JSON is a data tree of objects, lists, numbers and strings. TXT is plain text, with no markup of any kind. pandoc sits between the two, and this page says exactly what happens to a JSON file on the way to becoming a TXT one.
What runs when a JSON file becomes TXT
pandoc in two passes, on a machine we rent and watch. Your JSON file is uploaded once, pandoc runs once, the TXT comes back, and neither file is kept. JSON to TXT is one of the 3649 pairs that engine was probed on with a real file, which is why it has a page here and why the pairs the probe could not prove do not.
What survives from the JSON into the TXT
Lists from the JSON file, nesting included, plus code blocks, block quotes and links, all re-expressed in TXT.
Images: pandoc extracts them out of the JSON file into a working directory and re-embeds them in the TXT, so nothing ends up pointing at a file that no longer exists.
What JSON to TXT costs you
The presentation layer. pandoc does not translate the JSON file into TXT, it rebuilds it from its own document tree, so custom styles, page setup, headers and footers do not cross over. The structure does, and that is what the tree is made of.
If a model is going to read the TXT
Structure is what survives from the JSON file, and structure is what a model needs. JSON in, TXT out, with the heading tree intact instead of flattened into one long paragraph.
JSON to TXT, measured rather than promised
Running JSON to TXT against the real engine with a real file, pandoc wrote 264 bytes of TXT in under a tenth of a second, machine otherwise idle. That is one JSON file on one day and not an average, which is why the number is given together with the file that produced it.
The JSON to TXT verdict was reached by reading the text back, meaning the output decodes as readable text and still carries the witness word, which is the only check a plain text target allows. Which check was used matters, because they do not all prove the same thing, and a status code of 200 proves nothing whatsoever about whether the TXT file has anything inside it.
The same JSON file, sent somewhere else
Other outputs the probe measured out of a JSON file, so the cost of choosing TXT can be read against something. Sizes do not compare across engines, because each family was probed with its own JSON witness file.
JSON to MD: 266 bytes in under a tenth of a second, verified by a pandoc round trip.
JSON to DOCX: 10,106 bytes in 0.1 seconds, verified by a pandoc round trip.
JSON to EPUB: 5,035 bytes in 0.1 seconds, verified by a pandoc round trip.
JSON to HTML: 4,018 bytes in 0.1 seconds, verified by a pandoc round trip.
JSON to RTF: 687 bytes in 0.1 seconds, verified by a pandoc round trip.
JSON to ODT: 7,537 bytes in 0.1 seconds, verified by a pandoc round trip.
Other ways into TXT, and what they measured
Among the published routes into TXT, JSON is the fourth largest output of the 11 measured. The witness files differ, so this ranks the probe run and not your document.
MD to TXT: 264 bytes in under a tenth of a second.
MOBI to TXT: 219 bytes in 0.5 seconds.
ODT to TXT: 264 bytes in 0.1 seconds.
RTF to TXT: 263 bytes in under a tenth of a second.
DOCX to TXT: 264 bytes in 0.1 seconds.
What we will not pretend about JSON to TXT
A JSON file over 25 MB is refused before the upload finishes rather than after it, so you do not wait for a rejection.
A JSON to TXT run that passes 60 seconds is killed, and the pandoc process is killed with it. A run left behind would sit on one of the machine's two cores until somebody noticed.
32 of the 935 pairs probed in the family that serves JSON to TXT failed, and this pair is not one of them. They fail for reasons worth knowing: a writer that cannot carry what the document is made of, or output the engine could not read back. They are counted here rather than hidden, because a pair that fails quietly is worse than one that fails loudly.
pandoc never writes the TXT through a TeX engine here, and it never writes PDF at all: the eleven engines it would need are not on this machine and a TeX distribution weighs several gigabytes. Anyone who wants a PDF out of a JSON file goes through LibreOffice or calibre, both of which genuinely can.
One JSON file at a time, chosen in the browser. There is nothing else to set up and nothing else on offer.
JSON to TXT: what people ask
What actually converts my JSON file to TXT?
pandoc does it, in two passes, on a machine we rent and watch. Not a browser trick and not somebody else service: the JSON file is uploaded once, pandoc runs once, the TXT comes back, and neither file is kept afterwards.
How long does JSON to TXT take?
On the file the probe used, pandoc took under a tenth of a second and wrote 264 bytes of TXT. That is one real measurement on one real JSON file, not an average and not a promise about yours: a larger JSON takes longer, and past 60 seconds the run is stopped.
What do I lose going from JSON to TXT?
The one to know about first: The presentation layer. pandoc does not translate the JSON file into TXT, it rebuilds it from its own document tree, so custom styles, page setup, headers and footers do not cross over. The structure does, and that is what the tree is made of.
Are the tables in my JSON file still tables in the TXT?
No, and that is a property of TXT rather than a defect of this path. TXT cannot hold a table, so a JSON file built around one is the wrong candidate for this pair.
Is JSON to TXT free?
There is a free allowance every month, and one JSON to TXT conversion costs half a credit against it. When the allowance runs out the tool says so and stops, rather than quietly handing you a worse TXT.