Numbers Regex Python Validator

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Numbers Regex Python Validator

Search...

⌘K


Numbers Regex Python Validator

Numbers Regex Python Validator

Use the Numbers Regex Python Validator to accurately test patterns for integers, decimals, and formatted numbers in Python. Whether you’re validating user input or cleaning datasets, this tool helps ensure numerical values follow the correct structure. For more Python-specific regex tools, explore our Python Email Regex Validator, Python IP Address Regex Validator, or experiment freely with patterns in our Python Regex Tester.

28193
Possible security issues
This regex appears to be safe.
Explanation
  • [A-Z]: uppercase letters
  • [a-z]: lowercase letters
  • [0-9]: digits
  • \.: a literal dot
  • +: one or more of the preceding
  • *: zero or more of the preceding
  • ?: optional (zero or one)
  • ^: start of string
  • $: end of string
Match information
Match 1: "28193" at index 0
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Regular Expression - Documentation

What is the Numbers Regex Python Validator?


The Numbers Regex Python Validator is a tool designed to help developers test regular expressions for numeric values, including:


  • Whole numbers (integers)

  • Decimal numbers

  • Comma-formatted values like 1,000


It uses Python’s re module and is ideal for applications that require data validation, such as form handling, data analysis, and backend validation systems.


Common Patterns for Number Validation


  1. Integer Validation


    Regex: ^\d+$

    Validates a string containing only digits.


    Matches: 12345

    Does not match: 123a, 12.34

  2. Decimal Number Validation


    Regex: ^\d+\.\d+$

    Validates a string with digits before and after a decimal point.


    Matches: 45.67

    Does not match: .45, 45.

  3. Comma-Formatted Number Validation


    Regex: ^\d{1,3}(,\d{3})*$

    Validates numbers like 1,000 or 12,000,000.


    Matches: 1,000, 100,000

    Does not match: 10,00, 1,00,000


Python Code Example

import re

def is_valid_number(value):
    pattern = re.compile(r'^\d+$')  # Change pattern here for decimals or formatted numbers
    return bool(pattern.fullmatch(value))

# Example tests
print(is_valid_number("123456"))      # True
print(is_valid_number("12.34"))       # False
print(is_valid_number("1,000"))       # False

Use the Python Regex Tester to try variations.


Use Cases


  • Form Input Validation: Ensure numeric-only input for fields like age, quantity, or price.

  • Data Cleaning in Python Scripts: Filter out invalid numerical formats during preprocessing.

  • File/Data Imports: Validate numbers during CSV or Excel file processing.

  • Financial Apps: Match only correctly formatted numbers in calculations or reporting.


For related Python validators, check out:


Categorized Metacharacters for Number Regex


  • \d : Matches any digit (0–9)

  • \D : Matches any non-digit character

  • ^ : Anchors the match at the start of the string

  • $ : Anchors the match at the end of the string

  • + : Matches one or more of the preceding element

  • * : Matches zero or more of the preceding element

  • \. : Escapes the dot to match a literal decimal point

  • , : Matches comma when used in formatted numbers

  • () : Groups multiple tokens together


Pro Tips


  • Use fullmatch() in Python to ensure the entire string conforms to the pattern.

  • For decimals that accept optional digits after the point, use: ^\d+(\.\d+)?$

  • When validating thousands separators, ensure locale consistency (e.g., comma in US, dot in EU).

  • Use raw string literals in Python (r'^\d+$') to avoid escaping issues.


Explore related tools:


Frequently asked questions

Can I validate negative numbers using this?×
Yes, by modifying the pattern to allow optional minus sign, e.g., ^-?\d+$.
Does this tool support scientific notation like 1e10?+
How do I validate decimals with optional fractions?+
Can commas and decimals be combined in one pattern?+
Should I use regex or Python’s isnumeric()?+