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A Python library to automatically detect and fix common typos in email addresses

Project description

Email Typo Fixer

PyPI version Python Support License: MIT

A Python library to automatically detect and fix common typos in email addresses using intelligent algorithms and domain knowledge.

Features

  • Smart Typo Detection: Uses Levenshtein distance algorithm to detect and correct email typos
  • Domain Correction: Fixes common domain typos (e.g., gamil.comgmail.com)
  • Extension Validation: Validates and corrects top-level domains using the Public Suffix List
  • Email Normalization: Normalizes email addresses by removing invalid characters and formatting
  • Configurable: Customizable typo dictionary and distance thresholds
  • Logging Support: Built-in logging for debugging and monitoring

Installation

pip install email-typo-fixer

Quick Start

from email_typo_fixer import normalize_email, EmailTypoFixer

# Simple function interface
corrected_email = normalize_email("user@gamil.com")
print(corrected_email)  # user@gmail.com

# Class interface for more control
fixer = EmailTypoFixer(max_distance=2)
corrected_email = fixer.normalize("user@yaho.com")
print(corrected_email)  # user@yahoo.com

Usage Examples

Basic Email Correction

from email_typo_fixer import normalize_email

# Fix common domain typos
normalize_email("john.doe@gamil.com")     # → john.doe@gmail.com
normalize_email("jane@yaho.com")         # → jane@yahoo.com
normalize_email("user@outlok.com")       # → user@outlook.com
normalize_email("test@hotmal.com")       # → test@hotmail.com

# Fix extension typos
normalize_email("user@example.co")       # → user@example.com
normalize_email("user@site.rog")         # → user@site.org

Advanced Usage with Custom Configuration

from email_typo_fixer import EmailTypoFixer
import logging

# Create a custom logger
logger = logging.getLogger("email_fixer")
logger.setLevel(logging.INFO)

# Custom typo dictionary
custom_typos = {
    'companytypo': 'company',
    'orgtypo': 'org',
}

# Initialize with custom settings
fixer = EmailTypoFixer(
    max_distance=3,           # Allow more distant corrections
    typo_domains=custom_typos, # Use custom typo dictionary
    logger=logger             # Use custom logger
)

# Fix emails with custom rules
corrected = fixer.normalize("user@companytypo.com")
print(corrected)  # user@company.com

Email Validation and Normalization

from email_typo_fixer import EmailTypoFixer

fixer = EmailTypoFixer()

try:
    # Normalize and validate
    email = fixer.normalize("  USER@EXAMPLE.COM  ")
    print(email)  # user@example.com
    
    # Remove invalid characters
    email = fixer.normalize("us*er@exam!ple.com")
    print(email)  # user@example.com
    
except ValueError as e:
    print(f"Invalid email: {e}")

API Reference

normalize_email(email: str) -> str

Simple function interface for email normalization.

Parameters:

  • email (str): The email address to normalize

Returns:

  • str: The corrected and normalized email address

Raises:

  • ValueError: If the email cannot be fixed or is invalid

EmailTypoFixer

Main class for email typo correction with customizable options.

__init__(max_distance=2, typo_domains=None, logger=None)

Parameters:

  • max_distance (int): Maximum Levenshtein distance for extension corrections (default: 2)
  • typo_domains (dict): Custom dictionary of domain typos to corrections
  • logger (logging.Logger): Custom logger instance

normalize(email: str) -> str

Normalize and fix typos in an email address.

Parameters:

  • email (str): The email address to normalize

Returns:

  • str: The corrected and normalized email address

Raises:

  • ValueError: If the email cannot be fixed or is invalid

Default Typo Corrections

The library includes built-in corrections for common email provider typos:

Typo Correction
gamil gmail
gmial gmail
gnail gmail
gmaill gmail
yaho yahoo
yahho yahoo
outlok outlook
outllok outlook
outlokk outlook
hotmal hotmail
hotmial hotmail
homtail hotmail
hotmaill hotmail

Error Handling

The library raises ValueError exceptions for emails that cannot be corrected:

from email_typo_fixer import normalize_email

try:
    normalize_email("invalid.email")  # Missing @ symbol
except ValueError as e:
    print(f"Cannot fix email: {e}")

try:
    normalize_email("user@")  # Missing domain
except ValueError as e:
    print(f"Cannot fix email: {e}")

Requirements

  • Python 3.8+
  • Levenshtein >= 0.25.0
  • publicsuffixlist >= 0.10.0

Development

Setting up for Development

# Clone the repository
git clone https://github.com/yourusername/email-typo-fixer.git
cd email-typo-fixer

# Install Poetry (if not already installed)
curl -sSL https://install.python-poetry.org | python3 -

# Install dependencies
poetry install

# Activate the virtual environment
poetry shell

Running Tests

# Run tests with coverage
poetry run pytest

# Run tests with verbose output
poetry run pytest -v

# Run specific test file
poetry run pytest tests/test_email_typo_fixer.py

Code Quality

# Format code with Black
poetry run black email_typo_fixer tests

# Lint with flake8
poetry run flake8 email_typo_fixer tests

# Type checking with mypy
poetry run mypy email_typo_fixer

Contributing

Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.

  1. Fork the repository
  2. Create your feature branch (git checkout -b feature/AmazingFeature)
  3. Commit your changes (git commit -m 'Add some AmazingFeature')
  4. Push to the branch (git push origin feature/AmazingFeature)
  5. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Changelog

[0.1.0] - 2025-08-07

  • Initial release
  • Basic email typo correction functionality
  • Support for domain and extension corrections
  • Configurable typo dictionary
  • Comprehensive test suite

Acknowledgments

  • Uses the python-Levenshtein library for string distance calculations
  • Uses publicsuffixlist for domain validation
  • Inspired by various email validation libraries in the Python ecosystem

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