jaq

jaq (pronounced /ʒaːk/, like Jacques[^jacques]) is a clone of the JSON data processing tool jq. jaq aims to support a large subset of jq's syntax and operations.

You can try jaq online on the jaq playground. Instructions for the playground can be found here.

jaq focuses on three goals:

• Correctness: jaq aims to provide a more correct and predictable implementation of jq, while preserving compatibility with jq in most cases.
• Performance: I created jaq originally because I was bothered by the long start-up time of jq 1.6, which amounts to about 50ms on my machine. This can be particularly seen when processing a large number of small files. Although the startup time has been vastly improved in jq 1.7, jaq is still faster than jq on many other benchmarks.
• Simplicity: jaq aims to have a simple and small implementation, in order to reduce the potential for bugs and to facilitate contributions.

I drew inspiration from another Rust program, namely jql. However, unlike jql, jaq aims to closely imitate jq's syntax and semantics. This should allow users proficient in jq to easily use jaq.

[^jacques]: I wanted to create a tool that should be discreet and obliging, like a good waiter. And when I think of a typical name for a (French) waiter, to my mind comes "Jacques". Later, I found out about the old French word jacquet, meaning "squirrel", which makes for a nice ex post inspiration for the name.

Installation

Binaries

You can download binaries for Linux, Mac, and Windows on the releases page.

You may also install jaq using homebrew on macOS or Linux:

$ brew install jaq
$ brew install --HEAD jaq # latest development version

Or using scoop on Windows:

$ scoop install main/jaq

From Source

To compile jaq, you need a Rust toolchain. See https://rustup.rs/ for instructions. (Note that Rust compilers shipped with Linux distributions may be too outdated to compile jaq.)

Any of the following commands install jaq:

$ cargo install --locked jaq
$ cargo install --locked --git https://github.com/01mf02/jaq # latest development version

On my system, both commands place the executable at ~/.cargo/bin/jaq.

If you have cloned this repository, you can also build jaq by executing one of the commands in the cloned repository:

$ cargo build --release # places binary into target/release/jaq
$ cargo install --locked --path jaq # installs binary

jaq should work on any system supported by Rust. If it does not, please file an issue.

Examples

The following examples should give an impression of what jaq can currently do. You should obtain the same outputs by replacing jaq with jq. If not, your filing an issue would be appreciated. :) The syntax is documented in the jq manual.

Access a field:

$ echo '{"a": 1, "b": 2}' | jaq '.a'
1

Add values:

$ echo '{"a": 1, "b": 2}' | jaq 'add'
3

Construct an array from an object in two ways and show that they are equal:

$ echo '{"a": 1, "b": 2}' | jaq '[.a, .b] == [.[]]'
true

Apply a filter to all elements of an array and filter the results:

$ echo '[0, 1, 2, 3]' | jaq 'map(.*2) | [.[] | select(. < 5)]'
[0, 2, 4]

Read (slurp) input values into an array and get the average of its elements:

$ echo '1 2 3 4' | jaq -s 'add / length'
2.5

Repeatedly apply a filter to itself and output the intermediate results:

$ echo '0' | jaq '[recurse(.+1; . < 3)]'
[0, 1, 2]

Lazily fold over inputs and output intermediate results:

$ seq 1000 | jaq -n 'foreach inputs as $x (0; . + $x)'
1 3 6 10 15 [...]

Performance

The following evaluation consists of several benchmarks that allow comparing the performance of jaq, jq, and gojq. The empty benchmark runs n times the filter empty with null input, serving to measure the startup time. The bf-fib benchmark runs a Brainfuck interpreter written in jq, interpreting a Brainfuck script that produces n Fibonacci numbers. The other benchmarks evaluate various filters with n as input; see bench.sh for details.

I generated the benchmark data with bench.sh target/release/jaq jq-1.7.1 gojq-0.12.16 | tee bench.json on a Linux system with an AMD Ryzen 5 5500U.[^binaries] I then processed the results with a "one-liner" (stretching the term and the line a bit):

jq -rs '.[] | "|`\(.name)`|\(.n)|" + ([.time[] | min | (.*1000|round)? // "N/A"] | min as $total_min | map(if . == $total_min then "**\(.)**" else "\(.)" end) | join("|"))' bench.json

(Of course, you can also use jaq here instead of jq.) Finally, I concatenated the table header with the output and piped it through pandoc -t gfm.

[^binaries]: The binaries for jq-1.7.1 and gojq-0.12.16 were retrieved from their GitHub release pages.

Table: Evaluation results in milliseconds ("N/A" if error or more than 10 seconds).

The results show that jaq-2.0 is fastest on 25 benchmarks, whereas jq-1.7.1 is fastest on 1 benchmark and gojq-0.12.16 is fastest on 3 benchmarks. gojq is much faster on tree-flatten because it implements the filter flatten natively instead of by definition.

Features

Here is an overview that summarises:

• features already implemented, and
• features not yet implemented.

Contributions to extend jaq are highly welcome.

