DEV Community: Preethii V

🏏 The 18-Day DSA Cover Drive | Day 4: The 5 Questions I Ask Before Solving Any DSA Problem

Preethii V — Mon, 06 Jul 2026 16:14:47 +0000

🏏 The 18-Day DSA Cover Drive | Day 4— How I Identify DSA Patterns Before Writing Code

Learn DSA one pattern at a time.

What's up, DEV Community! 👋

Welcome back to The 18-Day DSA Cover Drive.

🏆 Kohli Corner

🏏 "The best batters don't guess the ball. They read it."

Virat Kohli doesn't decide his shot before the bowler releases the ball.

He watches.

He reads.

Then he chooses the perfect shot.

💡 DSA is no different.

Don't memorize solutions.

Read the problem first. Choose the right pattern. Then write the code.

🧩 Day 4 — Pattern Recognition

When I started learning DSA, every problem looked different.

Some people said,

"Just solve 500 questions."

But I realized something...

Experienced programmers don't memorize problems.

They recognize patterns.

Now, before writing a single line of code, I ask myself these 5 simple questions.

❓ Question 1

Is the data continuous?

Look for words like:

Subarray
Substring
Contiguous
Continuous

🎯 Think: Sliding Window

❓ Question 2

Does the order matter?

If YES

➡️ Keep the original order.

If NO

➡️ Sorting might make the problem much easier.

❓ Question 3

Am I searching for the same thing repeatedly?

Look for words like:

Frequency
Count
Duplicate
Lookup
Pair
Already seen
Mapping

🎯 Think: Dictionary (HashMap)

Ask yourself:

"Do I need to remember information?"

If yes...

Use a Dictionary.

❓ Question 4

Am I comparing from both ends?

Keywords:

Sorted Array
Palindrome
Reverse
Pair
Left
Right

🎯 Think: Two Pointers

❓ Question 5

Is my brute-force solution repeating work?

If you're calculating the same thing again...

There is probably a better approach.

Ask yourself:

"Can I reuse my previous work?"

⚡ My Pattern Decision Tree

Problem
   │
   ▼
Subarray / Substring?
   │
 YES ─────────► Sliding Window
   │
   NO
   │
Need Frequency?
   │
 YES ─────────► Dictionary
   │
   NO
   │
Need Unique Elements?
   │
 YES ─────────► Set
   │
   NO
   │
Sorted / Palindrome / Pair?
   │
 YES ─────────► Two Pointers
   │
   NO
   │
Start with Brute Force.

🏏 Cover Drive Cheat Sheet

If the problem says...	Think...	Ask Yourself
Frequency, Count, Lookup	🗂️ Dictionary	Do I need to remember information?
Duplicate, Unique, Visited	📦 Set	Do I only care if it exists?
Sorted Array, Pair, Reverse, Palindrome	👉👈 Two Pointers	Can two indices move together?
Subarray, Substring, Contiguous	🪟 Sliding Window	Can I reuse previous work?
Window Size = K	📏 Fixed Sliding Window	Remove one, add one?
Longest / Shortest	🔄 Variable Sliding Window	Expand or shrink the window?

💼 Interview Insight

One habit I'm trying to build:

❌ Don't jump into coding.

✅ Spend the first minute asking:

What are the keywords?
Which pattern fits?
Why does it fit?

Choosing the correct pattern is often harder than writing the code.

🏏 Nets Practice

Which pattern would you choose?

🥎 Problem 1

Find the longest substring without repeating characters.

🤔 Pattern?

🥎 Problem 2

Find whether an array contains duplicate elements.

🤔 Pattern?

🥎 Problem 3

Find two numbers in a sorted array whose sum equals the target.

🤔 Pattern?

🥎 Problem 4

Find the maximum sum of a subarray of size k.

🤔 Pattern?

👇 Comment only the pattern names.

No code.

Let's see how many you get right!

🏏 Cover Drive of the Day

🏏 Concept: Pattern Recognition

⭐ Goal: Identify the pattern before writing code.

💼 Interview Insight: One minute of thinking can save thirty minutes of debugging.

