# SamirPaulb/DSAlgo: a structured Python3 solutions repository for interview prep

> DSAlgo is a topic-indexed collection of Python3 solutions, notes and sheets for data structures and algorithms. It is a study companion, not a library you import, and its value depends on how you use the folder structure.

**SamirPaulb/DSAlgo** — 📚A repository that contains all the Data Structures and Algorithms concepts and solutions to various problems in Python3 stored in a structured manner.👨‍💻🎯

- Repository: https://github.com/SamirPaulb/DSAlgo
- Website: https://samirpaulb.github.io/DSAlgo
- Stars: 2,595 · Forks: 539
- Language: Python
- License: NOASSERTION
- Published: 2026-09-28 · Updated: 2026-09-28 · Language: en
- Canonical page: https://hysenlabs.com/projects/samirpaulb-dsalgo

## What DSAlgo is and who it is for

DSAlgo is a GitHub repository that stores solutions to data structures and algorithms problems in Python3, arranged by topic. The README describes it as a place where solutions and concepts are kept "in a structured manner", and the top-level directories confirm that: 01_LeetCode, 02_Dynamic-Programming, 03_Sorting-Algorithms, and so on through 23_Recursion. There is no package to install and no runtime to configure. The audience is narrow but clear: someone preparing for coding interviews in Python who wants reference implementations grouped by technique rather than scattered across a dozen bookmarks.

The repository also carries material beyond raw solutions. The Questions-Sheet directory holds questions the README says were asked by top product-based companies. BOOKS-and-PDFs collects books and PDFs on computer science fundamentals. 30-Days-SDE-Sheet-Practice stores solutions to Striver's SDE Sheet questions day by day, with short notes attached to each solution. The Dynamic Programming folder is organised around Aditya Verma's playlist, folder-wise, and links to handwritten notes.

If you are looking for a library that exposes sorting or graph functions through an import statement, this is the wrong shape of project. It is a study corpus. The unit of use is a file you read, not a module you call.

## How the repository is organised and how you move through it

The structure is flat and numeric. Each top-level folder is prefixed with a two-digit index, so the directory listing itself is the table of contents. 01_LeetCode comes first, then the algorithmic topics in roughly the order a course would present them, ending with 23_Recursion. That ordering matters more than it looks: it means browsing the repository in a file manager gives you a syllabus, and the README's topics list mirrors the same order with links to each folder.

Inside a topic folder you find individual solution files. The README does not document a naming convention, a file template, or a per-problem metadata format, so the only way to know what a given file contains is to open it. That is a real limitation for anyone who wants to script against the repository, for example to generate a progress tracker or to diff solutions. The README does point contributors toward adding "well-documented source code with detailed explanations", which suggests explanation quality varies by file and by contributor.

The cross-cutting folders sit outside the numeric sequence: 30-Days-SDE-Sheet-Practice, Questions-Sheet, and BOOKS-and-PDFs. These are organised by source (a sheet, a company list, a reading list) rather than by technique, which is why they are separate. There is also a CP_Template_in_Python.py at the top level, a competitive programming template, and an index.html that backs the online view.

## Getting DSAlgo locally and working through a first problem

There is nothing to install in the package-manager sense. The README points to an online VS Code view at https://samirpaulb.github.io/DSAlgo, which is the fastest way to read files without cloning anything. To get the files locally, clone the repository. The README gives the repository URL as https://github.com/SamirPaulb/DSAlgo.

```bash
git clone https://github.com/SamirPaulb/DSAlgo.git
```

After the clone, change into the directory and list the top level. You should see the numbered folders from 01_LeetCode through 23_Recursion alongside Questions-Sheet and BOOKS-and-PDFs.

```bash
cd DSAlgo
ls
```

The repository is Python3, so reading or running a file needs only a Python 3 interpreter. The README does not describe a test runner or a requirements file, and it does not document how a file is meant to be executed, so a given solution may print results, define functions, or do neither. If you are following Striver's SDE Sheet, start in 30-Days-SDE-Sheet-Practice instead, where the README says solutions are grouped by day with short notes. That folder is the one place where the repository's own description makes a claim about revision value rather than just coverage.

## Where DSAlgo falls short

The repository has no stated correctness guarantee. The README invites contributors to "Update the existing solution with a better one (better complexity)", which is an admission that some solutions are suboptimal and that quality is maintained socially rather than by tests. The README describes no CI job that runs solutions, so a file that was correct when written can silently drift if a problem's constraints change. Treat every solution as a starting point to verify, not as a reference answer.

The LeetCode folder is the sharpest example. LeetCode adds and revises problems continuously, and the repository's last push was on 2026-06-17. Problems added after that date are not present, and the README does not claim the folder is exhaustive. If your target company's loop leans on recent problems, this folder will not cover them.

Language is another boundary. Everything is Python3. If your interview is in C++ or Java, you can still read the approaches, but the syntax, the standard library idioms, and the performance characteristics you practise will be different. The README does not offer translations or parallel implementations in other languages.

