README

Description

Parses JSON strings into CSV files. Creates multiple tables from a single JSON. Uses Keboola\CsvFile for results. The root of the JSON must be an array. JSON parser is part of Generic Extractor (see also end-user documentation).

Usage

use Keboola\Json\Parser;
$parser = new Parser(new Analyzer(new NullLogger(), new Structure()));
$file = file_get_contents("some/data.json");
$json = json_decode($file);

$parser->process($json);

$results = $parser->getCsvFiles(); // array of CsvFile objects

\Keboola\Json\Analyzer

Analyzes JSON data for JSON parser.

__construct(\Psr\Log\LoggerInterface $logger, \Keboola\Json\Structure $structure, $nestedArraysAsJson, $strict)

• $logger - a logger, use NullLogger if no logger is used.
• $structure - a representation of JSON structure .
• $nestedArraysAsJson - if true, then nested arrays will be encoded as JSON strings. If false (default), the conversion will fail.
• $strict - if true, then JSON node data types will be checked more strictly (int, string, ...).

\Keboola\Json\Parser

Parses JSON data into CSV files.

__construct($analyzer, $definitions = [])

• $definitions - optional array with results from previous process.
• $analyzer - instance of analyzer class.

process($data, $type, $parentId)

• $data - array of objects retrieved from JSON data.
• $type - is used for naming the resulting table(s).
• $parentId - either a string, which will be saved in a JSON_parentId column, or an array with "column_name" => "value", which will name the column(s) by array key provided.
• If the data is analyzed, it is stored in Cache and NOT PARSED until the getCsvFiles() method is called.

getCsvFiles()

• returns a list of \Keboola\CsvTable\Table objects with parse results

Parse characteristics

The analyze function loops through each row of an array (generally an array of results) and passes the row into analyzeRow() method. If the row only contains a scalar, it's stored in a "data" column. If the row is an object, each of the object's variables will be used as a column name, and its values are analyzed:

• if it is a scalar, it'll be saved as a value of that column.
• if it is an array, it'll be passed to analyze() to create a new table, linked by a generated JSON_parentId column
• if it is another object, it'll be parsed recursively to analyzeRow(), with its variable names prepended by current objects' name, e.g.:

"parent": {
    "child" : "value1"
}

will result in a parent_child column with a string type of "value1".