💬 Let's Discuss

When you first started DSA...

Which pattern confused you the most?

Or...

Do you have another trick for identifying patterns quickly?

I'd love to learn from your experience too! 👇

18DayDSACoverDrive | Python | DSA | Algorithms | Beginners

🏏 The 18-Day DSA Cover Drive | Day 3 — Sliding Window: Stop Recalculating, Start Sliding

Preethii V — Fri, 03 Jul 2026 17:32:04 +0000

🏏 The 18-Day DSA Cover Drive | Day 3 — Sliding Window: Stop Recalculating, Start Sliding

Learn DSA one pattern at a time.

What's up, DEV Community! 👋

Welcome back to Day 18 of The 18-Day DSA Cover Drive.

🏆 Kohli Corner

Legacy isn't built in one innings.

Virat Kohli's cover drive wasn't perfected overnight.

Thousands of practice balls.

Hundreds of innings.

One unforgettable shot.

The same goes for DSA. Great problem-solving isn't about memorizing solutions. It's about training your thinking until patterns become instinct.

📊 Day 3 — Sliding Window

🎯 Today's DSA Power-Up

Imagine you're solving this problem:

Find the maximum sum of any subarray of size k.

Your first instinct?

Probably nested loops.

Mine too. 😅

❌ The Brute Force Mindset

For every starting position...

Calculate the sum again.

And again.

max_sum = 0

for i in range(len(arr) - k + 1):
    current_sum = 0

    for j in range(i, i + k):
        current_sum += arr[j]

    max_sum = max(max_sum, current_sum)

Works?

✅ Yes.

Efficient?

❌ Not really.

Every time the window moves...

We're recalculating values we already know.

Time Complexity:

O(n²)

🤔 Imagine This...

Imagine you're sitting beside a train window.

As the train moves...

Do you look at the entire city again?

No.

You only notice:

🚆 What's leaving your view.

🚆 What's entering your view.

That's exactly how the Sliding Window pattern works.

🚀 The Better Approach

Instead of calculating everything again...

Keep the current sum.

When the window moves:

➖ Remove the left element.

➕ Add the new right element.

That's it.

window_sum = 0
max_sum = 0
left = 0

for right in range(len(arr)):

    window_sum += arr[right]

    if right >= k - 1:

        max_sum = max(max_sum, window_sum)

        window_sum -= arr[left]

        left += 1

Look closely.

No nested loops.

Just two pointers working together.

🎯 What's Really Happening?

Every iteration does only two things:

✅ Add one element.

✅ Remove one element.

The window keeps sliding.

No repeated work.

⚡ Why is it Faster?

Brute Force

For every index
      ↓
Calculate the whole window again

Time Complexity

O(n²)

Sliding Window

Move Right →
Remove Left ←

Every element is visited only once.

Time Complexity

O(n)

That's a massive improvement.

💼 Interview Insight

Whenever you see words like:

Subarray
Substring
Contiguous
Window size k
Longest
Shortest
Maximum
Minimum

🚨 Pause.

Before writing nested loops...

Ask yourself:

"Can I slide a window instead?"

Many interview questions become much simpler with this mindset.

🧠 Quick Challenge

Can you solve this using Sliding Window?

Find the maximum sum of a subarray of size 3.

arr = [2, 1, 5, 1, 3, 2]
k = 3

👇 Drop your answer in the comments before running the code.

Bonus Question:

Can you think of another problem where Sliding Window can replace nested loops?

🏏 Cover Drive of the Day

🏏 Pattern: Sliding Window

⭐ Mindset: Don't recalculate. Slide.

🧠 Memory Trick: Train Window / Cricket Camera

💼 Interview Insight: Whenever you see contiguous arrays or substrings, think Sliding Window before nested loops.

⏭️ Next Innings: Two Pointers — Two indices. One elegant solution.

💬 Let's Discuss

When did the Sliding Window pattern finally click for you?

Or...

Are you still getting confused between Sliding Window and Two Pointers?

Let's discuss in the comments! 👇

If you enjoyed this post and want to follow my 18-Day DSA Cover Drive journey, let's connect!

