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README.md

jtc - cli tool to extract, manipulate and transform source JSON

jtc stand for: JSON test console, but it's a legacy name, don't get misled.

jtc offers a powerful way to select one or multiple elements from a source JSON and apply various actions on the selected elements at once (wrap selected elements into a new JSON, filter in/out, update elements, insert new elements, remove, copy, move, compare, transform and swap around).

Content:

  1. Short description

  2. Quick-start guide

  3. Complete User Guide

  4. Class usage and c++14 interface

  5. jtc vs jq

Short description

- jtc is simple but efficient cli utility tool to manipulate JSON data

jtc offers following features (a short list of main features):

  • simple user interface allowing applying a bulk of changes in one command
  • featured walk-path interface lets extracting any combination of data from source JSON
  • extracted data is representable either as it found, or encapsulated in JSON array/object
  • support Regular Expressions when searching source JSON
  • fast and efficient processing very large JSON files (built-in search cache)
  • insert/updates operations optionally may undergo shell cli evaluation
  • features namespaces, interpolation from namespaces and templates
  • supports buffered and streamed modes of input reads
  • written entirely in C++14, no dependencies (STL only, idiomatic C++, no memory leaks)
  • extensively debuggable
  • conforms JSON specification (json.org)

Walk path feature is easy to understand - it's only made of 2 types of lexemes:

  • subscripts - enclosed into [, ]: subscripts let traversing JSON tree downwards and upwards
  • search lexemes - encased into <, >: search lexemes facilitate either full match or Regex search.

Both types of lexemes are iterable - subscript let iterating over children of currently addressed iterables node (array/object), while iterable search lexemes let iterating over all matches for a given search criteria. A walk path is made of an arbitrary number of lexemes, while the tool accepts a virtually unlimited number of walk paths. See below more detailed explanation with examples

Linux and MacOS precompiled binaries are available for download

For compiling, c++14 (or later) is required:

  • to compile under MacOS, use cli: c++ -o jtc -Wall -std=c++14 -Ofast jtc.cpp
  • To compile under Linux, use cli: c++ -o jtc -Wall -std=gnu++14 -static -Ofast jtc.cpp

pass -DNDEBUG flag if you like to compile w/o debugs, however it's unadvisable - there's no performance gain from doing so

or download the latest precompiled binary:

Installing via MacPorts

On macOS, you can install jtc via the MacPorts package manager:

$ sudo port selfupdate
$ sudo port install jtc

Compile and install instructions:

download jtc-master.zip, unzip it, descend into unzipped folder, compile using an appropriate command, move compiled file into an install location.

here're the example steps for MacOS:

  • say, jtc-master.zip has been downloaded to a folder and the terminal app is open in that folder:
  • unzip jtc-master.zip
  • cd jtc-master
  • c++ -o jtc -Wall -std=c++14 -Ofast jtc.cpp
  • sudo mv ./jtc /usr/local/bin/

For Linux you'd have to compile using this line:

  • c++ -o jtc -Wall -std=gnu++14 -static -Ofast jtc.cpp

Release Notes

See the latest Release Notes

Quick-start guide:

run jtc -g for walk path explanations, usage notes and additional usage examples

Consider a following JSON (a mockup of a bookmark container), stored in a file Bookmarks:

{
   "Bookmarks": [
      {
         "children": [
            {
               "children": [
                  {
                     "name": "The New York Times",
                     "stamp": "2017-10-03, 12:05:19",
                     "url": "https://www.nytimes.com/"
                  },
                  {
                     "name": "HuffPost UK",
                     "stamp": "2017-11-23, 12:05:19",
                     "url": "https://www.huffingtonpost.co.uk/"
                  }
               ],
               "name": "News",
               "stamp": "2017-10-02, 12:05:19"
            },
            {
               "children": [
                  {
                     "name": "Digital Photography Review",
                     "stamp": "2017-02-27, 12:05:19",
                     "url": "https://www.dpreview.com/"
                  }
               ],
               "name": "Photography",
               "stamp": "2017-02-27, 12:05:19"
            }
         ],
         "name": "Personal",
         "stamp": "2017-01-22, 12:05:19"
      },
      {
         "children": [
            {
               "name": "Stack Overflow",
               "stamp": "2018-05-01, 12:05:19",
               "url": "https://stackoverflow.com/"
            },
            {
               "name": "C++ reference",
               "stamp": "2018-06-21, 12:05:19",
               "url": "https://en.cppreference.com/"
            }
         ],
         "name": "Work",
         "stamp": "2018-03-06, 12:07:29"
      }
   ]
}

