- Fast. As usual, up to 15x faster than the standard encoding/json. See benchmarks.
- Parses arbitrary JSON without schema, reflection, struct magic and code generation contrary to easyjson.
- Provides simple API.
- Outperforms jsonparser and gjson
when accessing multiple unrelated fields, since
fastjson
parses the input JSON only once. - Validates the parsed JSON unlike jsonparser and gjson.
- May quickly extract a part of the original JSON with
Value.Get(...).MarshalTo
and modify it with Del and Set functions. - May parse array containing values with distinct types (aka non-homogenous types).
For instance,
fastjson
easily parses the following JSON array[123, "foo", [456], {"k": "v"}, null]
. fastjson
preserves the original order of object items when calling Object.Visit.
- Requies extra care to work with - references to certain objects recursively returned by Parser must be released before the next call to Parse. Otherwise the program may work improperly. The same applies to objects returned by Arena. Adhere recommendations from docs.
- Cannot parse JSON from
io.Reader
. There is Scanner for parsing stream of JSON values from a string.
One-liner accessing a single field:
s := []byte(`{"foo": [123, "bar"]}`)
fmt.Printf("foo.0=%d\n", fastjson.GetInt(s, "foo", "0"))
// Output:
// foo.0=123
Accessing multiple fields with error handling:
var p fastjson.Parser
v, err := p.Parse(`{
"str": "bar",
"int": 123,
"float": 1.23,
"bool": true,
"arr": [1, "foo", {}]
}`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("foo=%s\n", v.GetStringBytes("str"))
fmt.Printf("int=%d\n", v.GetInt("int"))
fmt.Printf("float=%f\n", v.GetFloat64("float"))
fmt.Printf("bool=%v\n", v.GetBool("bool"))
fmt.Printf("arr.1=%s\n", v.GetStringBytes("arr", "1"))
// Output:
// foo=bar
// int=123
// float=1.230000
// bool=true
// arr.1=foo
See also examples.
fastjson
shouldn't crash or panic when parsing input strings specially crafted by an attacker. It must return error on invalid input JSON.fastjson
requires up tosizeof(Value) * len(inputJSON)
bytes of memory for parsinginputJSON
string. Limit the maximum size of theinputJSON
before parsing it in order to limit the maximum memory usage.
- Re-use Parser and Scanner for parsing many JSONs. This reduces memory allocations overhead. ParserPool may be useful in this case.
- Prefer calling
Value.Get*
on the value returned from Parser instead of callingGet*
one-liners when multiple fields must be obtained from JSON, since eachGet*
one-liner re-parses the input JSON again. - Prefer calling once Value.Get
for common prefix paths and then calling
Value.Get*
on the returned value for distinct suffix paths. - Prefer iterating over array returned from Value.GetArray
with a range loop instead of calling
Value.Get*
for each array item.
Install go-fuzz & optionally the go-fuzz-corpus.
go get -u github.com/dvyukov/go-fuzz/go-fuzz github.com/dvyukov/go-fuzz/go-fuzz-build
Build using go-fuzz-build
and run go-fuzz
with an optional corpus.
mkdir -p workdir/corpus
cp $GOPATH/src/github.com/dvyukov/go-fuzz-corpus/json/corpus/* workdir/corpus
go-fuzz-build github.com/wundergraph/astjson
go-fuzz -bin=astjson-fuzz.zip -workdir=workdir
Go 1.12 has been used for benchmarking.
Legend:
-
small
- parse small.json (190 bytes). -
medium
- parse medium.json (2.3KB). -
large
- parse large.json (28KB). -
canada
- parse canada.json (2.2MB). -
citm
- parse citm_catalog.json (1.7MB). -
twitter
- parse twitter.json (617KB). -
stdjson-map
- parse into amap[string]interface{}
usingencoding/json
. -
stdjson-struct
- parse into a struct containing a subset of fields of the parsed JSON, usingencoding/json
. -
stdjson-empty-struct
- parse into an empty struct usingencoding/json
. This is the fastest possible solution forencoding/json
, may be used for json validation. See also benchmark results for json validation. -
fastjson
- parse usingfastjson
without fields access. -
fastjson-get
- parse usingfastjson
with fields access similar tostdjson-struct
.
