JSON to CSV Converter — Flatten, Escape, Export

Real-world use cases

• Hand an API JSON dump to a non-technical teammate as a spreadsheet

  Your `/api/orders` endpoint returns a JSON array and a colleague in ops needs it in Google Sheets. Copy the response body, paste it into the input, leave the delimiter on comma and the header row on. The tool reads the union of keys across all orders — so even orders that carry an optional `discount_code` field line up under one column with blanks where it's absent. Download the .csv, drag it into Sheets, done. No "can you export this for me" thread.

• Flatten a nested config or settings object for diffing

  You have two environments' settings as nested JSON and want a flat, line-by-line comparison. Paste each one with "Flatten nested objects" on — `{"db":{"pool":{"max":20}}}` becomes a `db.pool.max` column with value `20`. Now each setting is one row/column you can eyeball or drop into a spreadsheet to diff side by side, instead of squinting at two deeply indented JSON blobs.

• Export survey or form responses with multi-select answers

  A form library hands you responses where multi-select questions are JSON arrays: `"interests": ["design", "code", "ops"]`. Switch "Array values" to "Join with" and set the separator to a comma or pipe. Each respondent becomes one clean row and the multi-select reads as `design | code | ops` in a single cell — exactly the shape analysts expect when they pivot the table, instead of an unreadable JSON fragment.

• Get a JSON list into Excel without the Chinese turning to mojibake

  You're on Windows, the JSON has Chinese product names, and a naive export shows `鍟嗗搧` garbage when Excel opens it. Paste the JSON, tick "Add UTF-8 BOM", and hit Download .csv. The BOM forces Excel to read the file as UTF-8 so `商品名称` renders correctly. This single checkbox is the difference between a usable export and ten minutes of Data → From Text encoding-wizard fiddling.

• Build a quick CSV fixture for a test from sample JSON

  You're writing a test that ingests a CSV and you already have the equivalent sample as JSON. Paste it, pick the delimiter your parser uses (tab if your importer is tab-separated), and copy the output straight into your fixture file. The RFC 4180 escaping is handled, so a sample value like `he said "hi", ok` comes out correctly quoted and your test exercises the real edge cases instead of toy data.

Common pitfalls

• Wrapping the JSON array in an extra object. If you paste `{"data": [ ... ]}` the tool treats the top-level object as a single row, not the inner array. Paste the array itself (`[ ... ]`), or if you only have the wrapper, drill into the `data` key first. A top-level array of objects is the shape that maps cleanly to CSV rows.

• Forgetting the UTF-8 BOM for Excel and blaming the tool for "broken" Chinese. The CSV bytes are correct UTF-8 either way — Excel just mis-guesses the encoding without the BOM. Google Sheets, Numbers, and text editors read it fine without the BOM, so only tick the box when the target is Excel on Windows.

• Choosing "Join with" for arrays that contain objects and expecting a flat string. Arrays of objects can't be losslessly joined into one cell, so the tool keeps them as JSON regardless of the join setting. If you truly need those nested fields as columns, restructure the JSON so each object's fields live at the row level before converting.

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