DEV Community: Deepak Raj

🎙️ Speak2Summary: How We're Solving the Real-World Pain of Unproductive Meetings

Deepak Raj — Sun, 01 Jun 2025 11:28:03 +0000

Let’s face it — meetings are necessary, but often unproductive.

You jump on a 30-minute call. Great ideas are shared. Action points get tossed around. People agree on who’s doing what.

Then... nothing gets documented.

Days later, nobody remembers who said what, or what the next steps were.

We’ve all been there.

That’s the real-world problem we wanted to solve — and that’s why we built Speak2Summary.

❓ The Problem: Meetings Without Memory

Modern teams live on calls — standups, check-ins, brainstorms, sales calls, interviews.

But once the call ends:

Everyone moves on.
No notes were taken.
Tasks are forgotten.
Context is lost.

🧠 Human memory isn’t enough.
📝 Manual note-taking is slow and distracting.
📎 Existing tools are either expensive, limited, or raise privacy concerns.

We wanted a better way.

🚀 The Solution: Speak2Summary

Speak2Summary is our open-source tool to:

🎧 Take any meeting audio → 📝 Transcribe it → 📌 Summarize it → 🌐 Export clean, structured insights → 🧠 Visualize it as a mind map.

Built with speed and privacy in mind, it helps individuals, teams, and developers turn raw speech into actionable documentation — in seconds.

🛠️ Under the Hood

🎤 Drop your audio file (.mp3, .wav, .m4a)
🗣️ We transcribe it using Groq or OpenAI
🤖 Summarize using blazing-fast Groq/OpenAI LLMs
🧾 Output:
- Full transcript
- Markdown summary (with sections like Key Points, Action Items, and Follow-Ups)
- Beautiful HTML report for sharing
- Auto-generated mind map of the entire conversation

🧠 Mind Map Magic

We don’t just summarize your meetings — we visualize them.

Each meeting summary is automatically converted into a dynamic mind map, giving you a bird’s-eye view of:

Topics discussed
Decisions made
Follow-ups and action items
Hierarchical structure of the conversation

It’s perfect for quick reviews, presentations, or just making sense of complex calls.

✅ Real-World Impact

1. For Remote Teams

Get a clean summary and mind map of your daily standup. Assign tasks instantly.

2. For Students & Educators

Record a lecture. Review it later with a visual map and notes.

3. For Podcasters & Journalists

Turn raw interviews into polished transcripts and interactive summaries.

4. For Freelancers & Consultants

Instantly capture and present client discussions in mind map format.

🧠 Why It Works

⚡ Super-fast summaries with Groq’s cutting-edge LLMs.
💡 Structured outputs: not just transcripts, but meaningful insights.
🧩 Modular by design: Swap APIs, change prompts, extend features.
🗺️ Visual mind maps: Understand the big picture at a glance.

📥 Try It Out

You can explore the project here:
👉 GitHub: Speak2Summary

Just drop your audio file and run the pipeline — in less than a minute, you’ll have a polished summary and a visual mind map ready to share.

📌 What’s Next

We're actively improving the platform. Coming soon:

Real-time transcription
Language support beyond English
Speaker tagging
Mind map editor and export options

🙌 Final Thoughts

If you’ve ever left a meeting thinking “Wait... what did we just agree on?”, this tool is for you.

With Speak2Summary, we’re building more than a productivity hack — we’re creating a memory layer for your conversations.

Because ideas matter only when they’re captured — and visualized.

🔗 Check it out on GitHub, give it a ⭐️, and feel free to contribute!

Understanding RAG Workflow: Retrieval-Augmented Generation in Python

Deepak Raj — Thu, 02 Jan 2025 12:53:55 +0000

The Retrieval-Augmented Generation (RAG) workflow is an advanced approach in natural language processing (NLP) that combines retrieval and generation capabilities. It is particularly useful for tasks where the model needs to generate responses based on both its training data and external knowledge sources. This article will delve into how RAG works, its use cases, and how to implement it in Python.

