Extract Emails from Text (Regex + Free Online Tool)

You have a wall of text—maybe a document, a webpage, or log files—and you need to extract all the email addresses from it.

Manually finding them? Tedious and error-prone.

This guide shows you the fastest way to extract emails from any text, plus the regex patterns behind it.

Quick Solution: Extract Emails Online

The fastest way to extract emails:

Go to CleanTextLab's Email Extractor
Paste your text
Get all email addresses instantly
Export as TXT, CSV, or copy to clipboard

No signup. No ads. Works offline.

Example: Extracting Emails

Input text:

Contact us at support@example.com for help.
Sales inquiries: sales@company.org
John's email is john.doe@email.co.uk
Send feedback to feedback+test@gmail.com

Extracted emails:

support@example.com
sales@company.org
john.doe@email.co.uk
feedback+test@gmail.com

The Email Extractor finds all valid emails, including:

Subdomains (email@sub.domain.com)
Plus addressing (email+tag@gmail.com)
Country TLDs (.co.uk, .com.au)
Dots and hyphens in local parts

The Regex Behind Email Extraction

Basic Email Regex

[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}

Breakdown:

[a-zA-Z0-9._%+-]+ – Local part (before @)
@ – The @ symbol
[a-zA-Z0-9.-]+ – Domain name
\. – Literal dot
[a-zA-Z]{2,} – TLD (com, org, co.uk)

More Robust Regex (RFC 5322 Compliant)

(?:[a-z0-9!#$%&'*+/=?^_`{|}~-]+(?:\.[a-z0-9!#$%&'*+/=?^_`{|}~-]+)*|"(?:[\x01-\x08\x0b\x0c\x0e-\x1f\x21\x23-\x5b\x5d-\x7f]|\\[\x01-\x09\x0b\x0c\x0e-\x7f])*")@(?:(?:[a-z0-9](?:[a-z0-9-]*[a-z0-9])?\.)+[a-z0-9](?:[a-z0-9-]*[a-z0-9])?|\[(?:(?:25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?)\.){3}(?:25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?|[a-z0-9-]*[a-z0-9]:(?:[\x01-\x08\x0b\x0c\x0e-\x1f\x21-\x5a\x53-\x7f]|\\[\x01-\x09\x0b\x0c\x0e-\x7f])+)\])

Pro tip: Don't write this yourself. Use the Email Extractor tool which handles edge cases correctly.

Extract Emails in Code

JavaScript

const text = "Contact support@example.com or sales@company.org";
const emailRegex = /[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}/g;
const emails = text.match(emailRegex);
console.log(emails);
// ['support@example.com', 'sales@company.org']

Python

import re

text = "Contact support@example.com or sales@company.org"
pattern = r'[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}'
emails = re.findall(pattern, text)
print(emails)
# ['support@example.com', 'sales@company.org']

PHP

$text = "Contact support@example.com or sales@company.org";
preg_match_all('/[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}/', $text, $matches);
print_r($matches[0]);
// ['support@example.com', 'sales@company.org']

Bash (grep)

grep -oE '[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}' file.txt

Common Use Cases

1. Building Contact Lists

Extract emails from:

Business directories
LinkedIn exports
Conference attendee lists
Email threads

2. Data Cleaning

Clean messy CRM data:

Extract valid emails from notes fields
Find emails in unstructured text
Validate email formats

3. Log Analysis

Find emails in:

Server logs
Application logs
Error reports

4. Web Scraping

Extract emails from:

Scraped web pages
PDF documents
Exported data

5. Document Processing

Extract from:

Word documents
PDF files (copy text first)
Spreadsheets

Features of the Email Extractor Tool

Automatic Deduplication

Extracts unique emails only. No duplicates.

Domain Filtering

Filter emails by domain:

Only @gmail.com addresses
Exclude certain domains
Group by domain

Export Options

CSV – Open in Excel/Sheets
TXT – Plain text list
JSON – For programmatic use
Excel – Direct download

Validation

Each extracted email is validated for proper format.

Edge Cases Handled

The Email Extractor correctly handles:

Email Type	Example	Status
Standard	user@example.com	✅ Extracted
Subdomain	user@mail.example.com	✅ Extracted
Plus addressing	user+tag@gmail.com	✅ Extracted
Country TLD	user@example.co.uk	✅ Extracted
Numbers	user123@example.com	✅ Extracted
Dots in local	first.last@example.com	✅ Extracted
Hyphens	user-name@example.com	✅ Extracted

What's NOT a Valid Email?

These are rejected:

Invalid Format	Reason
user@example	Missing TLD
@example.com	Missing local part
user @example.com	Space in address
user..name@example.com	Double dots
.user@example.com	Starts with dot

Privacy & Security

Your Data is Private

All processing happens in your browser. The text you paste:

Never leaves your device
Is not stored anywhere
Is not sent to any server

Ethical Use

Please use extracted emails responsibly:

✅ Your own contact lists
✅ Data cleaning tasks
✅ Research with consent
❌ Spam or unsolicited emails
❌ Selling email lists

Frequently Asked Questions

How many emails can it extract?

No limit. The tool handles thousands of emails efficiently.

Does it validate emails?

Yes, format validation is included. It won't extract invalid patterns.

Can it extract from PDFs?

Copy text from the PDF first, then paste into the tool.

Can I filter by domain?

Yes, you can filter results to show only specific domains.

Is it free?

Completely free. No signup required.

Alternative Methods

Using grep (Command Line)

grep -oE '[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}' file.txt | sort -u

Pro: Works offline. Con: Regex can miss edge cases.

Using Excel

Not recommended. Excel doesn't have built-in email extraction.

Using Python Script

Good for automation but requires coding knowledge.

Using CleanTextLab (Recommended)

No installation
Handles all edge cases
Export to any format
Try it free

Related Tools

Remove Duplicates – Deduplicate email lists
Regex Tester – Test your own patterns
URL Extractor – Extract URLs from text

Conclusion

Extracting emails from text is a common task that shouldn't require coding. With CleanTextLab's Email Extractor:

Paste any text
Get all emails instantly extracted
Export as CSV, TXT, or JSON
No duplicates, properly validated