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Back to ben-strasser/fast-cpp-csv-parser

Open-source alternatives to Fast Cpp Csv Parser

30 open-source projects similar to ben-strasser/fast-cpp-csv-parser, ranked by how many features they have in common. Compare stars, activity and what each one does to find the best Fast Cpp Csv Parser alternative.

  • vincentlaucsb/csv-parserAvatar von vincentlaucsb

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    A modern C++ CSV parser and serializer that doesn't make you choose between ease of use or performance.

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    C++ CSV parser library

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    622Auf GitHub ansehen↗

    Fast CSV parser and writer for Modern C++

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    a header-file-only, JSON parser serializer in C++

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    Header-only TOML config file parser and serializer for C++17.

    C++
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    cJSON is a lightweight library for parsing, creating, and modifying JSON data structures within C applications. It provides a comprehensive set of utilities for transforming raw text into navigable objects, manipulating data fields within collections, and serializing complex structures into formatted or unformatted strings. The library is designed for memory-sensitive and resource-constrained environments, utilizing manual memory management and type-tagged union structures to maintain a minimal footprint. It employs recursive descent parsing and in-place string manipulation to process data ef

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    This library is a header-only C++ framework designed for the serialization, parsing, and manipulation of structured data. It provides a recursive variant data model that represents arbitrary structures as native types, allowing developers to navigate, modify, and patch hierarchical data using standard pointer paths and declarative update patterns. The project distinguishes itself through its template-based architecture, which enables type-safe data structures and custom type mapping at compile time. It offers a unified interface for binary format abstraction, supporting multiple compact repre

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    jc is a tool that transforms plain-text results from command-line utilities, system tools, log formats, and text tables into structured JSON data. It functions as a structured data transformer capable of converting various file formats, including CSV, INI, XML, and YAML, into JSON representations for programmatic use. The project includes a collection of specific parsers for Unix commands and system tools such as df, blkid, and various package managers. It also features specialized converters for web server logs, Common Log Format, and Common Event Format strings. The tool covers broad capab

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    VisiData is a terminal-based interactive data analysis tool and browser designed for exploring, filtering, and sorting large tabular datasets. It functions as a structured data inspector that loads and flattens complex formats like JSON, XML, and PCAP into interactive sheets, as well as a terminal file manager for navigating directories and performing staged filesystem operations. The project distinguishes itself by rendering data visualizations, such as scatter plots and histograms, directly in the terminal using Unicode Braille characters. It provides a Python-based data wrangling environme

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    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

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    Arroyo is a high-performance stream processing platform built in Rust. It executes continuous SQL queries on streaming data with event-time semantics, enabling accurate windowed aggregations, joins, and stateful computations on unbounded event streams. The platform uses native Rust execution for high throughput and low latency, with periodic checkpointing for exactly-once fault tolerance and horizontal scaling across distributed workers. The system integrates deeply with Kafka for reading and writing topics with exactly-once delivery and supports change data capture (CDC) from MySQL and Postg

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