Python - Copy Arrays

Python's built-in sequence types i.e. list, tuple, and string are indexed collection of items. However, unlike arrays in C/C++, Java etc. , they are not homogenous, in the sense the elements in these types of collection may be of different types. Python's array module helps you to create object similar to Java like arrays. In this chapter, we discuss how to copy an array object to another.

Python arrays can be of string, integer or float type. The array class constructor is used as follows −

import array
obj = array.array(typecode[, initializer])

The typecode may be a character constant representing the data type.

Copy Arrays Using Assignment Operator

We can assign an array to another by the assignment operator.

Example

a = arr.array('i', [1, 2, 3, 4, 5])
b=a.copy()

However, such assignment doesn't create a new array in the memory. In Python, a variable is just a label or reference to the object in the memory. So, a is the reference to an array, and so is b. Check the id() of both a and b. Same value of id confirms that simple assignment doesn't create a copy

import array as arr
a = arr.array('i', [1, 2, 3, 4, 5])
b=a
print (id(a), id(b))

It will produce the following output −

2771967068656 2771967068656

Because "a" and "b" refer to the same array object, any change in "a" will reflect in "b" too −

a[2]=10
print (a,b)

It will produce the following output −

array('i', [1, 2, 10, 4, 5]) array('i', [1, 2, 10, 4, 5])

Copy Arrays Using Deep Copy

To create another physical copy of an array, we use another module in Python library, named copy and use deepcopy() function in the module. A deep copy constructs a new compound object and then, recursively inserts copies into it of the objects found in the original.

Example

import array, copy
a = arr.array('i', [1, 2, 3, 4, 5])
import copy
b = copy.deepcopy(a)

Now check the id() of both "a" and "b". You will find the ids are different.

print (id(a), id(b))

It will produce the following output −

2771967069936 2771967068976

This proves that a new object "b" is created which is an actual copy of "a". If we change an element in "a", it is not reflected in "b".

a[2]=10
print (a,b)

It will produce the following output −

array('i', [1, 2, 10, 4, 5]) array('i', [1, 2, 3, 4, 5])
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