A small, fast, and correct TOML parser and serializer. smol-toml is fully(ish) spec-compliant with TOML v1.0.0.
Why yet another TOML parser? Well, the ecosystem of TOML parsers in JavaScript is quite underwhelming, most likely due to a lack of interest. With most parsers being outdated, unmaintained, non-compliant, or a combination of these, a new parser didn't feel too out of place.
[insert xkcd 927]
Nowadays, smol-toml is the most downloaded TOML parser on npm thanks to its quality. From frameworks to tooling, it has been battle-tested and is actively used in production systems.
smol-toml passes most of the tests from the toml-test
suite; use the
run-toml-test.bash
script to run the tests. Due to the nature of JavaScript and the limits of the language,
it doesn't pass certain tests, namely:
- Invalid UTF-8 strings are not rejected
- Certain invalid UTF-8 codepoints are not rejected
- Certain invalid dates are not rejected
- For instance,
2023-02-30
would be accepted and parsed as2023-03-02
. While additional checks could be performed to reject these, they've not been added for performance reasons.
- For instance,
Please also note that by default, the behavior regarding integers doesn't preserve type information, nor does it allow deserializing integers larger than 53 bits. See Integers.
You can see a list of all tests smol-toml fails (and the reason why it fails these) in the list of skipped tests in
run-toml-test.bash
. Note that some failures are not specification violations per-se. For instance, the TOML spec
does not require 64-bit integer range support or sub-millisecond time precision, but are included in the toml-test
suite. See toml-lang/toml-test#154 and toml-lang/toml-test#155
[pnpm | yarn | npm] i smol-toml
import { parse, stringify } from 'smol-toml'
const doc = '...'
const parsed = parse(doc)
console.log(parsed)
const toml = stringify(parsed)
console.log(toml)
Alternatively, if you prefer something similar to the JSON global, you can import the library as follows
import TOML from 'smol-toml'
TOML.stringify({ ... })
A few notes on the stringify
function:
- <
8000
code>undefined and
null
values on objects are ignored (does not produce a key/value). undefined
andnull
values in arrays are rejected.- Functions, classes and symbols are rejected.
- By default, floats will be serialized as integers if they don't have a decimal part. See Integers
stringify(parse('a = 1.0')) === 'a = 1'
- JS
Date
will be serialized as Offset Date Time- Use the
TomlDate
object for representing other types.
- Use the
When parsing, both integers and floats are read as plain JavaScript numbers, which essentially are floats. This means loss of type information, and makes it impossible to safely represent integers beyond 53 bits.
When serializing, numbers without a decimal part are serialized as integers. This allows in most cases to preserve
whether a number is an integer or not, but fails to preserve type information for numbers like 1.0
.
To parse integers beyond 53 bits, it's possible to tell the parser to return all integers as BigInt. This will therefore preserve the type information at the cost of using a slightly more expensive container.
import { parse } from 'smol-toml'
const doc = '...'
const parsed = parse(doc, { integersAsBigInt: true })
If you want to keep numbers for integers that can safely be represented as a JavaScript number, you can pass
"asNeeded"
instead.
To get end-to-end type preservation, you can tell the serializer to always treat numbers as floating point numbers. Then, only BigInts will be serialized as integers and numbers without a decimal part will still be serialized as float.
import { stringify } from 'smol-toml'
const obj = { ... }
const toml = stringify(obj, { numbersAsFloat: true })
smol-toml
uses an extended Date
object to represent all types of TOML Dates. In the future, smol-toml
will use
objects from the Temporal proposal, but for now we're stuck with the legacy Date object.
import { TomlDate } from 'smol-toml'
// Offset Date Time
const date = new TomlDate('1979-05-27T07:32:00.000-08:00')
console.log(date.isDateTime(), date.isDate(), date.isTime(), date.isLocal()) // ~> true, false, false, false
console.log(date.toISOString()) // ~> 1979-05-27T07:32:00.000-08:00
// Local Date Time
const date = new TomlDate('1979-05-27T07:32:00.000')
console.log(date.isDateTime(), date.isDate(), date.isTime(), date.isLocal()) // ~> true, false, false, true
console.log(date.toISOString()) // ~> 1979-05-27T07:32:00.000
// Local Date
const date = new TomlDate('1979-05-27')
console.log(date.isDateTime(), date.isDate(), date.isTime(), date.isLocal()) // ~> false, true, false, true
console.log(date.toISOString()) // ~> 1979-05-27
// Local Time
const date = new TomlDate('07:32:00')
console.log(date.isDateTime(), date.isDate(), date.isTime(), date.isLocal()) // ~> false, false, true, true
console.log(date.toISOString()) // ~> 07:32:00.000
You can also wrap a native Date
object and specify using different methods depending on the type of date you wish
to represent:
import { TomlDate } from 'smol-toml'
const jsDate = new Date()
const offsetDateTime = TomlDate.wrapAsOffsetDateTime(jsDate)
const localDateTime = TomlDate.wrapAsLocalDateTime(jsDate)
const localDate = TomlDate.wrapAsLocalDate(jsDate)
const localTime = TomlDate.wrapAsLocalTime(jsDate)
Note
These benchmarks are starting to get a bit old. They will be updated in the (hopefully near) future to better reflect numbers of the latest version of smol-toml on the latest version of Node.js.
