In-place Operators in Python

Python provides a set of in-place operators in Python. In-place operators allow you to perform arithmetic, logical, and bitwise operations on variables updating their values in place. These operators are denoted by combining the assignment operator (=) with another operator. It enhances the program's performance and saves memory.

In this article, we will explore the various in-place operators available in Python, along with examples.

1. iadd() - In-place Addition

The iadd(x, y) operator performs an in-place addition operation. It updates the value of the variable with the result. It is represented by the += symbol.

import operator

# Variables
a = 5
b = 4

print("Original, a =", a)

# In-place Addition
a += b

# The above operation is equivalent to
# a = a + b
# a = operator.iadd(a, b)
# a = operator.__iadd__(a, b)

print("Updated, a =", a)

Output:

Original, a = 5
Updated, a = 9

The above code demonstrates how to perform in-place addition.

2. isub() - In-place Subtraction

The isub(x, y) operator performs an in-place subtraction operation. It updates the value of the variable with the result. It is represented by the -= symbol.

import operator

# Variables
a = 5
b = 4

print("Original a =", a)

# In-place Subtraction
a -= b

# The above operation is equivalent to
# a = a - b
# a = operator.isub(a, b)
# a = operator.__isub__(a, b)

print("Updated a =", a)

Output:

Original, a = 5
Updated, a = 1

The above code demonstrates how to perform in-place subtraction.

3. imul() - In-place Multiplication

The imul(x, y) operator performs an in-place multiplication operation. It updates the value of the variable with the result. It is represented by the *= symbol.

import operator

# Variables
a = 5
b = 4

print("Original, a =", a)

# In-place Multiplication
a *= b

# The above operation is equivalent to
# a = a * b
# a = operator.imul(a, b)
# a = operator.__imul__(a, b)

print("Updated, a =", a)

Output:

Original, a = 5
Updated, a = 20

The above code demonstrates how to perform in-place multiplication.

4. itruediv() - In-place True Division

The itruediv(x, y) operator performs an in-place true division operation. It updates the value of the variable with the result. It is represented by the /= symbol.

import operator

# Variables
a = 5
b = 4

print("Original, a =", a)

# In-place true division
a /= b

# The above operation is equivalent to
# a = a / b
# a = operator.itruediv(a, b)
# a = operator.__itruediv__(a, b)

print("Updated, a =", a)

Output:

Original, a = 5
Updated, a = 1.25

The above code demonstrates how to perform in-place true division.

5. iand(), ior(), ixor() - In-place Bitwise AND, Bitwise OR, Bitwise XOR

The iand(x, y) operator performs an in-place Bitwise AND operation. It is represented by the &= symbol.

The ior(x, y) operator performs an in-place Bitwise OR operation. It is represented by the |= symbol.

The ixor(x, y) operator performs an in-place Bitwise XOR operation. It is represented by the ^= symbol

They all update the value of the variable with the result.

import operator

# Variables
a = 5
b = 4
c = 3
d = 2

print("Original, a =", a)
print("Original, c =", c)
print("Original, d =", d)

# In-place Bitwise AND
a &= b
# The above operation is equivalent to
# a = a & b
# a = operator.iand(a, b)
# a = operator.__iand__(a, b)

# In-place Bitwise OR
c |= b
# The above operation is equivalent to
# c = c | b
# c = operator.iand(c, b)
# c = operator.__iand__(c, b)

# In-place Bitwise XOR
d ^= b
# The above operation is equivalent to
# d = d ^ b
# d = operator.iand(d, b)
# d = operator.__iand__(d, b)

print("Updated, a =", a)
print("Updated, c =", c)
print("Updated, d =", d)

Output:

Original, a = 5
Original, c = 3
Original, d = 2
Updated, a = 4
Updated, c = 7
Updated, d = 6

The above code demonstrates how to perform in-place AND, OR, and XOR operations.

6. imod() and ifloordiv() - In-place Modulo and Floor Division

The imod(x, y) operator performs an in-place modulo operation. It is represented by the %= symbol.

The ifloordiv(x, y) operator performs an in-place floor division operation. It is represented by the //= symbol.