💼 LinkedIn: https://www.linkedin.com/in/PreethiiV

Happy Coding! 🚀

18DayDSACoverDrive | Python | DSA | Algorithms | Beginners

🏏 The 18-Day DSA Cover Drive | Day 2: Meet Python's Counter

Preethii V — Wed, 01 Jul 2026 17:55:58 +0000

🏏 The 18-Day DSA Cover Drive | Day 2 — Meet `Counter`

Learn DSA one Python trick at a time.

What's up, DEV community! 👋

Welcome back to Day 2 of The 18-Day DSA Cover Drive.

🏆 Kohli Corner

Fastest to 8,000 ODI Runs

Virat Kohli didn't score 8,000 ODI runs in a single innings.

He reached the milestone by scoring one run at a time, trusting the process, and showing up consistently.

Just like great innings are built one run at a time, great code is built one improvement at a time.

📊 Day 2 — Meet `Counter`

🎯 Today's Python Power-Up

Yesterday, we learned how to build a Frequency Map manually.

freq = {}

for item in arr:
    freq[item] = freq.get(item, 0) + 1

It works.

It's clean.

But Python says...

"Why write four lines when one line is enough?" 😄

Meet Counter.

✨ The Magic Line

from collections import Counter

arr = [1, 2, 1, 3, 2, 1]

freq = Counter(arr)

print(freq)

Output

Counter({1: 3, 2: 2, 3: 1})

That's it!

No loop.

No .get().

No if-else.

Just one line.

🤔 Imagine This...

Your teacher asks,

"How many students are wearing blue?"

❌ Yesterday's Way

You walk around the classroom and count everyone manually.

Again.

✅ Today's Way

The teacher presses a button on a smart attendance machine.

Blue  → 8
Black → 12
White → 6

Instant result.

That's exactly what Counter does.

❌ Before

freq = {}

for item in arr:
    freq[item] = freq.get(item, 0) + 1

✅ After

from collections import Counter

freq = Counter(arr)

✅ Cleaner

✅ Smaller

✅ More Pythonic

🚀 Bonus Powers of `Counter`

Count a specific element

print(freq[1])

Output

Find the most frequent element

print(freq.most_common(1))

Output

[(1, 3)]

Pretty cool, right? 😄

💡 Where is `Counter` useful?

You'll commonly use it in problems like:

Finding duplicate elements
Counting character frequencies
Valid Anagram
Majority Element
Top K Frequent Elements
Frequency-based array problems

⚡ Interview Insight

Should you always use Counter?

✅ Use Counter when the problem is mainly about counting frequencies.

❌ Don't immediately use Counter if an interviewer specifically asks you to implement the frequency map yourself.

Understanding how Counter works internally (which we learned on Day 1 using dict.get()) is just as important as knowing the shortcut.

First learn the logic. Then learn the shortcut.

🧠 Quick Challenge

Without running the code...

Can you guess the output?

from collections import Counter

word = "mississippi"

freq = Counter(word)

print(freq["s"])
print(freq.most_common(1))

👇 Drop your answer in the comments before checking!

🎯 Bonus Question

Can you think of another DSA problem where Counter can replace an entire counting loop?

I'd love to hear your answers!

🏏 Cover Drive of the Day

🏏 Concept: Counter

⭐ Python Gem: collections.Counter

💼 Interview Insight: Learn the logic first, then use the shortcut.

⏭️ Next Innings: defaultdict — A dictionary that creates missing keys automatically.

💬 Let's Discuss

Have you used Counter before?

Or did you learn something new today?

If you know another hidden Python gem that makes DSA easier, drop it in the comments! 👇

18DayDSACoverDrive | Python | DSA | Beginners | Learning

The 18-Day DSA Cover Drive: Day 1 — Unleashing the Frequency Map 🏏

Preethii V — Tue, 30 Jun 2026 16:54:54 +0000

🏏 The 18-Day DSA Cover Drive

Learn DSA one Python trick at a time.

What's up, DEV community! 👋

Welcome to Day 1 of my brand-new coding series.

