Implementing the Bubble Sort Algorithm with Python
### Bubble Sort: A Comprehensive Analysis of a Basic Sorting Algorithm Bubble Sort is based on the "bubble rising" principle. Its core idea is to repeatedly compare adjacent elements and swap those in the wrong order, allowing larger elements to gradually "bubble" to the end of the array until the entire array is sorted. The working steps are as follows: traverse the array for multiple rounds, compare and swap adjacent elements with reverse order pairs in each round, and after each round, the largest unsorted element is placed in its correct position; if no swaps occur in a round, the array is already sorted, and the process terminates early. In Python implementation, the outer loop controls the number of sorting rounds (at most n-1 rounds), the inner loop compares adjacent elements and swaps them, and a `swapped` flag is used to optimize the termination condition. The worst-case time complexity is O(n²) (for a completely reversed array), the best-case is O(n) (for a sorted array with optimization), the space complexity is O(1), and it is a stable sorting algorithm. Bubble Sort is simple and intuitive, suitable for small-scale data, and serves as a foundational understanding of sorting concepts. By examining its principles and Python code implementation, one can quickly grasp the core logic of comparing and swapping adjacent elements.
Read MoreImplementing the Bubble Sort Algorithm in Java
Bubble Sort is a basic sorting algorithm whose core idea is to repeatedly compare adjacent elements and swap their positions, allowing larger elements to "bubble up" to the end of the array (in ascending order). Its sorting process is completed through multiple iterations: each iteration determines the position of the largest element in the current unsorted portion and moves it to the end until the array is sorted. In Java implementation, the outer loop controls the number of sorting rounds (at most n-1 rounds), while the inner loop compares adjacent elements and performs swaps. A key optimization is using a `swapped` flag; if no swaps occur in a round, the algorithm terminates early, reducing the best-case time complexity to O(n). The worst and average-case time complexities are O(n²), with a space complexity of O(1) (in-place sorting). Despite its simple and intuitive principle, which makes it suitable for teaching the core concepts of sorting, bubble sort is inefficient and only applicable for small-scale data or educational scenarios. For large-scale data sorting, more efficient algorithms like Quick Sort are typically used.
Read More