What is Retrieval-Augmented Generation (RAG)?

RAG is a hybrid approach that marries two components:

Retriever: Fetches relevant documents or information from an external knowledge base.
Generator: Generates coherent and contextually relevant responses based on the retrieved documents.

By combining these components, RAG workflows enable models to generate more accurate, context-aware, and up-to-date outputs compared to standalone generative models.

How RAG Workflow Works

Input Query: The user provides a query, such as a question or a prompt.
Document Retrieval: The retriever searches for relevant documents in an external database, such as Elasticsearch, a vector database, or even a simple text corpus.
Contextual Embedding: Retrieved documents are passed to the generator along with the original query to provide additional context.
Response Generation: The generator uses the query and retrieved documents to produce a final response.

Key Use Cases of RAG

Question Answering: Providing precise answers using both internal and external knowledge bases.
Chatbots: Enhancing conversational AI systems with up-to-date or domain-specific knowledge.
Customer Support: Resolving queries by fetching and generating answers from a large corpus of FAQs or manuals.
Research Assistance: Summarizing and answering questions based on scientific papers or other research materials.

Implementing RAG in Python

Here’s a step-by-step implementation of a basic RAG workflow using Python:

Install Necessary Libraries:

   pip install transformers langchain faiss-cpu sentence-transformers

Set Up the Retriever: Use a vector database like FAISS for efficient retrieval.

   from sentence_transformers import SentenceTransformer
   import faiss

   # Initialize embedding model
   model = SentenceTransformer('all-MiniLM-L6-v2')

   # Example documents
   documents = [
       "Python is a versatile programming language.",
       "Transformers are powerful models for NLP tasks.",
       "FAISS is used for vector similarity search."
   ]

   # Generate embeddings
   doc_embeddings = model.encode(documents)

   # Create FAISS index
   dimension = doc_embeddings.shape[1]
   index = faiss.IndexFlatL2(dimension)
   index.add(doc_embeddings)

Define the Generator: Use a pre-trained language model from Hugging Face.

   from transformers import pipeline

   # Initialize text generation pipeline
   generator = pipeline('text-generation', model='gpt2')

Integrate Retriever and Generator: Combine the retriever and generator to form the RAG workflow.

   def rag_pipeline(query):
       # Retrieve similar documents
       query_embedding = model.encode([query])
       distances, indices = index.search(query_embedding, k=2)
       retrieved_docs = [documents[i] for i in indices[0]]

       # Generate response using retrieved documents
       context = "\n".join(retrieved_docs)
       prompt = f"Context: {context}\nQuery: {query}\nAnswer:"
       response = generator(prompt, max_length=50, num_return_sequences=1)

       return response[0]['generated_text']

   # Example query
   query = "What is FAISS?"
   print(rag_pipeline(query))

Test the Workflow: Run the script and provide various queries to test the system’s performance.

Benefits of RAG Workflow

Improved Accuracy: Leverages external knowledge for generating contextually accurate responses.
Flexibility: Adapts to various domains by changing the knowledge base.
Scalability: Works efficiently with large datasets using scalable retrieval mechanisms like FAISS.

Conclusion

The Retrieval-Augmented Generation (RAG) workflow represents a significant advancement in NLP by integrating retrieval and generation. It is highly versatile and finds applications in domains ranging from customer support to research. By implementing RAG in Python, as demonstrated above, you can create powerful, context-aware AI systems tailored to your specific needs.

Feel free to experiment with different retrieval systems or fine-tune the generator to better suit your applications. The possibilities are vast with RAG workflows!

Mini-Max Sum - HackerRank Problem Solving

Deepak Raj — Fri, 27 Dec 2024 12:26:35 +0000

Mini-Max Sum is a Hackerrank problem from the Algorithms subdomain that requires the understanding of the sum of For-Loop and Array. In this post, you will learn how to solve Hackerrank’s Mini-Max Sum problem and its solution in Python and C++.

Problem Statement and Explanation

Find the maximum and minimum sum of the given array of integers. print the maximum and minimum sum of any four elements of the array.

