5 Ways to Validate Phone Numbers with Regex

Validating phone numbers with regular expressions is a frequent challenge. We'll explore five different regex approaches, complete with code snippets, to tackle this. We will also examine the common pitfalls of these methods and see how Abstract API provides a more robust solution for handling them.

How to Implement Phone Number Validation in Regex

Regular expressions offer several ways to check phone number formats. Below are four distinct methods, from strict international standards to flexible, multi-step approaches for different validation needs.

E.164-Only Validation

This method validates numbers against the ITU E.164 standard. The pattern looks for a mandatory plus sign, a first digit that is not zero, and then between one and fourteen additional digits. This approach works for any country because it confirms the international format, not a specific national plan. A Stack Overflow discussion provides the pattern.

e164 = re.compile(r'^\+[1-9]\d{1,14}$')
if e164.fullmatch(raw): …

Free-Form International Validation

This pattern accommodates various international formats. It supports an optional country code of one to three digits, an optional trunk digit '1', and parentheses around the area code. It also permits spaces, dots, or hyphens as separators and allows for variable subscriber number lengths. This pattern is detailed in a phone regex list.

const intl = new RegExp(String.raw`^(\+\d{1,3}\s?)?…$`);
if (intl.test(raw)) { … }

Strict North American Numbering Plan Validation

This regex is for the North American Numbering Plan (NANP), used in the US and Canada. It allows for an optional "+1" prefix. The pattern ensures the three-digit area code does not start with a zero or one. It also handles optional parentheses around the area code and validates a consistent separator to enforce exactly ten digits. A similar US pattern is available for reference.

reNANP := regexp.MustCompile(`^(?:\+1\s?)?(?:\([2-9]\d{2}\)|[2-9]\d{2})[\s.-]?\d{3}[\s.-]?\d{4}$`)
reNANP.MatchString(raw)

Two-Pass Normalization and Validation

This technique uses two steps. First, a regex pass strips any character that is not a digit, or a plus sign at the start of the string. This converts the input into a clean, canonical format.

The second step applies business rules or another regex to the normalized string. For example, the logic can check if the clean string matches the E.164 format or a 10-digit NANP structure. This is effective when user input comes in many formats but must be stored uniformly.

# Step 1
clean = re.sub(r'(?!^\+)[^\p{Nd}]', '', raw, flags=re.U)

# Step 2
if clean.startswith('+'):
    ok = bool(re.fullmatch(r'\+[1-9]\d{1,14}', clean))
elif len(clean) == 10 and clean[0] in '23456789':
    ok = True
else:
    ok = False
    

The Challenges of Regex Phone Number Validation

While regex can check a number's format, it falls short in semantic validation. This approach introduces several practical problems that can lead to incorrect results and a poor user experience.

• National numbering plans change often. A pattern like the Strict NANP method becomes obsolete with new area codes or length rules, which causes it to reject valid numbers over time.
• Regex only confirms a number's structure, not its status. A number can match a pattern, like the Free-form international one, yet belong to an unassigned or retired block, a fact regex cannot know.
• Real-world numbers contain extra characters like extensions or vanity text. A single, comprehensive regex to handle this noise, like the Free-form international pattern, becomes unwieldy and fragile.
• Strict formats like E.164-only validation reject common national formats that users enter with spaces or parentheses. This creates false negatives and frustrates users who input otherwise valid numbers.