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About

Deequ is a library built on top of Apache Spark for defining "unit tests for data", which measure data quality in large datasets. We are happy to receive feedback and contributions. Deequ depends on Java 8. Deequ version 2.x only runs with Spark 3.1, and vice versa. If you rely on a previous Spark version, please use a Deequ 1.x version (legacy version is maintained in legacy-spark-3.0 branch). We provide legacy releases compatible with Apache Spark versions 2.2.x to 3.0.x. The Spark 2.2.x and 2.3.x releases depend on Scala 2.11 and the Spark 2.4.x, 3.0.x, and 3.1.x releases depend on Scala 2.12. Deequ's purpose is to "unit-test" data to find errors early, before the data gets fed to consuming systems or machine learning algorithms. In the following, we will walk you through a toy example to showcase the most basic usage of our library.

About

GitAuto is an AI-powered coding agent that integrates with GitHub (and optional Jira) to read backlog tickets or issues, analyze your repository’s file tree and code, then autonomously generate and review pull requests, typically within three minutes per ticket. It can handle bug fixes, feature requests, and test coverage improvements. You trigger it via issue labels or dashboard selections, it writes code or unit tests, opens a PR, runs GitHub Actions, and automatically fixes failing tests until they pass. GitAuto supports ten programming languages (e.g., Python, Go, Rust, Java), is free for basic usage, and offers paid tiers for higher PR volumes and enterprise features. It follows a zero data‑retention policy; your code is processed via OpenAI but not stored. Designed to accelerate delivery by enabling teams to clear technical debt and backlogs without extensive engineering resources, GitAuto acts like an AI backend engineer that drafts, tests, and iterates.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Anyone looking for an Unit Testing solution that measures data quality in large datasets

Audience

Software engineering teams and managers requiring a tool to offload routine bug fixes, feature work, and test generation to AI in order to speed up development and reclaim valuable developer time

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

$100 per month
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Deequ
github.com/awslabs/deequ

Company Information

GitAuto
Founded: 2024
United States
gitauto.ai/

Alternatives

NUnit

NUnit

.NET Foundation

Alternatives

Gru

Gru

Gru.ai
Early

Early

EarlyAI
Early

Early

EarlyAI
TestComplete

TestComplete

SmartBear

Categories

Categories

Integrations

Apache Spark
CSS
ChatGPT
Claude
Claude Sonnet 4
Gemini
GitHub
GitLab
Go
HTML
Java
JavaScript
Kotlin
OpenAI o4-mini
Python
Ruby
Rust
Swift
Tailwind CSS
TypeScript

Integrations

Apache Spark
CSS
ChatGPT
Claude
Claude Sonnet 4
Gemini
GitHub
GitLab
Go
HTML
Java
JavaScript
Kotlin
OpenAI o4-mini
Python
Ruby
Rust
Swift
Tailwind CSS
TypeScript
Claim Deequ and update features and information
Claim Deequ and update features and information
Claim GitAuto and update features and information
Claim GitAuto and update features and information