🦥 Static Typing vs Dynamic Typing

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Hello friends!

Welcome to this week’s Sloth Bytes. I hope you had a great week!

As always, if you have any suggestions or if I got something wrong let me know!

Sloths have a lot of bugs in their fur

Just one sloth can have up to 950 moths and beetles living in its fur. Don’t worry! These aren’t parasites. When one animal lives on another animal in this way, it’s called symbiosis.

Static vs Dynamic Typing

What is this?

• Static Typing: Types are checked at compile time

int your_iq = 0;

• Dynamic Typing: Types are checked at runtime

your_iq = 0

Key Differences

1. Type Declaration:

   • Static: Variables declared with specific types

   • Dynamic: Variables can hold any type

2. Error Detection:

   • Static: Many errors caught before running

   • Dynamic: Errors often surface during execution

3. Performance:

   • Static: Generally faster execution

   • Dynamic: More flexible, potentially slower

4. Code Flexibility:

   • Static: Less flexible, more rigid

   • Dynamic: More flexible, easier to change

Examples of SOME Statically Typed Languages

• Java

• C++

• Rust

• Swift

• Kotlin

• Scala

• Haskell

Examples of SOME Dynamically Typed Languages

• Python

• JavaScript

• Ruby

• PHP

• Lua

Pros and Cons

Which to Choose?

From my experience, this is what I think. I could be wrong (I probably am)

• Large, complex projects: Static typing

• Making something fast: Dynamic might be better

Other alternatives

• Gradual typing: Add type hints to dynamic languages (e.g., Python with type hints)

• TypeScript: Adds static typing to JavaScript

Why Should I Care?

• Choose the right language for your project

• Write more robust and maintainable code

• Anticipate and prevent certain types of bugs

Remember: Both systems have their place. The best choice depends on your project needs, team skills, and development goals. Many modern languages are adopting features from both worlds!

Stacks and Queues

What are Stacks and Queues?

• Stack: Last-In-First-Out (LIFO) data structure. The last element added is the first that goes out. Think of it like a stack of pancakes. Normal people start at the top of the stack and make their way to the bottom.

• Queue: First-In-First-Out (FIFO) data structure. The First item that gets added is the first that goes out. Think of it as a line/waiting queue, the first person there gets to leave.

Stack Operations and Time Complexity:

• push(item): Add item to top - O(1)

• pop(): Remove and return top item - O(1)

• peek(): View top item without removing - O(1)

• isEmpty(): Check if stack is empty - O(1)

Queue Operations and Time Complexity::

• enqueue(item): Add item to back - O(1)

• dequeue(): Remove and return front item - O(1)

• front(): View front item without removing - O(1)

• isEmpty(): Check if queue is empty - O(1)

Stack Implementation (Python):

# Stack implementation
class Stack:
    def __init__(self):
        self.items = []
    
    def push(self, item):
        self.items.append(item)
    
    def pop(self):
        return self.items.pop()
    
    def peek(self):
        return self.items[-1]
    
    def isEmpty(self):
        return len(self.items) == 0

Queue Implementation (Python):

# Queue implementation

class Queue:
    def __init__(self):
        #if you use the deque library you could do
        #self.items = deque()
        self.items = []
    
    def enqueue(self, item):
        self.items.append(item)
    
    def dequeue(self):
        #if you use the deque library you could do
        #return self.items.popleft()
        return self.items.pop(0)
    
    def front(self):
        return self.items[0]
    
    def isEmpty(self):
        return len(self.items) == 0

Key Points to Remember

1. Understand the difference between LIFO and FIFO

2. Know how to implement both structures

3. Be familiar with time complexities of operations

4. Practice problems involving multiple stacks/queues

5. Understand when to use stacks vs queues in problem-solving

Why This Matters

• Fundamental to many algorithms and data structures

• Often used in depth-first search (stack) and breadth-first search (queue)

• Common in system design (e.g., task scheduling, undo functionality)

Remember: Practice implementing these structures from scratch and solving related problems. Understanding when and how to use stacks and queues can greatly improve your problem-solving skills in interviews!

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Thank you to everyone who submitted last week!

tobiaoy, xitsjacob, ShiSui97x, afiqzudinhad, QueenlyHeart, ravener, RelyingEarth87, ddat888 and last but not least…

Alright, let’s do some stack/queue practice

Implement a Stack using Queues

Implement a Stack using only two queues. The implemented stack should support all the functions of a normal stack (push, top, pop, and empty).

Implement the MyStack class:

• void push(int x) Pushes element x to the top of the stack.

• int pop() Removes the element on the top of the stack and returns it.

• int top() Returns the element on the top of the stack.

• boolean empty() Returns true if the stack is empty, false otherwise.

Example:

Input
["MyStack", "push", "push", "top", "pop", "empty"]
[[], [1], [2], [], [], []]
Output
[null, null, null, 2, 2, false]

Explanation
MyStack myStack = new MyStack();
myStack.push(1);
myStack.push(2);
myStack.top(); // return 2
myStack.pop(); // return 2
myStack.empty(); // return False

Follow-up: Can you implement the stack using only one queue?

How To Submit Answers

Reply with

• A link to your solution (github, twitter, personal blog, portfolio, replit, etc)

• or if you’re on the web version leave a comment!

SLOTH WHERE NEW VID 😡

uhhhh…. I’m working on it (I swear). It’s going to be about some tools I like to use for programming/productivity, I think most of you will like it!

That’s all from me!

Have a great week, be safe, make good choices, and have fun coding.

See you all next week.