Start with the file you actually have
A useful list often starts as an untidy text file: copied notes, an export from a system you manage, or addresses collected with permission. The first job is to identify the email-shaped strings without carrying over labels, timestamps and repeated entries. Extraction is a formatting task. It does not prove that an address exists, belongs to the person you expect, or can receive mail.
Extract and inspect
Open the Email Extractor from TXT. Paste the text or choose a TXT file. The tool scans locally in your browser and returns one unique address per line. It compares addresses in lowercase to remove ordinary duplicates. This is convenient for most contact lists, although a rare mail system may treat the local part before the @ differently.
Before saving the result, inspect a sample from the beginning, middle and end. Check for punctuation accidentally included next to an address, misspelled domains, and example addresses from documentation. A pattern-based extractor cannot understand the context of every match. If your source contains placeholders, remove them before using the list.
Separate extraction from verification
A syntactically plausible address is not a verified inbox. A domain may be offline, accept all recipients, or reject messages later. Do not label an extracted list “100% valid.” If delivery matters, use an appropriate verification process and keep an unknown category for addresses that cannot be confirmed. Avoid repeated connection tests against mail servers you do not administer.
Keep the original
Save the extracted output under a new filename. Keep the original file until you have checked that important entries were preserved. When several files overlap, combine their extracted outputs and use the Duplicate Line Remover once more. Trim whitespace so invisible spaces do not make identical lines appear different.
Respect the purpose of the data
Finding an address inside a file does not grant permission to contact its owner. Use your list for the purpose for which it was obtained and follow applicable consent and unsubscribe requirements. When sharing a report, consider masking contact details with the CSV Privacy Masker rather than distributing a raw contact list.
A simple finishing check
- One address per line, with no labels or extra columns.
- No repeated entries after whitespace cleanup.
- No obvious placeholders or accidental matches.
- An original copy kept for comparison.
- A clear reason and permission for using the data.
Small checks like these make the output easier to use and reduce the chance of turning a formatting mistake into a bigger workflow problem.