143 Repos
Checks that a value matches a specific type or instance constructor to ensure data conforms to expected structures.
Distinct from Data Schema Validation: Focuses on runtime type checking against schema definitions, distinct from general testing.
Explore 143 awesome GitHub repositories matching software engineering & architecture · Data Type Validation. Refine with filters or upvote what's useful.
30-seconds-of-code is a comprehensive knowledge base and programming snippet library designed to support software engineering education and professional development. It provides a curated collection of reusable code units and technical guides that help developers master core language mechanics, design patterns, and architectural philosophies. The project distinguishes itself by offering a wide-ranging library of algorithmic solutions and web development patterns that are organized into modular, independently testable units. It emphasizes functional programming paradigms and declarative logic,
Provides standardized type-checking patterns to ensure data integrity and prevent runtime errors.
Lodash is a JavaScript utility library and data manipulation toolkit. It provides a collection of modular functions for transforming, filtering, and validating arrays, objects, strings, and numbers. The project functions as a functional programming toolkit, offering capabilities for function composition, currying, and lazy evaluation. It includes mechanisms for execution control, such as debouncing and throttling, to manage the timing and frequency of function invocations. The library covers a broad surface of data operations, including deep cloning and merging of complex nested structures,
Checks if values match specific types such as arrays, objects, dates, or booleans to ensure data consistency.
graphql-engine is an automated GraphQL API engine that transforms database tables and relationships into a queryable GraphQL schema. It functions as a federation gateway and mapper, instantly generating APIs with built-in filtering, pagination, and mutations from existing databases and remote schemas. The project distinguishes itself through a fine-grained access control layer that enforces row-level and field-level permissions. It further provides a real-time data subscription server that converts standard queries into live streams and a system for triggering event-driven webhooks and notifi
Parses and validates metadata types at runtime using generated conversion classes to ensure data integrity.
Pydantic ist eine Datenvalidierungsbibliothek und ein Parsing-Framework für Python. Es fungiert als typbasierter Schema-Validator, der Standard-Python-Typannotationen verwendet, um sicherzustellen, dass Eingabedaten vordefinierten strukturellen Schemata entsprechen. Das Projekt bietet Funktionen zum Parsen von Rohdaten in typisierte Objekte durch automatische Typkonvertierung und Validierung. Dies umfasst die Serialisierung von Daten und die Validierung von Datenstrukturen zur Durchsetzung der Korrektheit. Das Framework deckt verschiedene Anwendungsbereiche ab, einschließlich der Verifizierung von API-Anfragen und der Verwaltung von Anwendungskonfigurationen. Es ermöglicht die Transformation von Rohformaten wie JSON in strukturierte Python-Objekte.
Ensures input data conforms to defined schemas by checking values against Python type constructors.
Underscore is a JavaScript utility library providing a suite of functional programming and data manipulation helpers. It serves as a framework for transforming data collections, composing functions, managing objects, and performing precise data type validation without modifying core language prototypes. The project includes a functional programming toolkit designed to control function execution timing and behavior through techniques such as debouncing, throttling, and partial application. It also provides a dedicated object manipulation utility for cloning, merging, picking, and omitting prop
Offers a system to validate if values are arrays, functions, dates, or other specific JavaScript types.
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
Performs runtime type checking against schema definitions to ensure data conforms to expected structures.
This project is a comprehensive educational resource and programming guide for the TypeScript language. It serves as a manual for the type system and a reference for the language's core syntax, focusing on writing type-safe code and building scalable applications. The content provides detailed instruction on the TypeScript type system, covering interfaces, generics, and structural typing. It further acts as a compiler reference, analyzing how source code is transformed into an abstract syntax tree through scanning and parsing. The guide also covers software architecture design, detailing pro
Instructs on verifying that objects match required member shapes to ensure compatibility between data structures.
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
Enforces that values match specific primitive or complex types according to a defined schema.
Joi is a JavaScript data validation library used to define schemas that ensure the structure and data types of objects remain consistent. It functions as a schema-based validator and object schema definition tool, preventing invalid information from entering an application by checking data against predefined constraints and rules. The library employs a chainable fluent interface and a constraint-based validation engine to build complex validation pipelines. It utilizes recursive tree traversal to validate nested data structures and a type-coercion pipeline to transform input values into the t
Provides a validation engine that checks input data against a predefined tree of type requirements and logic rules.
NetBox is a network infrastructure source of truth, acting as a centralized database for modeling and documenting the intended state of network devices, IP addresses, and cabling. It functions as a data center infrastructure management tool, an IP address management system, and a network automation platform. The system provides a programmable interface and a validated data model designed to drive external network configuration and provisioning tools. It enables the maintenance of records for network circuits, devices, and logical connections with full change auditing. Capabilities include ne
Enforces data integrity rules and property requirements on infrastructure objects to prevent configuration errors.