1. let's start with a simple thing - list all URLs:

bash $ jtc -w'<url>l:' Bookmarks
"https://www.nytimes.com/"
"https://www.huffingtonpost.co.uk/"
"https://www.dpreview.com/"
"https://stackoverflow.com/"
"https://en.cppreference.com/"

The walk-path (an argument of -w) is a combination of lexemes. There are only 2 types of lexemes:

  1. subscript lexemes - enclosed in [,]
  2. search lexemes - enclosed in <,> - the walk-paths may contain any number of lexemes

let's take a look at the walk-path <url>l::

  • search lexemes are enclosed in angular brackets <, > - that style provides a recursive search
  • suffix l instructs to search among labels only
  • quantifier : instructs to find all occurrences, such quantifiers makes a path iterable

2. dump all bookmark names from the Work folder:

bash $ jtc -w'<Work>[-1][children][:][name]' Bookmarks
"Stack Overflow"
"C++ reference"

here the walk path <Work>[-1][children][:][name] is made of following lexemes (spaces separating lexemes are optional):

a. <Work>: find within a JSON tree the first occurrence where the JSON string value is matching "Work" exactly
b. [-1]: step up one tier in the JSON tree structure (i.e. address an immediate parent of the found JSON element)
c. [children]: select/address a node whose label is "children" (it'll be a JSON array, at the same tier with Work)
d. [:]: select an each node in the array
e. [name]: select/address a node whose label is "name"

  • subscript offsets are enclosed into square brackets [, ] and may have different meaning:
    • simple numerical offsets (e.g.: [0], [5], etc) select/address a respective JSON immediate child in the addressed node - a.k.a. numerical subscripts
    • slice/range offsets, expressed as [N:N] let selecting any slice/range of element in the array/object (any of N could be omitted in that notation)
    • numerical offsets proceeded with + make a path iterable - all children starting with the given index will be selected (e.g.: [+2] will select/address all immediate children starting from 3rd one) - such notation is equivalent of [N:]
    • numerical negative offsets (e.g.[-1], [-2], etc ) will select/address a parent of currently selected/found node, a parent of a parent, etc
    • textual offsets (e.g. [name], [children], etc) select/address nodes with corresponding labels among immediate children (i.e. textual subscripts)

*** there's more on offsets and search quantifiers below

in order to understand better how a walk path works, let's run a series of cli in a slow-motion, gradually adding lexemes to the path, perhaps with the option -l to see also the labels (if any) of the selected elements:

bash $ jtc -w'<Work>' -l Bookmarks
"name": "Work"
bash $ jtc -w'<Work>[-1]' -l Bookmarks
{
   "children": [
      {
         "name": "Stack Overflow",
         "stamp": "2018-05-01, 12:05:19",
         "url": "https://stackoverflow.com/"
      },
      {
         "name": "C++ reference",
         "stamp": "2018-06-21, 12:05:19",
         "url": "https://en.cppreference.com/"
      }
   ],
   "name": "Work",
   "stamp": "2018-03-06, 12:07:29"
}
bash $ jtc -w'<Work>[-1][children]' -l Bookmarks
"children": [
   {
      "name": "Stack Overflow",
      "stamp": "2018-05-01, 12:05:19",
      "url": "https://stackoverflow.com/"
   },
   {
      "name": "C++ reference",
      "stamp": "2018-06-21, 12:05:19",
      "url": "https://en.cppreference.com/"
   }
]
bash $ jtc -w'<Work>[-1][children][:]' -l Bookmarks
{
   "name": "Stack Overflow",
   "stamp": "2018-05-01, 12:05:19",
   "url": "https://stackoverflow.com/"
}
{
   "name": "C++ reference",
   "stamp": "2018-06-21, 12:05:19",
   "url": "https://en.cppreference.com/"
}
bash $ jtc -w'<Work>[-1][children][:][name]' -l Bookmarks
"name": "Stack Overflow"
"name": "C++ reference"

