py-text-toolkit 0.1.0

A comprehensive string utility library for Python.

py-text-toolkit

A lightweight, dependency-minimal Python library for everyday string operations — cleaning, validation, analysis, case conversion, and generation.

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Installation

pip install py-text-toolkit

Requires: Python 3.8+
Optional dependency: emoji (required only for cleaning.remove_emojis)

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Modules at a Glance

Module	What it does
py-text-toolkit.cleaning	Strip, replace, and normalize raw text
py-text-toolkit.validation	Validate emails, URLs, passwords, and character sets
py-text-toolkit.analysis	Count, compare, and measure strings
py-text-toolkit.format_cases	Convert between naming conventions and formatting styles
py-text-toolkit.generation	Generate slugs, masks, ciphers, and reversed strings

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Quick Start

from py-text-toolkit.cleaning import remove_html_tags, remove_urls
from py-text-toolkit.validation import is_email, is_strong_password
from py-text-toolkit.analysis import word_count, is_palindrome
from py-text-toolkit.format_cases import to_snake_case, to_camel_case
from py-text-toolkit.generation import generate_slug, mask_range

# Clean
remove_html_tags("<p>Hello <b>world</b></p>")   # "Hello world"
remove_urls("Visit https://example.com today")  # "Visit today"

# Validate
is_email("[e-mail]")        # True
is_strong_password("Passw0rd!")     # True

# Analyse
word_count("Hello, world!")         # 2
is_palindrome("A man a plan a canal Panama")  # True

# Convert case
to_snake_case("camelCaseText")      # "camel_case_text"
to_camel_case("hello_world")        # "helloWorld"

# Generate
generate_slug("Hello World!")       # "hello-world"
mask_range("1234-5678-9012", 5, 9, "*")  # "1234-****-9012"

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Module Reference

py-text-toolkit.cleaning

Functions for sanitising and normalising raw text.

Function	Signature	Description
normalize_whitespace	(text) → str	Collapse all whitespace runs to a single space and strip ends
remove_punctuation	(text, replace="") → str	Remove or replace all punctuation characters
remove_digits	(text, replace="") → str	Remove or replace all digit characters
remove_html_tags	(text, replace="") → str	Strip or replace HTML tags
remove_urls	(text, replace="") → str	Remove or replace HTTP/HTTPS and www. URLs
remove_emojis	(text, replace="") → str	Remove or replace emoji characters (requires emoji)
collapse_spaces	(text) → str	Remove all whitespace (not just collapse)

All cleaning functions accept an optional replace argument — the string substituted in place of each removed element (defaults to ""). After replacement, whitespace is always normalized.

from py-text-toolkit.cleaning import remove_punctuation, remove_html_tags, remove_emojis

remove_punctuation("Hello, world!")              # "Hello world"
remove_punctuation("Hello, world!", replace=" ") # "Hello world"

remove_html_tags("<p>Hello <b>world</b></p>")    # "Hello world"
remove_html_tags("<br/>line1<br/>line2", replace=" ")  # "line1 line2"

remove_emojis("Great job! 🎉")                   # "Great job!"
remove_emojis("Hello 😊", replace="[emoji]")     # "Hello [emoji]"

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py-text-toolkit.validation

Boolean predicates for common string formats.

Function	Signature	Description
is_email	(text) → bool	Check for a valid email address
is_url	(text) → bool	Check for a valid HTTP or HTTPS URL
contains_only	(text, allowed_chars) → bool	Check that every character is in the allowed set
is_strong_password	(text) → bool	Check that a password meets strength requirements

Password requirements (is_strong_password):

• Minimum 8 characters
• At least one lowercase letter
• At least one uppercase letter
• At least one digit
• At least one special character from @$!%*?&

from py-text-toolkit.validation import is_email, is_url, contains_only, is_strong_password

is_email("[e-mail]")          # True
is_email("not-an-email")              # False

is_url("https://api.service.io/v1")   # True
is_url("ftp://files.example.com")     # False

contains_only("12345", "0123456789")  # True
contains_only("hello!", "a-z")        # False  (literal chars only, not a range)

is_strong_password("Passw0rd!")       # True
is_strong_password("weakpass")        # False

Note on contains_only: allowed_chars is treated as a set of literal characters. Special regex characters are escaped automatically, so "a-z" matches only the three characters a, -, and z, not a range.

