Logfmt Converter

logfmt · JSON · NDJSON · CSV converter

Paste a block of log lines, pick a target format, and convert it. Unlike most logfmt tools, this one converts in both directions: it parses logfmt and writes it, so you can take JSON, NDJSON (JSON Lines), or a CSV export and turn it back into key=value log records. Nothing is uploaded — the converter is compiled to WebAssembly and runs locally in your browser tab.

How it works

• From — leave it on Auto-detect and the input is sniffed: text starting with [ is a JSON array, { is a single JSON object (or NDJSON when every line is its own JSON value), a leading key=value token means logfmt, and anything else is parsed as CSV. Force a source format if detection guesses wrong on an unusual sample.
• To — choose logfmt, JSON (a single array), NDJSON / JSONL (one compact record per line), or CSV.
• CSV delimiter — comma, semicolon, tab, or pipe. It applies to CSV on both sides, so you can re-delimit a file by setting From and To to CSV.
• Detect types — unquoted logfmt and CSV values become JSON numbers, true/false, and null. Quoted values always stay strings, so status="200" survives as text. Values that would not round-trip — leading zeros like 007, a leading + — stay strings too, keeping zip codes and phone numbers intact. Turn the option off to keep every value as a string.
• Pretty-print — indent the JSON target. NDJSON is always one compact record per line, so this option does not affect it.
• Flatten — when writing a flat format (logfmt or CSV), expand nested objects and arrays into dot-notation keys: {"user":{"id":7}} becomes user.id=7 and a list becomes tags.0, tags.1. Turn it off to write nested values as compact JSON strings instead.
• Keep only these fields — a comma-separated allow-list that both selects and orders the output fields, e.g. ts,level,msg. Leave it blank to keep every field in first-seen order.

logfmt output follows the de-facto go-logfmt rules: key=value pairs separated by a single space, one record per line, and values double-quoted whenever they contain a space, an =, a quote, or a control character, with \", \\, \n, \r, and \t escapes.

Worked example

Input logfmt (two records):

ts=2026-08-13T10:04:00Z level=info msg="user signed in" user_id=42 ok=true
ts=2026-08-13T10:04:07Z level=warn msg="slow query" dur_ms=812 ok=false

To JSON →

[{"ts":"2026-08-13T10:04:00Z","level":"info","msg":"user signed in","user_id":42,"ok":true},{"ts":"2026-08-13T10:04:07Z","level":"warn","msg":"slow query","dur_ms":812,"ok":false}]

To CSV → the header is the union of every record's keys, in first-seen order, with a blank cell where a record has no such field:

ts,level,msg,user_id,ok,dur_ms
2026-08-13T10:04:00Z,info,user signed in,42,true,
2026-08-13T10:04:07Z,warn,slow query,,false,812

Going the other way, [{"level":"error","msg":"disk full","retries":2}] as JSON → logfmt gives level=error msg="disk full" retries=2 — the message is quoted because it contains a space.

Limits & edge cases

• Up to 1,000,000 characters of input per run. Larger logs are rejected with a clear message rather than hanging the tab; split them first.
• Records must be objects. A JSON array of scalars ([1,2,3]) or a CSV file with only a header row is an error, not a silent empty result.
• A bare logfmt key with no = is treated as a boolean flag: verbose msg=hi parses to {"verbose":true,"msg":"hi"}.
• null and the empty string are kept apart when writing logfmt: a null writes as a bare key= and an empty string as key="", so a JSON → logfmt → JSON round trip with Detect types on preserves the difference.
• Keys that logfmt cannot express — ones containing whitespace, =, or a quote — are sanitised to _ (a bad key field becomes bad_key) rather than being dropped silently.
• If the same key appears twice on one logfmt line, the last value wins and the field keeps its first position.
• Blank lines are ignored, and a trailing \r from Windows line endings is stripped.

Related conversions

This tool exists for the logfmt legs of the matrix — the JSON ↔ NDJSON ↔ CSV legs work here too, and a dedicated tabular converter covers the CSV/TSV corners (header-less rows, TSV) that log records do not need.

FAQ