3. dump all URL's names:

bash $ jtc -w'<url>l:[-1][name]' Bookmarks
"The New York Times"
"HuffPost UK"
"Digital Photography Review"
"Stack Overflow"
"C++ reference"

this walk path <url>l:[-1][name]:

  • finds recursively (encasement <, >) all (:) JSON elements with a label (l) matching url

  • then for an each found JSON element, select its parent ([-1])

  • then, select a JSON element with the label "name" (encasement [, ])

4. dump all the URLs and their corresponding names, preferably wrap found pairs in JSON:

bash $ jtc -w'<url>l:' -w'<url>l:[-1][name]' -jl Bookmarks
[
   {
      "name": "The New York Times",
      "url": "https://www.nytimes.com/"
   },
   {
      "name": "HuffPost UK",
      "url": "https://www.huffingtonpost.co.uk/"
   },
   {
      "name": "Digital Photography Review",
      "url": "https://www.dpreview.com/"
   },
   {
      "name": "Stack Overflow",
      "url": "https://stackoverflow.com/"
   },
   {
      "name": "C++ reference",
      "url": "https://en.cppreference.com/"
   }
]
  • yes, multiple walks (-w) are allowed
  • option -j will wrap the walked outputs into a JSON array, but not just,
  • option -l used together with -j will ensure relevant walks are grouped together (try without -l)
  • if multiple walks (-w) are present, by default, walked results will be printed interleaved (with respect to each other JSON position, if the latter can be inferred)

5. Subscripts (offsets) and Searches explained

In short:

  • Subscript lexemes ([..]) facilitate:
    • addressing children (by index/label) in JSON iterables (arrays and objects) - i.e. traverse JSON structure downward from the root (toward leaves), e.g.: [2], [id]
    • addressing parents (immediate and distant) - i.e. traverse JSON structure upwards, toward the the root (from leaves), e.g.: [-1] (tier offset from the walked element), [^2] (tier offset from the root)
    • select ranges and slices of JSON elements in JSON iterables, e.g.: [+2], [:], [:3], [-2:], [1:-1]
  • Search lexemes (<..>, >..<) facilitate:
    • recursive (<..>) and non-recursive (>..<) matches
    • there're optional one-letter suffixes that may follow the lexemes (e.g.: <..>Q) which define type of search: (REGEX) string search, (REGEX) label search, (REGEX) numerical, boolean, null, atomic, objects, arrays (or either), arbitrary JSONs, unique, duplicates, etc.
    • there're also optional quantifiers to lexemes (must take the last position, after the suffix if one present) - let selecting match instance, or range of matches (e.g.: <id>l3- will match 4th (zero based) label "id"; if no quantifier present 0 is assumed - first match)
  • subscript lexemes could be joined with search lexemes over ':' to facilitate scoped search, e.g.: [id]:<value> is a single lexeme which will match recursively the first occurrence of the string "value" with the label "id" - i.e. "id": "value"
  • Directives: there are a few suffixes which turn a search lexeme into a directive:
    • directives do not do any matching, instead they facilitate a certain action/operation with the currently walked JSON element, like: memorize it in the namespace, or erase from it, or memorize its label, or perform a shell cli evaluation
    • couple directives (<>f and <>F) facilitate also walk branching

Refer to jtc User Guide for the detailed explanation of the subscripts, search lexemes and directives.

6. Debugability / JSON validation

jtc is extensively debuggable: the more times option -d is given the more debugs will be produced (currently debug depth may go as deep as 7: -ddddddd). Enabling too many debugs might be overwhelming, though one specific case many would find extremely useful - when validating a failing JSON:

bash $ <addressbook-sampe.json jtc
jtc json exception: expected_json_value

If JSON is big, it's desirable to locate the parsing failure point. Specifying just one -d let easily spotting the parsing failure point and its locus:

bash $ <addressbook-sampe.json jtc -d
.read_inputs(), reading json from <stdin>
.parsejson(), exception locus: ...       ],|       "children": [,],|       "spouse": null|    }...
.location_(), exception spot: --------------------------------->| (offset: 967)
jtc json exception: expected_json_value
bash $

Complete User Guide

Refer to a complete User Guide for further examples and guidelines.

