CSV.jl 1.1.0 release notes

Released September 21, 2026. Requires Julia 1.10 or later.

`CSV.Chunks` streams windows of the source

CSV.Chunks no longer builds a structural index of the whole source. One batch is now one window of the source's data bytes: the window is indexed when its batch is produced and released with it, so a chunked read holds one window's index instead of the file's. The index of a narrow numeric file is several times the size of the file, so this is the difference between a bounded read and one that cannot start on a file larger than memory.

chunkbytes is the target size of that window, in source bytes. It defaults to 64 MiB, or the whole source when it is smaller. A window ends at a row boundary, so one complete row can push a batch past chunkbytes.
ntasks bounds the parallel work inside one window. It is not a batch count and no longer affects the batch size.
The constructor still validates every row it will yield, before the first batch, to settle one schema: every batch has the same column types, missingness, and settled text width, as in 1.0. That pass stops where limit stops, and its final run walks the same windows iteration walks, so it also counts them. length(chunks) is the batch count and costs no extra pass.
Only the structural index is bounded. The source bytes stay in memory for later batches, and each returned batch owns its own bytes.

Batch boundaries therefore differ from 1.0 for the same options. The rows, column types, values, and diagnostics do not.

Fixes

Generic ARM64 package precompilation works on Julia 1.13. The quote scanner retains its accelerated PMULL path behind a runtime CPU check, with a shift/XOR fallback. CI checks generic package images and JIT compilation on ARM64 and x86-64 with Julia 1.10 and current Julia.
Typed CSV.Rows column access avoids per-row allocations.
Floating-point output is quoted when its text conflicts with the delimiter or quote characters, including decimal separators, exponents, and NaN/Inf.
A quote that does not start its field makes a reader prepare the source again under the lenient quote rule. That retry now keeps the whole syntax the first pass resolved, including a sniffed ignorerepeated. 1.0 kept only the delimiter, so an aligned-column source such as "a b\n1 2\n3 x\"y\n" gained an empty column between a and b; it now reads as the two columns an explicit delim=' ', ignorerepeated=true always gave.

CSV.jl 1.0 release notes

CSV.jl 1.0 replaces the parsing and writing internals while keeping the main CSV.jl entry points. It requires Julia 1.10 or later.

Highlights

A quote-aware structural index separates row and field discovery from typed value parsing. The same index drives eager files, row views, lazy access, and batches.
CSV.lazy returns an indexed table that parses cells only when they are accessed. CSV.File(lazyfile) reuses the existing index.
Inferred text uses DataStrings.DataString by default. Short text is stored in the value; longer text lives in column-owned buffers, so eager tables never refer to the source or to a mapped file.
Typed value parsing uses the low-level parsers of Parsers, now even faster in version 3.
Parse recovery produces structured CSV.problems(file) data. on_error selects one summary warning (:warn, the default), silent collection (:collect), or fail-fast CSV.ParseError (:error).
CSV.Chunks uses one stable schema for its complete row window.
A Tables.Scan projection, filter, type request, offset, and limit go into the parser.
The writer has deterministic parallel output, explicit quote styles, Printf-style floating-point formatting, bounded row-block memory, gzip suffix detection, parallel gzip compression (one member per row block), and parallel partition output.
String conversion (stringtype=String, types=String, InlineStrings), CSV.Chunks batch parsing, and gzip output run in parallel. Files with comment rows, skipto, and footerskip use the vector scanner, and so do files with a separate escapechar or distinct openquotechar and closequotechar. CSV.Rows carries its schema in its type, so row.name on a typed column returns a typed value without allocation. Transposed reads parse each row as a typed column. Several sources concatenate text as DataString columns.

Compatibility changes

The most important default changes are:

Julia 1.10 is the minimum runtime;
DataStrings.DataString replaces InlineStrings.jl as the default text type;
pooling is off unless requested;
an unquoted empty field is always missing;
true, True, TRUE, false, False, and FALSE are the default Boolean spellings;
a date-time column is a Timestamp{Nanosecond} (Durations.jl) instead of a Dates.DateTime, ISO date-times accept T or a space, and no fraction digit is truncated; and
parse problems are retained as problem objects, with one summary warning per read instead of one warning per problem.