Finally, the licence is listed as NOASSERTION. That means GitHub could not map the LICENSE file to a recognised identifier. If you plan to reuse code from the repository in your own project, read the LICENSE file yourself rather than assuming a permissive default.

## DSAlgo compared with VisuAlgo and Grokking Algorithms

The most common alternatives people search alongside DSAlgo are VisuAlgo and Grokking Algorithms, and they solve different problems. VisuAlgo is an interactive visualisation tool: it animates how a data structure or algorithm behaves step by step. That is useful when a recurrence or a rotation is not clicking, and it is useless when you want to read a working implementation. DSAlgo is the opposite. It gives you code to read and adapt, but it will not show you why a red-black tree rebalances.

Grokking Algorithms is a book, and the search results around it point to PDF copies on GitHub. A book gives you narrative explanation and illustrations in a fixed order. DSAlgo gives you a directory tree you can jump around in, plus company question sheets and a 30-day practice plan. Neither format is strictly better. If you learn by reading prose and drawing diagrams, the book wins. If you learn by reading code and running it, DSAlgo is the closer fit.

The practical difference comes down to feedback. Visualisation tools give you immediate visual feedback on a mechanism. A solutions repository gives you no feedback at all unless you write your own tests or compare against a judge. That is the gap to plan around: use DSAlgo for reference implementations, and use an actual judge or your own test cases to check whether you understood them.

## Maintenance, contributions and licence

The repository is not archived, and the last push was on 2026-06-17. That is recent enough that the project is still receiving changes, but the README's own contribution list is the best guide to what those changes look like: better solutions, new Python3 questions, new resources in BOOKS-and-PDFs and Questions-Sheet, and issue fixes. There is no versioned release cadence to track. The only release listed is v1.0 (DSAlgo) from 2023-03-24, so do not expect semantic versioning or changelogs. Upgrading means pulling the latest main branch and accepting whatever changed.

Contribution is open and the README lists hacktoberfest among the repository topics, which historically attracts bulk pull requests. If you depend on a specific file, pin the commit you cloned rather than tracking main, because a well-meaning contributor can rewrite the solution you were studying.

On licensing, the repository's licence is reported as NOASSERTION. GitHub uses that label when the LICENSE file does not match a known template. That is not a statement that the code is unlicensed, and it is not legal advice either way. Before copying a solution into your own repository, open the LICENSE file and read it, and if the terms are unclear for your use, ask someone qualified rather than guessing.

## Conclusion

Adopt DSAlgo if you are preparing for coding interviews in Python and want a topic-indexed reference you can browse offline or in the online VS Code view at samirpaulb.github.io/DSAlgo. Do not adopt it if you need a maintained library, a test harness, or non-Python solutions; the repository is a solutions collection, and the last push was on 2026-06-17, so the LeetCode folder will not track every new problem. Before relying on it, clone the repository and open 01_LeetCode and 30-Days-SDE-Sheet-Practice to check that the topics you care about are actually covered, since the README lists folders rather than a completeness guarantee.

## FAQ

### What is DSAlgo?

DSAlgo is a GitHub repository that stores solutions to data structures and algorithms problems and concepts in Python3, organised into numbered topic folders such as 01_LeetCode, 02_Dynamic-Programming and 23_Recursion. It also includes company question sheets, a 30-day SDE sheet practice folder, and a collection of books and PDFs.

### How do I get DSAlgo running locally?

There is no package to install. You can read the repository through the online VS Code view at https://samirpaulb.github.io/DSAlgo, or clone it with git clone https://github.com/SamirPaulb/DSAlgo.git and read the Python3 files with a Python 3 interpreter.

### Does DSAlgo include solutions for every LeetCode problem?

The README links to a LeetCode All Problems Solutions folder but does not claim the folder is exhaustive, and the repository's last push was on 2026-06-17, so problems added after that date are not present. Treat the folder as a large sample rather than a complete set.

### Is DSAlgo only in Python?

Yes. The README states that solutions and concepts are stored in Python3, and the contribution guidelines ask for new questions and solutions in Python3. There are no parallel implementations in other languages.

### What licence does DSAlgo use?

The repository's licence is reported as NOASSERTION, meaning GitHub could not match the LICENSE file to a recognised identifier. Read the LICENSE file directly before reusing code from the repository.

## Sources

- [Issues](https://github.com/SamirPaulb/DSAlgo/issues)
- [Project website](https://samirpaulb.github.io/DSAlgo)
- [README](https://github.com/SamirPaulb/DSAlgo/blob/main/README.md)
- [Releases](https://github.com/SamirPaulb/DSAlgo/releases)
- [SamirPaulb/DSAlgo on GitHub](https://github.com/SamirPaulb/DSAlgo)

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Hysen Labs editorial analysis, written from the project's own repository and release notes. Cite the canonical page: https://hysenlabs.com/projects/samirpaulb-dsalgo