Awesome GitHub RepositoriesCSV Row Indexes

xsv is a suite of high-performance command-line utilities written in Rust for the analysis, manipulation, and statistical processing of large delimited datasets. It provides a toolkit for processing comma-separated value files through a command line interface. The project provides capabilities for statistical analysis, including the computation of column statistics, value frequencies, and descriptive metrics. It also includes data manipulation utilities for joining, slicing, sampling, and reformatting records. The toolkit covers a broad range of data operations including column selection, da

csvkit is a composable Unix-style command-line toolkit for converting, filtering, and analyzing CSV files directly from the terminal. It provides a suite of focused single-purpose commands that can be combined via pipes to build complex data processing workflows, with a modular architecture that includes a column-type inference engine for automatically detecting data types and a streaming-pipeline design for efficient handling of tabular data. The toolkit distinguishes itself through its SQL-engine abstraction layer, which allows users to run SQL queries directly against CSV files without req

Leaf is a game server framework written in Go designed for building multiplayer game backends. It provides a modular backend architecture that organizes server logic into independent modules and includes a concurrent task scheduler for managing ordered, delayed, or recurring functions. The framework features a TCP and WebSocket server that manages simultaneous connections through a single interface. It incorporates a message router capable of decoding Protobuf and JSON data to map incoming network packets to specific internal server modules. The system includes capabilities for multi-protoco

qsv is a high-performance command line toolkit for querying, transforming, and analyzing comma-separated value files. It functions as a data wrangling interface and a tabular data profiler, featuring a query engine capable of executing SQL statements and joins directly on flat files without requiring a database. The project is distinguished by its ability to process massive datasets that exceed available system memory. This is achieved through disk-based external memory processing, including multithreaded merge sorting, on-disk hash tables for deduplication, and lightweight file indexing for