Basics

• Identity (.)
• Recursion (..)
• Basic data types (null, boolean, number, string, array, object)
• if-then-else (if .a < .b then .a else .b end)
• Folding (reduce .[] as $x (0; . + $x), foreach .[] as $x (0; . + $x; . + .))
• Error handling (try ... catch ...)
• Breaking (label $x | f | ., break $x)
• String interpolation ("The successor of \(.) is \(.+1).")
• Format strings (@json, @text, @csv, @tsv, @html, @sh, @base64, @base64d)

Paths

• Indexing of arrays/objects (.[0], .a, .["a"])
• Iterating over arrays/objects (.[])
• Optional indexing/iteration (.a?, .[]?)
• Array slices (.[3:7], .[0:-1])
• String slices

Operators

• Composition (|)
• Variable binding (. as $x | $x)
• Pattern binding (. as {a: [$x, {("b", "c"): $y, $z}]} | $x, $y, $z)
• Concatenation (,)
• Plain assignment (=)
• Update assignment (|=)
• Arithmetic update assignment (+=, -=, ...)
• Alternation (//)
• Logic (or, and)
• Equality and comparison (.a == .b, .a < .b)
• Arithmetic (+, -, *, /, %)
• Negation (-)
• Error suppression (?)

Definitions

• Basic definitions (def map(f): [.[] | f];)
• Recursive definitions (def r: r; r)

Core filters

• Empty (empty)
• Errors (error)
• Input (inputs)
• Length (length, utf8bytelength)
• Rounding (floor, round, ceil)
• String <-> JSON (fromjson, tojson)
• String <-> integers (explode, implode)
• String normalisation (ascii_downcase, ascii_upcase)
• String prefix/postfix (startswith, endswith, ltrimstr, rtrimstr)
• String whitespace trimming (trim, ltrim, rtrim)
• String splitting (split("foo"))
• Array filters (reverse, sort, sort_by(-.), group_by, min_by, max_by)
• Stream consumers (first, last, range, fold)
• Stream generators (range, recurse)
• Time (now, fromdateiso8601, todateiso8601)
• More numeric filters (sqrt, sin, log, pow, ...) (list of numeric filters)
• More time filters (strptime, strftime, strflocaltime, mktime, gmtime, and localtime)

Standard filters

These filters are defined via more basic filters. Their definitions are at std.jq.

• Undefined (null)
• Booleans (true, false, not)
• Special numbers (nan, infinite, isnan, isinfinite, isfinite, isnormal)
• Type (type)
• Filtering (select(. >= 0))
• Selection (values, nulls, booleans, numbers, strings, arrays, objects, iterables, scalars)
• Conversion (tostring, tonumber)
• Iterable filters (map(.+1), map_values(.+1), add, join("a"))
• Array filters (transpose, first, last, nth(10), flatten, min, max)
• Object-array conversion (to_entries, from_entries, with_entries)
• Universal/existential (all, any)
• Recursion (walk)
• I/O (input)
• Regular expressions (test, scan, match, capture, splits, sub, gsub)
• Time (fromdate, todate)

Numeric filters

jaq imports many filters from libm and follows their type signature.

Modules

• include "path";
• import "path" as mod;
• import "path" as $data;

Advanced features

jaq currently does not aim to support several features of jq, such as:

• SQL-style operators
• Streaming

Differences between jq and jaq

Numbers

jq uses 64-bit floating-point numbers (floats) for any number. By contrast, jaq interprets numbers such as 0 or -42 as machine-sized integers and numbers such as 0.0 or 3e8 as 64-bit floats. Many operations in jaq, such as array indexing, check whether the passed numbers are indeed integer. The motivation behind this is to avoid rounding errors that may silently lead to wrong results. For example:

$ jq  -n '[0, 1, 2] | .[1.0000000000000001]'
1
$ jaq -n '[0, 1, 2] | .[1.0000000000000001]'
Error: cannot use 1.0 as integer
$ jaq -n '[0, 1, 2] | .[1]'
1

The rules of jaq are:

• The sum, difference, product, and remainder of two integers is integer.
• Any other operation between two numbers yields a float.

Examples:

$ jaq -n '1 + 2'
3
$ jaq -n '10 / 2'
5.0
$ jaq -n '1.0 + 2'
3.0

You can convert an integer to a floating-point number e.g. by adding 0.0, by multiplying with 1.0, or by dividing with 1. You can convert a floating-point number to an integer by round, floor, or ceil:

$ jaq -n '1.2 | [floor, round, ceil]'
[1, 1, 2]

NaN and infinity

In jq, division by 0 yields an error, whereas in jaq, n / 0 yields nan if n == 0, infinite if n > 0, and -infinite if n < 0. jaq's behaviour is closer to the IEEE standard for floating-point arithmetic (IEEE 754).

jaq implements a total ordering on floating-point numbers to allow sorting values. Therefore, it unfortunately has to enforce that nan == nan. (jq gets around this by enforcing that nan < nan is true, yet nan > nan is false, which breaks basic laws about total orders.)

Like jq, jaq prints nan and infinite as null in JSON, because JSON does not support encoding these values as numbers.