If you're wondering why it's called The 18-Day DSA Cover Drive, let me let you in on a secret...

I'm a massive Virat Kohli fan. 🤫

Just like a perfect cover drive isn't built in one net session, strong DSA isn't built in one night.

For the next 18 days, I'll share:

🐍 One Python trick
🧩 One DSA lesson
❌ One mistake I made
🧠 One memory trick to remember it forever

A perfect cover drive isn't born on match day. An optimal solution isn't born during interviews. Both are built in practice.

📊 Day 1 — Frequency Count

🎯 Today's Hidden Gem

freq[item] = freq.get(item, 0) + 1

Looks simple.

But this single line can turn an O(n²) solution into an O(n) solution.

🤔 Imagine this...

You walk into your classroom.

The teacher asks,

"How many students are wearing blue?"

❌ Method 1

Every time someone asks, you walk around the entire classroom counting students.

Again.

Sounds exhausting?

That's exactly what nested loops do.

✅ Method 2

Walk through the classroom once and maintain a notebook.

Blue  → 8
Black → 12
White → 6

Now every answer takes just a second.

That's the idea behind Frequency Count.

🎬 Movie Memory Trick

Think of Doraemon's Anywhere Door.

Without a dictionary

🚶 Search the whole house.

With a dictionary

🚪 Open the door.

You're already there.

✨ The Magic Line

freq[item] = freq.get(item, 0) + 1

Read it like English.

Get the current count.
If it doesn't exist, assume it's 0.
Add 1.
Save it back.

Done.

Before

if item in freq:
    freq[item] += 1
else:
    freq[item] = 1

After

freq[item] = freq.get(item, 0) + 1

✅ Cleaner

✅ Smaller

✅ Easier

🧠 Quick Challenge

What will be the output?

arr = [1, 2, 1, 3, 2, 1]

freq = {}

for item in arr:
    freq[item] = freq.get(item, 0) + 1

print(freq)

👇 Put your answer in the comments before running the code!

🏏 Cover Drive of the Day

🏏 Concept: Frequency Count

⭐ Python Gem: dict.get()

🧠 Memory Trick: Classroom Attendance Notebook

⏭️ Next Innings: defaultdict (Less code. Same logic. Even cleaner.)

18DayDSACoverDrive | Python | DSA | Beginners Learning

"Talk to Your Terminal: Building a Voice AI Agent in Python"

Preethii V — Sun, 12 Apr 2026 19:58:21 +0000

Have you ever wished your computer could understand your voice and do tasks for you?

I decided to build a simple Voice AI Agent in Python that can listen to my voice, understand what I want, and perform actions automatically.

For example, I can say:

"Create a file called notes.txt"

"Write a Python binary search program"

"Summarize this text"

"What is machine learning?"

And the AI takes care of the rest!

How Does It Work?

The workflow is surprisingly simple:

🎤 Speak

↓

👂 AI listens

↓

🧠 AI understands

↓

⚡ AI performs the task

↓

The Technologies I Used

Whisper

Whisper converts my voice into text.

Example:

Voice:

"Create a file called test.txt"

Text:

"Create a file called test.txt"

GPT-4o-mini / Ollama

Once the speech becomes text, the AI figures out what I actually want.

Is it:

Creating a file?
Generating code?
Summarizing text?
Answering a question?

The AI decides and chooses the correct action.

Streamlit

I used Streamlit to build a simple and clean web interface.

This lets me upload audio files and see the results instantly.

What Can It Do?

📁 Create Files

Say:

"Create a file called project_notes.txt"

The agent creates the file automatically.

💻 Generate Code

Say:

"Write a Python bubble sort program"

The AI generates the code and saves it.

📝 Summarize Text

Have a long paragraph?

Just say:

"Summarize this"

The AI gives a shorter version.

💬 Answer Questions

You can also ask:

"What is a linked list?"

And get an explanation immediately.

Challenges I Faced

Building it wasn't as smooth as I expected 😅

Windows File Issues

Sometimes Windows locked temporary audio files, preventing Whisper from reading them.

After a lot of debugging, I discovered the file needed to be closed before processing.

