data-testing

⚡ Data quality testing for the modern data stack (SQL, Spark, and Pandas) https://www.soda.io

re_data - fix data issues before your users & CEO would discover them 😊

Code review for data in dbt

Data validation made beautiful and powerful

Various files useful for manual testing and test automation etc.

Great Expectations Airflow operator

re_data - fix data issues before your users & CEO would discover them 😊

A simple and easy to use Data Validation library for Python.

DataOps Data Quality TestGen is part of DataKitchen's Open Source Data Observability. DataOps TestGen delivers simple, fast data quality test generation and execution by data profiling,  new dataset hygiene review, AI generation of data quality validation tests, ongoing testing of data refreshes, & continuous anomaly monitoring

Soda Spark is a PySpark library that helps you with testing your data in Spark Dataframes

⚡ Prevent downstream data quality issues by integrating the Soda Library into your CI/CD pipeline.

Develop a data science project using historical sales data to build a regression model that accurately predicts future sales. Preprocess the dataset, conduct exploratory analysis, select relevant features, and employ regression algorithms for model development. Evaluate model performance, optimize hyperparameters, and provide actionable insights.

This library is inspired by the Great Expectations library. The library has made the various expectations found in Great Expectations available when using the inbuilt python unittest assertions.

DataBridge Quality Control

Spark Data Test - A PySpark-based automation testing utility to compare Spark DataFrames

data and pipeline testing with and for SQL

Data generation and validation tool for any data source

Software Testing in Open Source and Data Science: A talk delivered at the Data Umbrella speaker series

Example API implementation for Data Caterer

Documentation for Data Caterer