Example: 2 3 1 4 5

Maximum sum: 3 + 4 + 5 + 2 = 14
Minimum sum: 1 + 2 + 3 + 4 = 10

Mini-Max Sum Solution in Python

Explanation of Solution in Python

The miniMaxSum(), which takes an array of integers as input and prints the minimum and maximum sum of any four elements of the array.

The function works by first initializing a variable sum to 0. Then, it iterates over the input array and adds each element to sum.

After the loop has finished iterating, the function calculates the minimum and maximum sum of any four elements of the array by subtracting the largest and smallest elements from sum, respectively.

Finally, the function prints the minimum and maximum sum to the console.

Mini-Max Sum Solution in C++

Explanation of Solution in C++

The miniMaxSum(), takes a vector of integers as input and prints the minimum and maximum sum of any four elements of the vector.

The function works by first initializing two variables: min and max, to the maximum and minimum possible long values, respectively.

Then, it iterates over the input vector and calculates the sum of all the elements in the vector except for the current element. This is done by using a nested for loop.

For each iteration of the outer loop, the function updates the min and max variables if the calculated sum is less than min or greater than max, respectively.

After the loop has finished iterating, the function prints the values of min and max to the console.

Birthday Cake Candles - HackerRank Problem Solving

Deepak Raj — Wed, 18 Dec 2024 03:58:57 +0000

Birthday Cake Candles is a Hackerrank problem from Algorithms subdomain that requires the understanding of loops. In this post, you will learn how to solve Hackerrank’s Birthday Cake Candles problem and its solution in Python and C++.

Problem Statement and Explanation

You are in charge of the cake for a child’s birthday. You have decided the cake will have one candle for each year of their total age. They will only be able to blow out the tallest of the candles. Count how many candles are tallest.

In other words, find the number of occurrences of the maximum element in the array.

Example: 4 4 1 3

The maximum value in the array is 4, and there are 2 instances of that value.

Input Format

n : the number of candles in the cake
ar : the candle heights in the cake

Output Format

Occurrences of the maximum height

Birthday Cake Candles Solution in Python

Explanation of Solution in Python

birthdayCakeCandles(), which takes an array of integers (representing the heights of the candles on a birthday cake) as input and returns the number of candles that the birthday person can blow out.

The function works by first initializing a variable count to 0. Then, it finds the tallest candle in the array by using the max() function.

Next, the function iterates over the array and increments count each time it finds a candle that has the same height as the tallest candle.

Finally, the function returns the value of count, which is the number of candles that the birthday person can blow out.

Birthday Cake Candles Solution in C++

Explanation of Solution in C++

The function works by first initializing two variables: max and count. max will store the height of the tallest candle, and count will store the number of candles that have the same height as the tallest candle.

The function then iterates over the input array and compares each element to max. If the current element is greater than max, then the function updates max to be equal to the current element.

After the loop has finished iterating, the function iterates over the input array again and compares each element to max. If the current element is equal to max, then the function increments count.

Finally, the function returns the value of count, which is the number of candles that the birthday person can blow out.

AI-Powered Graph Exploration with LangChain's NLP Capabilities, Question Answer Using Langchain

Deepak Raj — Wed, 18 Dec 2024 03:39:05 +0000

Have you ever struggled to write complex SQL or graph database queries? What if you could just describe what you want in plain English and get the results directly? Thanks to advancements in natural language processing, tools like LangChain make this not only possible but incredibly intuitive.

In this article, I will demonstrate how to use Python, LangChain, and Neo4j to seamlessly query a graph database using natural language. LangChain will handle the conversion of natural language queries into Cypher queries, providing a streamlined and time-saving experience.

What is LangChain?

LangChain is an open-source framework designed to simplify the creation of applications that utilize large language models (LLMs). Whether you're building chatbots, question-answering systems, text summarizers, or tools for generating database queries, LangChain provides a robust foundation.

By leveraging LangChain, developers can quickly prototype and deploy applications that bridge the gap between natural language and machine intelligence.

