Basic idea of quick sort:
Split the data to be sorted into two independent parts through one sorting. All the data in one part is smaller than all the data in the other part, and then use this method to sort the two parts of the data. Quick sort is performed separately, and the entire sorting process can be performed recursively, so that the entire data becomes ordered.
Example:
arr = [49,38,04,97,76,13,27,49,55,65], set the first digit 49 as the key value, and find the number smaller than the key value from right to left , assign the found number to the first digit;
arr = [27,38,04,97,76,13,27,49,55,65], and then find the key value from the first digit on the left to the right For large numbers, assign the found number to the last number found from right to left;
arr = [27,38,04,97,76,13,97,49,55,65], and then proceed from right to left Left, from left to right, until left=right, break out of the loop, and assign the key value to some index value. Finally, recurse the groups on both sides.
Code:
def quick_sort(lists, left, right): #快速排序 if left >= right: #当递归调用的分组为1个数时返回列表 return lists key = lists[left] #保存key值,在一轮调用结束时,存到中间值 low = left high = right #供递归调用时使用 while left < right: #通过下面两个循环依次交替赋值并使key值两侧为大小分组 while left < right and lists[right] >= key: right -= 1 lists[left] = lists[right] while left < right and lists[left] <= key: left += 1 lists[right] = lists[left] lists[right] = key quick_sort(lists, low, left-1) #对key值左侧进行排序分组 quick_sort(lists, left+1, high) #对key值右侧进行排序分组 return lists

Python and C each have their own advantages, and the choice should be based on project requirements. 1) Python is suitable for rapid development and data processing due to its concise syntax and dynamic typing. 2)C is suitable for high performance and system programming due to its static typing and manual memory management.

Choosing Python or C depends on project requirements: 1) If you need rapid development, data processing and prototype design, choose Python; 2) If you need high performance, low latency and close hardware control, choose C.

By investing 2 hours of Python learning every day, you can effectively improve your programming skills. 1. Learn new knowledge: read documents or watch tutorials. 2. Practice: Write code and complete exercises. 3. Review: Consolidate the content you have learned. 4. Project practice: Apply what you have learned in actual projects. Such a structured learning plan can help you systematically master Python and achieve career goals.

Methods to learn Python efficiently within two hours include: 1. Review the basic knowledge and ensure that you are familiar with Python installation and basic syntax; 2. Understand the core concepts of Python, such as variables, lists, functions, etc.; 3. Master basic and advanced usage by using examples; 4. Learn common errors and debugging techniques; 5. Apply performance optimization and best practices, such as using list comprehensions and following the PEP8 style guide.

Python is suitable for beginners and data science, and C is suitable for system programming and game development. 1. Python is simple and easy to use, suitable for data science and web development. 2.C provides high performance and control, suitable for game development and system programming. The choice should be based on project needs and personal interests.

Python is more suitable for data science and rapid development, while C is more suitable for high performance and system programming. 1. Python syntax is concise and easy to learn, suitable for data processing and scientific computing. 2.C has complex syntax but excellent performance and is often used in game development and system programming.

It is feasible to invest two hours a day to learn Python. 1. Learn new knowledge: Learn new concepts in one hour, such as lists and dictionaries. 2. Practice and exercises: Use one hour to perform programming exercises, such as writing small programs. Through reasonable planning and perseverance, you can master the core concepts of Python in a short time.

Python is easier to learn and use, while C is more powerful but complex. 1. Python syntax is concise and suitable for beginners. Dynamic typing and automatic memory management make it easy to use, but may cause runtime errors. 2.C provides low-level control and advanced features, suitable for high-performance applications, but has a high learning threshold and requires manual memory and type safety management.


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