10 repository-uri
Systems optimized for processing massive volumes of text with predictable memory and time complexity.
Distinct from Text Processing: Candidates focus on audio, collections, or AI inference; this is general-purpose high-performance text processing via regex.
Explore 10 awesome GitHub repositories matching data & databases · High-Performance Text Processing. Refine with filters or upvote what's useful.
cppformat is a type-safe C++ formatting library that serves as a high-performance alternative to standard C++ input and output streams for converting data into formatted strings. It integrates a compile-time format validator to ensure format specifiers match argument types, preventing runtime crashes. The library includes a positional argument engine that enables the reordering of text arguments for internationalization and localization. It also features a Unicode text formatter to ensure consistent and portable character representation across different operating systems. The project provide
Provides a high-performance alternative to standard C++ I/O streams for converting data into strings.
Xi Editor is a high-performance text editor core written in Rust. It employs a decoupled architecture that separates core logic from the presentation layer using a JSON-based client-server protocol. The project features a language-agnostic plugin system that communicates with external extensions via JSON messages over pipes. It manages text buffers using a persistent rope data structure to enable efficient editing of very large files. The system supports asynchronous editor workflows by running expensive operations in background threads using data snapshots. This prevents background processi
Ensures high-performance editing of very large files with low latency using a rope data structure.
re2 is a C++ regular expression library designed for high-performance text processing. It is a non-backtracking regex engine that provides linear-time pattern matching, ensuring that execution time remains proportional to the size of the input string regardless of the pattern used. The library supports UTF-8 and Latin-1 text encodings for searching and extracting substrings. It includes capabilities for multi-pattern optimization, allowing multiple regular expressions to be combined into a single representation to scan text for several patterns in one pass. The project covers core regex oper
Ensures predictable execution time and memory usage when processing large volumes of text with regular expressions.
Bloop is an AI code analysis tool and semantic search engine designed for understanding and querying large-scale codebases. It utilizes a high-performance indexing system written in Rust to enable fast symbol and text retrieval across multiple programming languages. The project differentiates itself by using on-device embeddings for semantic code search, allowing users to locate logic based on meaning and intent rather than exact keywords. It combines a language model with a retrieval-augmented generation approach to provide a natural language interface for conversational querying and the gen
Employs high-performance regular expression processing to rapidly filter and isolate specific text segments across large volumes of source code.
Oni2 is a high-performance, extensible text editor and project-based file manager. It functions as a modal code editor, utilizing a keyboard grammar of verbs and motions to navigate and modify source code without a mouse. It also serves as an LSP client, integrating Language Server Protocol servers to provide code completion, symbol navigation, and refactoring. The editor distinguishes itself by acting as a VSCode extension host, allowing it to load and execute language servers and debuggers from the VSCode ecosystem. It provides a programmable environment where custom functionality is implem
Utilizes a high-performance environment optimized for the speed and efficiency of writing and modifying text files.
This project is a pandas data analysis cookbook and Python data science guide. It provides a collection of programmatic recipes and examples for cleaning, manipulating, and analyzing structured data. The project focuses on providing a containerized analysis environment to ensure a consistent workspace and reproducible dependencies when executing data processing scripts. It covers a broad range of data science capabilities, including data ingestion from external sources, raw data cleaning, and exploratory data analysis. These recipes demonstrate how to perform structured data analysis through
Performs high-performance string operations to transform text data for analysis.
Lark este un toolkit de parsare Python utilizat pentru a defini gramatici și a converti textul brut în arbori de parsare adnotați. Servește drept generator de arbori de sintaxă abstractă și un limbaj de definire a gramaticii pentru specificarea regulilor limbajului prin terminale și expresii regulate. Biblioteca oferă două implementări principale de parsare: o bibliotecă de parsare Earley capabilă să gestioneze toate limbajele context-free, inclusiv cele cu ambiguitate și recursivitate la stânga, și o bibliotecă de parsare LALR de înaltă performanță concepută pentru limbaje deterministe cu un consum redus de memorie. Dincolo de parsarea de bază, toolkit-ul include capabilități pentru compoziția gramaticală modulară, transformarea arborilor bazată pe reguli și urmărirea coordonatelor pentru pozițiile sursă. De asemenea, suportă serializarea gramaticilor LALR în module de parsare independente.
Uses LALR algorithms to process large volumes of text with high efficiency and low memory usage.
This is a collection of classical algorithms and data structures implemented as a header-only C++ library. It provides a suite of tools for general algorithm implementation, including data structure management, graph theory analysis, and string processing. The library is distinguished by its specialized toolkits for cryptographic hashing and encoding, featuring implementations of MD5, SHA-1, and Base64. It also includes advanced capabilities for high-performance string processing via suffix trees and arrays, as well as computational number theory for primality testing and arbitrary-precision
Uses suffix trees and arrays for high-performance pattern matching and text analysis.
Chumsky este o bibliotecă de parser combinator utilizată pentru a construi parsere de înaltă performanță prin compunerea unor funcții mici de parsare în gramatici complexe. Oferă mai multe motoare de parsare, inclusiv implementări de tip „recursive descent” și „precedence-climbing” pentru rezolvarea ordinii operațiilor în expresii matematice și logice. Biblioteca se distinge prin parsarea textului de tip „zero-copy”, care minimizează alocările de memorie pentru a crește throughput-ul, și prin capacitatea sa de a rula fără o bibliotecă standard pentru utilizare în medii încorporate sau cu resurse limitate. De asemenea, dispune de un parser cu recuperare la erori care identifică input-ul malformat și reia procesarea pentru a raporta mai multe erori de sintaxă într-o singură trecere. Framework-ul acoperă o gamă largă de capabilități, inclusiv gestionarea stării sensibile la context, suport pentru gramatici recursive și integrarea modelelor de expresii regulate. Include instrumente pentru analiza structurii parserului, inspecția nodurilor și caching-ul rezultatelor pentru a susține backtracking-ul și recursivitatea la stânga. Biblioteca susține dezvoltarea de limbaje personalizate, parsarea formatelor de date și instrumente pentru limbaje de programare.
Enables high-performance text processing optimized for low memory and high throughput in resource-constrained environments.
This is a Rust regular expression library that provides a finite automata engine for searching and matching text patterns. It functions as a Unicode-compliant text scanner designed to guarantee linear time execution on all inputs to prevent catastrophic backtracking. The engine supports both single and multi-pattern search capabilities, allowing it to scan a piece of text for multiple regular expressions simultaneously. It operates on both strings and raw byte slices to identify matching text segments. The library covers text parsing, string validation, and pattern searching. It includes cap
Provides high-performance text extraction with guaranteed linear time complexity to prevent performance crashes.