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🛠️ SQLMongo - A PyPI package for converting SQL queries to MongoDB queries and vice versa. Effortlessly translate between relational and NoSQL query formats for seamless database interoperability.

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SQL-Mongo Converter - A Lightweight SQL to MongoDB (and Vice Versa) Query Converter 🍃

License: MIT
Python Version
SQL
MongoDB
PyPI

SQL-Mongo Converter is a lightweight Python library for converting SQL queries into MongoDB query dictionaries and converting MongoDB query dictionaries into SQL statements. It is designed for developers who need to quickly migrate or prototype between SQL-based and MongoDB-based data models without the overhead of a full ORM.

Currently live on PyPI: https://pypi.org/project/sql-mongo-converter/


Table of Contents


Features

  • SQL to MongoDB Conversion:
    Convert SQL SELECT queries—including complex WHERE clauses with multiple conditions—into MongoDB query dictionaries with filters and projections.

  • MongoDB to SQL Conversion:
    Translate MongoDB find dictionaries, including support for comparison operators, logical operators, and list conditions, into SQL SELECT statements with WHERE clauses, ORDER BY, and optional LIMIT/OFFSET.

  • Extensible & Robust:
    Built to handle a wide range of query patterns. Easily extended to support additional SQL functions, advanced operators, and more complex query structures.


Installation

Prerequisites

  • Python 3.7 or higher
  • pip

Install via PyPI

pip install sql-mongo-converter

Installing from Source

Clone the repository and install dependencies:

git clone https://github.com/yourusername/sql-mongo-converter.git
cd sql-mongo-converter
pip install -r requirements.txt
python setup.py install

Usage

Converting SQL to MongoDB

Use the sql_to_mongo function to convert a SQL SELECT query into a MongoDB query dictionary. The output dictionary contains:

  • collection: The table name.
  • find: The filter dictionary derived from the WHERE clause.
  • projection: The columns to return (if not all).

Example

from sql_mongo_converter import sql_to_mongo

sql_query = "SELECT name, age FROM users WHERE age > 30 AND name = 'Alice';"
mongo_query = sql_to_mongo(sql_query)
print(mongo_query)
# Expected output:
# {
#   "collection": "users",
#   "find": { "age": {"$gt": 30}, "name": "Alice" },
#   "projection": { "name": 1, "age": 1 }
# }

Converting MongoDB to SQL

Use the mongo_to_sql function to convert a MongoDB query dictionary into a SQL SELECT statement. It supports operators such as $gt, $gte, $lt, $lte, $in, $nin, and $regex, as well as logical operators like $and and $or.

Example

from sql_mongo_converter import mongo_to_sql

mongo_obj = {
    "collection": "users",
    "find": {
        "$or": [
            {"age": {"$gte": 25}},
            {"status": "ACTIVE"}
        ],
        "tags": {"$in": ["dev", "qa"]}
    },
    "projection": {"age": 1, "status": 1, "tags": 1},
    "sort": [("age", 1), ("name", -1)],
    "limit": 10,
    "skip": 5
}
sql_query = mongo_to_sql(mongo_obj)
print(sql_query)
# Example output:
# SELECT age, status, tags FROM users WHERE ((age >= 25) OR (status = 'ACTIVE')) AND (tags IN ('dev', 'qa'))
# ORDER BY age ASC, name DESC LIMIT 10 OFFSET 5;

API Reference

sql_to_mongo(sql_query: str) -> dict

  • Description:
    Parses a SQL SELECT query and converts it into a MongoDB query dictionary.
  • Parameters:
    • sql_query: A valid SQL SELECT query string.
  • Returns:
    A dictionary containing:
    • collection: The table name.
    • find: The filter derived from the WHERE clause.
    • projection: A dictionary specifying the columns to return.

mongo_to_sql(mongo_obj: dict) -> str

  • Description:
    Converts a MongoDB query dictionary into a SQL SELECT statement.
  • Parameters:
    • mongo_obj: A dictionary representing a MongoDB find query, including keys such as collection, find, projection, sort, limit, and skip.
  • Returns:
    A SQL SELECT statement as a string.

Testing

The package includes a unittest suite to verify conversion functionality.

Running Tests

  1. Create a virtual environment (optional but recommended):

    python -m venv venv
    source venv/bin/activate  # On Windows: venv\Scripts\activate
  2. Install test dependencies:

    pip install -r requirements.txt
    pip install pytest
  3. Run tests:

    python -m unittest discover tests
    # or using pytest:
    pytest --maxfail=1 --disable-warnings -q

Demo Script

A demo script in the tests directory is provided to showcase the conversion capabilities. It can be run directly to see examples of SQL to MongoDB and MongoDB to SQL conversions.

python demo.py

The script demonstrates various conversion scenarios.


Building & Publishing

Building the Package

  1. Ensure you have setuptools and wheel installed:

    pip install setuptools wheel
  2. Build the package:

    python setup.py sdist bdist_wheel

    This creates a dist/ folder with the distribution files.

Publishing to PyPI

  1. Install Twine:

    pip install twine
  2. Upload your package:

    twine upload dist/*
  3. Follow the prompts for your PyPI credentials.


Contributing

Contributions are welcome! To contribute:

  1. Fork the Repository

  2. Create a Feature Branch:

    git checkout -b feature/my-new-feature
  3. Commit Your Changes:

    git commit -am "Add new feature or fix bug"
  4. Push Your Branch:

    git push origin feature/my-new-feature
  5. Submit a Pull Request on GitHub.

For major changes, please open an issue first to discuss your ideas.


License

This project is licensed under the MIT License.


Final Remarks

SQL-Mongo Converter is a powerful, lightweight tool that bridges SQL and MongoDB query languages. It is ideal for developers migrating between SQL and MongoDB data models, or those who want to prototype and test queries quickly. Extend and customize the converter as needed to support more advanced queries or additional SQL constructs.

Happy converting! 🍃

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