diff --git a/README.md b/README.md index be50aba..de36735 100644 --- a/README.md +++ b/README.md @@ -5,15 +5,20 @@ These packages have not been vetted or approved by the pydantic team. +## Data Engineering + +- [Laktory](https://github.com/opencubes-ai/laktory) 🌟(1) - A DataOps framework for building Databricks lakehouse. + + ## Machine Learning -- [Transformers](https://github.com/huggingface/transformers) 🌟(116673) - State-of-the-art Natural Language Processing for PyTorch and TensorFlow 2.0. +- [Transformers](https://github.com/huggingface/transformers) 🌟(116684) - State-of-the-art Natural Language Processing for PyTorch and TensorFlow 2.0. -- [ray](https://github.com/ray-project/ray) 🌟(28938) - Ray provides a simple, universal API for building distributed applications. +- [ray](https://github.com/ray-project/ray) 🌟(28942) - Ray provides a simple, universal API for building distributed applications. -- [spaCy](https://github.com/explosion/spaCy) 🌟(27747) - spaCy is a free open-source library for Natural Language Processing in Python. It features NER, POS tagging, dependency parsing, word vectors and more. +- [spaCy](https://github.com/explosion/spaCy) 🌟(27752) - spaCy is a free open-source library for Natural Language Processing in Python. It features NER, POS tagging, dependency parsing, word vectors and more. -- [jina](https://github.com/jina-ai/jina) 🌟(19409) - Jina is geared towards building search systems for any kind of data, including text, images, audio, video and many more. With the modular design & multi-layer abstraction, you can leverage the efficient patterns to build the system by parts, or chaining them into a Flow for an end-to-end experience. +- [jina](https://github.com/jina-ai/jina) 🌟(19410) - Jina is geared towards building search systems for any kind of data, including text, images, audio, video and many more. With the modular design & multi-layer abstraction, you can leverage the efficient patterns to build the system by parts, or chaining them into a Flow for an end-to-end experience. - [ZenML](https://github.com/zenml-io/zenml) 🌟(3305) - MLOps framework to create reproducible ML pipelines for production machine learning. @@ -21,14 +26,14 @@ These packages have not been vetted or approved by the pydantic team. - [DocArray](https://github.com/docarray/docarray) 🌟(2576) - Represent, send, store and search multimodal data based on Pydantic. Compatible with Multiple Vector Databases -- [Instructor](https://github.com/jxnl/instructor) 🌟(2509) - Controlling OpenAI Function Calling via Pydantic Models +- [Instructor](https://github.com/jxnl/instructor) 🌟(2512) - Controlling OpenAI Function Calling via Pydantic Models - [FastMRI](https://github.com/facebookresearch/fastMRI) 🌟(1175) - fastMRI is a collaborative research project from Facebook AI Research (FAIR) and NYU Langone Health to investigate the use of AI to make MRI scans faster. ## Object Mapping -- [SQLModel](https://github.com/tiangolo/sqlmodel) 🌟(11598) - SQLModel is a library for interacting with SQL databases from Python code, with Python objects. +- [SQLModel](https://github.com/tiangolo/sqlmodel) 🌟(11604) - SQLModel is a library for interacting with SQL databases from Python code, with Python objects. - [Beanie](https://github.com/roman-right/beanie) 🌟(1579) - Beanie - is an Asynchronous Python object-document mapper (ODM) for MongoDB, based on Motor and Pydantic. @@ -57,7 +62,7 @@ These packages have not been vetted or approved by the pydantic team. ## Utilities -- [HttpRunner](https://github.com/httprunner/httprunner) 🌟(3860) - HttpRunner is a simple & elegant, yet powerful HTTP(S) testing framework. +- [HttpRunner](https://github.com/httprunner/httprunner) 🌟(3861) - HttpRunner is a simple & elegant, yet powerful HTTP(S) testing framework. - [Strawberry GraphQL](https://github.com/strawberry-graphql/strawberry) 🌟(3548) - Python GraphQL library based on dataclasses. @@ -83,20 +88,22 @@ These packages have not been vetted or approved by the pydantic team. - [easyconfig](https://github.com/spacemanspiff2007/easyconfig) 🌟(3) - Easy application configuration with yaml files and pydantic models. Allows automatic creation of default configuration files with value descriptions as comments. Additionally has environment variable expansion and support for docker secrets. Can also has support for reloading values on the fly e.g. in combination with a file watcher. Works with normal pydantic models and pydantic settings. +- [Settus](https://github.com/okube-ai/settus) 🌟(0) - Settings management using Pydantic Settings and extended to secrets from Azure Keyvault, Databricks secrets, AWS Secrets Manager and GCP Secrets Manager + ## Web -- [FastAPI](https://github.com/tiangolo/fastapi) 🌟(65525) - FastAPI is a modern, fast (high-performance), web framework for building APIs with Python 3.6+ based on standard Python type hints. +- [FastAPI](https://github.com/tiangolo/fastapi) 🌟(65535) - FastAPI is a modern, fast (high-performance), web framework for building APIs with Python 3.6+ based on standard Python type hints. -- [Django Ninja](https://github.com/vitalik/django-ninja) 🌟(5411) - Django + Pydantic = Fast, Async-ready, OpenAPI, type hints based framework for building APIs. +- [Django Ninja](https://github.com/vitalik/django-ninja) 🌟(5413) - Django + Pydantic = Fast, Async-ready, OpenAPI, type hints based framework for building APIs. -- [Litestar (before Starlite)](https://github.com/litestar-org/litestar) 🌟(3548) - Flexible ASGI API framework built on top of Starlette and pydantic. +- [Litestar (before Starlite)](https://github.com/litestar-org/litestar) 🌟(3549) - Flexible ASGI API framework built on top of Starlette and pydantic. - [BlackSheep](https://github.com/Neoteroi/BlackSheep) 🌟(1545) - BlackSheep is an asynchronous web framework to build event based web applications with Python. It is inspired by Flask, ASP.NET Core, and the work by Yury Selivanov. -- [FastStream](https://github.com/airtai/faststream) 🌟(1254) - FastStream simplifies the process of writing producers and consumers for message queues, handling all the parsing, networking and documentation generation automatically. +- [FastStream](https://github.com/airtai/faststream) 🌟(1255) - FastStream simplifies the process of writing producers and consumers for message queues, handling all the parsing, networking and documentation generation automatically. -- [Propan](https://github.com/Lancetnik/Propan) 🌟(451) - Propan is a powerful and easy-to-use Python framework for building event-driven applications that interact with any MQ Broker. +- [Propan](https://github.com/Lancetnik/Propan) 🌟(452) - Propan is a powerful and easy-to-use Python framework for building event-driven applications that interact with any MQ Broker. - [Flask Pydantic](https://github.com/bauerji/flask_pydantic) 🌟(309) - Flask extension for integration of the awesome pydantic package with Flask.