Reverse Dependencies of delta-spark

The following projects have a declared dependency on delta-spark:

• butterfree — A tool for building feature stores - Transform your raw data into beautiful features.
• calista — Comprehensive Python package designed to simplify data quality checks across multiple platforms
• data-ecosystem-python — Program Agnostic Data Ecosystem (PADE) - Python Services
• data-ecosystem-services — Program Agnostic Data Ecosystem (PADE) - Python Services
• data-quality-sdk — A Data Quality SDK for real-time metrics and checks.
• dbl-discoverx — DiscoverX - Map and Search your Lakehouse
• delta-hydro — Advanced Delta-Lake related tooling based on Apache Spark
• delta-sync — Syncing delta tables
• dlt-meta — DLT-META Framework
• dlt-utils-lib — no summary
• dq-suite-amsterdam — Wrapper for Great Expectations to fit the requirements of the Gemeente Amsterdam.
• fabric-data-guard — A library for data quality checks in Microsoft Fabric using Great Expectations
• fabric-fast-start — Fabric Fast Start is a set of tools to help you get started with Fabric.
• hopsworks — Hopsworks Python SDK to interact with Hopsworks Platform, Feature Store, Model Registry and Model Serving
• idg-metadata-client — Ingestion Framework for OpenMetadata
• jobsworthy — no summary
• katonic — A modern, enterprise-ready MLOps Python SDK
• kedro-datasets — Kedro-Datasets is where you can find all of Kedro's data connectors.
• koheesio — The steps-based Koheesio framework
• l2-data-utils — no summary
• labelspark — Labelbox Connector for Databricks
• lakehouse-engine — A configuration-driven Spark framework serving as the engine for several lakehouse algorithms and data flows.
• metamart-ingestion — Ingestion Framework for MetaMart
• mx-stream-core — This is package stream core of mindx
• myetljob-run — My first ETL library
• openmetadata-ingestion — Ingestion Framework for OpenMetadata
• patek — A collection of utilities and tools for accelerating pyspark development and productivity.
• prt-databricks-simplify-7da-data-ingest — providing creating data layers from pdro s3 buckets
• pushcart — Metadata transformations for Spark
• pyeqx — no summary
• pyeqx-core — no summary
• pyspark-helpers — A collection of tools to help when developing PySpark applications
• pysparkdt — An open-source Python library for simplifying local testing of Databricks workflows that use PySpark and Delta tables.
• pysparta — Library to help ETL using pyspark
• pytest-dbx — Pytest plugin to run unit tests for dbx (Databricks CLI extensions) related code
• pytest-kuunda — pytest plugin to help with test data setup for PySpark tests
• python-prakashravip1 — Common Python Utility and Client Tools
• rialto — Rialto is a framework for building and deploying machine learning features in a scalable and reusable way. It provides a set of tools that make it easy to define and deploy features and models, and it provides a way to orchestrate the execution of these features and models.
• rtdip-sdk — no summary
• schemon-python-client — no summary
• seedspark — Spark ETL Utility Framework
• spalah — Spalah is a set of PySpark dataframe helpers
• spark-batch — spark_delta_batch for bronze > silve > gold > mart auto
• spark-hydro — Advanced Delta-Lake related tooling based on Apache Spark
• spark-utils — Utility classes for comfy Spark job authoriing.
• sparkpipelineframework — Framework for simpler Spark Pipelines
• sparkpipelineframework.testing — Testing Framework for SparkPipelineFramework
• sphinxHub — Basic library helpers
• stacks-data — A suite of utilities to support data engineering workloads within an Ensono Stacks data platform.
• toolbox-pyspark — Helper files/functions/classes for generic PySpark processes
• trawler-on-lake — no summary
• tuberia — Tuberia... when data engineering meets software engineering
• xedro — Kedro helps you build production-ready data and analytics pipelines
• yetl-framework — yet (another spark) etl framework