Code Beautify / MULTIVERTO
Turn a header-based CSV table into JSON objects.
Apply each text tool to the previous result.
01 / Guide
Parses a documented input subset and writes the corresponding output representation.
For complex syntax or production assets, verify the output with the destination application and a dedicated parser or build tool.
02 / Example
name,city
Ada,Hello
Lin,Welcome[
{
"name": "Ada",
"city": "Hello"
},
{
"name": "Lin",
"city": "Welcome"
}
]03 / Guide
Turn a header-based CSV table into JSON objects. Parses a documented input subset and writes the corresponding output representation. The first CSV row becomes JSON property names, and every later row becomes an object. All cell values remain strings, so a value like 42 is not automatically a number. Duplicate headings or rows of inconsistent width are reported instead of silently merging fields.
CSV is a table of records and cells, not a typed object model. The first row is treated as a header; commas inside a cell require quotation marks and a quotation mark inside a quoted cell is doubled. The parser accepts line breaks within quoted fields and rejects inconsistent row widths or duplicate header names. CSV-to-JSON therefore produces strings for every cell, even when a value looks like a number or boolean. JSON-to-CSV accepts a nonempty array of flat objects and gathers their keys into columns. Missing or null values become empty cells, so a reverse conversion cannot distinguish them without an external schema.
A change of data format is a mapping between two information models, not merely a change of punctuation. Begin with a tiny representative record that includes a non-ASCII value, a missing field or a nested value when relevant. Run the conversion and inspect how keys, ordering, numbers, null values, arrays and repeated items appear. Some target formats have no native equivalent for a source feature; the individual guide states the supported mapping. Feed the result to the intended receiver and, if possible, convert it back to compare the meaningful fields. For a bulk migration or an external contract, use a full parser and a schema test, because a plausible-looking sample does not establish complete interoperability.
Keep the original next to the output and test a small known example before handling a large document. Compare meaningful content, not only file size or the number of lines. Check names, quoted strings, non-ASCII characters, line endings and any repeated fields after the transformation. A syntactically readable result does not validate a schema, prove that code executes, or establish that data is safe to publish. This site processes the entered text in the browser and displays the result as text, but the copy you paste into another application will follow that application’s rules. If the tool rejects an input, do not remove unexplained characters merely to get an output: identify which construct is outside the supported subset and use a dedicated parser when necessary.