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GenFu is a library you can use to generate realistic test data. It is composed of several property fillers that can populate commonly named properties through reflection using an internal database of values or randomly created data. You can override any of the fillers, give GenFu hints on how to fill them.

We well know GANs for success in the realistic image generation. However, they can be applied in tabular data generation. We will review and examine some recent papers about tabular GANs in action.

  • tabular-data
  • gans
  • train-dataframe
  • adversarial-filtering

Event data simulator. Generates a stream of pseudo-random events from a set of users, designed to simulate web traffic.

Port of a popular ruby faker gem written in kotlin. Generate realistically looking fake data such as names, addresses, banking details, and many more, that can be used for testing and data anonymization purposes.

Generate mocks from ActiveRecord models for unit tests that run fast because they don’t need to load Rails or a database.

Framework allows to perform load testing with Apache Jmeter, view application/server metrics in real-time with Grafana, analyze errors cause with detailed traces for failed requests, compare different test runs in scripted dashboard and perform frontend performance testing with sitespeed.io+webpagetest

Shift-left API Integration | Auto-fix integration drift before integration. Specmatic turns API specifications into executable contracts, continuously verifying that every change made by AI coding agents and engineers stays true to the desired behaviour. Ship AI-ready APIs 10x faster, from intent to implementation, with Spec-Driven API Development.