{"id":299,"date":"2025-06-13T13:48:26","date_gmt":"2025-06-13T08:18:26","guid":{"rendered":"https:\/\/codeanddebug.in\/blog\/?p=299"},"modified":"2025-07-07T20:07:56","modified_gmt":"2025-07-07T14:37:56","slug":"quick-sort-in-python","status":"publish","type":"post","link":"https:\/\/codeanddebug.in\/blog\/quick-sort-in-python\/","title":{"rendered":"Quick Sort Algorithm in Python | Explained"},"content":{"rendered":"\n

Quick Sort<\/strong> is a popular sorting algorithm that follows a divide-and-conquer<\/strong> approach.<\/p>\n\n\n\n

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  1. Choose a Pivot<\/strong>: Select one element of the array (in this code, the element at index low).<\/li>\n\n\n\n
  2. Partition<\/strong>: Arrange the array such that all elements less than or equal<\/strong> to the pivot lie to the pivot\u2019s left, and those greater<\/strong> than the pivot lie to its right.<\/li>\n\n\n\n
  3. Recursively<\/strong> sort the subarrays on both sides of the pivot.<\/li>\n<\/ol>\n\n\n\n

    When implemented well, Quick Sort can be extremely efficient, often outperforming more stable algorithms like Merge Sort in practice, due to better cache performance. However, it does have a worst-case time complexity of O(n<\/strong>2<\/sup><\/strong>)<\/strong> if the pivot selection is poor.<\/p>\n\n\n\n

    So let’s get started with the [Problem Link<\/span><\/mark><\/a><\/strong>].<\/p>\n\n\n

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