Need to feed CSV into your API or front-end? CSV to JSON in one click — paste your rows, hit Convert and download a typed JSON array. Runs in your browser, nothing uploaded.
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CSV is great for spreadsheets but awkward to consume from code: it has no types, no nesting, and quoting rules that catch out naive parsers. A CSV to JSON converter turns each row into an object using the header row as property names, so the data is ready to feed straight into an API, a NoSQL store, or a typed front-end.
JSON Pretty parses input per RFC 4180 — quoted commas, escaped quotes and embedded line breaks all survive — and infers obvious types (numbers, booleans, empty cells) so the JSON is closer to what your application actually expects. Once converted, drop the result into our JSON editor for a tree view with search and copy-by-path. New to JSON? Read the beginner's guide first.
The same rows, before and after conversion:
id,user,active
1,alice,true
2,bob,false
3,carol,true[
{ "id": 1, "user": "alice", "active": true },
{ "id": 2, "user": "bob", "active": false },
{ "id": 3, "user": "carol", "active": true }
]Convert CSV to JSON in three simple steps — no account needed
Paste CSV rows (header line first), or click "Upload file" to load a .csv from your device.
Press Convert. The header row becomes property names, each row becomes an object, and obvious types are inferred automatically.
Copy the JSON to the clipboard, or download a .json file ready for your API, database or front-end code.
Why bother converting in the first place? A few reasons CSV to JSON is usually the right move.
Format any JSON response and explore it in a clean tree view — right where you open it, no copy-paste.
Reverse direction — convert a JSON array of objects into CSV rows.
Open the converted JSON in a full editor with tree view, search and copy-by-path.
Parse YAML configs into clean indented JSON ready for APIs and code.
Parse XML documents into a clean JSON tree ready for modern code.
Generate a Draft 2020-12 JSON Schema from a sample document for validators and code generators.
Convert JSON into clean YAML ready for Kubernetes, Docker Compose or CI configs.
It reads CSV rows, treats the first line as the header, and emits a JSON array where every row becomes an object keyed by the headers. Cells are decoded according to RFC 4180 quoting rules, so commas, line breaks and quotes inside values survive intact.
Add a header line before pasting — even a placeholder like "a,b,c" will work and produces objects with those property names. Without headers, every row would have to be returned as an array, which is rarely what callers want.
Cells that look like numbers, booleans or empty values are coerced automatically: "42" becomes 42, "true" becomes true, and a blank cell becomes null. Cells that look like JSON objects or arrays are parsed back into real nested structures — so a round-trip through the matching JSON to CSV converter preserves the original shape. Everything else stays as a string. If you need a value to remain a string (zip codes, IDs with leading zeros), quote it in the CSV.
Yes. RFC 4180 quoting is fully supported: a cell wrapped in double quotes can contain commas, line breaks and escaped double quotes (""). The output JSON preserves the original text exactly.
Yes. The byte-order mark some editors prepend to CSV files is stripped automatically before parsing, so it never leaks into the first property name.
Comma is the default. If your file uses a different delimiter, find-and-replace it with a comma before pasting. A delimiter picker is on the roadmap.
Yes. Parsing happens entirely in your browser — nothing is sent to a server, nothing is stored.
Yes. The parser runs in the browser and processes multi-megabyte files comfortably on a modern device. For files in the hundreds of megabytes, a streaming command-line tool is a better fit.
A JSON array where each element is an object. Property names come from the header row, and values are typed when possible. The output is indented two spaces so it is human-readable.
Yes — use the matching JSON to CSV converter for the reverse direction.
Short rows leave the trailing properties undefined. Extra cells beyond the header are reported as a parse error so you can fix the input rather than silently dropping data.