30 open-source projects similar to geal/nom, ranked by how many features they have in common. Compare stars, activity and what each one does to find the best Geal Nom alternative.
nom is a parser combinator framework for Rust used to build complex parsers by combining small, reusable parsing functions. It functions as a zero-copy parsing tool that minimizes memory overhead by returning slices of the original input instead of allocating new memory. The framework is designed for diverse data formats, serving as a binary data parser with configurable endianness and a bitstream processing library capable of extracting values of arbitrary bit length. It also functions as a streaming data parser that can process data arriving in chunks and signal when additional input is req
rkyv is a zero-copy deserialization framework for Rust that provides a binary serialization format for memory-mappable data archives. It allows complex data structures to be mapped to bytes and accessed directly from a buffer without allocating new memory or copying data. The project enables the serialization of polymorphic types and trait objects, maintaining their dynamic behavior and structure within the binary form. It utilizes relative-pointer addressing and byte-aligned structure packing to ensure data remains valid regardless of where it is loaded in memory. The framework covers high-
jsmn is a lightweight JSON parser library written in C. It provides zero-copy tokenization and incremental parsing designed for use in embedded systems and memory-constrained environments. The library identifies structural JSON elements by providing offsets into the original string rather than allocating new memory for data. It uses a single-pass scanning method and requires static-buffer allocation, meaning the caller provides the memory for tokens to avoid dynamic allocation during the parsing process. The parser supports incremental streaming, allowing it to process JSON data in chunks fr
gjson is a Go JSON parser designed for schema-less reading and value extraction. It allows for the retrieval of specific data from JSON documents using dot-notation paths without requiring the definition of predefined Go structs. The library provides tools for path-based querying, including the use of wildcards and index-based queries to locate data within objects and arrays. It also functions as a JSON lines processor, treating multi-line documents as arrays to iterate and query individual entries. Additional capabilities include converting JSON values into native Go types such as strings,
Fury is a multi-language binary serialization framework designed for encoding domain objects and complex graphs to facilitate cross-language data exchange. It includes an interface definition language compiler that translates schema definitions into idiomatic native types and serialization boilerplate across multiple languages. The project distinguishes itself through a zero-copy binary reader that allows specific fields to be accessed without deserializing the entire object, as well as an object graph serializer that preserves circular references and referential integrity. It also features a
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
Fory is a cross-language serialization framework and binary data serializer designed to convert complex object graphs into a compact binary format for high-performance data exchange. It includes an IDL-based schema compiler to transform interface definition language files into type-safe native data models and a schema evolution manager to maintain forward and backward compatibility. The project features a zero-copy data access layer that allows reading specific fields from binary rows without deserializing the entire object. It supports dual-mode serialization, enabling a toggle between a por
This project is an LLM-powered web crawler and data extractor that uses large language models to navigate websites and parse content into structured JSON or Markdown formats. It functions as an automated browser orchestrator and domain discovery engine, interpreting plain English instructions to identify relevant pages and extract specific information. The system distinguishes itself through agentic browser automation, allowing it to perform human-like interactions such as clicking buttons and scrolling based on natural language commands. It employs goal-oriented crawling to analyze website s
language-ext is a functional programming framework for C# that provides a suite of immutable data structures and monadic types. It enables the implementation of pure functional programming patterns, utilizing containers to manage side effects, optional values, and error handling. The library is distinguished by its advanced concurrency and state management tools, including a software transactional memory system and lock-free atomic references. It also provides specialized utilities for distributed systems, such as vector clocks for causality tracking and deterministic data conflict resolution
Kreuzberg is a document extraction engine that converts PDFs, Office files, images, and over 90 other formats into clean, structured text and metadata. It is built around a compiled Rust core that can be used as a native library, a command-line tool, a REST API server, or a WebAssembly module for browser-based processing. The system is designed to run entirely on self-hosted infrastructure, with no data leaving the user's environment. What distinguishes Kreuzberg is its breadth of integration surfaces and its pipeline architecture. It exposes extraction capabilities through native bindings fo
