Python: Examples of fast sorting and insertion sorting algorithms and custom sorting. python Algorithm
I. Quick sorting
Quicksort is an improvement in Bubble sorting. Proposed by C. A. R. Hoare in 1962. Its basic idea is: Split the data to be sorted into two independent parts by one sort, and all the data in one part is smaller than all the data in the other part, then, sort the two data parts by using this method. The entire sorting process can be recursive to convert the entire data into an ordered sequence.
Quick sorting and Recursion
Def quick_sort (num_list): "Quick Sort" if num_list = []: return num_list smallList = [] bigList = [] middleElement = num_list [0] for I in num_list [1:]: if I <= middleElement: smallList. append (I) else: bigList. append (I) return quick_sort (smallList) + [middleElement] + quick_sort (bigList)
Ii. Insert sorting
The description of Insertion Sort is a simple and intuitive sorting algorithm. Its working principle is to build an ordered sequence. For unordered data, scan the sorted sequence from the back to the front, locate the corresponding position, and insert it. Insert sorting usually uses in-place sorting (that is, sorting of the extra space of O (1). Therefore, during the scanning from the back to the forward, the sorted elements need to be moved backward repeatedly to provide the insert space for the new elements.
Insert sort
Def insert_sort (num_list): "insert sort" for I in range (len (num_list)-1): for j in range (I + 1, len (num_list): if num_list [I]> num_list [j]: num_list [I], num_list [j] = num_list [j], num_list [I] return num_list
Iii. Custom sorting
You can use the sort () or sorted () key.
Example:
Def sort_key (obj): sorted_list = [4, 2, 5, 9, 7, 8, 1, 3, 6, 0] return sorted_list.index (obj) if _ name _ = '_ main _': print sorted (range (10), key = sort_key) # The output result is as follows: [4, 2, 5, 9, 7, 8, 1, 3, 6, 0]
# Use the index position of the keyword in the list for custom sorting
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