great-expectations / great_expectations
Always know what to expect from your data.
☆9,997Updated this week
Related projects ⓘ
Alternatives and complementary repositories for great_expectations
- Amundsen is a metadata driven application for improving the productivity of data analysts, data scientists and engineers when interacting…☆4,440Updated last week
- Deequ is a library built on top of Apache Spark for defining "unit tests for data", which measure data quality in large datasets.☆3,309Updated last month
- the portable Python dataframe library☆5,318Updated this week
- Data quality testing for the modern data stack (SQL, Spark, and Pandas) https://www.soda.io☆1,913Updated this week
- An orchestration platform for the development, production, and observation of data assets.☆11,711Updated this week
- dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build application…☆9,976Updated this week
- The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️☆3,511Updated 2 months ago
- The Open Source Feature Store for Machine Learning☆5,613Updated this week
- A unified interface for distributed computing. Fugue executes SQL, Python, Pandas, and Polars code on Spark, Dask and Ray without any rew…☆2,013Updated last month
- A light-weight, flexible, and expressive statistical data testing library☆3,401Updated this week
- re_data - fix data issues before your users & CEO would discover them 😊☆1,552Updated 6 months ago
- Open Source Platform for developing, scaling and deploying serious ML, AI, and data science systems☆8,256Updated this week
- Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and…☆10,016Updated this week
- ZenML 🙏: The bridge between ML and Ops. https://zenml.io.☆4,073Updated this week
- Data-Centric Pipelines and Data Versioning☆6,181Updated this week
- Prefect is a workflow orchestration framework for building resilient data pipelines in Python.☆17,507Updated this week
- An open-source storage framework that enables building a Lakehouse architecture with compute engines including Spark, PrestoDB, Flink, Tr…☆7,608Updated this week
- Voilà turns Jupyter notebooks into standalone web applications☆5,465Updated 2 weeks ago
- Open source platform for the machine learning lifecycle☆18,812Updated this week
- Modin: Scale your Pandas workflows by changing a single line of code☆9,898Updated last month
- 📚 Parameterize, execute, and analyze notebooks☆5,977Updated last month
- Evidently is an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. Fro…☆5,405Updated this week
- Agile Data Preparation Workflows made easy with Pandas, Dask, cuDF, Dask-cuDF, Vaex and PySpark☆1,481Updated this week
- 🦉 Data Versioning and ML Experiments☆13,927Updated this week
- An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models☆4,386Updated this week
- Panel: The powerful data exploration & web app framework for Python☆4,792Updated this week
- Luigi is a Python module that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, vis…☆17,883Updated last week
- Modern columnar data format for ML and LLMs implemented in Rust. Convert from parquet in 2 lines of code for 100x faster random access, v…☆3,964Updated this week
- Distributed data engine for Python/SQL designed for the cloud, powered by Rust☆2,336Updated this week