Prerequisites

Before we dive in, ensure that you have Python and Neo4j installed on your system. If not, you can install them using the resources below:

Alternatively, you can run Neo4j in Docker. Here’s the command to do so:

Run Neo4j in Docker

Setting Up the Environment

Install Python Dependencies

Install the necessary Python libraries by running the following command:

pip install --upgrade --quiet langchain langchain-neo4j langchain-openai langgraph

Download the Dataset

For this tutorial, we’ll use the Goodreads Book Datasets With User Rating 2M, which can be downloaded from here.

Load the Dataset into Neo4j

To populate the graph database with our dataset, use the following script:

Querying the Graph Database Using LangChain

With everything set up, we’ll now use LangChain to query the graph database using natural language. LangChain will process your input, convert it into a Cypher query, and return the results. For this demonstration, we’ll leverage the GPT-4o-mini model and the following tools:

Example Queries

Here are some sample queries and their results:

Query 1: Find all the books written by "J.K. Rowling" and published by "Bloomsbury Publishing".

Result:

Harry Potter and the Sorcerer’s Stone: Rating: 4.8, Language: English
Harry Potter and the Chamber of Secrets: Rating: 4.7, Language: English

Query 2: Who is the author of "The Lord of the Rings"?

Result: The author of "The Lord of the Rings" is J.R.R. Tolkien.

Query 3: Who is the author of "The Power of One"?

Result: The author of "The Power of One" is Bryce Courtenay.

Query 4: List books published by Penguin Books.

Result:
The following books are published by Penguin Books:

Untouchable - Rating: 3.72, Language: English
The Complete Verse and Other Nonsense - Rating: 4.18, Language: Not Available
The Beloved: Reflections on the Path of the Heart - Rating: 4.19, Language: English
Americana - Rating: 3.43, Language: English
Great Jones Street - Rating: 3.48, Language: English
Gravity’s Rainbow - Rating: 4.0, Language: English
City of Glass (The New York Trilogy, #1) - Rating: 3.79, Language: English
Ghosts (The New York Trilogy, #2) - Rating: 3.64, Language: English
Moon Palace - Rating: 3.94, Language: English
The Invention of Solitude: A Memoir - Rating: 3.78, Language: Not Available

Why Use Natural Language Queries?

Natural language querying offers numerous advantages:

Ease of Use: No need to memorize complex query languages like SQL or Cypher.
Efficiency: Quickly retrieve results without debugging intricate query syntax.
Accessibility: Enables non-technical users to interact with databases effortlessly.

Conclusion

LangChain combined with Neo4j demonstrates how powerful natural language processing can be in simplifying database interactions. This approach opens up possibilities for creating user-friendly tools like chatbots, question-answering systems, and even analytics platforms.

If you found this guide helpful or have any questions, feel free to share them in the comments below. Let’s continue exploring the limitless possibilities of natural language and AI-driven technologies!

Compare the Triplets - Problem Solving | HackerRank

Deepak Raj — Sat, 28 Sep 2024 01:18:29 +0000

Compare the Triplets is an easy-level Python problem that requires basic knowledge of Python. In this post, we will provide a Python solution for Compare the Triplets.

Problem Statement and Explanation

Alice and Bob each submitted a problem to HackerRank. A reviewer evaluated the challenges on three categories - problem clarity, originality, and difficulty - using a scale of 1 to 100.

The rating for Alice’s challenge is the triplet a = (a[0], a[1], a[2]), and the rating for Bob’s challenge is the triplet b = (b[0], b[1], b[2]).

The task is to find their comparison points by comparing a[0] with b[0], a[1] with b[1], and a[2] with b[2].

If a[i] > b[i], then Alice is awarded 1 point.
If a[i] < b[i], then Bob is awarded 1 point.
If a[i] = b[i], then neither person receives a point.

Comparison points are the total points a person earned.

Given a and b, determine their respective comparison points.

