vincentlaucsb/csv-parser

Health v2 · maintenance only

Adoption not part of the score

1121 stars · 204 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A modern C++17 CSV parser and serializer that is RFC 4180 compliant and balances ease of use with high performance. It supports streaming arbitrarily large files, memory-mapped I/O, type conversions, JSON output, and an in-memory DataFrame with parallel ETL capabilities.

Use cases

• parse large csv files in c++ without loading everything into memory
• read csv files with quoted fields and embedded newlines
• convert csv rows to
• write csv files from c++ containers
• load csv data into a dataframe for random access and editing
• parse tab-separated or custom-delimited files
• run parallel extract-transform-load over csv chunks

When to choose

• you need a fast, standards-compliant CSV reader/writer in C++
• you must process files too large to fit in memory
• you want type inference and conversions (numbers, booleans, timestamps) out of the box
• you need easy integration via CMake, Bazel, or a single header

When to avoid

• you are working in Python and only need basic CSV reading (stdlib csv may suffice)
• you need a full spreadsheet or Excel file (xlsx) parser
• your project is limited to pre-C++11 compilers

Facets

library · maturity active

parser serialization csv etl files developer-tools data-science cpp cross-platform wasm python csv-parser rfc4180 dataframe single-header memory-mapped-io multithreaded cmake header-only-option data-engineering

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