cerbero90 / json-parser Goto Github PK

Detailed description

Getting multiple nested content dynamically.

Context

$json = JsonParser::parse($source)->pointer('/results/-/gender');

foreach ($json as $key => $value) {
    // 1st iteration: $key === 'gender', $value === 'female'
    // 2nd iteration: $key === 'gender', $value === 'female'
    // 3rd iteration: $key === 'gender', $value === 'male'
    // and so on for all the objects in the array...
}

Same like above example we can skip any element keys after results, but we cant do that on multiple level

- $json = JsonParser::parse($source)->pointer('/results/-/gender');
+ $json = JsonParser::parse($source)->pointer('/results/-/-/gender');

I get a TypeError when I try to use the JsonParser on an array. The error happens on line 59 in \Cerbero\JsonParser\Tokens\Lexer because the Lexer assumes the $chunk variable will contain a string and calls strlen() upon it, however when parsing from a nested array the $chunk variable contains an array as well.

Basically, I think this is a bug. I'm open to the option that I'm doing something wrong, but I couldn't figure out what it could be and it feels like a bug. Or did I get all of this completely wrong and the iterable source should contain an array of JSON strings? 😅

Here is a chunk of code that should produce the bug I'm describing:

$data = [
    "pre" => [
        "locations" => [
            "locations" => [
                [
                    "id" => 2333,
                    "title" => "Hollywood",
                    "created_at" => "2022-10-02 10:17:12",
                    "updated_at" => "2022-10-02 10:17:12",
                    "deleted_at" => null
                ]
            ]
        ],
        "categories" => [
            "categories" => [
                [
                    "id" => 1302,
                    "business_id" => 186,
                    "title" => "Drama",
                    "deleted_at" => null,
                    "created_at" => "2019-02-10 06:28:28",
                    "updated_at" => "2020-02-08 05:16:52"
                ]
            ]
        ]
    ],
    "products" => [
        [
            "id" => 4465,
            "backoffice_title" => "Acting class",
            "created_at" => "2017-02-22 16:20:19",
            "updated_at" => "2023-06-30 10:25:59",
            "deleted_at" => null
        ]
    ],
    "post" => [
        "timeslots-4465" => [
            "timeslots" => [
                [
                    "id" => 250334,
                    "product_id" => 4465,
                    "created_at" => "2019-02-10 06:28:29",
                    "updated_at" => "2021-09-03 15:03:27"
                ]
            ]
        ]
    ]
];
        
(new JsonParser($data))->pointer('/pre/locations', fn ($data) => var_dump($data))->traverse();

Possible implementation

I'm guessing the iterable source should not be processed by the Lexer at all

Your environment

• Version used: 1.0.0
• PHP version: 8.2.7
• Ran on Laravel Sail 1.7 with Laravel 8.83.27

Detailed description

After using this library to iterate larger JSON responses from Guzzle (using the pointer /- on \Psr\Http\Message\StreamInterface), I noticed a significant reduction in memory usage (great!), but as well a significant increase in CPU load.
Is this expected?
What are possible mitigation strategies? Would different options (chunk size, lazy pointers, ..) help?

Context

Of course generally the "space-time tradeoff" implies some increase in CPU, but I expected this to be not significant..

Possible implementation

Possibly a section on this in the readme would help, maybe even a comparison to the alternatives to see if this is on the same level?

Your environment

• Version used: PHP 8.1
• Operating system and version: Ubuntu 22.0

There is a already a package with 0 dependencies and over 3 million downloads doing more or less the same. How is this package different from it?

It would be great if there were examples for each source. Since now it is not clear, for example, how to work with Laravel request, when you receive data via the API, the request immediately produces an array and because of this an error.