They update the value of the variable with the result.

import operator

# Variables
a = 5
b = 4
c = 15

print("Original, a =", a)
print("Original, c =", c)

# In-place modulo
a %= b
# The above operation is equivalent to
# a = a % b
# a = operator.imod(a, b)
# a = operator.__imod__(a, b)

# In-place floor division
c //= b
# The above operation is equivalent to
# c = c // b
# c = operator.ifloordiv(c, b)
# c = operator.__ifloordiv__(c, b)

print("Updated, a =", a)
print("Updated, c =", c)

Output:

Original, a = 5
Original, c = 15
Updated, a = 1 # Remainder when 5 is divided by 4
Updated, c = 3 # Floor value of the result

The above code demonstrates how to perform in-place modulo and floor division operations.

7. ilshift() and irshift() - In-place Left Shift and Right Shift

The ilshift(x, y) operator performs an in-place left-shift operation. It is represented by the <<= symbol.

The irshift(x, y) operator performs an in-place right-shift operation. It is represented by the >> = symbol.

They update the value of the variable with the result.

import operator

# Variables
a = 20
b = 25

print("Original, a =", a)
print("Original, b =", b)

# In-place left shift
a <<= 2 # Shifts two bits to the left
# The above operation is equivalent to
# a = a << 2
# a = operator.ilshift(a, 2)
# a = operator.__ilshift__(a, 2)

# In-place right shift
b >>= 2 # Shifts two bits to the right
# The above operation is equivalent to
# b = b >> 2

# b = operator.irshift(b, 2)
# b = operator.__irshift__(b, 2)

print("Updated, a =", a)
print("Updated, b =", b)

Output:

Original, a = 20
Original, b = 25
Updated, a = 80
Updated, b = 6

The above code demonstrates how to perform in-place modulo and floor division operations.

8. ipow() - In-place Exponentiation

The ipow(x, y) operator performs an in-place exponentiation operation. It is represented by the **= symbol. It updates the value of the variable with the result.

import operator

# Variables
a = 10
b = 2

print("Original, a =", a)

# In-place exponentiation
a **= b
# The above operation is equivalent to
# a = a ** b
# a = operator.ipow(a, b)
# a = operator.__ipow__(a, b)

print("Updated, a =", a)

Output:

Original, a = 10
Updated, a = 100

The above code demonstrates how to perform an in-place exponentiation operation.

9. imatmul() - In-place Matrix Multiplication

The imatmul() operator performs an in-place matrix multiplication operation. It updates the value of the variable with the result. It is represented by the @= symbol.

import operator
import numpy as np

# Numpy Arrays
a = np.array([[1, 2], [3, 4]])
b = np.array([[5, 6], [7, 8]])

print("Original, a =", a)

# In-place exponentiation
a @= b
# The above operation is equivalent to
# a = a @ b
# a = operator.imatmul(a, b)
# a = operator.__imatmul__(a, b)

print("Updated, a =", a)

Output:

Original, a = [[1 2] [3 4]]
Updated, a = [[19 22] [43 50]]

The above code demonstrates how to perform an in-place matrix multiplication operation.

10. iconcat() - In-place Concatenation

The iconcat(x, y) performs an in-place concatenation operation. It is represented by the += symbol and used to concatenate strings, lists, and other sequences. It updates the value of the variable with the concatenated result.

import operator

# Example with strings
s = "Hello"
print("Original, s =", s)

s += " World"
# Equivalent to s = s + " World"
# Equivalent to s = operator.iconcat(s, " World")
# Equivalent to s = operator.__iconcat__(s, " World")

print("Updated, s =", s)

# Example with lists
numbers = [1, 2, 3]
print("Original, numbers =", numbers)

numbers += [4, 5]
# Equivalent to numbers = numbers + [4, 5]
# Equivalent to numbers = operator.iconcat(numbers, [4, 5])
# Equivalent to numbers = operator.__iconcat__(numbers, [4, 5])

print("Updated, numbers =", numbers)

Output:

Original, s = Hello
Updated, s = Hello World
Original, numbers = [1, 2, 3]
Updated, numbers = [1, 2, 3, 4, 5]

The above code demonstrates how to perform in-place concatenation operation.

CONCLUSION

In conclusion, in-place operators allow you to perform different operations in place means updating the value of the variable without creating a new variable or object. They provide an efficient way to perform operations, save memory, and make your code more readable. By using these in-place operators, you can streamline your code and improve its performance.

Next TopicIn-place vs. Standard Operators in Python

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