CSV.jl

CSV.jl reads and writes comma-separated and other delimited text data in Julia. It implements the Tables.jl interface.

Installation

Install the registered release from the Julia REPL:

] add CSV

CSV.jl 1.0 requires Julia 1.10 or later. See the 0.10 to 1.0 migration guide before you update an existing application.

Quick start

using CSV

file = CSV.File("input.csv")
CSV.write("output.csv", file)

Use CSV.read("input.csv", DataFrame) after you load DataFrames.jl. Use CSV.Rows to process one row at a time, CSV.Chunks to process batches, or CSV.lazy to index a source before you choose which cells to parse.

Documentation

• Stable documentation describes the latest registered release.
• Development documentation describes the main branch.
• 1.0 release notes summarize what changed.

Support

Use GitHub Issues for bug reports, feature requests, and questions.

Generative-AI contribution disclosure

The CSV.jl 1.0 internal rewrite contains substantial generative-AI contributions. Claude drove the initial rewrite. Codex performed review, fixes, documentation, and validation. Human maintainers must hand-review these changes and own the final approval.

Alternatives

• DelimitedFiles is a Julia standard library for simple, homogeneous delimited matrices.
• CSVFiles.jl provides FileIO.jl load and save integration.
• DLMReader.jl reads delimited data and integrates with InMemoryDatasets.jl.

CSV.jl uses shared string columns from DataStrings.jl. With DataDecimals.jl loaded, an explicitly requested decimal type such as types=Dict(:amount => DataDecimals.Decimal64{2}) parses exactly; CSV does not infer decimal types, and fractional numbers infer as Float64.