Collect email addresses from a passage and return a unique list. Clean up contact notes or a message archive without copying each match by hand.
How to use
Paste the source text. Review the extracted addresses, then copy the list with one address per line. Exact duplicate matches are removed.
Example
Contact [email protected], then repeat [email protected] elsewhere. The result contains that exact address once.
FAQ
Does it verify mailboxes?
No. It finds address shaped text, not working inboxes. Some international formats are outside the pattern. Use contact data only with permission.
Related tools
A practical task
Extract from material you are entitled to process, such as your own support archive. After extraction, check obvious punctuation around addresses and preserve the source when an address needs context. A list of strings is not a verified contact database.
Another useful question
Can I use the list for unsolicited mail?
Extraction does not establish permission to contact people. Confirm the basis for using the addresses and respect the recipients' communication preferences.
Details for interpreting the result
| Detail | Explanation |
|---|---|
| Extracted values | Extraction identifies text that matches a rule. It does not establish that the result is a real person, a working address, or a valid business value. Validate the extracted data according to its intended use. |
| Pattern and literal search | A literal search matches the typed characters. A regular expression describes a pattern with operators. Characters such as dots and brackets have different roles in the two systems, so choose the right search mode. |
| Case sensitivity | Case sensitive matching distinguishes capital and lowercase letters. Ignoring case merges some of those distinctions, but it does not turn different spellings or word forms into the same term. |
| Literal separators | A literal separator is an exact sequence of characters, including any spaces. A comma and a comma followed by a space are different separators. Match the source consistently before extracting or exchanging fields. |
| Similar looking text | Two strings can look identical but use different Unicode sequences. An accented letter can be stored directly or as a letter plus an accent. Visual similarity alone does not establish byte equality. |
| Column headers | Headers provide names for columns; they are not extra data values. Keep their order aligned with each row. When building objects, duplicate header names create ambiguity about which value belongs to a key. |
| Strings and values | The JSON string "12" differs from the number 12, and "false" differs from false. Type changes affect comparisons and imports. Keep identifiers as strings when their leading zeros or exact digits matter. |