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Comprehensive ODM for MongoDB

Version Supported Python Versions

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.

License

This project is licensed under the terms of the Apache 2.0 license.