Auto-LeetCode-Notes

Auto-LeetCode-Notes is a Python-based automation tool designed to streamline the process of creating detailed, high-quality study notes for LeetCode problems. It fetches problem details from LeetCode, combines them with your Python solution, and leverages a GPT model to generate in-depth analysis and comparative notes in Markdown format.

This tool helps you focus on solving problems while it handles the note-taking, ensuring you build a structured and professional personal knowledge base.

Features

• Automated Note Generation: Automatically creates detailed Markdown notes from your solution files.
• Batch Processing: Process multiple solutions at once based on a simple todo.yml configuration file.
• GPT-Powered Analysis: Uses AI to identify your approach, suggest alternative solutions, and provide a comprehensive analysis of time/space complexity.
• Customizable Prompts: Easily tailor the GPT prompts to fit your specific learning style or requirements.
• Organized by Category: Automatically organizes notes into subdirectories based on problem categories (e.g., Two Pointers, Binary Tree).

Quick Start

Follow these steps to get the tool up and running.

1. Installation

First, clone the repository and install the required Python packages.

git clone git@github.com:maxx1031/leetcode-auto-notes.git
cd Auto-LeetCode-Notes
pip install -r requirements.txt

2. Configuration

The tool requires an OpenAI API key to function.

1. Create a file named .env in the root directory of the project.

2. Add your OpenAI API key to the .env file as shown below. You can also specify a custom base URL if you are using a proxy.

   OPENAI_API_KEY="sk-your-key-here"
   # Optional: If you use a proxy or a different API endpoint
   # OPENAI_BASE_URL="https://api.example.com/v1"

Usage

The tool offers two primary modes of operation: processing a single solution or batch processing an entire category of solutions.

Processing a Single Solution

To generate a note for a single LeetCode problem, use the process_single.py script. You need to provide the path to your solution file and optionally a category name.

The script infers the LeetCode problem "slug" from the filename (e.g., 15-3sum.py becomes 3sum).

python scripts/process_single.py solutions/15.py --category "Two Pointers"

Batch Processing Solutions

For batch processing, first define your problem lists in todo.yml. The keys represent categories (which will become folder names), and the values are lists of LeetCode problem IDs.

Example todo.yml:

Two Pointers-Two Sum:
  - 15
  - 2824

Binary Tree-BFS:
  - 107
  - 116
  - 117

Once todo.yml is configured, run process_batch.py with the desired category name.

python scripts/process_batch.py "Two Pointers-Two Sum"

The script will find all corresponding solution files in the solutions/ directory (e.g., 15.py, 2824.py) and generate notes for them, skipping any that already exist.

Customization

How to Modify the GPT Prompt

The core of the AI-generated analysis lies in the prompt. You can customize it to change the structure, tone, or content of the output.

1. Locate the Prompt File: The prompt is constructed in the create_prompt function within src/lc_automator/gpt.py.

2. Edit the Prompt: Open the file and modify the prompt string variable. You can change any part of the template, such as:

   • The introductory instructions for the AI.
   • The sections to be generated (e.g., adding a new "Pitfalls" section).
   • The format of the test cases or complexity analysis tables.

Example: To change the tone to be more concise, you could modify the initial instruction from "You are a world-class algorithm expert..." to "Generate a brief technical summary...".

File and Directory Structure

• solutions/: Place your raw Python solution files here. The filename should ideally be the problem ID (e.g., 2824.py).
• notes/: The generated Markdown notes are stored here. The tool creates subdirectories inside notes/ based on the categories you provide.
• src/lc_automator/: Contains the core logic for fetching data (fetcher.py) and interacting with GPT (gpt.py).
• scripts/: Contains the executable scripts for single and batch processing.
• todo.yml: The control file for batch processing.
• .env: Your local environment configuration (API keys, etc.). Not version controlled.

By following this structure, you can easily manage your solutions and generated notes.

Automated Committing

To help maintain a clean and conventional commit history, this project includes an interactive script auto_commit.sh.

How to Use

1. Make the script executable (one-time setup): Before you can run the script, you need to give it execution permissions. You only need to do this once.

   chmod +x scripts/auto_commit.sh

2. Run the script: Whenever you want to commit your changes, run the script from the project's root directory.

   ./scripts/auto_commit.sh

The script will then guide you through an interactive process:

• It will ask you to choose a commit type (like feat, fix, docs).
• It will prompt you to enter a short commit message.

After you confirm, it will automatically stage all changes, commit them with the formatted message, and push them to your remote repository.