Monster is a grammar based production tool. At present I am using this to generate json documents using production grammar.
Can be invoked via command-line like,
$ go run monster/monster.go -h
-bagdir="": directory path containing bags
-n=1: generate n combinations
-nonterm="": evaluate the non-terminal
-o="-": specify an output file
-seed=37: seed valueExample production grammar, that generate randomized json documents.
s : value.
object : "{" properties "}".
properties : properties "," property
| property.
property : DQ (bag "./web2") DQ ":" value.
array : "[" values "]".
values : value "," value
| (weigh 0.8 0.2) values.
value : (weigh 0.1) basic
| (weigh 0.45 0.1) array
| (weigh 0.45 0.1) object.
basic : "true"
| "false"
| "null"
| number
| string.
string : DQ (bag "./web2") DQ.
number : (range 0 100000)
| (rangef 0.0 100.0).
The grammar can be invoked via command line like,
go run monster/monster.go -bagdir ./bags -n 10 ./prods/json.produse -n switch to generate as many document as needed, documents will be output
to stdout by default, to redirect them to a file use -o switch.
different commands to debug monster,
// To generate GCTRACE.
GCDEBUG=gctrace=2 go run monster/monster.go -bagdir bags -count 1000000 -o o prods/users.prod
// To generate mem-profile.
go run monster/monster.go -bagdir bags -count 1000000 -memprof apr21.1.mprof -o o prods/users.prod
// To analyse alloc-space.
go tool pprof --svg --alloc_space monster/monster apr21.1.mprof > apr21.1.mprof.alloc.svg