Open-source alternatives to Cerberus

CONTRIBUTIONS ONLY: Voluptuous, despite the name, is a Python data validation library.

A JSONSchema validator that uses code generation to be extremely fast

Yup is a JavaScript schema validation library used to define data shapes and validate runtime values. It functions as an object schema validator and a data coercion engine, allowing developers to transform raw input values into desired types before performing validation checks. The library is distinguished by its support for dynamic schema validation, where rules can be adjusted at runtime based on sibling field values or external context. It also enables recursive data structuring for polymorphic fields and provides a system for extracting static TypeScript interfaces from runtime schema def

Zod is a TypeScript-first schema declaration and validation library designed to ensure end-to-end data integrity. It functions as a runtime type guard, allowing developers to define complex data structures through a declarative, chainable syntax. By using these schema definitions, the library automatically derives static TypeScript types, eliminating the need for manual type duplication and ensuring that runtime data matches expected application contracts. The library distinguishes itself through functional schema composition, which enables the creation of hierarchical structures by nesting a

This project is a JSON Schema validation library and framework used to verify that data instances conform to declarative definitions. It functions as a validation engine that enforces structural constraints and data types, while also serving as a meta-validator to ensure schema definitions themselves are syntactically correct against official meta-schemas. The library is designed for extensibility, allowing users to define custom validation logic by mapping schema keywords to specialized callable functions. It includes a registry-based reference resolver for managing internal and external URI

Superstruct is a JavaScript and TypeScript data validation library used to verify that data structures match defined shapes and types. It functions as a composable schema builder and a TypeScript schema validator, ensuring that runtime data checks remain synchronized with static type definitions. The library features a data coercion engine that transforms input values or injects default values before the validation process is executed. It enables the creation of complex validation rules by nesting, merging, or omitting properties from existing structures. Its capabilities cover the validatio

This library is a PHP framework for enforcing data integrity and business rules by validating scalar values and complex object structures against predefined constraints. It provides a structured approach to inspecting object graphs and property metadata, ensuring that data conforms to expected requirements before it is processed by an application. The framework distinguishes itself through a metadata-driven mapping system that uses reflection or configuration files to apply rules directly to object properties. It supports contextual rule orchestration, allowing developers to organize constrai

Valibot is a modular, type-safe schema library for validating and parsing structural data in TypeScript environments.

SeaTunnel is a distributed data integration engine designed to synchronize structured and unstructured data across diverse sources and sinks. It functions as a multi-engine execution framework that can run data integration tasks across different distributed computing backends to optimize workload performance. The project is distinguished by a visual data pipeline designer for configuring workflows without manual code and a specialized change data capture tool for streaming incremental database updates. It also includes an enrichment pipeline that integrates large language models and embedding

This project is an open-source customer relationship management platform that functions as a low-code application development framework. It provides a unified interface for tracking sales pipelines, managing customer interactions, and automating lead routing. The platform is built to serve as a business process automation tool, allowing users to define custom data structures and workflows to streamline operational tasks. The system distinguishes itself through its metadata-driven architecture, which enables dynamic form generation and relational document modeling. By utilizing server-side scr

This project is a Python implementation of the JSON Schema specification, providing a library for verifying that data instances conform to defined schemas. It serves as a data validation framework capable of validating both the data itself and the schemas against official meta-schemas to ensure structural correctness. The library features a schema reference resolver that maps URIs to definitions, enabling the resolution of internal and remote references for modular schema management. It is designed for extensibility, allowing for the definition of custom keywords, custom type-checking logic,

A robust email syntax and deliverability validation library for Python.

Deepchecks is a machine learning model validation framework and MLOps testing library. It serves as an AI data quality suite and performance evaluator designed to verify the integrity and performance of models and datasets from research through production. The project functions as a model monitoring tool for tracking data drift and performance degradation in production environments. It allows for the creation of custom validation suites and utilizes a pluggable check architecture to automate quality checks within continuous integration pipelines. The framework covers a broad range of capabil

Cleanlab is a data-centric AI library and toolkit designed to improve machine learning model performance by detecting label errors and increasing overall dataset quality. It implements a confident learning framework that iteratively refines label noise estimates by comparing model predictions with estimated label probabilities to identify mislabeled examples. The project provides specialized utilities for active learning optimization, allowing for the selection of the most impactful examples for labeling or re-labeling. It also includes an outlier detection tool to identify atypical data poin

Data Validation for Elixir

Object/value validation library

Joi is a JavaScript data validation library used to define schemas that validate, cast, and sanitize data objects. It functions as an object schema validator and parser, ensuring that input data matches specific types and formats before it is processed by an application. The library features a conditional validation engine capable of dynamic schema enforcement, where validation logic and dependencies change based on the values of other keys within an object. It also serves as a data casting and sanitization tool, transforming input values into target types and removing sensitive keys from the

Structural validation library for Clojure(Script)

Pandas, Polars, Spark, and Snowpark DataFrame comparison for humans and more!

v8n is a JavaScript data validation library used to verify that values, objects, and arrays meet specific criteria. It functions as a schema-based validator and an asynchronous validation engine, utilizing a fluent API to construct sequences of chainable rules and constraints. The framework is distinguished by its ability to execute promises and network requests during the validation process to determine if a value is valid. It allows for the creation of reusable validation schemas and provides a customizable rule framework where users can define their own logic and configure how error result

Complete instrumentation for clojure.spec

Efficient, hassle-free function call validation with a concise inline syntax for clojure.spec and Malli

Modeling domain data on the basis of Clojure records.

Fast, extensible and easy to use data structure validation for elixir with nested structures support.

```gleam import gleam/io import crossbar.{int, maxvalue, minvalue, required, to_float, validate}