Bit manipulation cheat sheet | Python

Why bit manipulation? 💭

• Bit manipulation introduces low-level control and speeds up code execution, thus improving performance.

Cheatsheet | python 🐍

# =================

print(~13 & 1) # op: 0, odd num
print(~12 & 1) # op: 1, even num

# =================

# Left shift and Right shift
x << n == x * pow(2, n)
x >> n == x / pow(2, n)

# =================

# Power of 2 -> MSB of the number should be 1
# Eg: n=8(1000b), n-1=7(0111b)
# so n & (n-1) = 0
(n & (n-1))==0 # power of 2

# =================

# xor operator of the same number is 0
# simplifying a^b^b =a
# b^b -> 0
# a^0 -> a
nums = [4,1,2,1,2]
        res = 0
        for num in nums:
            res = num ^ res  # will be able to store unique value

        return res  # 4

# =================

# finding missing numbers in an array.  Again use xor. 
# Eg: [0, 1, 3].
# xor = 3.
# 0^1^2^3^0^1^3 -> 2 which is the missing number.
        xor = len(nums)

        for index in range(len(nums)):
            xor = xor ^ index ^ nums[index]

        return xor

• Note: I will be adding more useful bit operations as and when I encounter them 😄

=================

The End!

Linkedin github 🚀☁️🖤