Add your NPY file
Drop one or more .npy files onto the converter above, or browse for them. They load into browser memory only — nothing is uploaded, so there is no size-based pricing and no server queue.
NPY to JSON
Converting a .npy font to .json repackages the same glyphs and metrics for a different delivery target. Free, private, and validated — the file never leaves your browser.
Private for supported formats — processed in your browser
Runs on your deviceConvert supported files
Drop NPY files here
Batch files can each use a different output. Nothing uploads for local conversions.
Working inputs include camera RAW, browser-local audio/video, PDF, CBZ/CBR comics, office documents, ebooks, markup, 3D models, structured text, images, and archives.About converting NumPy array to JSON data
Converting a .npy font to .json repackages the same glyphs and metrics for a different delivery target. An .npy file is a single NumPy array saved to disk: a short header describing the element type, the shape and the memory order, then the raw array bytes. It is deliberately the simplest thing that can round-trip an array exactly, and the specification fits on one page.
A .json file holds JavaScript Object Notation: nested objects, arrays, strings, numbers, booleans, and null written in a strict text syntax. It is the default data language of the web — most APIs speak nothing else. For this route the practical draw is parsers ship in the standard library of essentially every language and readable by humans and machines alike — balanced against no comments — a perpetual annoyance for configuration files, which is worth knowing before you commit a large batch.
Why convert NPY to JSON?
The practical trigger for this conversion is usually a mismatch: with .npy, uncompressed, so large arrays are large files. Switching to .json buys you parsers ship in the standard library of essentially every language, which is why it is the better fit for rEST and HTTP API request and response payloads. Because the conversion runs locally, trying it costs nothing but a few seconds of compute on your own machine.
NPY vs JSON at a glance
| Aspect | NumPy array (.npy) | JSON data (.json) |
|---|---|---|
| Format type | Lossless — every pixel or sample is preserved exactly | Text-based — characters and structure, so there is no visual quality loss |
| How it stores data | the file begins with the magic byte 0x93 followed by 'NUMPY' and a two-byte version | exactly six value types; no dates, no comments, no trailing commas — the strictness is deliberate |
| Strongest at | saving model weights, embeddings or intermediate results between processing steps | rEST and HTTP API request and response payloads |
| Weak spot | uncompressed, so large arrays are large files | no comments — a perpetual annoyance for configuration files |
Pick JSON as the output
Select .json in the output menu next to each file. The menu only offers targets this engine can genuinely produce, so if JSON is selectable, the route is real and validated.
Convert on your device
Press Convert. The font tables are parsed and rewritten locally with fonteditor-core; glyph outlines, hinting, and kerning survive the trip.
Verify and download
Each result is signature-checked before the download unlocks, so a failed encode can never masquerade as a valid JSON file. Outputs keep the original filename with the .json extension.
NPY to JSON questions, answered
Will converting NPY to JSON lose quality?
There is no visual quality to lose — npy is lossless-oriented and json is text-oriented, so the question is structural fidelity. Text, ordering, and basic structure are preserved; complex layout, embedded objects, and styling beyond the target's model are simplified.
Is it private to convert NPY files here?
Yes — the .npy file is processed inside your browser tab and never uploaded. The font tables are parsed and rewritten locally with fonteditor-core; glyph outlines, hinting, and kerning survive the trip. Close the tab and the file is gone from memory.
Where will the JSON file work?
Browsers parse it natively through JSON.parse, every mainstream language bundles support, and most editors validate and highlight it out of the box. Viewing a raw .json file is possible in any text editor or browser tab.
Will the JSON file be bigger or smaller than my NPY?
It depends on the content: exactly six value types; no dates, no comments, no trailing commas — the strictness is deliberate. Convert one representative file first and compare before batch-processing a large set.
What happens to the metadata in my NPY file?
In .npy, the dtype, shape and storage order are read and reported; the format itself has no field-name or unit channel, so CSV and spreadsheet targets receive positional column headings. Re-encoding through the browser pipeline does not carry embedded metadata into the output, which doubles as a privacy scrub — check the exported file if you specifically need tags preserved.
Can I convert JSON back to NPY?
Yes — the reverse route exists as a separate tool. Bear in mind that round-tripping .npy → .json → .npy is not a perfect undo when any lossy step is involved; keep your original if fidelity matters.