Ohm is a compiler construction toolkit and parser combinator library used to build parsers, interpreters, and compilers. It provides a formal grammar language for specifying the structural rules of data formats to ensure precise parsing of input strings. The project functions as a parsing debugging tool and program execution visualizer. It generates text traces and graphical visualizations to show the step-by-step logic used during parsing and renders runtime state changes and method call hierarchies. The toolkit covers custom parser development and the construction of compilers and interpre
cuDF is a GPU-accelerated dataframe library and data processing engine designed for manipulating and analyzing large tabular datasets. It provides a high-level API for executing filtering, joining, and aggregating operations directly on GPU hardware. The project integrates the Apache Arrow memory format to enable zero-copy data transfers and includes a just-in-time compiler for executing custom user-defined functions on the GPU. The library features specialized acceleration for existing workflows by redirecting standard Pandas dataframe calls and Polars query plans to a GPU backend. It also p
syn is a Rust syntax tree parser and token stream converter. It serves as a toolkit for procedural macro development, providing a framework to parse Rust source code into structured syntax trees for analysis and transformation. The project enables the manipulation of Rust abstract syntax trees through specialized visitor and folder patterns for traversing and mutating nodes. It provides a bidirectional mapping that allows developers to convert token streams into structured trees and print those trees back into tokens for code generation. The library covers a broad range of syntax analysis ca
Unstructured is an enterprise-grade data orchestration engine designed to transform raw, unstructured files into structured, machine-readable formats. It functions as a comprehensive platform for document ingestion, partitioning, and enrichment, specifically engineered to prepare complex data for retrieval-augmented generation and agentic AI workflows. The platform distinguishes itself through its sophisticated document processing strategies, which combine rule-based extraction with vision-language models to handle diverse file layouts, tables, and images. It provides a modular architecture t
This project is a comprehensive Python toolkit designed for natural language processing, research, and education. It functions as a linguistic data processor that provides a standardized framework for managing, cleaning, and analyzing large collections of annotated text corpora and lexical resources. The library distinguishes itself through its integration of both symbolic and statistical methods, allowing users to perform complex tasks ranging from rule-based grammar parsing to machine learning-driven classification. It offers a modular pipeline for text processing, enabling the transformati
Nearley is a JavaScript parser toolkit used to define context-free grammars and generate corresponding parsers. It features an EBNF grammar compiler that transforms language definitions written in extended Backus-Naur Form into executable JavaScript code, utilizing an Earley parser implementation to process any context-free grammar. The toolkit distinguishes itself by its ability to handle left-recursion and ambiguity without failing, allowing it to identify and return multiple valid derivations for a single input string. It also includes a grammar fuzzing generator to produce random strings
Ohm is a formal grammar parser generator and domain-specific language framework. It provides a system for defining custom languages to parse, validate, and extract data from input text, transforming raw strings into hierarchical abstract syntax trees based on specified formal rules. The project utilizes an Earley parsing algorithm, which allows it to support all context-free grammars, including those with left recursion and ambiguity, without requiring predefined operator precedence. It also includes a dedicated debugging toolkit for tracing and visualizing the step-by-step state transitions
Nokogiri is an XML and HTML parsing library that builds navigable document trees from strings, files, or URLs using native C parsers for speed and standards compliance. It provides a CSS selector engine that translates CSS3 selectors into XPath expressions for querying nodes, an XPath query interface with namespace support, a document manipulation toolkit for modifying parsed documents, XSD schema validation, and XSLT transformation capabilities. The library wraps libxml2 and libxslt C libraries with Ruby bindings for high-performance parsing, and integrates Google's Gumbo parser for standard
LanceDB is a vector database and columnar data store designed to function as a versioned dataset manager and vector search engine. It serves as a high-performance backend for indexing and retrieving high-dimensional embeddings, providing the foundation for machine learning data pipelines. The system distinguishes itself through a combination of cloud-native object storage and immutable version tracking, allowing for data time-travel and reproducible AI experiments. It integrates hybrid search capabilities, merging dense vector similarity with BM25 full-text search and SQL-like scalar filters
Langroid is a multi-agent orchestration framework and tool integration suite designed for building complex AI applications. It serves as a multi-modal integration layer that connects diverse local and remote language models with an agentic retrieval-augmented generation system. The project distinguishes itself through a collaborative message-exchange paradigm, allowing specialized agents to delegate tasks hierarchically and coordinate via structured communication. It features an advanced state management system for conversational AI, including the ability to rewind and prune conversation hist