A tiny example of class usage and its interface (c++14):

Say, we want to accomplish a following task:

  1. read Address Book JSON from <stdin>
  2. sort all records by Name (for simplicity, assume all records have that label)
  3. output resulting Address Book JSON

Below is the code sample how that could be achieved using Json.hpp class and the source JSON - Address Book:

#include <iostream>
#include <fstream>
#include "lib/Json.hpp"

// compile with: c++ -o sort_ab -Wall -std=c++14 sorting_ab.cpp
using namespace std;


int main(int argc, char *argv[]) {
 Json jin( {istream_iterator<char>(cin>>noskipws), istream_iterator<char>{}} );  // read and parse json from cin
 vector<string> names(jin.walk("[AddressBook][+0][Name]"), jin.walk().end());    // get all the names
 sort(names.begin(), names.end());                                               // sort the names

 Json srt = ARY{};                                                               // rebuild AB with sorted records
 for(const auto &name: names)
  srt.push_back( move( *jin.walk("[AddressBook][Name]:<" + name + ">[-1]") ) );

 cout << jin["AddressBook"].clear().push_back( move(srt) ) << endl;              // put back into the original container and print
}

Address Book JSON:

bash $ cat addressbook-sample.json
{
  "AddressBook": [
    {
       "Name": "John",
       "age": 25,
       "address": {
          "city": "New York",
          "street address": "599 Lafayette St",
          "state": "NY",
          "postal code": "10012"
       },
       "phoneNumbers": [
          {
             "type": "mobile",
             "number": "212 555-1234"
          }
       ],
       "children": [],
       "spouse": null
    },
    {
       "Name": "Ivan",
       "age": 31,
       "address": {
          "city": "Seattle",
          "street address": "5423 Madison St",
          "state": "WA",
          "postal code": "98104"
       },
       "phoneNumbers": [
          {
             "type": "home",
             "number": "3 23 12334"
          },
          {
             "type": "mobile",
             "number": "6 54 12345"
          }
       ],
       "children": [],
       "spouse": null
    },
    {
       "Name": "Jane",
       "age": 25,
       "address": {
          "city": "Denver",
          "street address": "6213 E Colfax Ave",
          "state": "CO",
          "postal code": "80206"
       },
       "phoneNumbers": [
          {
             "type": "office",
             "number": "+1 543 422-1231"
          }
       ],
       "children": [],
       "spouse": null
    }
  ]
}
bash $

Output result:

bash$ cat addressbook-sample.json | sort_ab
[
   [
      {
         "Name": "Ivan",
         "address": {
            "city": "Seattle",
            "postal code": "98104",
            "state": "WA",
            "street address": "5423 Madison St"
         },
         "age": 31,
         "children": [],
         "phoneNumbers": [
            {
               "number": "3 23 12334",
               "type": "home"
            },
            {
               "number": "6 54 12345",
               "type": "mobile"
            }
         ],
         "spouse": null
      },
      {
         "Name": "Jane",
         "address": {
            "city": "Denver",
            "postal code": "80206",
            "state": "CO",
            "street address": "6213 E Colfax Ave"
         },
         "age": 25,
         "children": [],
         "phoneNumbers": [
            {
               "number": "+1 543 422-1231",
               "type": "office"
            }
         ],
         "spouse": null
      },
      {
         "Name": "John",
         "address": {
            "city": "New York",
            "postal code": "10012",
            "state": "NY",
            "street address": "599 Lafayette St"
         },
         "age": 25,
         "children": [],
         "phoneNumbers": [
            {
               "number": "212 555-1234",
               "type": "mobile"
            }
         ],
         "spouse": null
      }
   ]
]
bash $

for the complete description of Json class interface, refer to Json.hpp

jtc vs jq:

jtc was inspired by the complexity of jq interface (and its DSL), aiming to provide a user tool which would let attaining the desired result in a more feasible way

utility ideology:

