How Does Python Implement Its Lists: Array, Linked List, or Something Else?

Unveiling the Implementation of Python's List

Python lists are fundamental data structures widely used for managing collections of objects. Understanding their underlying implementation can provide valuable insights into their functionality and performance.

Is it a Linked List or an Array?

Contrary to speculations, Python lists are neither linked lists nor arrays explicitly. Instead, they utilize a hybrid approach that combines the benefits of both.

Underlying Structure: Vector with Overallocation

Delving into the source code, we encounter the list object definition in listobject.h. It comprises a vector or array of pointers, ob_item, that holds references to each list element. Additionally, two critical attributes accompany this vector: ob_size, indicating the current size of the list, and allocated, representing the allocated capacity.

Dynamic Memory Management

Python lists employ a dynamic resizing strategy to adapt to varying data loads. When the list is full, a new, larger array is allocated based on a specific formula. This overallocation helps minimize the frequency of resizing operations.

Benefits of the Hybrid Approach

Python's unique implementation combines the advantages of arrays and linked lists:

• Array Structure for Efficient Access: The vector-like nature of the list allows for efficient random access to its elements.
• Dynamic Resizing for Handling Variable Data: The overallocation strategy ensures smooth expansion as the list grows, mitigating excessive resizing operations.

Conclusion

Python lists leverage a hybrid approach, effectively blending the strengths of arrays and linked lists. The resulting implementation provides a versatile and flexible data structure that can efficiently handle variable-sized collections.

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