Input Format

The first line contains 3 space-separated integers, a[0], a[1], and a[2], describing the respective values in triplet a.
The second line contains 3 space-separated integers, b[0], b[1], and b[2], describing the respective values in triplet b.

Output Format

Return an array of two integers denoting the respective comparison points earned by Alice and Bob.

Solve Me First Solution in Python

Explanation of Solution in Python

The function called compareTriplets() that takes two lists as input, a and b. The function compares the corresponding elements of a and b and keeps a running tally of the number of times each person scores a point. The function then returns a list with the scores for Alice and Bob.

The function takes two lists as input, but they must have the same length.
The function uses a for loop to iterate over the elements of the two lists.
The function uses the if statement to compare the corresponding elements of the two lists.
The function uses the return statement to return the scores for Alice and Bob.

Solve Me First Solution in C++

Explanation of Solution in C++

The function first declares two variables, aliceScore and bobScore, to keep track of the scores for Alice and Bob. Then, it loops through the elements of the two lists, comparing the corresponding elements. If the element in a is greater than the corresponding element in b, then aliceScore is incremented. Otherwise, bobScore is incremented.

After the loop, the function pushes the scores for Alice and Bob onto a vector and then returns the vector.

A Very Big Sum - Problem-Solving | HackerRank

Deepak Raj — Tue, 10 Oct 2023 05:54:01 +0000

A Very Big Sum is an easy-level Python problem that requires basic knowledge of Python. In this post, we will provide a Python solution for A Very Big Sum.

Problem Statement and Explanation

In this challenge, you need to compute and print the sum of the elements in an array, taking into account that some of those integers may be exceedingly large.

Input Format

The array ‘arr’ includes integers ‘a[i]’ ranging from 1 to 10^10.

Output Format

The sum of the elements in the array, as a single integer.

Solve Me First Solution in Python

Solve Me First Solution in C++

Explanation of Solution

aVeryBigSum is a function in C++ that takes a vector of integers as input and returns the sum of all the elements in the vector. The function uses the accumulate() function to calculate the sum.
The accumulate() function is a standard library function in C++. It takes three arguments: the beginning iterator of the range, the end iterator of the range, and an initial value. In this case, the initial value is 0.
The accumulate() function works by iterating over the range and adding each element to the initial value. The final value of the accumulator is the sum of all the elements in the range.

Simple Array Sum - Problem Solving | HackerRank

Deepak Raj — Tue, 10 Oct 2023 05:48:40 +0000

Simple Array Sum is easy-level Python problem that requires basic knowledge of Array. In this post, we will provide a Python solution for Simple Array Sum.

Problem Statement and Explanation

Given an array of integers, find the sum of its elements. For example, if the array ar = [1, 4, 5], 1 + 4 + 5 = 10, so return 10.

Where n is the size of the array, the function simpleArraySum takes an array of integers as input and returns the sum of all the elements in the array. And arr[i] is the ith element of the array. The function works as follows:

It initializes a variable sum to 0.
It uses the accumulate() function to iterate over the elements of the array. The accumulate() function takes three arguments: the beginning iterator of the range, the end iterator of the range, and an initial value.
In this case, the initial value is 0. For each element in the array, the accumulate() function adds the element to the variable sum.

Input Format

The first line contains an integer, n, denoting the size of the array.

Output Format

Sum of the array’s elements as a single integer.

Simple Array Sum Solution in Python

Simple Array Sum Solution in C++

Explanation of Solution(C++)

The function takes an array of integers as input and returns the sum of all the elements in the array. The function works as follows:

It initializes a variable sum to 0.
It uses the accumulate() function to iterate over the elements of the array. The accumulate() function takes three arguments: the beginning iterator of the range, the end iterator of the range, and an initial value.
In this case, the initial value is 0. For each element in the array, the accumulate() function adds the element to the variable sum.
Finally, the function returns the value of sum.

Here is an explanation of the accumulate() function:

The accumulate() function is a standard library function in C++. It takes three arguments:

The beginning iterator of the range
The end iterator of the range
An initial value.

