regexa

Regexa - Python Regex Utility Library

Regexa is a comprehensive Python library that simplifies working with regular expressions for common text processing tasks. It provides an easy-to-use interface for validations, extractions, and text processing operations.

Features

• Email, phone number and URL validation
• Password strength validation with detailed feedback
• Text extraction (emails, phones, URLs, hashtags, mentions etc)
• Date extraction in multiple formats
• File path processing
• Network validations (IP address, MAC address)
• Credit card validation
• Text cleaning utilities
• Pattern matching and counting

Installation

pip install regexa

Basic Usage

Initialization

from regexa import Regexa

rx = Regexa()

1. Email validation

email = "[e-mail]"
print(f"Is email valid? {rx.match_email(email)}")

# Result: Is email valid? True
# Comment: The email is valid as it follows the standard email format

2. Password strength check

password = "MyStr0ng#Pass"
strength = rx.validate_password_strength(password)
print(f"Password strength: {strength['strength']}")
print(f"Password feedback: {strength['feedback']}")

# Result:
# Password strength: Excellent
# Password feedback: ['Password length sufficient', 'Has uppercase letters', 'Has lowercase letters', 'Has numbers', 'Has special characters']
# Comment: The password is excellent because it meets all criteria: length, uppercase, lowercase, numbers, and special characters

3. Extract all data from text

text = """
Contact me at [e-mail] or call [phone]
Visit our website: https://example.com
Follow us @company #tech #python
Meeting on 25/12/2023 and 2023-12-31
Credit card: 4111111111111111
"""

extracted = rx.extract_all(text)
print("\nExtracted data:")
for key, value in extracted.items():
    print(f"{key}: {value}")

# Result:
# emails: ['[e-mail]']
# phones: ['[phone]']
# urls: ['https://example.com']
# hashtags: ['#tech', '#python']
# mentions: ['@company']
# numbers: ['6281234567890', '25', '12', '2023', '2023', '12', '31']
# words: ['Contact', 'me', 'at', 'john', 'doe', 'example', 'com', ...]
# Comment: Successfully extracted all different types of data from the text

4. Date extraction

dates = rx.extract_dates(text)
print("\nFound dates:")
for date in dates:
    print(f"Date: {date['date']} (Format: {date['format']})")

# Result:
# Date: 25/12/2023 (Format: dd/mm/yyyy)
# Date: 2023-12-31 (Format: yyyy-mm-dd)
# Comment: Detected dates in different formats

5. URL validation

url = "https://example.com"
print(f"\nIs URL valid? {rx.match_url(url)}")

# Result: Is URL valid? True
# Comment: URL is valid as it contains the correct protocol and domain format

6. Credit card validation

card_number = "4111111111111111"
card_validation = rx.validate_credit_card(card_number)
print(f"\nCredit card validation: {card_validation}")

# Result: Credit card validation: {'is_valid': True, 'card_type': 'visa', 'number': '4111111111111111'}
# Comment: Detected as a valid Visa card number

7. Clean text

cleaned_text = rx.clean_text("Hello, World! @#$%")
print(f"\nCleaned text: {cleaned_text}")

# Result: Cleaned text: Hello World
# Comment: Removed all special characters, leaving only alphanumeric characters and spaces

8. IP validation

ip = "192.168.1.1"
ip_validation = rx.validate_ip(ip)
print(f"\nIP validation: {ip_validation}")

# Result: IP validation: {'is_valid': True, 'type': 'IPv4', 'private': True}
# Comment: Valid IPv4 address identified as a private IP address

Documentation

Email Validation

rx.match_email(text: str) -> bool

Validates if a string is a properly formatted email address.

Phone Number Validation

rx.match_phone_id(text: str) -> bool

Validates Indonesian phone numbers.

URL Validation

rx.match_url(text: str) -> bool

Checks if a string is a valid URL with HTTP/HTTPS protocol.

Password Validation

rx.validate_password_strength(password: str) -> Dict[str, Any]

Validates password strength and provides detailed feedback:

• Score (0-5)
• Strength level
• Specific feedback
• Overall validity

Text Extraction

rx.extract_all(text: str) -> Dict[str, List[str]]

Extracts various elements from text:

• Email addresses
• Phone numbers
• URLs
• Hashtags
• @mentions
• Numbers
• Words

Text Cleaning

rx.clean_text(text: str, remove_spaces: bool = False) -> str

Cleans text by removing special characters. Optional space removal.

Date Extraction

rx.extract_dates(text: str) -> List[Dict[str, Any]]

Extracts dates in various formats:

• dd/mm/yyyy
• yyyy-mm-dd
• dd-mm-yyyy
• Natural format (e.g. "25 December 2023")

File Path Processing

rx.extract_filename(path: str) -> Dict[str, str]

Extracts components from file paths:

• Directory
• Filename
• Extension
• Full path

IP Address Validation

rx.validate_ip(ip: str) -> Dict[str, Any]

Validates IPv4 and IPv6 addresses and provides:

• Validity status
• IP version
• Private network status (IPv4)

Pattern Matching

rx.count_matches(text: str, pattern: str) -> Dict[str, Any]

Counts pattern matches in text and provides:

• Match count
• Match positions
• Used pattern

Credit Card Validation

rx.validate_credit_card(number: str) -> Dict[str, Any]

Validates credit card numbers and identifies card type:

• Visa
• Mastercard
• American Express
• Discover

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

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