rexa 0.2.2

A powerful regex utility library for validation, extraction, conversion, and formatting.

🎉 Rexa Usage Guide

Welcome to Rexa, your one-stop Python library for powerful regex operations and text preprocessing! Whether you’re building web scrapers, form validators, or NLP pipelines, this guide will help you harness Rexa’s full potential.

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🔍 1. Validator (validation.py)

Validate and match common patterns with ease:

Method	What it does	Example
Is_Email(s)	✅ Returns True if s is a valid email	Rex().Is_Email("[e-mail]") # True
Match_Email(s)	🔎 Returns a Match object for valid email, else None	Rex().Match_Email("bad@") # None
Is_URL(s)	✅ Validate HTTP/HTTPS URLs	Rex().Is_URL("https://site.io") # True
Match_URL(s)	🔎 Match URL and capture path/query	m = Rex().Match_URL("site.com/path")
Is_Date_ISO(s)	✅ Check YYYY-MM-DD date format	Rex().Is_Date_ISO("2025-08-02") # True
Match_Date_ISO(s)	🔎 Capture ISO date, if present	Rex().Match_Date_ISO("02/08/2025") # None

And many more Is_* / Match_* methods for phones, UUIDs, etc.

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📥 2. Extractor (extraction.py)

Pull data out of messy text:

Method	Extracts…	Example
Extract_Emails(text)	All email addresses	Rex().Extract_Emails("[e-mail] [e-mail]") # [[e-mail],[e-mail]]
Extract_URLs(text)	All web links	Rex().Extract_URLs("Go to http://x.com") # [http://x.com]
Extract_Dates(text)	Dates in ISO/EU formats	Rex().Extract_Dates("2021-01-01 or 01/01/2021")
Extract_Phones(text)	Phone numbers (intl & local)	Rex().Extract_Phones("[phone], 09121234567")

…plus IPv4, UUIDs, and more.

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🔄 3. Converter (conversion.py)

Normalize and reformat strings:

Method	Transforms…	Example
Convert_MultipleSpaces(text)	Collapse extra spaces	Rex().Convert_MultipleSpaces("A B") → "A B"
Convert_ThousandSeparatedNumbers(text)	Strip commas from large numbers	Rex().Convert_ThousandSeparatedNumbers("1,000,000") → "1000000"
Convert_DateFormat(s,from,to)	Swap date separators	Rex().Convert_DateFormat("01.01.2025",".","/") → "01/01/2025"
Slugify(text)	Generate SEO-friendly URL slugs	Rex().Slugify("Hello World!") → "hello-world"

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✨ 4. Formatter (formatting.py)

Clean up and standardize:

Method	Cleans…	Example
Strip_HTMLTags(s)	Remove HTML tags	Rex().Strip_HTMLTags("<b>Hi</b>") → "Hi"
Normalize_Spaces(s)	Single-space normalization	Rex().Normalize_Spaces("A B") → "A B"
Remove_ThousandSeparators(s)	Drop commas in numbers	Rex().Remove_ThousandSeparators("1,234") → "1234"
Normalize_DateSeparator(s,sep)	Consistent date delimiter	Rex().Normalize_DateSeparator("2021/01.01","-") → "2021-01-01"

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🧹 5. TextTools (texttools.py)

Advanced NLP & text cleaning utilities:

Method	Description	Example
to_lower(s)	Lowercase entire string	TextTools.to_lower("HELLO") → "hello"
to_upper(s)	Uppercase entire string	TextTools.to_upper("hi") → "HI"
remove_emojis(s)	Strip Unicode emojis	TextTools.remove_emojis("I ❤️ you") → "I you"
remove_numbers(s)	Remove all digits	TextTools.remove_numbers("a1b2") → "ab"
remove_usernames(s)	Remove @username tokens	TextTools.remove_usernames("@me hi") → " hi"
remove_punctuation(s)	Strip punctuation & symbols	TextTools.remove_punctuation("Hey!?@") → "Hey"
remove_urls_emails(s)	Drop URLs & email addresses	TextTools.remove_urls_emails("[e-mail] http://x") → " "
remove_stopwords(s)	Filter common words (using NLTK)	TextTools.remove_stopwords("the cat sits") → "cat sits"
lemmatize_text(s)	Lemmatize tokens	TextTools.lemmatize_text("running") → "running"
stem_text(s)	Stem tokens	TextTools.stem_text("running") → "run"
normalize_whitespace(s)	Collapse whitespace	TextTools.normalize_whitespace(" A B\n") → "A B"
normalize_arabic(s)	Persian/Arabic char mapping & diacritics	TextTools.normalize_arabic("كیف") → "کیف"
count_tokens(s)	Count word tokens	TextTools.count_tokens("a b c") → 3
remove_short_long_words(s,min,max)	Keep words len in range	TextTools.remove_short_long_words("a bb ccc",2,3) → "bb ccc"
detect_language(s)	Auto-detect text language	TextTools.detect_language("hello") → "en"
clean_text(...kwargs)	Pipeline for common cleaning options	TextTools.clean_text("Hi @you 123 😊", lowercase=True, remove_emoji=True, remove_username=True, remove_urls_emails=True, remove_punct=True) → "hi"

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🚀 Quick Tips

• Mix & Match: Call only the methods you need or use clean_text for a one-shot pipeline.
• Extendable: Create subclasses to add domain-specific patterns.
• Performance: For bulk text, parallelize tokenization and regex calls.

Happy coding with Rexa! Questions or feedback? Open an issue at https://github.com/arshia82sbn/rexa/issues