Appending objects to Python array becomes linearly slower as more items are added

Title: Understanding the Performance Impact of Appending Objects to Python Arrays
Introduction:
Appending objects to a Python array is a common operation in many applications. However, it's essential to be aware that the time complexity of this operation is not constant. As more items are added to the array, the time it takes to append new elements becomes linearly slower. In this tutorial, we'll explore why this happens and discuss potential alternatives.
Background:
Understanding Time Complexity:
Code Example:
In the above example, we're appending a varying number of items to an array and measuring the time it takes to perform the operation. As the number of items increases, you may notice that the time to append also increases, indicating a linearly slower performance.
Alternative Approaches:
Conclusion:
While Python's list type is versatile and convenient, it's crucial to be aware of the potential performance impact when appending objects, especially in scenarios with a large number of elements. Consider the alternatives mentioned above based on your specific use case to ensure optimal performance.
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