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chicken-cjson

Chicken Scheme bindings for the JSON parser cjson. It cannot read from ports and must have the entire JSON object in memory. It also does not serialize to ports as cjson->string returns a string.

The string->json procedure returns the same datastrucures as medea's, read-json, so if you're passing that strings already, string->json should be a drop-in replacement:

    
$ printf '{"array":[1,2,3],"null":null}' | csi -R cjson -p '(string->json (read-line))'
((null . null) (array . #(1.0 2.0 3.0)))
$ printf '{"array":[1,2,3],"null":null}' | csi -R medea -p '(read-json (read-line))'
((array . #(1 2 3)) (null . null))

chicken-cjson may offer a significant performance improvement over medea and json, but comes at a price: all data must be availabe as a string. This means you cannot parse JSON coming in from a port directly, and that's why there is no read-json here.

chicken-cjson offers an alternative API which exposes a JSON c-struct as a #<cjson> scheme record, and accompanying procedures like cjson-string. This is for performance reasons and allows you to pick apart JSON objects using lolevel C-functions, without transitioning into the Scheme data-structure. This may be faster but is a lot uglier:

    
$ printf '{"array":[1,2,3],"null":null}' |\
  csi -R cjson -p '(cjson-double (cjson-array-ref (cjson-obj-ref (string->cjson (read-line)) "array") 1))'
2.0

Note that if you know that a number is fixnum, you can use cjson-int instead.

Requirements

None. cjson comes bundled.

TODO

API

string->cjson stringprocedure

Note that that's not string->json! Parses the string and returns a #<cjson> record which holds a c-struct representing the JSON. The returned record has a finalizer attached to it so the underlying c-struct gets freed on garbage collection.

string->cjson* stringprocedure

Like string->cjson but does not attach a finalizer to the #<cjson> record. cjson-free must be explicitly called later on the returned value to avoid memory leaks. This is sometimes faster than attaching finalizers, particularly if there are large numbers of #<cjson> objects.

cjson->string cjson #!optional pretty-print?procedure

Convert the #<cjson> object to its JSON-representation, returned as a string. pretty-print? defaults to true. Note that this can only serialize cjson records, and not scheme objects.

cjson-schemify cjsonprocedure

Convert the #<cjson> object to scheme data-structures. The data-structures are the same as medea's, where array => vector and object => alist.

string->json stringprocedure

Make scheme data-structures of the json data in string using [cjson]:

    
(define (string->json str)
  (let* ((j (string->cjson* str))
         (s (cjson-schemify j)))
    (cjson-free j)
    s))

For string inputs, this should be API-equivalent of medea's (read-json).

cjson-type cjsonprocedure

Pick out the type of a cjson record. Returns a fixnum.

   [variable] cjson/false
   [variable] cjson/true
   [variable] cjson/null
   [variable] cjson/number
   [variable] cjson/string
   [variable] cjson/array
   [variable] cjson/object

Exposes the cjson-type constants.

cjson-int cjsonprocedure
cjson-double cjsonprocedure
cjson-string cjsonprocedure
cjson-key cjsonprocedure

"Unbox" the json value. cjson-type must match like this:

    
(select (cjson-type cjson)
   ((cjson/false) #f)
   ((cjson/true)  #t)
   ((cjson/null) 'null)
   ((cjson/number) (cjson-double cjson))
   ((csjon/string) (cjson-string cjson))
   (else (error "probably a vector or object")))

[procedure] (cjson-array-size cjson)

Return the number of elements in the array. If cjson's type is not an array, this is undefined bahaviour.

cjson-array-ref cjson indexprocedure

Return the element of cjson at position index. index must be a fixnum. Undefined behaviour if cjson is not an array.

cjson-obj-ref cjson keyprocedure

Select field key from cjson. Key must be a string. Undefined behaviour if cjson is not of type cjosn/object.

Performance

The performance characteristics of JSON parsing is mysterious. It is recommended to use medea or json in most usage-cases because they can parse directly off ports and they also serialize. For particular cases, however, there may be significant performace improvements in using cjson.

Sometimes the speedup is negligible:

    
$ (echo '[' ; for i in {0..1000} ; do echo '"str", 1, 2, 3, 4,' ; done ; echo ' 0]') > bigjson
$ time csi -R medea -e '(pp (read-json))' < bigjson >/dev/null

real    0m0.152s
user    0m0.140s
sys     0m0.013s
$ time csi -R cjson -e '(pp (string->json (read-string)))' < bigjson >/dev/null

real    0m0.114s
user    0m0.103s
sys     0m0.010s

Here, having to doing a read-string first isn't great. cjson may shine when you already have the JSON data as a string:

    
$ for i in {0..100000} ; do echo '{"field" : {"id" : 1}}' ; done > jsonlines
$ time csi -R medea -R ports -e '(port-for-each (lambda (line) (pp (alist-ref `field (read-json line)))) read-line)' < jsonlines  > /dev/null

real    0m3.997s
user    0m3.933s
sys     0m0.067s
$ time csi -R cjson -R ports -e '(port-for-each (lambda (line) (pp (alist-ref `field (string->json line)))) read-line)' < jsonlines  > /dev/null

real    0m1.099s
user    0m1.083s
sys     0m0.017s

That's four times faster. In some cases, though, keeping the #<cjson> record and using its combersome API can pay off:

    
$ JSON='{"field" : {"id" : "ID"} , "a":1, "b":2, "c":[1,{"x":{"y":"y"}},3],"d":{"e":[]}}'
$ for i in {0..100000} ; do echo $JSON ; done > jsonlines
$ for f in test*.scm ; do echo ===== $f === ; cat $f ; done
===== test-cjson.scm ===
(import cjson ports)

(port-for-each
 (lambda (line)
   (let ((cjson (string->cjson* line)))
     (print (cjson-string (cjson-obj-ref (cjson-obj-ref cjson "field") "id")))
     (cjson-free cjson)))
 read-line)

===== test-medea.scm ===
(import medea ports)

(port-for-each
 (lambda (line)
   (print (alist-ref 'id (alist-ref 'field (read-json line)))))
   read-line)

$ for f in test*.scm ; do echo $f ; time csi -s $f < jsonlines >/dev/null ; done
test-cjson.scm

real    0m0.541s
user    0m0.523s
sys     0m0.020s
test-medea.scm

real    0m13.870s
user    0m13.717s
sys     0m0.153s
$ time jq '.field.id' < jsonlines  > /dev/null

real    0m0.513s
user    0m0.500s
sys     0m0.017s

In this particular run, chicken-cjson is 25 times faster than medea, and performas about as well as jq. This speedup typically only happens where you are parsing a lot of JSON, but only a small part of that needs to go back into scheme. Also, this only works because we have one JSON object per line, effectively giving us a json-object delimiter.

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