Regex Generator from Sample Strings — Deterministic, No AI
Free regex generator from sample strings — paste 2-5 examples, get a generalized regex with character classes and length quantifiers. No AI, no signup.
PDFFlare's regex generator from sample strings is a free, deterministic, browser-based tool that turns example data into a working regex. Paste 2-5 sample strings (emails, dates, IDs, log timestamps, postal codes — whatever you want to match), click Generate, and the algorithm emits a regex with the right character classes and length quantifiers. No AI, no remote API, no signup. Same input always produces the same output, so the tool is safe to use in regulated environments and easy to share with teammates.
Use it as a regex generator online for the patterns you hit weekly, a regex builder from text where you have the data but not the rule, an auto regex generator that beats writing patterns from memory, a regex inference tool that surfaces shape mismatches in your sample set, or a no-AI alternative to ChatGPT-style prompt-driven regex generation. After generating, jump straight into PDFFlare's Regex Tester to verify against more data, switch flags, and copy paste-ready code for 10 languages. Pairs with the JWT Decoder for validating token shapes, and UUID Generator for sample IDs to feed in.
Acts as a generate regex from examples engine, a regex from sample data extractor, and a pattern induction regex tool — all in one page, all client-side, all free. Works for any regularly-shaped data: log file timestamps, ticket IDs, phone numbers in fixed format, ZIP codes, hex hashes, MAC addresses, semver strings.
How does this generator work?
1. Tokenize each sample.The algorithm walks each sample character by character, grouping consecutive letters into one “letter run,” consecutive digits into one “digit run,” and treating each non-alphanumeric character (like @, ., -) as a literal anchor.
2. Verify shape. All samples must produce the same sequence of run types and the same literal anchors in the same order. If sample 2 has an @ where sample 1 has a ., the generator reports a shape mismatch and stops — better to fail loudly than emit a wrong regex.
3. Generalize. For each run position across samples, the algorithm computes the union character class (e.g., if all samples are lowercase letters → [a-z]; if mixed case → [a-zA-Z]; if digits → \d) and the min/max length range (emitted as {N} if all samples have the same length, or {min,max} if they vary).
4. Emit anchored regex.The result is a ready-to-use regex that matches every input sample exactly, plus other strings of the same shape. Click “Open in Regex Tester” to verify against more data and refine with custom flags.
Limitations:No AI, no NLP — pure structural induction. Works great for emails, dates, IDs, log timestamps, postal codes, and other regularly-shaped data. Doesn't work for free-form text where length varies wildly or where the same logical field can have multiple shapes.
How to Generate Regex from Samples
Paste 2-5 sample strings (one per line)
Drop in example strings of what you want to match — emails, dates, IDs, log timestamps, postal codes. The more samples you paste (covering edge cases like longest/shortest), the tighter the generated regex. Pick from 6 built-in example sets if you want to see how it works first.
Click Generate regex
PDFFlare tokenizes each sample into letter/digit/alnum runs separated by literal punctuation, verifies all samples share the same structural shape, then emits a regex with the right character classes and {min,max} length quantifiers. Pure pattern induction — deterministic, no AI required, runs entirely in your browser.
Verify the sample match check
PDFFlare runs the generated regex against your originals — every sample should show a green ✓. If any show ✗, the regex needs refinement (paste a tighter or more representative sample set). The match check is anchored (^...$) so partial matches don't count as success.
Open in Regex Tester to refine
Click Open in Regex Tester — PDFFlare loads the generated pattern into the full tester with live highlighting, capture groups, code output for 10 languages, ReDoS detection, and substitution mode. Test against real data, tweak anchors and quantifiers, copy the final code into your project.
When Do You Need a Regex Generator from Sample Strings?
Extracting structured fields from log files: You have a 50 MB log dump and need every timestamp, every request ID, every error code. Grep one line out, paste 3-5 examples into the regex generator, get a pattern that matches the shape, refine in the tester, run on the real file. Faster than writing the regex from scratch, and the generated min/max ranges catch edge cases (request IDs of varying length) that hand-written regex usually misses.
Validating user-input data with no published spec: Internal APIs that emit IDs in a specific shape (your company's ticket IDs, internal SKUs, batch numbers) often have no documented regex. Paste 5-10 real examples from your database, generate the regex, use it for validation. The generator's shape-mismatch error is a feature: if your sample set has outliers, the algorithm tells you instead of silently producing a regex that doesn't match them.
Migrating data between systems with different formats: Source database stores phones as (415) 555-1234; destination expects +14155551234. Generate a regex that captures the source format, generate another that captures the destination, write a transform between them. Pair with the substitution mode in the Regex Tester for the actual conversion.
Reverse-engineering a regex from a code review: A teammate's PR contains ^[A-Z]{3}-\d{4}-[a-z0-9]{6}$ with no test cases. What does it match? Generate examples in your head, paste them into the regex generator, see if you can produce the same pattern. If not, the original regex is too lax or the samples you generated don't cover its intent — both are red flags worth raising in code review.
Why Use PDFFlare's Regex Generator?
Deterministic Pattern Induction
Same samples always produce the same regex. No AI, no LLM API call, no inconsistency between runs. Algorithm: tokenize each sample into letter/digit runs, verify all samples share the same shape, generalize each run into character class + length quantifier. Pure code, no model.
Live Sample Match Verification
After generating, PDFFlare runs the regex against every input sample and shows ✓ or ✗ per sample. The regex either matches all your originals or the tool tells you exactly which one fails — no silent failures, no “trust the AI” mode.
100% Browser-Based
Tokenization, shape comparison, and regex emission all run client-side. No upload, no remote service. Open DevTools → Network and you'll see zero requests. Safe for samples drawn from confidential data — production logs, internal databases, PII.
Direct Hand-Off to Regex Tester
Click “Open in Regex Tester” — PDFFlare deep-links to the full Regex Tester with the generated pattern pre-loaded. Refine with custom flags, run against larger test strings, and copy paste-ready code for 10 programming languages.