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py-text-toolkit.analysis

Functions that measure and compare strings.

Function	Signature	Description
word_count	(text) → int	Count words using regex word-boundary matching
char_frequency	(text, char) → int	Count non-overlapping occurrences of a character or substring
count_vowels	(text) → int	Count English vowels (a e i o u), case-insensitive
longest_word	(text) → int	Return the length of the longest whitespace-delimited word
is_palindrome	(text, case_sensitive=False, ignore_formatting=True) → bool	Check if a string is a palindrome
is_anagram	(word1, word2) → bool	Check if two strings are anagrams (case-insensitive, ignores spaces)

from py-text-toolkit.analysis import word_count, is_palindrome, is_anagram, char_frequency

word_count("Hello, world!")                   # 2
word_count("  spaces   everywhere  ")         # 2

char_frequency("banana", "an")                # 2

is_palindrome("racecar")                      # True
is_palindrome("A man a plan a canal Panama")  # True
is_palindrome("Racecar", case_sensitive=True) # False

is_anagram("listen", "silent")                # True
is_anagram("Astronomer", "Moon starer")       # True

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py-text-toolkit.format_cases

Convert strings between naming conventions and apply text formatting.

Function	Signature	Description
to_snake_case	(text) → str	Convert to snake_case
to_camel_case	(text) → str	Convert to camelCase
to_pascal_case	(text) → str	Convert to PascalCase
to_kebab_case	(text) → str	Convert to kebab-case
to_title_case	(text) → str	Convert to Title Case
truncate	(text, max_length, suffix="...") → str	Truncate to a maximum length with a suffix
pad_center	(text, width, fillchar=" ") → str	Center-pad to a given width

All case converters handle mixed input (camelCase, PascalCase, snake_case, kebab-case, spaces).

from py-text-toolkit.format_cases import to_snake_case, to_camel_case, truncate, pad_center

to_snake_case("camelCaseText")    # "camel_case_text"
to_snake_case("Hello World!")     # "hello_world"

to_camel_case("hello_world")      # "helloWorld"
to_camel_case("PascalCaseText")   # "pascalCaseText"

to_pascal_case("kebab-case-text") # "KebabCaseText"
to_kebab_case("camelCaseText")    # "camel-case-text"
to_title_case("hello_world")      # "Hello World"

truncate("Hello, World!", 8)      # "Hello..."
truncate("Hi", 10)                # "Hi"

pad_center("hello", 11)           # "   hello   "
pad_center("hi", 10, "-")         # "----hi----"

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py-text-toolkit.generation

Functions that produce new strings from existing ones.

Function	Signature	Description
generate_slug	(text) → str	Convert to a URL-friendly slug
reverse_word	(text) → str	Reverse all characters
mask_range	(text, start_index, end_index, placeholder="X") → str	Mask a character range with a placeholder
ceasar_cipher	(text, shift) → str	Encrypt/decrypt with the Caesar cipher

from py-text-toolkit.generation import generate_slug, mask_range, ceasar_cipher, reverse_word

generate_slug("Hello World!")               # "hello-world"
generate_slug("Python 3.11 -- Release Notes")  # "python-3-11-release-notes"

reverse_word("hello")                       # "olleh"

mask_range("1234-5678-9012", 5, 9, "*")     # "1234-****-9012"
mask_range("secret", -3, -1)               # "secXXt"

ceasar_cipher("Hello, World!", 3)           # "Khoor, Zruog!"
ceasar_cipher("Khoor, Zruog!", -3)          # "Hello, World!"  (decrypt)

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Dependencies

Package	Required	Used by
re (stdlib)	Always	All modules
string (stdlib)	Always	cleaning
emoji	Optional	cleaning.remove_emojis only

Install with the optional dependency:

pip install py-text-toolkit[emoji]

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License

MIT License — see LICENSE for details.