Audience
Anyone looking for an Unit Testing solution that measures data quality in large datasets
About Deequ
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.
Bright Security
Bright Security is a developer-centric Dynamic Application Security Testing (DAST) solution that helps organizations ship secure applications and APIs quickly and cost-effectively. Its approach enables quick and iterative scans to identify critical security vulnerabilities early in the SDLC without compromising on quality or delivery speed. Bright empowers AppSec teams to provide governance for securing APIs and web apps while allowing developers to take ownership of security testing and remediation work.
Unlike legacy DAST solutions built for AppSec professionals, which are complex to deploy and find vulnerabilities late in the development process, Bright's DAST solution is optimized for the DevOps world. It can be deployed as early as the Unit Testing phase and run throughout the SDLC, learning and optimizing from every scan. By enabling organizations to detect and remediate vulnerabilities early in the SDLC, Bright reduces risk at a lower cost and effort.
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Refraction
Refraction is a code-generation tool for developers. It uses AI to generate code for you. You can use it to generate unit tests, documentation, refactor code, and more. Generate code using AI in 34 languages — Assembly, C#, C++, CoffeeScript, CSS, Dart, Elixir, Erlang, Go, GraphQL, Groovy, Haskell, HTML, Java, JavaScript, Kotlin, LaTeX, Less, Lua, MatLab, Objective-C, OCaml, Perl, PHP, Python, R Lang, Ruby, Rust, Sass / SCSS, Scala, Shell, SQL, Swift, and TypeScript. Join thousands of developers around the world using Refraction to generate documentation, create unit tests, refactor code, and more using AI. Use the power of AI to automate the tedious parts of software development like testing, documentation, and refactoring, so you can focus on what matters. Refactor, optimize, fix and style-check your code. Generate unit tests for your code with various test frameworks. Explain the purpose of your code to make it easier to understand.
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Catch2
Catch2 is mainly a unit testing framework for C++, but it also provides basic micro-benchmarking features and simple BDD macros. Catch2's main advantage is that using it is both simple and natural. Test names do not have to be valid identifiers, assertions look like normal C++ boolean expressions, and sections provide a nice and local way to share set-up and tear-down code in tests. You are on the devel branch, where the v3 version is being developed. v3 brings a bunch of significant changes, the big one being that Catch2 is no longer a single-header library. Catch2 now behaves as a normal library, with multiple headers and separately compiled implementation. Quick and easy to get started. Just download two files, add them to your project and you're away. No external dependencies. As long as you can compile C++14 and have the C++ standard library available. Write test cases as, self-registering, functions (or methods, if you prefer).
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pytest
pytest helps you write better programs. The pytest framework makes it easy to write small tests, yet scales to support complex functional testing for applications and libraries. Due to pytest’s detailed assertion introspection, only plain assert statements are used. Detailed info on failing assert statements. Auto-discovery of test modules and functions. Modular fixtures for managing small or parametrized long-lived test resources. Can run unittest (including trial) and nose test suites out of the box. Supports Python 3.6+ and PyPy 3. Rich plugin architecture, with over 315+ external plugins and thriving community. The maintainers of pytest and thousands of other packages are working with Tidelift to deliver commercial support and maintenance for the open source dependencies you use to build your applications. Save time, reduce risk, and improve code health, while paying the maintainers of the exact dependencies you use.
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Integrations
Company Information
Deequ
github.com/awslabs/deequ
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