  • jq is a stateful processor with own DSL, variables, operations, control flow logic, IO system, etc, etc
  • jtc is a unix utility confining its functionality to operation types with its data model only (as per unix ideology). jtc performs one operation at a time and if successive operations required, then cli to be daisy-chained over the pipe symbol |

jq is non-idiomatic in a unix way, e.g., one can write a program in jq language that even has nothing to do with JSON. Most of the requests (if not all) to manipulate JSONs are ad hoc type of tasks, and learning jq's DSL for ad hoc type of tasks is an overkill (that purpose is best facilitated with GPL). The number of asks on the stackoverflow to facilitate even simple queries for jq is huge - that's the proof in itself that for many people feasibility of attaining their asks with jq is a way too low, hence they default to posting their questions on the forum.

jtc on the other hand is a utility (not a language), which employs a novel but powerful concept, which "embeds" the ask right into the walk-path. That facilitates a much higher feasibility of attaining a desired result: building the walk-path a lexeme by a lexeme, one at a time, provides an immediate visual feedback and let coming up with the desired result quite quickly.

learning curve:

  • jq: before you could come up with a query to handle even a relatively simple ask, you need to become an expert in jq's language, which will take some time. Coming up with the complex queries requires it seems having a "PhD" in jq, or spending lots of time on stackoverflow and similar forums
  • jtc employs only a single (but powerful) concept of the walk-path (which is made only of 2 types of lexemes, each type though has several variants) which is easy to grasp.

handling irregular JSONs:

  • jq: handling irregular JSONs for jq is not a challenge, building a query is! The more irregularities you need to handle the more challenging the query (jq program) becomes
  • jtc was conceived with the idea of being capable of handling complex irregular JSONs with a simplified interface - that all is fitted into the concept of the walk-path, while daisy-chaining multiple jtc operations it's possible to satisfy almost every query.

programming model

  • jq is written in C, which drags all intrinsic problems the language has dated its creation
  • jtc is written in idiomatic C++ (the most powerful programming language to date) using STL only. Main JSON engine/library does not have a single new operator, nor it has a single naked pointer acting as a resource holder/owner, thus jtc is guaranteed to be free of memory leaks (at least one class of the problems is off the table) - STL guaranty. Also, jtc is written in a very portable way, it should not cause any problems compiling it under any unix like system.

JSON numerical fidelity:

  • jq is not compliant with JSON numerical definition. What jq does, it simply converts a symbolic numerical representation to an internal binary and keeps it that way. That approach:
    • is not compliant with JSON definition of the numerical values
    • it has problems retaining required precision
    • might change original representation of numericals
  • jtc validates all JSON numericals per JSON standard and keep numbers internally in their original symbolical format, so it's free of all the above caveats:
Handling jtc jq
Invalid Json: [ 00 ] <<<'[00]' jtc <<<'[00]' jq -c .
Parsing result jtc json exception: missed_prior_enumeration [0]
Precision test: <<<'[0.99999999999999999]' jtc -r <<<'[0.99999999999999999]' jq -c .
Parsing result [ 0.99999999999999999 ] [1]
Retaining original format: <<<'[0.00001]' jtc -r <<<'[0.00001]' jq -c .
Parsing result [ 0.00001 ] [1e-05]

performance:

here's a 4+ million node JSON test file:

bash $ jtc -zz standard.json
4329975

The table below compares jtc and jq performance for similar operations (using TIMEFORMAT="user %U sec", a median value is selected from 5 attempts):

jtc jq
parsing JSON: parsing JSON:
bash $ time jtc standard.json | wc -l bash $ time jq . standard.json | wc -l
7091578 7091578
user 8.686 sec user 18.848 sec
removing by key from JSON: removing by key from JSON:
bash $ time jtc -pw'<attributes>l:' standard.json | wc -l bash $ time jq 'del(..|.attributes?)' standard.json | wc -l
5573690 5573690
user 9.765 sec user 27.399 sec

The computer's spec used for tests:

  Model Name:                 MacBook Pro (15-inch, 2019)
  Model Identifier:           MacBookPro15,1
  Processor Name:             Intel Core i7
  Processor Speed:            2,6 GHz
  Number of Processors:       1
  Total Number of Cores:      6
  L2 Cache (per Core):        256 KB
  L3 Cache:                   12 MB
  Hyper-Threading Technology: Enabled
  Memory:                     16 GB 2400 MHz DDR4

Refer to a complete User Guide for further examples and guidelines.

Enhancement requests are more than welcome: ldn.softdev@gmail.com
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