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PaavanGupta
PaavanGupta

Reputation: 31

How are python lists different from Java arrays

As we know the array stores data in the memory in a contiguous manner i.e. the data(element of the array) stored is sequential and is not stored randomly at different addresses. And that's the reason why we cannot change the size of the array dynamically. But in the case of python lists, the size of the array can be changed when required. So, do python lists also store data in a contiguous way or do they use some different approach of storing data? Also, the size of all the data elements is also the same in an array for example in java or c++ i.e. all the elements of the array consume the same amount of memory and we clearly know that it isn't the case in python as we can store different data types in the same list. So, basically, my question is, what is the fundamental difference between lists in python and arrays in java(or any other language like c++ or c). I would really appreciate your help.

Upvotes: 1

Views: 2208

Answers (2)

Paul Tofunmi
Paul Tofunmi

Reputation: 530

Here's a breakdown of the key differences between Python lists and Java arrays, including explanations and examples:

  1. Fixed Size vs. Dynamic Size

Java arrays: Have a fixed size that must be declared when you create the array. You cannot add or remove elements beyond this size.

Java

int[] numbers = new int[5]; // Array can only hold 5 integers

Python lists: Can dynamically grow or shrink. You can add or remove elements as needed.

Python

numbers = [1, 2, 3]  # List initialized
numbers.append(4)    # Adding an element
  1. Homogeneous vs. Heterogeneous Types

Java arrays: Must store elements of the same data type.

Java

String[] names = {"Alice", "Bob"}; 
int[] ages = {25, 30};

Python lists: Can store elements of different data types.

Python

my_list = [10, "hello", 3.14, True]
  1. Mutability

Java arrays: The contents of the array can be changed after the array is created. You can alter the value of individual elements.

Java

int[] numbers = {1, 2, 3};
number[0] = 5; // Now numbers is {5, 2, 3}

Python lists: Lists are fully mutable. You can change elements, add elements, remove elements, and rearrange them.

Python

my_list = [1, 2, 3]
my_list[1] = "new value"  # Now my_list is [1, "new value", 3]
my_list.remove(3)         # Now my_list is [1, "new value"]
  1. Efficiency and Performance

Java arrays: Generally more memory-efficient for storing homogeneous data, especially primitive data types. They offer fast access to elements by index.

Python lists: More flexible, but have some overhead due to their dynamic nature and ability to store different types. This flexibility comes at a slight cost in terms of memory and, in some cases, speed.

  1. Functionality

Python lists: Have a rich set of built-in methods that make common operations very convenient:

append() to add an element
remove() to remove an element
sort() to sort in place
reverse() to reverse in place

And many more... Java arrays: Require the use of external utility classes like Arrays for advanced operations like sorting, searching, etc.

Java

Arrays.sort(my_array);

Python's array Module Python has an array module that provides array-like structures similar to Java arrays for storing homogenous data types. However, even these array objects are somewhat more flexible than Java's arrays, allowing some resizing.

Summary

In essence, Python lists offer more versatility for general-purpose programming, while Java arrays are more suited for scenarios where you know the size of your data in advance and need better performance for specific operations on homogeneous data.

Upvotes: 0

Saksham Tiwari
Saksham Tiwari

Reputation: 21

Although people compare Python lists to arrays in Java, actually lists are more like ArrayLists in Java (Or Vectors in C++). Lists in Python store pointers to objects rather than objects themselves, which is why they can store heterogenous types ([1,2,3,'x',"hello"]). So, technically the list still stores elements of specific size and type (pointers), but those pointers can point to objects of any type, size and value.

These variable length lists in Python keep a pointer to themselves and the their length in a list head structure, which work with exponential over-allocation, so that the code can have linear time complexity for append/remove operations.

Over-allocating the memory is used to avoid having to resize the list too many times (Say, after every append operation). The growth pattern of the list is something like: 0, 4, 8, 16, 25, 35, 46, 58, 72, 88, …

Similarly for remove/pop operations, if the new size is less than half the allocated size then the list is shrunk. Although additional cost of Slicing the list is added in case of removing the element from non-terminal positions.

Upvotes: 2

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