Command line text processing

sd is a command line text manipulation utility designed for searching and replacing text patterns across multiple files. It functions as a regex-based find and replace tool that allows for in-place file editing directly from the terminal. The project supports both regular expression replacements, including the use of capture groups for complex transformations, and fixed string replacement for literal text substitutions. It specifically handles multi-line text replacement by processing file contents as single blocks to match patterns that span across newline characters. The tool provides capa

This project is a suite of basic command line utilities rewritten in Rust, providing a cross-platform implementation of POSIX shell utilities. It serves as a portable CLI toolset designed to run across different operating systems and architectures. The implementation includes a WebAssembly shell environment, which allows these essential command line tools to be executed directly within a web browser without requiring a local installation. The toolset covers a broad range of system capabilities, including filesystem operations, text processing and stream editing, and system administration too

This tool is a command-line processor designed for querying, updating, and transforming structured data files. It functions as a versatile engine for manipulating YAML, JSON, TOML, and XML documents, allowing users to perform complex operations directly from the terminal. By utilizing a path-based expression language, it enables precise navigation and modification of data structures within configuration files and infrastructure-as-code workflows. What distinguishes this tool is its ability to perform in-place document mutations while preserving original formatting, comments, and metadata. It

Fx is a command-line processing suite designed for the transformation, conversion, exploration, and visualization of structured data. It functions as a terminal-based utility that handles both automated shell pipelines and interactive navigation of complex, nested data hierarchies. The tool distinguishes itself by integrating a JavaScript-based engine that executes user-provided logic to filter, map, or modify data fields within a sandboxed runtime. It maintains a responsive interface by decoupling data processing from the display loop, allowing users to explore large datasets through an inte

Nushell is a cross-platform shell and programming language designed to treat all input and output as structured data rather than raw text streams. By enforcing data types and command signatures, it provides a consistent environment for building robust, pipeline-oriented workflows. The shell allows users to chain commands that pass structured objects between stages, enabling complex data processing and automation tasks that remain predictable across different operating systems. What distinguishes the project is its focus on interactive data exploration and modular extensibility. Users can quer

Gron is a command line utility that transforms nested JSON data into a flat list of path-value assignments. This process converts hierarchical structures into line-based statements, mapping every leaf value to its absolute path to make the data compatible with standard text-processing tools. The tool allows for the bidirectional transformation of data, enabling the reconstruction of original nested JSON objects from flattened path assignments. It can ingest JSON from local files, standard input, or remote URLs, with the ability to route network traffic through proxy servers. The utility supp

This project is a comprehensive suite of essential command-line tools and standardized Unix-like utilities. It provides the fundamental building blocks for system administration, file management, and text processing on Unix-like systems, implementing a wide range of POSIX command-line tools. The collection is distinguished by its broad coverage of low-level system operations. This includes a complete toolkit for file system management, such as creating and modifying files and directories, and a specialized text processing toolkit for filtering, sorting, and transforming data streams. The pro

jq is a command-line JSON processor and data transformer. It provides a functional query language used to slice, filter, map, and transform structured JSON data directly within a terminal. The utility functions as a data transformer that reshapes JSON input into different structures or formats based on declarative logic. This allows for the extraction and analysis of structured data from sources such as API responses and system logs.

lnav is a terminal-based log viewer and analyzer designed for aggregating, filtering, and analyzing multiple log files in a single chronological view. It functions as a console application that can replace the system pager, providing syntax highlighting and document navigation for system or application logs. The project distinguishes itself by mapping unstructured log data to virtual SQLite tables, enabling the use of SQL and PRQL for structured data analysis, aggregations, and relational queries. It further differentiates its capability set through native integration for retrieving and taili

Jo is a command-line utility designed to construct and manipulate JSON objects and arrays directly from shell arguments and standard input. It functions as a data processing tool that transforms raw input into structured formats, enabling the generation of complex payloads for APIs, configuration files, and automated data pipelines. The tool distinguishes itself through its ability to resolve hierarchical data structures using delimiter-based path definitions and its integrated type-inference engine, which automatically casts input values into native boolean, numeric, or null types. Users can

ack is a grep-like search tool optimized for source code.

Data Hacks is a collection of command-line utilities designed for statistical computation, real-time stream processing, and text-based data visualization. The toolkit enables users to perform rapid analysis on large datasets directly within the terminal by processing information through standard input and output streams. The project distinguishes itself through its focus on memory-efficient, stream-oriented operations that allow for the analysis of large-scale data without requiring heavy infrastructure. It utilizes stateless functional transformations and reservoir sampling to handle data st