Easy Regex

`py_simple.easy_regex`

easy_regex is built to simplify pulling common patterns (emails, URLs, numbers) out of text without writing your own regex.

`clean_extra_whitespace(text)`

Returns the text with all extra whitespace replaced by a single space.

This removes multiple spaces, tabs, and newlines, and strips leading/trailing whitespace.

Parameters:

Name	Type	Description	Default
`text`	`str`	Text to clean.	required

Returns:

Name	Type	Description
`str`	`str`	The cleaned text.

Example

The Py_simple WayThe Traditional Way

from py_simple import clean_extra_whitespace

result = clean_extra_whitespace("Hello    world\n\nthis is Python")
# -> 'Hello world this is Python'

import re

text = "Hello    world\n\nthis is Python"
result = re.sub(r'\s+', ' ', text).strip()
# -> 'Hello world this is Python'

`extract_emails(text)`

Returns a list of all email addresses found in the text.

Parameters:

Name	Type	Description	Default
`text`	`str`	Text to search for email addresses.	required

Returns:

Name	Type	Description
`list`	`list \| None`	All email addresses found in the text. Empty list if none found.

Example

The Py_simple WayThe Traditional Way

from py_simple import extract_emails

result = extract_emails("Contact us at hello@example.com or support@test.org")
# -> ['hello@example.com', 'support@test.org']

import re

pattern = r'[a-zA-Z_.%+-]+@[a-zA-Z0-9-]+\.[a-zA-Z]+'
result = re.findall(pattern, "Contact us at hello@example.com or support@test.org")
# -> ['hello@example.com', 'support@test.org']

`extract_hashtag_names(text)`

Returns hashtag names without their leading hash symbols.

Names contain Unicode alphanumeric characters and underscores. A hash immediately preceded by a word character or another hash is ignored. Case, order, and duplicates are preserved. Punctuation ends a name; combining marks are not included and text is not Unicode-normalized. This is a text helper, not a social platform's hashtag validator.

Parameters:

Name	Type	Description	Default
`text`	`str`	Text to search for hashtag names.	required

Returns:

Type	Description
`list[str]`	list[str]: Names without `#`, or an empty list if none are found.

Example

The Py_simple WayThe Traditional Way

from py_simple.easy_regex import extract_hashtag_names

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

import re

result = re.findall(r'(?<![\w#])#(\w+)', "Hello #Python #hello_world!")
# -> ['Python', 'hello_world']

`extract_hashtags(text)`

Returns a list of all hashtags found in the text.

A hashtag is defined as a hash symbol (#) followed by one or more alphanumeric characters or underscores.

Parameters:

Name	Type	Description	Default
`text`	`str`	Text to search for hashtags.	required

Returns:

Name	Type	Description
`list`	`list`	All hashtags found in the text. Empty list if none found.

Example

The Py_simple WayThe Traditional Way

from py_simple.easy_regex import extract_hashtags

result = extract_hashtags("Loving #Python and #OpenSource!")
# -> ['#Python', '#OpenSource']

import re

pattern = r'#\w+'
result = re.findall(pattern, "Loving #Python and #OpenSource!")
# -> ['#Python', '#OpenSource']

`extract_hex_colors(text)`

Returns a list of CSS-style hexadecimal color codes found in the text.

Supports the 3, 4, 6, and 8 digit forms, including their leading #.

Parameters:

Name	Type	Description	Default
`text`	`str`	Text to search for hexadecimal color codes.	required

Returns:

Name	Type	Description
`list`	`list \| None`	All hexadecimal color codes found in the text. Empty list if none are found.

Example

The Py_simple WayThe Traditional Way

from py_simple import extract_hex_colors

result = extract_hex_colors("Use #fff on #1a2b3c")
# -> ['#fff', '#1a2b3c']

import re

pattern = (
    r'(?<![\\w#])#(?:[0-9a-fA-F]{8}|[0-9a-fA-F]{6}|'
    r'[0-9a-fA-F]{4}|[0-9a-fA-F]{3})\\b'
)
result = re.findall(pattern, "Use #fff on #1a2b3c")
# -> ['#fff', '#1a2b3c']

`extract_ipv4_addresses(text)`

Returns a list of all IPv4 addresses found in the text.

