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https://github.com/yudataguy/beatcode
Leetcode space repetition memorization web app
https://github.com/yudataguy/beatcode
leetcode
Last synced: 8 days ago
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Leetcode space repetition memorization web app
- Host: GitHub
- URL: https://github.com/yudataguy/beatcode
- Owner: yudataguy
- Created: 2024-10-25T20:32:42.000Z (3 months ago)
- Default Branch: main
- Last Pushed: 2024-10-25T23:15:01.000Z (3 months ago)
- Last Synced: 2024-11-30T21:23:38.916Z (2 months ago)
- Topics: leetcode
- Language: JavaScript
- Homepage:
- Size: 3.26 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- stars - yudataguy/beatcode - Leetcode space repetition memorization web app (JavaScript)
README
# LeetCode Practice Buddy: Your daily companion for coding interview prep!
This app sends you 3 carefully selected coding problems each day from LeetCode's [Top 150](https://leetcode.com/studyplan/top-interview-150/) interview questions. It uses smart repetition to help you remember solutions better - just like how you'd learn flashcards, but for coding problems!
Built with React, Node.js, and MongoDB, the app runs smoothly in Docker containers so you can set it up with minimal hassle.
Get your daily dose of coding practice and ace those technical interviews! 🚀
## Note
This application was built in a single day using Claude 3.5 Sonnet (20241022) and Cursor. While I've worked with LLMs before, this was my first attempt at developing a complete application spanning frontend, backend, database, and Docker deployment.
### Key Learnings
#### Strengths
* Rapid prototyping and initial setup is remarkably fast
* Excellent for generating boilerplate code and basic structures
#### Challenges
* LLMs often hallucinate variable names and database fields
* Can produce incomplete functions, requiring manual intervention
* Debugging support is limited, especially for subtle logic errors
* Scope management is crucial - larger projects increase the risk of compounding errors
#### Best Practices
* Maintain active oversight throughout development
* Verify each step before moving forward
* Be prepared to restart conversations when the LLM loses context
* Keep project scope focused and manageable
* Leverage your technical expertise to guide the development process
#### Critical Insight
Success with LLM-assisted development requires finding the right balance between automation and human oversight. While LLMs can significantly accelerate development, they work best when paired with solid technical understanding and careful validation at each step.
## Getting Started
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.
### Prerequisites
- Docker
- Docker Compose
### Running the Application
1. Clone the repository to your local machine.
2. Navigate to the project root directory.
3. Build and start the containers:
```
docker compose up --build
```
This command will start three containers:
- Frontend (React app)
- Backend (Node.js server)
- MongoDB
The frontend will be accessible at `http://localhost:3721`.
### Initializing the Database
After the containers are up and running, you need to initialize the database with some data. We provide two scripts for this purpose:
1. Initialize user statistics:
```
docker compose exec backend node init_stats.js
```
This script will create initial statistics for a user in the database.
2. Populate practice questions:
```
docker compose exec backend node prepare_questions.js
```
This script will populate the database with a set of practice questions.
### Stopping the Application
To stop the application and remove the containers, use:
```
docker compose down
```
## Development
For development, the Docker setup mounts the source code directories as volumes. This means you can make changes to the code on your host machine, and the changes will be reflected in the running containers.