The function iterates over the range and adds each element to the initial value. The final value of the initial value is returned by the function.

In the case of the function simpleArraySum, the accumulate() function iterates over the elements of the array and adds each element to the initial value of 0. The final value of 0 is the sum of all the elements in the array.

I hope this explanation is clear. Let me know if you have any other questions.

Explanation of Solution(Python)

The function takes a list of integers as input and returns the sum of all the elements in the list. The function works as follows:

It initializes a variable sum to 0.
It iterates over the elements of the list using a for loop.
For each element in the list, the function adds the element to the variable sum.
Finally, the function returns the value of sum.

Solve Me First - Problem Solving | HackerRank

Deepak Raj — Tue, 10 Oct 2023 05:46:58 +0000

Solve me first is easy-level Python problem that requires basic knowledge of Python. In this post, we will provide a Python solution for Solve me first.

Problem Statement and Explanation

Add two numbers and return the sum. The numbers are provided as input to the function.

Input Format

int a - first number
int b - second number

Output Format

int - sum of the two numbers

Solve Me First Solution in Python

Solve Me First Solution in C++

Explanation of Solution

The #include statements at the top of the code tell the compiler to include the necessary header files. These header files contain definitions for functions and variables that are used in the code.
The using namespace std statement tells the compiler to use the std namespace. This namespace contains many commonly used functions and variables, such as cin and cout.
The solveMeFirst function takes two integers as input and returns their sum. The function definition starts with the keyword int, which tells the compiler that the function returns an integer value. The function name is solveMeFirst, and it takes two arguments, a and b. The body of the function is enclosed in curly braces ({}). The first line of the function body returns the sum of a and b.
The main function is the entry point of the program. It prompts the user to enter two integers, calls the solveMeFirst function to calculate their sum, and then prints the sum to the console. The main function definition starts with the keyword int, which tells the compiler that the function returns an integer value. The function name is *main, and it takes no arguments. The body of the function is enclosed in curly braces ({}). The first line of the function body reads two integers from the user. The second line calls the solveMeFirst function to calculate the sum of the two integers. The third line prints the sum to the console.

Default Arguments - HackerRank Solution Python

Deepak Raj — Sun, 10 Sep 2023 05:30:59 +0000

Default arguments are a feature of many programming languages that allow you to specify a value for an argument that is not explicitly provided by the caller. This can be useful for making your code more concise and reusable.

Problem Statement and Explanation

Python supports a useful concept of default argument values. For each keyword argument of a function, we can assign a default value which is going to be used as the value of said argument if the function is called without it.

Default Arguments Solution in Python

Explanation of Solution

The code you have given defines two classes, EvenStream and OddStream. Each class has a method called get_next() which returns the next even or odd number, respectively. The function print_from_stream() takes an integer n as input and prints the first n even or odd numbers, depending on the value of the stream parameter.
The main function first reads the number of queries from the user. Then, it loops over the queries. In each iteration, it reads the name of the stream and the number of numbers to print from the user. It then calls the print_from_stream() function, passing the number of numbers to print and the appropriate stream object.

For example, if the user enters the following input:

even 5

then the main function will call the print_from_stream() function with the following arguments:

n = 5 and stream = EvenStream() and the print_from_stream() function will print the first 5 even numbers.

0 2 4 6 and 8

The problem statement is taken from Hackerrank, and the solutions are implemented by the CodePerfectPlus team

Reverse Integer Algorithm in C++, Java, and Python - LeetCode Problem

Deepak Raj ・ Sep 9 '23

#programming #algorithms #leetcode #beginners

Compress the String! - HackerRank Solution Python

Deepak Raj — Sat, 09 Sep 2023 12:47:14 +0000

Compress the String! is a medium-level Python problem that requires string manipulation. In this post, we will provide a Python solution for Compress the String.

Problem Statement and Explanation

You are given a string S. If a character ‘c’ occurs consecutively X times in the string, replace these consecutive occurrences of the character ‘c’ with (X, c) in the string.

Input Format

String S in the user input.

