dnacryptdb-harshith 2.0.0

A secure triglot database system for DNA-based cryptographic applications

DNACryptDB

A secure triglot database system combining MySQL, MongoDB, and Neo4j with military-grade encryption.

A polyglot database system with a custom query language that unifies MySQL (relational) and MongoDB (document store) operations.

Features

• Unified Query Language**: One syntax for both MySQL and MongoDB
• Automatic Backend Routing**: Structured data → MySQL, Flexible data → MongoDB
• SQL Injection Proof**: Parameterized queries throughout
• Script Files**: Write .dnacdb files and execute them
• Interactive Mode**: Test queries in real-time
• Easy Configuration**: Simple JSON config file

Installation

From PyPI (once published)

pip install dnacryptdb

Quick Start

1. Initialize Configuration

dnacryptdb init

This creates dnacdb.config.json with your database credentials:

{
  "mysql": {
    "host": "localhost",
    "user": "root",
    "password": "your_password",
    "database": "dnacryptdb"
  },
  "mongodb": {
    "uri": "mongodb://localhost:27017/",
    "database": "dnacryptdb"
  }
}

2. Create a Script File

Create hello.dnacdb:

-- Create a table in MySQL
MAKE TABLE users WITH (name:text, email:text, age:int);

-- Insert data
PUT INTO users DATA {"name": "Alice", "email": "[e-mail]", "age": 30};
PUT INTO users DATA {"name": "Bob", "email": "[e-mail]", "age": 25};

-- Query data
FETCH FROM users WHERE age > 26;

-- Create a collection in MongoDB
MAKE COLLECTION logs;

-- Insert flexible documents
PUT INTO logs DATA {"level": "INFO", "message": "Application started"};

-- Show all structures
SHOW TABLES;
SHOW COLLECTIONS;

3. Run the Script

dnacryptdb run hello.dnacdb

4. Interactive Mode

dnacryptdb interactive

dnacdb> MAKE TABLE products WITH (name:text, price:float);
dnacdb> PUT INTO products DATA {"name": "Laptop", "price": 999.99};
dnacdb> FETCH FROM products ALL;
dnacdb> exit

Query Language Reference

Create Structures

-- Create relational table (MySQL)
MAKE TABLE tablename WITH (field1:type1, field2:type2);

-- Create document collection (MongoDB)
MAKE COLLECTION collectionname;

Data Types

• int / integer - Integer numbers
• float / double - Floating point numbers
• text / string - Text strings
• date - Date values
• datetime / timestamp - Date and time
• bool / boolean - Boolean values

Insert Data

PUT INTO target DATA {"field": "value", "field2": 123};

Query Data

-- Query all records
FETCH FROM source ALL;

-- Query with condition
FETCH FROM source WHERE field > value;
FETCH FROM source WHERE field = "value";

Update Data

CHANGE IN target SET field = value WHERE condition;
CHANGE IN target SET field = "value" WHERE name = "Alice";

Delete Data

REMOVE FROM target WHERE condition;
REMOVE FROM target WHERE age < 18;

Show Structures

SHOW TABLES;       -- List MySQL tables
SHOW COLLECTIONS;  -- List MongoDB collections

Drop Structures

DROP tablename;

Comments

-- This is a comment
# This is also a comment

Examples

Example 1: User Management

-- Create users table
MAKE TABLE users WITH (username:text, email:text, age:int);

-- Insert users
PUT INTO users DATA {"username": "alice", "email": "[e-mail]", "age": 30};
PUT INTO users DATA {"username": "bob", "email": "[e-mail]", "age": 25};
PUT INTO users DATA {"username": "charlie", "email": "[e-mail]", "age": 35};

-- Query users over 26
FETCH FROM users WHERE age > 26;

-- Update user age
CHANGE IN users SET age = 31 WHERE username = "alice";

-- Remove young users
REMOVE FROM users WHERE age < 30;

Example 2: Flexible Analytics

-- Create analytics collection
MAKE COLLECTION analytics;

-- Insert various event types
PUT INTO analytics DATA {"event": "page_view", "page": "/home", "timestamp": "2025-11-14T10:00:00"};
PUT INTO analytics DATA {"event": "click", "button": "signup", "metadata": {"campaign": "winter"}};
PUT INTO analytics DATA {"event": "purchase", "amount": 99.99, "items": ["laptop", "mouse"]};

-- Query all analytics
FETCH FROM analytics ALL;

Example 3: Mixed Data Types

-- Structured product data in MySQL
MAKE TABLE products WITH (name:text, price:float, stock:int);
PUT INTO products DATA {"name": "Laptop", "price": 999.99, "stock": 50};

-- Flexible review data in MongoDB
MAKE COLLECTION reviews;
PUT INTO reviews DATA {"product": "Laptop", "rating": 5, "comment": "Great!", "tags": ["fast", "reliable"]};

-- Query both
FETCH FROM products ALL;
FETCH FROM reviews ALL;

Architecture

Backend Selection

DNACryptDB automatically routes operations to the appropriate backend:

• Structured Data (MySQL): Tables with defined schemas
• Flexible Data (MongoDB): Collections with dynamic documents

Security

• Parameterized Queries: All user input is treated as data, not code
• No SQL Injection: Uses prepared statements for MySQL
• Safe JSON Parsing: No eval() or unsafe code execution

Database Structure

MySQL (ACID Properties)
├── Tables with fixed schemas
├── Auto-increment primary keys
├── Type enforcement
└── Relational integrity

MongoDB (BASE Properties)
├── Flexible document schemas
├── Automatic timestamps
├── Nested data support
└── Eventual consistency

Command Line Reference

# Initialize configuration
dnacryptdb init
dnacryptdb init -o custom_config.json

# Run script files
dnacryptdb run script.dnacdb
dnacryptdb run script.dnacdb -c custom_config.json

# Interactive mode
dnacryptdb interactive
dnacryptdb interactive -c custom_config.json

# Help
dnacryptdb --help
dnacryptdb run --help

Use as Python Library

from dnacryptdb import DNACryptDB

# Initialize
db = DNACryptDB(config_file="dnacdb.config.json")

# Execute single query
result = db.execute("MAKE TABLE users WITH (name:text, age:int)")
print(result)

# Execute script file
results = db.execute_file("script.dnacdb")

# Close connections
db.close()

Requirements

• Python 3.8+
• MySQL 5.7+ or MariaDB 10.2+
• MongoDB 4.0+

Development

# Clone repository
git clone https://github.com/Harshith2412/dnacryptdb.git
cd dnacryptdb

# Install in development mode
pip install -e .

# Run tests
python -m pytest tests/

# Format code
black dnacryptdb/

# Type checking
mypy dnacryptdb/

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

1. Fork the repository
2. Create your feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

• Built for the DNACrypt project at Northeastern University
• Integrates MySQL and MongoDB for polyglot database operations
• Part of MS in Cybersecurity research

Support

For issues, questions, or contributions, please visit:

• GitHub Issues: https://github.com/Harshith2412/dnacryptdb/issues
• Email: [e-mail]

Changelog

Version 1.0.0 (2025-11-14)

• Initial release
• Basic CRUD operations
• MySQL and MongoDB integration
• Script file execution
• Interactive mode
• Configuration management