ChatDB Project

ChatDB is an interactive database management tool that supports both SQL databases and MongoDB databases. It provides a user-friendly command-line interface for exploring, querying, and uploading data.

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Features

SQL Features:

• View database structure and sample table data.
• Auto-generate SQL queries.
• Parse natural language to generate SQL queries.
• Upload table data from CSV files.

MongoDB Features:

• List collections and their field information.
• Auto-generate MongoDB queries.
• Parse natural language to generate MongoDB queries.
• Upload collection data from JSON files.

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File Structure

ChatDB_Project/
│
├── main.py                # Main program providing entry point and menu logic
├── mongodb.py             # MongoDB-related functionality implementation
├── sql.py                 # SQL-related functionality implementation
├── requirements.txt       # List of required dependencies
└── README.md              # Project documentation

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Installation

1. Clone the Repository

git clone https://github.com/your-repo/ChatDB_Project.git
cd ChatDB_Project

2. Create a Virtual Environment and Install Dependencies (Optional)

python -m venv venv
source venv/bin/activate   # On Windows: venv\Scripts\activate

3. Install requirements

pip install -r requirements.txt

4. Configure the Databases

• SQL Database: Update connection details in sql.py (e.g., host, username, password, database name).
• MongoDB Database: Update connection details in mongodb.py (e.g., host and port).

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Running the Project

To start the program, run:

python main.py

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Usage

1. After starting the program, you will see a welcome screen. Choose the type of database:

   • Enter 1 for SQL database operations.
   • Enter 2 for MongoDB database operations.
   • Enter 3 to exit the program.

2. Follow the sub-menu prompts to explore tables/collections, generate queries, or upload data.

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Dependencies

This project relies on:

• pymysql: For connecting to SQL databases.
• pymongo: For connecting to MongoDB databases.
• pandas: For handling CSV data.

Refer to requirements.txt for the complete list.

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Developer Information

• Authors: Tengjiang Wang, Zifeng Zhou
• Academic Context: This project is part of USC's DSCI 551 course.

For inquiries, contact Waynewang229@gmail.com.