TXT is plain text, with no markup of any kind. JSON is a data tree of objects, lists, numbers and strings. pandoc sits between the two, and this page says exactly what happens to a TXT file on the way to becoming a JSON one.
What runs when a TXT file becomes JSON
pandoc in two passes, on a machine we rent and watch. Your TXT file is uploaded once, pandoc runs once, the JSON comes back, and neither file is kept. TXT to JSON 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 TXT into the JSON
Lists from the TXT file, nesting included, plus code blocks, block quotes and links, all re-expressed in JSON.
Images: pandoc extracts them out of the TXT file into a working directory and re-embeds them in the JSON, so nothing ends up pointing at a file that no longer exists.
What TXT to JSON costs you
The presentation layer. pandoc does not translate the TXT file into JSON, 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 JSON
Structure is what survives from the TXT file, and structure is what a model needs. TXT in, JSON out, with the heading tree intact instead of flattened into one long paragraph.
TXT to JSON, measured rather than promised
Running TXT to JSON against the real engine with a real file, pandoc wrote 1,343 bytes of JSON in under a tenth of a second, machine otherwise idle. That is one TXT file on one day and not an average, which is why the number is given together with the file that produced it.
The TXT to JSON verdict was reached by a pandoc round trip, meaning the output was read back by pandoc and had to still contain a witness word planted in the source, which proves the content travelled and not merely the container. 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 JSON file has anything inside it.
The same TXT file, sent somewhere else
Other outputs the probe measured out of a TXT file, so the cost of choosing JSON can be read against something. Sizes do not compare across engines, because each family was probed with its own TXT witness file.
TXT to PDF: 12,976 bytes in 1.8 seconds, verified by a format signature.
TXT to MD: 210 bytes in 0.1 seconds, verified by a pandoc round trip.
TXT to DOCX: 9,900 bytes in 0.1 seconds, verified by a pandoc round trip.
TXT to EPUB: 4,955 bytes in 0.1 seconds, verified by a pandoc round trip.
TXT to HTML: 3,896 bytes in 0.1 seconds, verified by a pandoc round trip.
TXT to RTF: 484 bytes in under a tenth of a second, verified by a pandoc round trip.
Other ways into JSON, and what they measured
Among the published routes into JSON, TXT is the sixth largest output of the 8 measured. The witness files differ, so this ranks the probe run and not your document.
CSV to JSON: 110 bytes in under a tenth of a second.
YAML to JSON: 110 bytes in under a tenth of a second.
DOCX to JSON: 1,722 bytes in 0.1 seconds.
HTML to JSON: 2,058 bytes in under a tenth of a second.
MD to JSON: 1,726 bytes in under a tenth of a second.
What we will not pretend about TXT to JSON
A TXT file over 25 MB is refused before the upload finishes rather than after it, so you do not wait for a rejection.
A TXT to JSON 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 TXT to JSON 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 JSON 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 TXT file goes through LibreOffice or calibre, both of which genuinely can.
One TXT file at a time, chosen in the browser. There is nothing else to set up and nothing else on offer.
TXT to JSON: what people ask
What actually converts my TXT file to JSON?
pandoc does it, in two passes, on a machine we rent and watch. Not a browser trick and not somebody else service: the TXT file is uploaded once, pandoc runs once, the JSON comes back, and neither file is kept afterwards.
How long does TXT to JSON take?
On the file the probe used, pandoc took under a tenth of a second and wrote 1,343 bytes of JSON. That is one real measurement on one real TXT file, not an average and not a promise about yours: a larger TXT takes longer, and past 60 seconds the run is stopped.
What do I lose going from TXT to JSON?
The one to know about first: The presentation layer. pandoc does not translate the TXT file into JSON, 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 TXT file still tables in the JSON?
No, and that is a property of JSON rather than a defect of this path. JSON cannot hold a table, so a TXT file built around one is the wrong candidate for this pair.
Is TXT to JSON free?
There is a free allowance every month, and one TXT to JSON 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 JSON.