Output Format

Modified string S'

Compress the String Python Solution

Explanation of Solution

The first line imports the itertools module, which provides functions for working with iterators.

The next function, compress_the_string(), takes a string as input and returns a compressed version of the string. The function first uses the itertools.groupby() function to group the characters in the string together based on their equality. For example, the string “AAABBBCCC” would be grouped into the following pairs:

[('A', ['A', 'A', 'A']), 
('B', ['B', 'B', 'B']), 
('C', ['C', 'C', 'C'])]

The function then iterates over the groups, printing the length of each group followed by the character that the group represents. For example, the compressed version of the string “AAABBBCCC” would be “3A2B3C”.

Here is a step-by-step explanation of how the code works:

The import itertools statement imports the itertools module.
The def compress_the_string(string): takes a string as input and returns a compressed version of the string.
The res = itertools.groupby(string): statement uses the itertools.groupby() function to group the characters in the string based on their equality.
The for k, g in res variable: statement iterates over the groups of characters.
The print((len(list(g)), int(k)), end=' ') statement prints the length of the group followed by the character that the group represents.
The if __name__ == ‘__main__’: clause defines the main function.
The string = input() statement prompts the user to enter a string.
The compress_the_string (string) statement calls the compress_the_string () function with the string that the user entered as input.
The print() statement prints the compressed version of the string to the console.

Time Complexity of the Solution

The time complexity of the solution is O(n), where n is the length of the input string. This is because of the itertools.groupby() function takes O(n) time to group the characters in the string. The for loop then iterates over the groups, which takes O(n) time. The print() statement takes constant time, so the overall time complexity is O(n).

Space Complexity of the Solution

The space complexity of the solution is O(n), where n is the length of the input string. This is because of the itertools.groupby() function creates a list of groups, which takes O(n) space. The for loop then iterates over the groups, which takes O(n) space. The print() statement takes constant space, so the overall space complexity is O(n).

The problem statement is taken from Hackerrank, and the solutions are implemented by the CodePerfectPlus team

30 Days of Code SubReddit

Reverse Integer Algorithm in C++, Java, and Python - LeetCode Problem

Deepak Raj — Sat, 09 Sep 2023 03:32:31 +0000

Reverse Integer is medium level problem of LeetCode. In this post, we will see the solution of this problem in C++, Java, and Python.

Problem Statement and Explanation

Given a signed 32-bit integer x, return x with its digits reversed. If reversing x causes the value to go outside the signed 32-bit integer range -2 **31, 2** 31 - 1, then return 0.

Example 1:

input: 134
output: 431

Example 2:

input: -312
output: -213

Reverse Integer Python Solution in Python

Reverse Integer Java Solution in Java

Reverse Integer C++ Solution in C++

Explanation of Solution

The while loop iterates until the number x is 0.
In each iteration, the function pops the last digit off the number x and stores it in the variable pop.
The number x is then divided by 10.
The function checks if the reversed number rev is greater than INT_MAX or less than INT_MIN. If it is, the function returns 0.
The reversed number rev is then multiplied by 10 and the last digit pop is added back.
The function returns the reversed number rev.

Time Complexity of the Solution

The time complexity of the solution is O(n), where n is the number of digits in the original number. This is because the while loop iterates n times.

Here is a breakdown of the time complexity of each step in the function:

The while loop iterates n times.
The pop operation takes constant time.
The x //= 10 operation takes constant time.
The if statement takes constant time.
The rev = rev * 10 + pop operation takes constant time.
Therefore, the total time complexity of the function is O(n).

Space Complexity of the Solution

The space complexity of the solution is O(1), since the function only uses a constant number of variables. Here is a breakdown of the space complexity of each step in the function:

The rev variable is a local variable and only needs to be stored on the stack.
The pop variable is a local variable and only needs to be stored on the stack.
The if statement does not introduce any new variables.
Therefore, the total space complexity of the function is O(1).

Problem statement is taken from Leet Code, and the solutions are implemented by CodePerfectPlus team.