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Extract phone numbers

Pull three families of phone number out of text: international (+33 6 12 34 56 78, 0033…), French national (06 12 34 56 78, 01.23.45.67.89) and North American ((555) 123-4567). Dates and long reference numbers are left alone. Takes a whole file, so a long log does not have to go through the clipboard.

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Extract numbersPull every number out of a block of text — grouped thousands stay one number (1,234.56 or 1 234,56), a hyphen inside a reference is not a minus sign, and you can normalise what comes out. Works on a pasted block or on a file you drop in.Extract text between delimitersPull out every piece of text that sits between a start and an end marker. Takes a whole file, so a long log does not have to go through the clipboard.Extract domainsPull the domain names out of URLs and email addresses in your text. Paste the text or drop the file; nothing leaves the page either way.Extract emailsPull every unique email address out of a block of text. Works on a pasted block or on a file you drop in.Extract IP addressesPull every valid IPv4 and IPv6 address out of a block of text. 999.1.1.1, 1.2.3.4.5 and 01.2.3.4 are not addresses and are skipped; compressed IPv6 such as ::1 is found. Drop a file in rather than pasting it — it is read in your browser and never uploaded.Extract URLsPull every unique link out of a block of text. Drop a file in rather than pasting it — it is read in your browser and never uploaded.ASCII code converterConvert text to ASCII/Unicode code points and back.Number base converterConvert numbers between all 35 bases, exactly, with two's complement.

Extract phone numbers is free to use as often as you like, directly from this page. It covers +33 6 12 34 56 78, 0033 — adjust any of them and the result follows immediately.

How to use it

  1. Open the tool — no signup or install needed.
  2. Enter your input or adjust the available options.
  3. Get your result instantly, then copy or download it.

Frequently asked questions

What does Extract phone numbers do?

Pull three families of phone number out of text: international (+33 6 12 34 56 78, 0033…), French national (06 12 34 56 78, 01.23.45.67.89) and North American ((555) 123-4567). Dates and long reference numbers are left alone. Takes a whole file, so a long log does not have to go through the clipboard.

What does it take into account?

It factors in +33 6 12 34 56 78, 0033. Change any of them and the output follows immediately.

When would I actually use this?

Getting usable data out of something that was never meant to be parsed: pulling every address out of a pasted thread, turning a column of lines into a JSON array or an SQL IN clause, renaming a hundred identifiers from snake_case to camelCase in one pass.

What is the most common mistake?

Trusting an extraction to be exhaustive. A pattern that catches every address in the sample will still miss the one wrapped across a line break, the one written with a display name, and the one an email client turned into a link — count what came out against what you expected before you use the list.

How is Extract phone numbers different from Extract numbers?

They sit next to each other but answer different questions: Extract numbers is the one to open when you need it to pull every number out of a block of text — grouped thousands stay one number (1,234.56 or 1 234,56), a hyphen inside a reference is not a minus sign, and you can normalise what comes out. Works on a pasted block or on a file you drop in. Pick whichever matches what you're starting from — both are free.

Is there a tool for the next step?

Extract text between delimiters is the closest one after this: Pull out every piece of text that sits between a start and an end marker. Takes a whole file, so a long log does not have to go through the clipboard.

What else is worth having open alongside it?

Extract domains and Extract emails — they come up in the same task often enough to be worth a second tab.

Where do the figures come from?

Extraction runs on patterns, not on a parser: it recognises the common shapes of an address, a URL or an IP rather than validating them against their specification. That is the right trade for a paste, and the wrong one for input you are about to store.

Further reading

All guides →
ExplainerExtracting Every Email Address or URL from a Block of TextA URL at the end of a sentence keeps the full stop; an email address at the end of the same sentence does not. An accented first name in an address comes back truncated. Every case here was run through the tools and the exact output is reported.How-toRegex Basics: A Beginner's GuideA regular expression is a pattern for matching text. Here are the building blocks — character classes, quantifiers and anchors — with a worked example.ExplainerBig O Notation for Beginners: O(1), O(n), O(n squared), and O(log n) ExplainedBig O describes how an algorithm's work grows as input grows. Here is what O(1), O(n), O(n squared), and O(log n) mean and why the difference matters.ExplainerWhat Is UTF-8 and Unicode? Code Points, Byte Encoding, and Why UTF-8 WonUnicode assigns every character a code point; UTF-8 encodes those code points in one to four bytes. Here is how it works and why it beat the alternatives.ExplainerHow Subnet Masks Work: CIDR, Network Bits, and Usable HostsUnderstand how a subnet mask splits an IP address into network and host parts, what /24 means, and how to count usable hosts.How-toHow to Read Binary and Convert It to Decimal and HexLearn how binary place values work and convert binary to decimal and hexadecimal by hand, with clear worked examples.