Code Interview: Python for Coding Interviews

Python for Coding Interviews

Variables

Python is dynamically typed, meaning you don’t need to declare the type of a variable. Here’s how it works:

n = 0
print(n)  # Output: 0

n = "ABC"
print(n)  # Output: ABC

Multiple Assignments

You can assign multiple variables in one line:

a, b = 1, "Hello"
print(a, b)  # Output: 1 Hello

Incrementing

Incrementing variables is straightforward:

n = 1
n = n + 1
n += 1

Note: n++ is not valid in Python.

Null Values

In Python, None represents the absence of a value:

n = 4
n = None
print(n)  # Output: None

If Statements

Python’s if statements don’t require parentheses or curly braces. Instead, they use colons and indentation:

if n == 0:
    print("Zero")
elif n == 1:
    print("One")
else:
    print("Other")

Logical Operators

Python uses and and or instead of && and ||:

if n > 0 and n < 10:
    print("Single digit")

Loops

While Loops

n = 0
while n < 5:
    print(n)
    n += 1

For Loops

Python’s for loops are quite powerful:

for i in range(5):
    print(i)

You can also specify start and end points:

for i in range(2, 6):
    print(i)

Reverse Loops

To loop in reverse:

for i in range(5, 1, -1):
    print(i)

Math Operations

Division

Python uses decimal division by default:

print(5 / 2)  # Output: 2.5

print(5 // 2)  # Output: 2 (integer division)
print(-3 // 2)  # Output: -2 (rounding down)

Modulo

The modulo operator % works as expected but can behave differently with negative numbers:

print(10 % 3)  # Output: 1
print(-10 % 3)  # Output: 2

Useful Math Helpers

Python’s math module offers many helpful functions:

import math

print(math.floor(2.7))  # Output: 2
print(math.ceil(2.7))  # Output: 3
print(math.sqrt(16))  # Output: 4.0
print(math.pow(2, 3))  # Output: 8.0

Arrays (Lists)

Basic Operations

Lists are dynamic arrays in Python:

arr = [1, 2, 3]
print(arr)  # Output: [1, 2, 3]

arr.append(4)
print(arr)  # Output: [1, 2, 3, 4]

arr.pop()
print(arr)  # Output: [1, 2, 3]

arr.insert(1, 7)
print(arr)  # Output: [1, 7, 2, 3]

Slicing

print(arr[1:3])  # Output: [7, 2]

List Comprehension

squared = [x**2 for x in range(5)]
print(squared)  # Output: [0, 1, 4, 9, 16]

Strings

Strings in Python are immutable:

s = "Hello"
print(s[1:4])  # Output: ell

# Strings are immutable
# s[0] = 'h'  # This will raise an error

# Concatenation creates a new string
s = s + " World"
print(s)  # Output: Hello World

Conversion

num = int("123")
print(num)  # Output: 123

s = str(123)
print(s)  # Output: 123

Queues

Python’s deque can be used for queues:

from collections import deque

q = deque()
q.append(1)
q.append(2)
print(q)  # Output: deque([1, 2])

q.popleft()
print(q)  # Output: deque([2])

Hash Sets

Sets in Python offer O(1) time complexity for inserts and lookups:

s = {1, 2, 3}
print(s)  # Output: {1, 2, 3}

s.add(4)
print(s)  # Output: {1, 2, 3, 4}

s.remove(2)
print(s)  # Output: {1, 3, 4}

Hash Maps (Dictionaries)

Dictionaries are the go-to data structure for key-value pairs:

d = {"Alice": 88, "Bob": 77}
print(d)  # Output: {'Alice': 88, 'Bob': 77}

d["Charlie"] = 99
print(d)  # Output: {'Alice': 88, 'Bob': 77, 'Charlie': 99}

print(d.get("Alice"))  # Output: 88

del d["Bob"]
print(d)  # Output: {'Alice': 88, 'Charlie': 99}

Tuples

Tuples are immutable lists:

t = (1, 2, 3)
print(t[0])  # Output: 1

# t[0] = 0  # This will raise an error

Heaps

Heaps are great for priority queues:

import heapq

heap = []
heapq.heappush(heap, 3)
heapq.heappush(heap, 1)
heapq.heappush(heap, 2)
print(heap)  # Output: [1, 3, 2]

print(heapq.heappop(heap))  # Output: 1
print(heap)  # Output: [2, 3]

Functions

Basic Functions

def multiply(n, m):
    return n * m

print(multiply(2, 3))  # Output: 6

Nested Functions

Nested functions can access variables from the outer function:

def outer(a, b):
    def inner():
        return a + b
    return inner()

print(outer(1, 2))  # Output: 3

Classes

Python classes are concise and powerful:

class MyClass:
    def __init__(self, nums):
        self.nums = nums
        self.size = len(nums)

    def get_length(self):
        return self.size

    def get_double_length(self):
        return self.get_length() * 2

my_obj = MyClass([1, 2, 3])
print(my_obj.get_length())  # Output: 3
print(my_obj.get_double_length())  # Output: 6

Conclusion

This covers the essentials of Python you need to know for coding interviews. With practice, you’ll find Python’s syntax straightforward and its features powerful. Python played a crucial role in my journey to securing a job at Google, and I hope it helps you too.

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by NeetCode