mongotoy 0.1.7

Comprehensive ODM for MongoDB

Mongotoy is a comprehensive Object-Document Mapper (ODM) that streamlines interactions with MongoDB databases in Python applications. Powered by Motor driver, Mongotoy seamlessly integrates with MongoDB, offering a versatile toolkit for constructing high-performance applications. This integration facilitates efficient communication with MongoDB databases, guaranteeing optimal scalability and responsiveness. With Mongotoy, you can unlock the full potential of MongoDB's features.

Features

• Asynchronous Power: Mongotoy leverages the asynchronous paradigm of Python, enabling efficient management of I/O operations for optimal performance and responsiveness in applications.

• Based on Motor Driver: Mongotoy is built on top of the asynchronous Motor MongoDB driver, ensuring seamless integration with asynchronous Python applications.

• Schemaless Flexibility: With a schemaless design, Mongotoy empowers developers to work with MongoDB databases without rigid schemas, adapting to evolving data models effortlessly.

• Intuitive API: Mongotoy features an elegant and straightforward API facilitating common database operations.

• Flexible Configuration Options: Mongotoy offers extensive configuration options at both the database and document levels, enabling fine-tuning of MongoDB interactions for optimal performance and reliability.

• Custom Data Types Support: Mongotoy simplifies handling of custom data types and allows defining new types through Data Mapper classes, enhancing data integrity and consistency.

• Object-Document Mapping: Simplifying MongoDB document manipulation, Mongotoy maps Python objects to MongoDB documents seamlessly, enabling intuitive and object-oriented interactions.

• Document Serialization: Mongotoy supports serialization of documents into JSON, BSON, or Python dictionaries, enabling seamless integration with different parts of an application stack.

• Document Inheritance Support: Mongotoy provides robust support for document inheritance, enabling the creation of hierarchical data models and promoting code reuse and maintainability.

• Python Type Hint Support: Mongotoy allows developers to define document fields using Python type hints, enhancing code readability and enabling type checking.

• Relationship Management: Simplifying relationship management between documents, Mongotoy offers robust support for references and embedded documents, automating insertions, deletions, and updates.

• Automatic Operation Handling: Mongotoy automates insertion and deletion management, ensuring data integrity and consistency across related documents.

• Query Building: Mongotoy provides a powerful query building interface for constructing complex queries using Pythonic syntax.

• Index Management: Mongotoy simplifies the management of database indexes, optimizing query performance for efficient data retrieval.

• Transactions: Supporting MongoDB transactions, Mongotoy ensures data consistency and atomicity across multiple operations within a single transactional context.

• Geospatial Data Support: Mongotoy offers robust support for geospatial data types, facilitating storage, querying, and spatial analysis.

• Database Seeding Management: With built-in support for database seeding, Mongotoy streamlines the initialization of databases with predefined data sets, enhancing developer productivity.

• Support for Capped Collections: Mongotoy natively supports capped collections in MongoDB, ideal for scenarios requiring fixed-size, ordered datasets.

• Time Series Collections Management: Mongotoy provides robust support for managing time series data in MongoDB, optimized for storing and querying time-stamped data points.

• GridFS File Handling: Mongotoy seamlessly integrates with MongoDB's GridFS storage system for efficient handling of large files, offering a high-level interface for file management within MongoDB.

Minimal Example

Let's begin with a minimal example by defining a document and performing CRUD operations on the database.

import asyncio
from mongotoy import Document, Engine
import datetime


class Person(Document):
    name: str
    last_name: str
    dob: datetime.date

    
# Create database engine
db = Engine('test-db')


async def main():
    # Create a new Person instance
    person = Person(
        name='John',
        last_name='Doe',
        dob=datetime.date(1990, 12, 25)
    )    
    
    # Connect to the MongoDB database
    await db.connect('mongodb://localhost:27017')
    
    # Open a database session
    async with db.session() as session:
        
        # Save the person to the database
        await session.save(person)
        
        # Fetch all persons from database
        async for c in session.objects(Person):
            print(c.dump_dict())
            
        # Update person dob
        person.dob=datetime.date(1995, 10, 25)
        await session.save(person)
        
        # Delete person from database
        await session.delete(person)


if __name__ == '__main__':
    asyncio.run(main())

Installing

To install, just run:

pip install mongotoy

Or, if using poetry:

poetry add mongotoy

Extras

See full documentation at: https://gurcuff91.github.io/mongotoy

If you like this project !!