A note on these performance numbers: in some highly synthetic tests, other parsers such as fast-toml
greatly
outperform other parsers, mostly due to their lack of compliance with the spec. For example, to parse a string,
fast-toml
skips the entire string while smol-toml
does validate the string, costing a fair share of performance.
The ~5MB test file used for benchmark here is filled with random data which attempts to be close-ish to reality in terms of structure. The idea is to have a file relatively close to a real-world application, with moderately sized strings etc.
The large TOML generator can be found here
Parse | smol-toml | @iarna/toml@3.0.0 | @ltd/j-toml | fast-toml |
---|---|---|---|---|
Spec example | 71,356.51 op/s | 33,629.31 op/s | 16,433.86 op/s | 29,421.60 op/s |
~5MB test file | 3.8091 op/s | DNF | 2.4369 op/s | 2.6078 op/s |
Stringify | smol-toml | @iarna/toml@3.0.0 | @ltd/j-toml |
---|---|---|---|
Spec example | 195,191.99 op/s | 46,583.07 op/s | 5,670.12 op/s |
~5MB test file | 14.6709 op/s | 3.5941 op/s | 0.7856 op/s |
Detailed benchmark data
Tests ran using Vitest v0.31.0 on commit f58cb6152e667e9cea09f31c93d90652e3b82bf5
CPU: Intel Core i7 7700K (4.2GHz)
RUN v0.31.0
✓ bench/parseSpecExample.bench.ts (4) 2462ms
name hz min max mean p75 p99 p995 p999 rme samples
· smol-toml 71,356.51 0.0132 0.2633 0.0140 0.0137 0.0219 0.0266 0.1135 ±0.37% 35679 fastest
· @iarna/toml 33,629.31 0.0272 0.2629 0.0297 0.0287 0.0571 0.0650 0.1593 ±0.45% 16815
· @ltd/j-toml 16,433.86 0.0523 1.3088 0.0608 0.0550 0.1140 0.1525 0.7348 ±1.47% 8217 slowest
· fast-toml 29,421.60 0.0305 0.2995 0.0340 0.0312 0.0618 0.0640 0.1553 ±0.47% 14711
✓ bench/parseLargeMixed.bench.ts (3) 16062ms
name hz min max mean p75 p99 p995 p999 rme samples
· smol-toml 3.8091 239.60 287.30 262.53 274.17 287.30 287.30 287.30 ±3.66% 10 fastest
· @ltd/j-toml 2.4369 376.73 493.49 410.35 442.58 493.49 493.49 493.49 ±7.08% 10 slowest
· fast-toml 2.6078 373.88 412.79 383.47 388.62 412.79 412.79 412.79 ±2.72% 10
✓ bench/stringifySpecExample.bench.ts (3) 1886ms
name hz min max mean p75 p99 p995 p999 rme samples
· smol-toml 195,191.99 0.0047 0.2704 0.0051 0.0050 0.0099 0.0110 0.0152 ±0.41% 97596 fastest
· @iarna/toml 46,583.07 0.0197 0.2808 0.0215 0.0208 0.0448 0.0470 0.1704 ±0.47% 23292
· @ltd/j-toml 5,670.12 0.1613 0.5768 0.1764 0.1726 0.3036 0.3129 0.4324 ±0.56% 2836 slowest
✓ bench/stringifyLargeMixed.bench.ts (3) 24057ms
name hz min max mean p75 p99 p995 p999 rme samples
· smol-toml 14.6709 65.1071 79.2199 68.1623 67.1088 79.2199 79.2199 79.2199 ±5.25% 10 fastest
· @iarna/toml 3.5941 266.48 295.24 278.24 290.10 295.24 295.24 295.24 ±2.83% 10
· @ltd/j-toml 0.7856 1,254.33 1,322.05 1,272.87 1,286.82 1,322.05 1,322.05 1,322.05 ±1.37% 10 slowest
BENCH Summary
smol-toml - bench/parseLargeMixed.bench.ts >
1.46x faster than fast-toml
1.56x faster than @ltd/j-toml
smol-toml - bench/parseSpecExample.bench.ts >
2.12x faster than @iarna/toml
2.43x faster than fast-toml
4.34x faster than @ltd/j-toml
smol-toml - bench/stringifyLargeMixed.bench.ts >
4.00x faster than @iarna/toml
18.33x faster than @ltd/j-toml
smol-toml - bench/stringifySpecExample.bench.ts >
4.19x faster than @iarna/toml
34.42x faster than @ltd/j-toml
Additional notes:
I initially tried to benchmark toml-nodejs
, but the 0.3.0 package is broken.
I initially reported this to the library author, but the author decided to
- a) advise to use a custom loader (via experimental flag) to circumvent the invalid imports.
- Said flag,
--experimental-specifier-resolution
, has been removed in Node v20.
- Said flag,
- b) delete the issue when pointed out links to the Node.js documentation about the flag removal and standard resolution algorithm.
For the reference anyway, toml-nodejs
(with proper imports) is ~8x slower on both parse benchmark with:
- spec example: 7,543.47 op/s
- 5mb mixed: 0.7006 op/s