Easy Regex

Working with text often requires extracting specific patterns like email addresses, websites, or numbers. Writing regular expressions from scratch can be tricky and frustrating, but the easy_regex module provides beginner-friendly helpers that make pattern extraction simple and readable.

A Small Real-World Example

Imagine you're building a tool to parse a batch of user feedback messages or customer support logs. You want to extract all submitted email addresses and website links to build a quick contact list.

from py_simple import extract_emails, extract_urls

text = """
Please contact our support team at support@example.com or
sales@test.org. You can also visit our website at https://www.example.com
or check out our partner page www.test.org.
"""

emails = extract_emails(text)
urls = extract_urls(text)

print(emails)
print(urls)

What Happened?

extract_emails() scans the text and returns a list of all valid email addresses found.

extract_urls() scans the text and identifies web addresses, including URLs that start with http://, https://, or www..

Instead of writing regular expressions manually, you can call these helpers directly with the text you want to search:

emails = extract_emails(text)
urls = extract_urls(text)

The results are returned as lists that are ready to use in your program.

Why Use These Helpers?

Writing regular expressions from scratch can be difficult because you need to create, test, and maintain complex patterns. The easy_regex helpers handle this complexity for you.

Using these helpers makes your code:

• Simple – No need to write complex regex patterns.
• Readable – The function names clearly describe what they do.
• Reusable – Use the same helpers whenever you need to extract emails or URLs.
• Beginner-friendly – Focus on solving your problem instead of learning complicated regex syntax.

For example:

emails = extract_emails(text)
urls = extract_urls(text)

This is much easier to understand than writing and maintaining the regular expression patterns yourself.

Extract Hashtag Names

Use extract_hashtag_names() when you want names without the leading #:

from py_simple.easy_regex import extract_hashtag_names

names = extract_hashtag_names("Hello #Python #hello_world #Python!")
# -> ['Python', 'hello_world', 'Python']

The helper preserves case, order, and duplicates. Names may contain Unicode alphanumeric characters and underscores, including digits at the start. Punctuation ends a name. Empty text or text without hashtags returns []. Hashes attached to a preceding word or another hash are ignored:

extract_hashtag_names("word#tag ##tag #valid")
# -> ['valid']

This helper follows Python's Unicode \w matching: combining marks are not included and no Unicode normalization is performed. It is not a validator for any particular social platform. The existing py_simple.easy_regex.extract_hashtags() continues to return tags with #.