$ GOMAXPROCS=1 go test github.com/wundergraph/astjson -bench='Parse$'
goos: linux
goarch: amd64
pkg: github.com/wundergraph/astjson
BenchmarkParse/small/stdjson-map 200000 7305 ns/op 26.01 MB/s 960 B/op 51 allocs/op
BenchmarkParse/small/stdjson-struct 500000 3431 ns/op 55.37 MB/s 224 B/op 4 allocs/op
BenchmarkParse/small/stdjson-empty-struct 500000 2273 ns/op 83.58 MB/s 168 B/op 2 allocs/op
BenchmarkParse/small/fastjson 5000000 347 ns/op 547.53 MB/s 0 B/op 0 allocs/op
BenchmarkParse/small/fastjson-get 2000000 620 ns/op 306.39 MB/s 0 B/op 0 allocs/op
BenchmarkParse/medium/stdjson-map 30000 40672 ns/op 57.26 MB/s 10196 B/op 208 allocs/op
BenchmarkParse/medium/stdjson-struct 30000 47792 ns/op 48.73 MB/s 9174 B/op 258 allocs/op
BenchmarkParse/medium/stdjson-empty-struct 100000 22096 ns/op 105.40 MB/s 280 B/op 5 allocs/op
BenchmarkParse/medium/fastjson 500000 3025 ns/op 769.90 MB/s 0 B/op 0 allocs/op
BenchmarkParse/medium/fastjson-get 500000 3211 ns/op 725.20 MB/s 0 B/op 0 allocs/op
BenchmarkParse/large/stdjson-map 2000 614079 ns/op 45.79 MB/s 210734 B/op 2785 allocs/op
BenchmarkParse/large/stdjson-struct 5000 298554 ns/op 94.18 MB/s 15616 B/op 353 allocs/op
BenchmarkParse/large/stdjson-empty-struct 5000 268577 ns/op 104.69 MB/s 280 B/op 5 allocs/op
BenchmarkParse/large/fastjson 50000 35210 ns/op 798.56 MB/s 5 B/op 0 allocs/op
BenchmarkParse/large/fastjson-get 50000 35171 ns/op 799.46 MB/s 5 B/op 0 allocs/op
BenchmarkParse/canada/stdjson-map 20 68147307 ns/op 33.03 MB/s 12260502 B/op 392539 allocs/op
BenchmarkParse/canada/stdjson-struct 20 68044518 ns/op 33.08 MB/s 12260123 B/op 392534 allocs/op
BenchmarkParse/canada/stdjson-empty-struct 100 17709250 ns/op 127.11 MB/s 280 B/op 5 allocs/op
BenchmarkParse/canada/fastjson 300 4182404 ns/op 538.22 MB/s 254902 B/op 381 allocs/op
BenchmarkParse/canada/fastjson-get 300 4274744 ns/op 526.60 MB/s 254902 B/op 381 allocs/op
BenchmarkParse/citm/stdjson-map 50 27772612 ns/op 62.19 MB/s 5214163 B/op 95402 allocs/op
BenchmarkParse/citm/stdjson-struct 100 14936191 ns/op 115.64 MB/s 1989 B/op 75 allocs/op
BenchmarkParse/citm/stdjson-empty-struct 100 14946034 ns/op 115.56 MB/s 280 B/op 5 allocs/op
BenchmarkParse/citm/fastjson 1000 1879714 ns/op 918.87 MB/s 17628 B/op 30 allocs/op
BenchmarkParse/citm/fastjson-get 1000 1881598 ns/op 917.94 MB/s 17628 B/op 30 allocs/op
BenchmarkParse/twitter/stdjson-map 100 11289146 ns/op 55.94 MB/s 2187878 B/op 31266 allocs/op
BenchmarkParse/twitter/stdjson-struct 300 5779442 ns/op 109.27 MB/s 408 B/op 6 allocs/op
BenchmarkParse/twitter/stdjson-empty-struct 300 5738504 ns/op 110.05 MB/s 408 B/op 6 allocs/op
BenchmarkParse/twitter/fastjson 2000 774042 ns/op 815.86 MB/s 2541 B/op 2 allocs/op
BenchmarkParse/twitter/fastjson-get 2000 777833 ns/op 811.89 MB/s 2541 B/op 2 allocs/op
Benchmark results for json validation:
$ GOMAXPROCS=1 go test github.com/wundergraph/astjson -bench='Validate$'
goos: linux
goarch: amd64
pkg: github.com/wundergraph/astjson
BenchmarkValidate/small/stdjson 2000000 955 ns/op 198.83 MB/s 72 B/op 2 allocs/op
BenchmarkValidate/small/fastjson 5000000 384 ns/op 493.60 MB/s 0 B/op 0 allocs/op
BenchmarkValidate/medium/stdjson 200000 10799 ns/op 215.66 MB/s 184 B/op 5 allocs/op
BenchmarkValidate/medium/fastjson 300000 3809 ns/op 611.30 MB/s 0 B/op 0 allocs/op
BenchmarkValidate/large/stdjson 10000 133064 ns/op 211.31 MB/s 184 B/op 5 allocs/op
BenchmarkValidate/large/fastjson 30000 45268 ns/op 621.14 MB/s 0 B/op 0 allocs/op
BenchmarkValidate/canada/stdjson 200 8470904 ns/op 265.74 MB/s 184 B/op 5 allocs/op
BenchmarkValidate/canada/fastjson 500 2973377 ns/op 757.07 MB/s 0 B/op 0 allocs/op
BenchmarkValidate/citm/stdjson 200 7273172 ns/op 237.48 MB/s 184 B/op 5 allocs/op
BenchmarkValidate/citm/fastjson 1000 1684430 ns/op 1025.39 MB/s 0 B/op 0 allocs/op
BenchmarkValidate/twitter/stdjson 500 2849439 ns/op 221.63 MB/s 312 B/op 6 allocs/op
BenchmarkValidate/twitter/fastjson 2000 1036796 ns/op 609.10 MB/s 0 B/op 0 allocs/op
-
Q: There are a ton of other high-perf packages for JSON parsing in Go. Why creating yet another package? A: Because other packages require either rigid JSON schema via struct magic and code generation or perform poorly when multiple unrelated fields must be obtained from the parsed JSON. Additionally,
fastjson
provides nicer API. -
Q: What is the main purpose for
fastjson
? A: High-perf JSON parsing for RTB and other JSON-RPC services. -
Q: Why fastjson doesn't provide fast marshaling (serialization)? A: Actually it provides some sort of marshaling - see Value.MarshalTo. But I'd recommend using quicktemplate for high-performance JSON marshaling :)
-
Q:
fastjson
crashes my program! A: There is high probability of improper use.- Make sure you don't hold references to objects recursively returned by
Parser
/Scanner
beyond the nextParser.Parse
/Scanner.Next
call if such restriction is mentioned in docs. - Make sure you don't access
fastjson
objects from concurrently running goroutines if such restriction is mentioned in docs. - Build and run your program with -race flag. Make sure the race detector detects zero races.
- If your program continue crashing after fixing issues mentioned above, file a bug.
- Make sure you don't hold references to objects recursively returned by