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csv · capture groups · downloadable

Turn regex matches into downloadable CSV

Capture groups become columns, every match becomes a row. Named groups produce friendly headers. Runs locally.

Regex Extract to CSV
Rows
3
matches
Columns
2
groups
Bytes
71
csv
Status
ready
live
Flags
input · pattern + text (g flag forced)
//g
output · csv
name,email
alice,alice@example.com
bob,bob@test.org
carol,carol@demo.io
Quick Start

How to extract regex matches as CSV

Capture groups become columns. Named groups give friendly headers, numbered groups become group_1, group_2, etc.

  1. 01

    Pattern with groups

    Add () for unnamed, (?<name>...) for named. Named groups yield better CSV headers.

    Patterns compile through the JavaScript RegExp constructor, so syntax errors surface immediately and engine quirks like Unicode property escapes (\p{L}) work when the u flag is on.

    patternECMAScriptliterallive
    input · literalregex · regex
    (?<name>\w+)\s+<(?<email>[^>]+)>
    loaded · ECMAScriptPCRE · ready
  2. 02

    Drop sample text

    Each match becomes one row. g flag is forced so all matches are captured.

    Each flag character mirrors the ECMAScript literal: g enables iteration, i folds case, m anchors per line, s lets . match newlines, u unlocks proper Unicode, y is sticky, and d emits indices.

    flagsoptionsg · i · mlive
    config · optionssample · flags
    alice <alice@x.com>
    flags applied · liveECMA · live
  3. 03

    Read or download

    CSV is comma-separated with proper quoting for cells that contain commas or quotes.

    Watch for catastrophic backtracking on nested quantifiers — a common ReDoS source. The tool caps match counts to keep the page responsive on pathological patterns.

    matchgroupshighlightReDoS-safe
    run · outputcsv · matches
    name,email alice,alice@x.com
    matches · livegroups · live
  4. 04

    Copy or export

    Grab the output as JSON, CSV, or plain text — ready for your editor or pipeline.

    Copy writes via navigator.clipboard.writeText; downloads use a Blob and object URL, so nothing transits the network and the output is byte-identical to what you see on screen.

    copyexportclipboardblob
    export · exportedready · saved
    Copied
    ready to shipsuccess
Pro tips

Regex patterns that don't melt down

Use named groups

(?<year>\d{4}) reads better than $1 and survives reordering. Supported in ECMAScript 2018+.

Anchor strictly

Use ^/$ with the m flag when matching whole lines. Without anchors, partial matches sneak through.

Avoid catastrophic backtracking

Nested quantifiers like (a+)+ can explode. Run patterns through ReDoS Detector first.

Escape every literal

Backslash any meta character you want literally: \.\$\^\*\+\?\(\)\[\]\{\}\|\\.

Test edge cases

Empty string, single character, unicode, the maximum length you expect — write fixtures for each.

Patterns aren&rsquo;t parsers

Don’t parse HTML, JSON, or balanced parens with regex. Use a proper parser when the grammar is recursive.

Related toolsRegex Extract GroupsRegex Find AllRegex TesterRegex ReplaceRegex SplitRegex Cheatsheet
Use Cases

When to export as CSV

Turn unstructured text into a spreadsheet.

Scrape into a spreadsheet

Capture groups from text → import into Excel or Sheets. Compiles through the JavaScript RegExp constructor — engine quirks (Unicode property escapes, sticky matching, named groups) work when their flags are on. Error messages cite the exact position of any syntax issue.

ReDoS-safe

Build datasets

Turn semi-structured logs into a clean CSV. Pairs with the ReDoS detector to catch catastrophic backtracking before you deploy. A pattern that handles 1k-character input fine can become a denial-of-service vector on attacker-controlled 1M-character input.

ECMA-compliant

Quick reports

Generate a CSV of findings without writing code. Output exports as JavaScript, Python re, Java util.regex, .NET System.Text.RegularExpressions, PCRE, and POSIX — language quirks are highlighted on conversion so you don't ship a JS-only pattern to a Go service.

spec-grade

Audit lists

Confirm a CSV format matches your spec. Capture groups (named or numbered) round-trip cleanly into replacement strings, JSON output, or CSV extraction without re-typing. Backreferences ($1, ${name}) preserve semantics across languages.

cross-engine

ETL prototypes

Sketch an extract before scripting it. Test against edge cases — empty input, single character, max length, multibyte boundaries — to catch off-by-one and zero-length match bugs before they reach production.

test-ready

Bulk renames

Pull old/new pairs and feed them to your migration. All matching runs client-side so secret patterns never leave the browser. Useful when the pattern itself is sensitive (PII regexes, internal data formats, security filters).

production-ready
FAQ

Frequently asked questions

If any named group is present, headers use those names. Otherwise numbered groups become group_1, group_2, …
Yes — without it you'd only get one row. You can still add i, m, s, u.
Yes. Cells with commas, quotes, or newlines are double-quoted per RFC 4180.
Not directly — one match equals one row. To get per-group rows, post-process or use the Extract Groups tool for JSON.
No. The tool runs entirely in your browser — your pattern and sample text never leave the page.
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