Assignments

Like jq, jaq allows for assignments of the form p |= f. However, jaq interprets these assignments differently. Fortunately, in most cases, the result is the same.

In jq, an assignment p |= f first constructs paths to all values that match p. Only then, it applies the filter f to these values.

In jaq, an assignment p |= f applies f immediately to any value matching p. Unlike in jq, assignment does not explicitly construct paths.

jaq's implementation of assignment likely yields higher performance, because it does not construct paths. Furthermore, this allows jaq to use multiple outputs of the right-hand side, whereas jq uses only the first. For example, 0 | (., .) |= (., .+1) yields 0 1 1 2 in jaq, whereas it yields only 0 in jq. However, {a: 1} | .a |= (2, 3) yields {"a": 2} in both jaq and jq, because an object can only associate a single value with any given key, so we cannot use multiple outputs in a meaningful way here.

Because jaq does not construct paths, it does not allow some filters on the left-hand side of assignments, for example first, last, limit: For example, [1, 2, 3] | first(.[]) |= .-1 yields [0, 2, 3] in jq, but is invalid in jaq. Similarly, [1, 2, 3] | limit(2; .[]) |= .-1 yields [0, 1, 3] in jq, but is invalid in jaq. (Inconsequentially, jq also does not allow for last.)

Folding

jq and jaq provide filters reduce xs as $x (init; update), foreach xs as $x (init; update), and foreach xs as $x (init; update; project), where foreach xs as $x (init; update) is equivalent to foreach xs as $x (init; update; .).

In jaq, the output of these filters is defined very simply: Assuming that xs evaluates to x0, x1, ..., xn, reduce xs as $x (init; update) evaluates to

init
| x0 as $x | update
| ...
| xn as $x | update

and foreach xs as $x (init; update; project) evaluates to

init |
( x0 as $x | update | project,
( ...
( xn as $x | update | project,
( empty )...)

The interpretation of reduce/foreach in jaq has the following advantages over jq:

• It deals very naturally with filters that yield multiple outputs. In contrast, jq discriminates outputs of f, because it recurses only on the last of them, although it outputs all of them.

  Example

  foreach (5, 10) as $x (1; .+$x, -.) yields 6, -1, 9, 1 in jq, whereas it yields 6, 16, -6, -1, 9, 1 in jaq. We can see that both jq and jaq yield the values 6 and -1 resulting from the first iteration (where $x is 5), namely 1 | 5 as $x | (.+$x, -.). However, jq performs the second iteration (where $x is 10) only on the last value returned from the first iteration, namely -1, yielding the values 9 and 1 resulting from -1 | 10 as $x | (.+$x, -.). jaq yields these values too, but it also performs the second iteration on all other values returned from the first iteration, namely 6, yielding the values 16 and -6 that result from 6 | 10 as $x | (.+$x, -.).

• It makes the implementation of reduce and foreach special cases of the same code, reducing the potential for bugs.

Miscellaneous

• Slurping: When files are slurped in (via the -s / --slurp option), jq combines the inputs of all files into one single array, whereas jaq yields an array for every file. This is motivated by the -i / --in-place option, which could not work with the behaviour implemented by jq. The behaviour of jq can be approximated in jaq; for example, to achieve the output of jq -s . a b, you may use jaq -s . <(cat a b).
• Cartesian products: In jq, [(1,2) * (3,4)] yields [3, 6, 4, 8], whereas [{a: (1,2), b: (3,4)} | .a * .b] yields [3, 4, 6, 8]. jaq yields [3, 4, 6, 8] in both cases.
• Indexing null: In jq, when given null input, .["a"] and .[0] yield null, but .[] yields an error. jaq yields an error in all cases to prevent accidental indexing of null values. To obtain the same behaviour in jq and jaq, you can use .["a"]? // null or .[0]? // null instead.
• List updating: In jq, [0, 1] | .[3] = 3 yields [0, 1, null, 3]; that is, jq fills up the list with nulls if we update beyond its size. In contrast, jaq fails with an out-of-bounds error in such a case.
• Input reading: When there is no more input value left, in jq, input yields an error, whereas in jaq, it yields no output value.
• Joining: When given an array [x0, x1, ..., xn], in jq, join(x) converts all elements of the input array to strings and intersperses them with x, whereas in jaq, join(x) simply calculates x0 + x + x1 + x + ... + xn. When all elements of the input array and x are strings, jq and jaq yield the same output.

Contributing

Contributions to jaq are welcome. Please make sure that after your change, cargo test runs successfully.

Acknowledgements

This project was funded through the NGI0 Entrust Fund, a fund established by NLnet with financial support from the European Commission's Next Generation Internet programme, under the aegis of DG Communications Networks, Content and Technology under grant agreement N^o 101069594.

jaq has also profited from:

• serde_json to read and colored_json to output JSON,
• chumsky to parse and ariadne to pretty-print parse errors,
• mimalloc to boost the performance of memory allocation, and
• the Rust standard library, in particular its awesome Iterator, which builds the rock-solid base of jaq's filter execution