 +  arr[i], arr[high] = arr[high], arr[i] 
| 30 +  return i 
[Agent] Iteration 3/300
The Python implementation of the Quicksort algorithm has been written to the file 'sorting_algo.py'. It includes both a recursive version and an in-place version for efficiency, along with the partition helper function. If you need further modifications or explanations, please let me know!
[Agent] has_tool_calls=false
[Agent] Completed in 3 iteration(s)
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