Extended the functionality, and increased the performance of the builtin json library for Pyjinn

[SmartBoty]

Upgraded json.py to use Gson instead of JsonParser: Significant performance improvements for deserialization and exposing dumps

Built in json.py:
1 280 307.60 ns / call (~1.28 ms)

This json.py:
852 362.57 ns / call (~0.85 ms)

Notes:

• I tried to match the header to the builtin json.py-s header, but may still require adjustments

Code used to determine these values:

System = JavaClass("java.lang.System")

data = (
r"""
{
  "version": "1.2.0",
  "generated": "2026-07-21T14:30:00Z",
  "success": true,
  "metadata": {
    "creator": "Test Generator",
    "description": "JSON parser stress test",
    "tags": [
      "json",
      "parser",
      "test",
      "nested",
      "unicode"
    ],
    "unicode": "こんにちは 🌍 Привет مرحبا",
    "escaped": "Line1\nLine2\tTabbed\\Backslash\"Quote\""
  },
  "numbers": {
    "zero": 0,
    "negative": -42,
    "integer": 123456789,
    "float": 3.1415926535,
    "negativeFloat": -0.000123,
    "scientific1": 6.022e23,
    "scientific2": -1.6e-19,
    "large": 999999999999999,
    "small": 0.000000000001
  },
  "emptyObject": {},
  "emptyArray": [],
  "nullValue": null,
  "users": [
    {
      "id": 1,
      "name": "Alice",
      "active": true,
      "roles": [
        "admin",
        "developer"
      ],
      "address": {
        "street": "123 Main St",
        "city": "Exampleville",
        "zip": "12345",
        "coords": {
          "lat": 41.40338,
          "lon": 2.17403
        }
      },
      "scores": [
        95,
        88,
        76,
        100
      ]
    },
    {
      "id": 2,
      "name": "Bob",
      "active": false,
      "roles": [
        "user"
      ],
      "address": {
        "street": "456 Side Rd",
        "city": "Somewhere",
        "zip": null,
        "coords": {
          "lat": -33.865143,
          "lon": 151.2099
        }
      },
      "scores": []
    },
    {
      "id": 3,
      "name": "Charlie",
      "active": true,
      "roles": [],
      "address": {},
      "scores": [
        50,
        75.5,
        -12,
        1.2e4
      ]
    }
  ],
  "matrix": [
    [1, 2, 3],
    [4, 5, 6],
    [7, 8, 9]
  ],
  "mixedArray": [
    null,
    true,
    false,
    123,
    -45.67,
    "hello",
    {
      "nested": [
        {
          "a": 1
        },
        {
          "b": 2
        }
      ]
    },
    [],
    {}
  ],
  "config": {
    "graphics": {
      "width": 1920,
      "height": 1080,
      "fullscreen": false,
      "vsync": true
    },
    "audio": {
      "master": 0.8,
      "music": 0.5,
      "effects": 0.9
    },
    "network": {
      "host": "localhost",
      "port": 8080,
      "timeout": 15.5
    }
  },
  "deep": {
    "level1": {
      "level2": {
        "level3": {
          "level4": {
            "level5": {
              "message": "Reached the bottom!"
            }
          }
        }
      }
    }
  },
  "inventory": [
    {
      "id": "itm001",
      "name": "Sword",
      "stats": {
        "damage": 25,
        "durability": 98
      },
      "enchantments": [
        "Fire",
        "Sharpness"
      ]
    },
    {
      "id": "itm002",
      "name": "Shield",
      "stats": {
        "defense": 40,
        "durability": 100
      },
      "enchantments": []
    },
    {
      "id": "itm003",
      "name": "Potion",
      "stats": null,
      "stack": 15
    }
  ],
  "objectArray": [
    {
      "k": "a",
      "v": 1
    },
    {
      "k": "b",
      "v": 2
    },
    {
      "k": "c",
      "v": {
        "nested": true
      }
    }
  ]
}
""")

start = System.nanoTime()
for _ in range(10000):
  loads(data)
print(f"Average: {(System.nanoTime()-start)/10000}")