Dooma is your ultimate, blazing-fast Data Structures and Algorithms (DSA) preparation companion. Built entirely for the terminal, it serves as a lightweight, interactive explorer for over 17,900+ real interview questions from 660+ top tech companies.
No more scrolling through clunky websites or losing track of which questions Amazon or Google actually ask. Dooma brings the entire dataset straight into your console with a beautiful, responsive UI.
- Massive Database: Access a curated, offline-first dataset of 17,931 question mappings across 662 companies.
- Interactive Terminal UI: Built with
RichandTyper, Dooma offers a stunning, paginated, and easy-to-navigate interface. - Alphabetical Explorer: Quickly jump to your target company (e.g., press
Gfor Google) and view all associated questions. - Data Rich: Instantly see Question Titles, Difficulty Ratings (color-coded), Frequency/Acceptance percentages, and direct LeetCode URLs.
- Zero Overhead: No accounts, no internet required to browse the database, no tracking. Just pure preparation.
Dooma is incredibly easy to set up and use.
Clone the repository and install it locally using pip:
git clone https://github.com/im-anishraj/dooma.git
cd dooma
pip install -e .Once installed, simply run the tool from anywhere in your terminal:
dooma- You will be greeted by an alphabet menu. Type the first letter of your target company (e.g.,
Afor Amazon). - Select your company from the beautifully paginated list.
- Browse the questions, take note of the difficulties and frequencies, and click the URLs to practice!
- Type
0at any time to safely step back through the menus.
We welcome contributions to make Dooma even better! Whether you want to update the dataset, add new features, or improve the UI, we'd love your help. Please see CONTRIBUTING.md for details on how to get started and the pull request process.
Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.
This project is licensed under the MIT License - see the LICENSE file for details.