FFmpeg Problems

Whisper requires FFmpeg.

The funny part?

I had installed FFmpeg correctly, but forgot to add it to the system PATH.

A classic developer mistake 😂

Offline Support

What if the internet is unavailable?

To solve this, I added Ollama and fallback rules so the agent can still work without cloud APIs.

Why This Project Excited Me

The coolest part wasn't the code.

It was the first time I spoke to my application and watched it actually understand me and perform a task.

That moment felt like talking to a mini personal assistant I had built myself.

Final Thoughts

This project showed me that building AI-powered tools is becoming more accessible than ever.

With Python, Whisper, Streamlit, and an LLM, you can create your own voice assistant capable of performing useful tasks in just a few hundred lines of code.

And honestly...

There's something satisfying about telling your computer what to do instead of typing it. 🎙️

GitHub Repository

https://github.com/Preethii19V/Voice-AI-Agent

DEV Community: Preethii V

🏏 The 18-Day DSA Cover Drive | Day 4: The 5 Questions I Ask Before Solving Any DSA Problem

🏏 The 18-Day DSA Cover Drive | Day 4— How I Identify DSA Patterns Before Writing Code

Learn DSA one pattern at a time.

🏆 Kohli Corner

🧩 Day 4 — Pattern Recognition

❓ Question 1

Is the data continuous?

❓ Question 2

Does the order matter?

❓ Question 3

Am I searching for the same thing repeatedly?

❓ Question 4

Am I comparing from both ends?

❓ Question 5

Is my brute-force solution repeating work?

⚡ My Pattern Decision Tree

🏏 Cover Drive Cheat Sheet

💼 Interview Insight

🏏 Nets Practice

Which pattern would you choose?

🥎 Problem 1

🥎 Problem 2

🥎 Problem 3

🥎 Problem 4

🏏 Cover Drive of the Day

💬 Let's Discuss

🏏 The 18-Day DSA Cover Drive | Day 3 — Sliding Window: Stop Recalculating, Start Sliding

🏏 The 18-Day DSA Cover Drive | Day 3 — Sliding Window: Stop Recalculating, Start Sliding

Learn DSA one pattern at a time.

🏆 Kohli Corner

📊 Day 3 — Sliding Window

🎯 Today's DSA Power-Up

❌ The Brute Force Mindset

🤔 Imagine This...

🚀 The Better Approach

🎯 What's Really Happening?

⚡ Why is it Faster?

Brute Force

Sliding Window

💼 Interview Insight

🧠 Quick Challenge

🏏 Cover Drive of the Day

💬 Let's Discuss

🏏 The 18-Day DSA Cover Drive | Day 2: Meet Python's Counter

🏏 The 18-Day DSA Cover Drive | Day 2 — Meet Counter

Learn DSA one Python trick at a time.

🏆 Kohli Corner

📊 Day 2 — Meet Counter

🎯 Today's Python Power-Up

✨ The Magic Line

🤔 Imagine This...

❌ Yesterday's Way

✅ Today's Way

❌ Before

✅ After

🚀 Bonus Powers of Counter

Count a specific element

Find the most frequent element

💡 Where is Counter useful?

⚡ Interview Insight

🧠 Quick Challenge

🎯 Bonus Question

🏏 Cover Drive of the Day

💬 Let's Discuss

The 18-Day DSA Cover Drive: Day 1 — Unleashing the Frequency Map 🏏

🏏 The 18-Day DSA Cover Drive

Learn DSA one Python trick at a time.

📊 Day 1 — Frequency Count

🎯 Today's Hidden Gem

🤔 Imagine this...

❌ Method 1

✅ Method 2

🎬 Movie Memory Trick

✨ The Magic Line

Before

After

🧠 Quick Challenge

🏏 Cover Drive of the Day

"Talk to Your Terminal: Building a Voice AI Agent in Python"

🏏 The 18-Day DSA Cover Drive | Day 2 — Meet `Counter`

📊 Day 2 — Meet `Counter`

🚀 Bonus Powers of `Counter`

💡 Where is `Counter` useful?