{"id":296,"date":"2025-06-13T13:42:52","date_gmt":"2025-06-13T08:12:52","guid":{"rendered":"https:\/\/codeanddebug.in\/blog\/?p=296"},"modified":"2025-07-07T20:05:14","modified_gmt":"2025-07-07T14:35:14","slug":"merge-sort-algorithm-in-python","status":"publish","type":"post","link":"https:\/\/codeanddebug.in\/blog\/merge-sort-algorithm-in-python\/","title":{"rendered":"Merge Sort Algorithm in Python | Explained"},"content":{"rendered":"\n

Merge Sort<\/strong> is a classic divide-and-conquer<\/strong> sorting technique. It divides the list into two halves, sorts each half recursively, and then merges<\/strong> the two sorted halves. <\/p>\n\n\n\n

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

The major steps are:<\/p>\n\n\n\n

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  1. Divide<\/strong>: Split the array into two parts.<\/li>\n\n\n\n
  2. Conquer<\/strong>: Recursively sort each half.<\/li>\n\n\n\n
  3. Combine<\/strong>: Merge the two sorted halves into a single sorted list.<\/li>\n<\/ol>\n\n\n\n

    This approach ensures a guaranteed<\/strong> time complexity of O(nlog\u2061n)<\/em><\/strong> in the worst, average, and best cases, making Merge Sort a reliable and efficient sorting algorithm, especially for large datasets.<\/p>\n\n\n

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