19 रिपॉजिटरी
Tools for parsing, validating, and enforcing data structures against predefined schemas.
Distinguishing note: Focuses on schema-based data validation and parsing logic rather than general database management or storage.
Explore 19 awesome GitHub repositories matching data & databases · Data Validation Libraries. Refine with filters or upvote what's useful.
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
Provides robust schema parsing and validation capabilities with support for both synchronous and asynchronous data processing.
Toon is a data serialization library and toolkit designed to convert complex objects into compact, human-readable formats optimized for large language models. By focusing on token efficiency, the library minimizes the context window footprint of structured data through techniques like key folding and tabular layout optimization. It provides a streaming-capable processor that handles the encoding and decoding of hierarchical data while maintaining structural integrity. The project distinguishes itself through its path-aware transformation pipeline and configurable serialization logic, which al
Enforces schema consistency and detects data corruption by checking serialized documents against structural invariants.
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
Ships a library for parsing and validating data structures against predefined schemas.
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
Defines schemas to validate, cast, and sanitize data objects in JavaScript environments.
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 comprehensive library for defining schemas to validate the structure and data types of JavaScript objects.
Elysia is a high-performance TypeScript web framework designed for building type-safe backend services. It provides a modular, plugin-based architecture that allows developers to compose server logic, middleware, and validation schemas into scalable application instances. By leveraging native web standards, the framework ensures portability across diverse JavaScript runtimes, including Node.js, Deno, and various edge computing environments. The framework distinguishes itself through its focus on end-to-end type safety, automatically synchronizing request and response definitions between the s
Integrates different schema validation libraries within the same application to ensure consistent data integrity.
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
Enforces validation constraints by comparing field values against other properties within the same object using pointers.
Lightweight Charts is a specialized library for rendering interactive time-series financial data visualizations within web applications. It provides a high-performance, responsive component designed to display historical and live market trends through various graphical formats, including candlesticks, histograms, and line series. The library distinguishes itself through a canvas-based rendering engine that decouples visual representation from raw data, enabling efficient updates and real-time monitoring of large datasets. It includes built-in support for accessibility, ensuring that interacti
Validates timestamps and business day objects to ensure data structural integrity and prevent rendering errors.
Great Expectations is a data quality testing framework and observability platform designed to monitor the reliability of data pipelines. It provides a structured environment for defining, documenting, and automating data quality assertions, allowing teams to validate datasets against expected structure and content before they move through downstream processes. The project distinguishes itself through a declarative domain-specific language that stores quality rules as version-controlled configuration files. It utilizes an execution engine abstraction to translate these high-level assertions in
Compares datasets against predefined rules to identify anomalies and schema deviations.
This project is a framework for the efficient serialization and deserialization of data structures. It provides a unified, macro-based interface that automates the conversion of complex internal objects into standardized formats and reconstructs them from raw input streams or buffers. By leveraging compile-time code generation, the library minimizes manual implementation overhead while ensuring consistent logic across diverse data types. The framework distinguishes itself through a format-agnostic data model and a visitor-based parsing architecture that decouples data structures from specific
Improves performance by ignoring incoming data during deserialization without storing it in memory.
ArduinoJson is a C++ library for parsing and manipulating JSON data and MessagePack binary streams on microcontrollers with limited memory and processing power. It provides the core primitives necessary for embedded data serialization and parsing, enabling devices to exchange structured data over serial or network interfaces. The library is distinguished by its focus on microcontroller memory management, employing strategies such as pool-based allocation, string deduplication, and non-owning string views to minimize RAM usage. It further optimizes for constrained environments by allowing cons
Minimizes memory usage by discarding unwanted JSON keys during the deserialization process.
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
Provides a comprehensive library for parsing, validating, and enforcing data structures against predefined schemas in JavaScript and TypeScript.
