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CSV looks simple until a field contains a comma, a quote, or a line break - at which point a naive split-on-comma parser silently produces the wrong number of columns. This uses a proper quoted-field-aware CSV parser in both directions: CSV to JSON records, or a JSON array back to CSV, with automatic type detection for numbers and booleans.
When you'd use this
Turning a spreadsheet export into JSON for a script or API request, or flattening a JSON array of objects back into a CSV that opens cleanly in a spreadsheet.
Common errors
A row that ends up with the wrong number of fields almost always has a comma inside an unquoted value - CSV requires quoting any field that contains the delimiter, a quote character, or a line break, and a source export that skips quoting will parse incorrectly no matter how good the parser is.
A semicolon-delimited file (common from European spreadsheet software) needs the delimiter switched from comma before parsing, or every row collapses into a single field.
Frequently asked questions
How does automatic type detection decide what's a number vs. a string?
A cell that's entirely digits (with an optional decimal point) becomes a number, "true"/"false" becomes a boolean, and everything else stays a string - turn detection off if you specifically need values like a zip code or an ID to stay as text even though they look numeric.