This project is the JavaScript reference implementation of the GraphQL specification. It provides a query engine and schema parser designed to parse, validate, and execute queries to retrieve or mutate data based on a defined schema. The implementation includes a framework for mapping codebase structures to a strongly typed system and a tool for converting query strings into abstract syntax trees for programmatic analysis. The library covers the full surface of GraphQL API implementation, including schema definition, language parsing, and query validation. It provides the necessary infrastru
Validates that query semantics and types conform to the predefined schema definitions.
This project is a reference guide and collection of implementation patterns for replacing legacy libraries with native JavaScript. It provides a vanilla JavaScript reference guide, a modern web API cookbook, and a DOM manipulation cheat sheet to help migrate frontend dependencies to standard browser APIs. The project focuses on mapping library functions to native interfaces for DOM manipulation, network requests, and event handling. It includes a utility pattern library for common tasks such as string cleaning, type checking, and element styling. The covered capabilities include DOM element
Offers a set of native language checks to validate if values are arrays, functions, or objects.
type-fest is a library of reusable utility types for performing complex transformations and validations on objects, arrays, strings, and numeric ranges in TypeScript. It provides a collection of type definitions designed to handle advanced structural changes and constraints. The project distinguishes itself by offering specialized logic for string literal processing, such as casing transformations and pattern-based modifications, and type-level arithmetic for calculating numeric ranges and absolute values. It also includes utilities for enforcing deep immutability, ensuring union mutual exclu
Determines if a type contains optional properties to allow conditional logic based on field presence.
Ajv is a high-performance data validation framework that compiles JSON schemas into optimized, standalone JavaScript functions. By transforming declarative schema definitions into executable code, it eliminates runtime interpretation overhead and provides a secure, efficient way to enforce data integrity across both browser and server environments. The library distinguishes itself through its focus on performance and type safety. It employs advanced compilation techniques, including abstract syntax tree optimization and function caching, to ensure rapid validation. Beyond standard checks, it
Checks that a value matches a specific type or instance constructor to ensure data conforms to expected structures.
This project is a structured Rust programming curriculum and systems programming course designed to take learners from beginner to expert levels. It provides a comprehensive set of training materials focused on mastering the core syntax, idioms, and technical foundations of the Rust language. The project features a specialized language transition framework that maps concepts from C++, managed languages, and dynamic typing to Rust idioms. This allows developers from different ecosystems to translate architectural patterns and memory models into idiomatic Rust. The training covers a broad rang
Instructs on using type system constraints to make invalid program states unrepresentable at compile time.
This repository contains the official technical specification for GraphQL. It serves as the formal standard defining the query language, the execution engine, and the schema definition rules required to maintain consistency across different API implementations. The specification establishes a language-agnostic standard for query syntax and semantics, alongside a formal protocol for introspection. It provides the documented algorithms and logic requirements necessary for implementing a consistent server, ensuring that metadata about types and fields can be discovered by automated tools. The p
Checks request structure and semantics against the schema before execution to ensure type safety.
This project is a comprehensive collection of web development reference guides and technical cheat sheets. It provides a curated set of markdown-based documentation designed to help developers quickly locate syntax patterns and API examples for common web technologies and programming languages. The repository serves as a specialized reference library covering several distinct technical domains. It includes extensive guides for CSS, focusing on selectors, Flexbox, Grid, and responsive layout properties, as well as a DevOps command reference for Docker, Kubernetes, AWS, Ansible, and general she
Offers reference patterns for validating data values using assertion styles in tests.
This project is a markdown knowledge base used to maintain a curated collection of concise technical notes and write-ups across various programming languages and tools. It serves as a searchable personal reference library for documenting technical discoveries and software development patterns. The system implements a learning in public workflow, transforming markdown-based content storage into a static site. It utilizes directory-based routing to map folder structures to URL paths and employs schema-driven type generation to ensure data consistency across the knowledge base. The codebase cov
Generates TypeScript definitions from content schemas to ensure data consistency across the knowledge base.
OpenHarness is a framework for building and orchestrating AI agents that utilize tools and plugins to execute complex tasks. It provides an orchestration system for managing language model lifecycles and a multi-agent coordination system for delegating workloads across teams of specialized subagents. The project features an agent gateway that bridges language model agents to external chat platforms and communication channels. It includes a tool integration engine for executing shell, file, and web operations, supported by a memory and skill manager that handles persistent user preferences and
Ensures language model outputs match expected schemas through strict type validation before tool execution.
This project is a static analysis engine and type checker designed for PHP codebases. It evaluates source code structure and type annotations to identify potential bugs, type mismatches, and logic errors without executing the application. By parsing code into an abstract syntax tree and applying a rule-based validation framework, it enforces code quality and safety standards across a project. What distinguishes this tool is its sophisticated type inference engine, which models dynamic language features, magic methods, and conditional types to maintain accuracy even in unconventional code. It
Enforces specific property requirements on objects to ensure they contain the expected data fields and types.