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First release. Everything below is the work that went into it, newest first.
A data frame’s row objects are now charged a nesting level in
both directions. Parsing, they were not charged at all, so a document
one level too deep to parse as a list parsed as a frame; writing, a list
column was charged twice, so a frame whose JSON sat exactly at the
1000-level limit was rejected. zujson_info()$max_depth now
means the same thing whichever options are passed.
Date and POSIXct outside
0000-01-01 to 9999-12-31 now raise
zujson_write_error. Both are doubles in R, so they reach
far past what a timestamp can be written as: 1e300 produced
"2030437271-06-06T-596523:-14:-8Z", and converting it to
int64_t on the way was undefined behaviour rather than
merely wrong.
A string whose Encoding() is "bytes"
now raises zujson_arg_error when parsing and
zujson_write_error when writing, instead of the bare
simpleError that Rf_translateCharUTF8() raises
from inside R. Everything this package can fail with is a
zujson_error again. Pass the bytes as a raw vector, which
is what the raw path is for.
data_frame = TRUE no longer drops a value when one
record carries the same key twice. It raises
zujson_parse_error: a column has one cell per record, and
plain parsing keeps both values, so quietly keeping one made an option
about shape change content.
Building a frame is now linear in the length of the input rather than quadratic in the number of distinct keys. The union of the keys is collected through a hash index instead of a scan of the keys so far, and cells are filled by one pass over the records instead of a lookup per cell that rescanned the record. A 4000 x 2000 frame went from 69s to 1.6s.
The size of a frame is now capped. Because the result is
rectangular, its size is set by the union of the keys and not by how
much JSON arrived: 5000 records sharing no keys is a 5000 x 5000 frame —
96 MB — from 72 kB of body, which is a denial-of-service path for a
package meant to be pointed at untrusted bodies. A limit on the body
cannot stand in for one here, because the growth is quadratic in it.
More than zujson_info()$max_df_cells cells now raises
zujson_limit_error, as the offending column appears rather
than after the allocation.
The default is 50 million cells, roughly 400 MB of doubles, plus the
same order again for the pointer matrix the records are scattered
through — 100k rows by 200 columns is 20 million, so a real tabular
response has room to spare. options(zujson.max_df_cells = )
changes it for the session, and zujson_info()$max_df_cells
reports the limit actually in force. Setting it larger than any frame
that could be built switches the check off, at the price that an
oversized body then raises R’s own allocation error rather than a
zujson_limit_error.
simplify = "none" takes precedence over
data_frame = TRUE, and says so. That mode’s promise is that
every JSON array arrives as an R list; the two options are not
combined.
A number too large for any finite double now parses
as Inf instead of failing the whole read. RFC 8259 puts no
limit on the magnitude of a number, so 1e309 is valid JSON,
and rejecting it let one absurd value anywhere in a response body make
the entire body unparseable. The value is the one
as.numeric() gives the same token, so an integer wider than
int64 reads as the nearest double.
json_validate("1e309") is TRUE for the same
reason. The bare literals Infinity, -Infinity
and NaN are not JSON and are still rejected.
json_parse_file() on a directory now raises
zujson_io_error on every platform. It already did on macOS
and Windows, where fopen() refuses a directory; on Linux
fopen() succeeds, so yyjson failed later with a memory
allocation error and the call raised zujson_parse_error
instead. The path is a directory either way, which is an io problem, not
a malformed document.
simplify gains named modes. "preserve"
(the default, and what TRUE has always meant) keeps a
mixed-kind array as a list; "coerce" promotes it to a
character vector following R’s own rules, so [1, "a"]
becomes c("1", "a") and a JSON null becomes
NA rather than the string "NA".
"none" is FALSE. TRUE and
FALSE keep working and mean exactly what they did, so
nothing written against the old API changes meaning.
data_frame = TRUE turns a non-empty array whose
elements are all objects into a data frame, wherever one appears.
Columns are the union of the keys in first-seen order and a missing key
reads as NA, so ragged records still give a rectangular
result. Columns simplify with the active simplify mode. Off
by default: the documented type mapping is unchanged unless you
ask.
Differential tests against jsonlite, in
tests/testthat/test-interop-jsonlite.R. Two tables over
JSON text: where the two packages agree, and a divergence table pinning
the places they are meant not to — [] is
logical(0), preserve keeps
[1, "a"] a list, there is no matrix detection, and data
frames are opt-in. The second table is the useful one: it fails if a
change quietly makes this package more jsonlite-like than
the documented mapping says. jsonlite is a suggested
package and the tests skip without it.
Conformance against nst/JSONTestSuite, in
tools/jsontestsuite.R. Every file is handed to
json_validate() as raw bytes — the suite is full of
deliberately invalid UTF-8 and embedded NULs, which a text read would
mangle. The package accepts all 95 files it must accept and rejects all
188 it must reject; of the 35 implementation-defined files it accepts
12, the rejections being invalid UTF-8 and lone surrogates. The script
pins an upstream commit so the result cannot drift under it, and needs
the network only once.
Sanitizer and randomised-input CI.
tools/sanitizer-exercise.R drives the C layer using nothing
but base R, with most of its effort on the error paths, where an R error
longjmps past the explicit free; hardening.yaml runs it
under clang-asan, clang-ubsan and gcc-asan, and fuzzes the parser
separately. tests/testthat/test-fuzz.R runs a smaller
version of the same idea on every test run.
The v1 work, previously labelled 0.1.0 — a version number, not a release.
json_parse(), json_parse_raw() and
json_parse_file() turn JSON into R vectors and lists.
Arrays simplify to atomic vectors only when their elements share a type,
so a value’s type survives the round trip; simplify = FALSE
turns simplification off entirely.json_write() and json_write_raw()
serialize R as JSON text or as UTF-8 bytes. A fully named vector or list
becomes an object, anything else becomes an array, and length-1 atomic
vectors unbox unless wrapped in I().json_validate() reports whether input parses, without
building a result.json_parse_ndjson(), json_write_ndjson()
and json_write_ndjson_raw() handle
application/x-ndjson (JSON Lines): one JSON value per line,
parsed and written with the same type mappings as single documents.
Parsing always returns a list of records and reports the line number on
failure; a data frame writes one object per row. There is no
pretty option, because indented JSON contains newlines and
would break the framing.zujson_info() reports the package version, the vendored
yyjson version and the nesting limit.zujson_error: zujson_parse_error,
zujson_write_error, zujson_unsupported_type,
zujson_depth_error, zujson_io_error and
zujson_arg_error.POSIXlt is refused rather than serialized as its 11
internal fields.src/vendor/yyjson; no
system library is needed.These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.