Ecto is an Elixir database toolkit that maps database rows to Elixir structs and validates data changes through changesets before persistence. It provides a language-integrated query syntax for composing database queries, building them incrementally and securely with compile-time expansion into safe SQL. The toolkit connects to multiple database backends including PostgreSQL, MySQL, MSSQL, SQLite3, ClickHouse, and ETS through a pluggable adapter interface. It supports eager and lazy preloading of associated records to eliminate N+1 query problems, and can store nested data structures as embed
Maps database rows to structs and validates changes through changesets before persistence.
Typia is a compile-time code generator that transforms TypeScript type annotations into runtime validation, serialization, and schema functions without requiring decorators or separate schema files. It generates optimized validation and serialization code during TypeScript compilation, producing dedicated functions for each type that eliminate runtime schema objects for faster execution. The project extends this core capability into several integrated areas. It generates fully typed client SDKs from NestJS controller source code, keeping server and client types synchronized automatically. It
Provides a lenient JSON parser that recovers data from malformed input while reporting syntax errors.
यह प्रोजेक्ट C में इम्प्लीमेंट की गई एक सपोर्ट वेक्टर मशीन लाइब्रेरी है, जो क्लासिफिकेशन और रिग्रेशन कार्यों के लिए एक इंजन प्रदान करती है। यह एक मशीन लर्निंग कर्नल लाइब्रेरी और एक सांख्यिकीय मॉडल वैलिडेटर के रूप में कार्य करती है जिसका उपयोग डेटा पॉइंट्स को वर्गीकृत करने और निरंतर संख्यात्मक वैल्यूज की भविष्यवाणी करने के लिए किया जाता है। यह लाइब्रेरी विशेष डेटासेट्स में डेटा पॉइंट्स के बीच समानता की गणना करने के लिए कस्टम कर्नल फंक्शन्स की परिभाषा की अनुमति देती है। इसमें क्लास मेंबरशिप, डेटा डेंसिटी, और वितरण सीमाओं का अनुमान लगाने जैसे संभाव्यता मॉडलिंग (probabilistic modeling) के लिए टूल्स भी शामिल हैं। व्यापक क्षमताएं मल्टी-क्लास डेटासेट्स के लिए मॉडल ट्रेनिंग को कवर करती हैं, जिसमें वेटेड लॉस फंक्शन्स के माध्यम से असंतुलित डेटा का प्रबंधन शामिल है। यह सिस्टम एक्यूरेसी कंटूर्स और स्ट्रैटिफाइड क्रॉस वैलिडेशन का उपयोग करके हाइपरपैरामीटर चयन और मॉडल ऑप्टिमाइज़ेशन के लिए वर्कफ़्लो प्रदान करता है। इनपुट वैलिडेशन और फीचर मैग्नीट्यूड को सामान्य करने के लिए एट्रिब्यूट स्केलिंग के लिए डेटा प्रीप्रोसेसिंग यूटिलिटीज शामिल हैं।
Checks datasets for consistency and formatting errors before they are processed by the learning algorithm.
Pandera is a data pipeline validation framework and statistical type validation tool. It functions as a library for defining and enforcing schemas on datasets to ensure data quality and consistency, specifically providing validation capabilities for Pandas dataframes. The project includes a schema inference tool that automates setup by analyzing existing dataset samples to generate validation schemas. It also serves as a synthetic data generator, creating artificial datasets based on predefined schemas to verify data-producing functions. The framework covers data engineering quality assuranc
Provides a specialized library for enforcing schemas and validating data structures within Pandas dataframes.
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
Functions as a tool for parsing and validating JavaScript data structures against predefined schemas.
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
Checks individual scalar values against defined constraints to ensure they meet specific format or value requirements.
Dry-validation is a Ruby library designed for defining type-safe schemas and complex validation rules to verify and sanitize input data structures. It provides a formal framework for constructing modular validation logic, ensuring that incoming information meets specific business requirements and data formats before it is processed by an application. The library utilizes a domain-specific language to declare validation rules, which are then parsed into executable objects. It distinguishes itself through a macro-driven system that bundles common validation logic into reusable shortcuts, alongs
Provides a library for defining type-safe schemas and complex validation rules to verify and sanitize input data structures in Ruby.