Matches the standard dotted-decimal format (e.g., 192.168.1.1). Rejects partial matches like 192.168.1 or 192.168.1.1.1.1.

Parameters:

Name	Type	Description	Default
`text`	`str`	Text to search for IPv4 addresses.	required

Returns:

Name	Type	Description
`list`	`list`	All IPv4 addresses found. Empty list if none found.

Example

The Py_simple WayThe Traditional Way

from py_simple import extract_ipv4_addresses

result = extract_ipv4_addresses("Server 192.168.1.1 connected to 10.0.0.5")
# -> ['192.168.1.1', '10.0.0.5']

import re

pattern = r'(?<![\d.])(?:\d{1,3}\.){3}\d{1,3}(?![\d.])'
result = re.findall(pattern, "Server 192.168.1.1 connected to 10.0.0.5")
# -> ['192.168.1.1', '10.0.0.5']

`extract_mentions(text)`

Returns a list of all username mentions found in the text.

A mention is defined as an @ symbol followed by one or more alphanumeric characters or underscores.

Parameters:

Name	Type	Description	Default
`text`	`str`	Text to search for mentions.	required

Returns:

Name	Type	Description
`list`	`list`	All mentions found in the text. Empty list if none found.

Example

The Py_simple WayThe Traditional Way

from py_simple import extract_mentions

result = extract_mentions("Hey @alice, please review @dev_team's code")
# -> ['@alice', '@dev_team']

import re

pattern = r'@\w+'
result = re.findall(pattern, "Hey @alice, please review @dev_team's code")
# -> ['@alice', '@dev_team']

`extract_number_sequences(text)`

Returns a list of number sequences found in the text, where numbers are joined by a separator such as -, _, : or . (e.g. dates, times, IP addresses, version numbers, or IDs).

Parameters:

Name	Type	Description	Default
`text`	`str`	Text to search for number sequences.	required

Returns:

Name	Type	Description
`list`	`list \| None`	All number sequences found in the text. Empty list if none found.

Example

The Py_simple WayThe Traditional Way

from py_simple import extract_number_sequences

result = extract_number_sequences("Server 192.168.1.1 logged in at 14:32 on 04-08-2026")
# -> ['192.168.1.1', '14:32', '04-08-2026']

import re

pattern = r'[0-9]+(?:(?:-|_|:|\.)?[0-9]+)+'
result = re.findall(pattern, "Server 192.168.1.1 logged in at 14:32 on 04-08-2026")
# -> ['192.168.1.1', '14:32', '04-08-2026']

`extract_numbers(text)`

Returns a list of all standalone digit sequences found in the text.

Parameters:

Name	Type	Description	Default
`text`	`str`	Text to search for numbers.	required

Returns:

Name	Type	Description
`list`	`list \| None`	All digit sequences found in the text. Empty list if none found.

Example

The Py_simple WayThe Traditional Way

from py_simple import extract_numbers

result = extract_numbers("I have 3 cats and 12 fish")
# -> ['3', '12']

import re

pattern = r'[0-9]+'
result = re.findall(pattern, "I have 3 cats and 12 fish")
# -> ['3', '12']

`extract_urls(text)`

Returns a list of all URLs found in the text.

Parameters:

Name	Type	Description	Default
`text`	`str`	Text to search for URLs.	required

Returns:

Name	Type	Description
`list`	`list \| None`	All URLs found in the text. Empty list if none found.

Example

The Py_simple WayThe Traditional Way

from py_simple import extract_urls

result = extract_urls("Visit https://www.example.com or www.test.org today")
# -> ['https://www.example.com', 'www.test.org']

import re

pattern = (r'(?:https?://(?:www\.)?|www\.)[a-zA-Z0-9-]+\.
(?:(?:[a-zA-Z0-9-]+\.)*)?(?:(?:[a-zA-Z0-9-]+\\)*)?[a-zA-Z]{2,}
(?:\.[a-zA-Z]{2,})?(?:/\S*)?')
result = re.findall(pattern, "Visit https://www.example.com or www.test.org today")
# -> ['https://www.example.com', 'www.test.org']