Data Formulator is an automated data analysis and visualization platform that uses large language models to interpret natural language instructions for data preparation and reporting. It functions as an interactive workbench where users can clean, filter, and aggregate datasets while simultaneously generating visual representations. By combining conversational interfaces with automated transformation tools, the system enables users to explore data patterns and refine schemas without manual coding. The platform distinguishes itself through an agentic architecture that translates natural langua
Crawlee is a web scraping framework designed for building scalable, reliable, and distributed data extraction pipelines. It provides a unified interface for managing headless browser automation and lightweight HTTP requests, allowing developers to handle complex web navigation, dynamic content rendering, and large-scale data collection within a single, modular architecture. The project distinguishes itself through its resource-aware concurrency controller, which dynamically scales task execution based on real-time CPU and memory usage to prevent host machine exhaustion. It also features a rob
This project is a comprehensive suite of AI tools and frameworks, featuring an LLM multi-agent orchestrator, an autonomous agent runtime, and a stateful application framework. It provides the infrastructure to build and manage specialized AI agents capable of coordinating complex tasks through graph-based workflows and shared state. The system is distinguished by its implementation of the Model Context Protocol, allowing for standardized resource discovery and communication between AI clients and servers. It further includes an AI-powered documentation generator designed to analyze source cod
Chumsky is a parser combinator library used to build high-performance parsers by composing small parsing functions into complex grammars. It provides multiple parsing engines, including recursive descent and precedence-climbing implementations for resolving the order of operations in mathematical and logical expressions. The library is distinguished by its zero-copy text parsing, which minimizes memory allocations to increase throughput, and its ability to run without a standard library for use in embedded or resource-constrained environments. It also features an error-recovering parser that
Fluvio is a distributed event streaming platform and cloud-native streaming engine designed for collecting, persisting, and replicating real-time data streams across a distributed cluster. It functions as a real-time data pipeline for building stateful workflows that ingest, enrich, and export data between external sources and sinks. The platform is distinguished by its use of WebAssembly to execute compiled modules for in-line data transformations and filtering. This allows for the execution of custom business logic to reshape information in motion without requiring a restart of the cluster.
Apache Storm is a distributed stream processing framework and real-time data processing engine. It functions as a fault-tolerant distributed computing system designed to analyze data in motion across a cluster of machines for continuous stream computation. The system enables the creation of fault-tolerant data pipelines and scalable event processing by distributing workloads across a network of computing nodes. This architecture ensures low latency and high throughput for live data while allowing the system to recover automatically from individual node failures. The framework provides capabi
RisingWave is a cloud-native streaming database and real-time analytics engine that uses standard SQL to process continuous data streams. It functions as a streaming data lakehouse, combining the capabilities of a streaming SQL database with a platform that integrates streaming ingestion with open table formats. The system is distinguished by its use of the PostgreSQL wire protocol, allowing it to integrate with existing SQL tools and drivers. It employs a decoupled compute and storage architecture, persisting streaming state and materialized views in cloud object storage to enable independen
This project is a comprehensive functional programming curriculum and learning resource for Haskell. It provides sequenced educational paths and technical reference guides designed to take developers from beginner to advanced levels of proficiency. The project distinguishes itself through a deep focus on theoretical and technical foundations, offering detailed studies on type theory, category theory, and runtime internals. It includes a dedicated performance handbook for optimizing execution speed and memory management, as well as an ecosystem guide for managing development tools and editor c
Storm is a distributed stream processing framework designed to execute unbounded computations across a cluster to process real-time data streams. It functions as a data pipeline orchestrator that allows users to define and deploy declarative data flow graphs connecting streaming sources to processing components. The system operates as a multi-tenant distributed compute engine that isolates workloads and limits resource usage across shared clusters using dedicated pools and access control. It is also a secure distributed processing engine that employs encrypted node communication and SSL-secur
CapnProto is a zero-copy serialization framework and remote procedure call system. It serves as a C++ communication library providing a schema-based data interchange format that eliminates the need to encode or decode data before reading it from memory. The system enables high-performance data serialization and low-latency network communication. It supports cross-language data exchange by using a defined schema to ensure consistent binary representation across different platforms. The framework provides tools for implementing remote procedure calls, allowing functions to be invoked on a remo