ValX Package Documentation

Package documentation for ValX, a Python package for handling text-cleaning tasks, including profanity and PII. Now includes hate speech detection and offensive language detection using AI.

Changelog

• 0.2.3 (Latest): Created new detection patterns for sensitive information, and created a new optional info_type parameter to control sensitive information detection and removal.

• 0.2.2: Refactored detect_profanity function to return more information about the found profanities. Also removed unnecessary printing in functions.

• 0.2.1: Updated project PYPI description.

• 0.2.0: Created a new function, to automatically remove detected hate speech or offensive speech from text.

• 0.1.8 - 0.1.9: Updated docstrings.

• 0.1.7: Added AI models to ValX for hate speech detection.

• 0.1.1 - 0.1.6: Fixed errors in code, and created several functions for text cleaning.

• 0.1.0: Initial release.

Installation

You can install ValX using PyPi, please make sure that you are using Python 3.6 or later before installing ValX:

pip install valx

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List of supported languages for profanity detection and removal

Below is a complete list of all the available supported languages for ValX's profanity detection and removal functions which are valid values for language:

• All

• Arabic

• Czech

• Danish

• German

• English

• Esperanto

• Persian

• Finnish

• Filipino

• French

• French (CA)

• Hindi

• Hungarian

• Italian

• Japanese

• Kabyle

• Korean

• Dutch

• Norwegian

• Polish

• Portuguese

• Russian

• Swedish

• Thai

• Klingon

• Turkish

• Chinese

Example Usage

Profanity Detection

from valx import detect_profanity

sample_text = [
    "This is a sample text containing some profanity like bad word 1, bad word 2, and bad word 3.",
    "This line doesn't contain any profanity.",
    "But this one has another, just in another language: bad word 4."
]

# Detect profanity
results = detect_profanity(sample_text, language='English')
print("Profanity Evaluation Results", results)

Profanity Removal

from valx import remove_profanity

sample_text = [
    "This is a sample text containing some profanity like bad word 1, bad word 2, and bad word 3.",
    "This line doesn't contain any profanity.",
    "But this one has another, just in another language: bad word 4."
]

# Remove profanity
removed = remove_profanity(sample_text, "text_cleaned.txt", language="English")

PII Detection

from valx import detect_sensitive_information

sample_text = [
        "Please contact [e-mail] or call 555-123-4567 for more information.",
        "We will need your credit card number to complete the transaction: 1234-5678-9012-3456.",
        "My social security number is 123-45-6789 and my ID number is AB123456.",
        "Our office address is 123 Main St, Anytown, USA. Please visit us!",
        "Your IP address is 192.168.1.1. Please don't share it with anyone."
]

# Detect sensitive information
detected_information = detect_sensitive_information(sample_text)

PII Removal

from valx import remove_sensitive_information

sample_text = [
        "Please contact [e-mail] or call 555-123-4567 for more information.",
        "We will need your credit card number to complete the transaction: 1234-5678-9012-3456.",
        "My social security number is 123-45-6789 and my ID number is AB123456.",
        "Our office address is 123 Main St, Anytown, USA. Please visit us!",
        "Your IP address is 192.168.1.1. Please don't share it with anyone."
]

# Detect sensitive information
cleaned_information = remove_sensitive_information(sample_text)

Hate Speech Detection

from valx import detect_hate_speech

# Detect hate speech or offensive language
outcome_of_detection = detect_hate_speech("You are stupid.")

Remove Hate Speech

from valx import detect_hate_speech

sample_text = [
    "This is a sample text containing some profanity like bad word 1, bad word 2, and bad word 3.",
    "This line doesn't contain any profanity.",
    "But this one has another, just in another language: bad word 4."
]
# Remove hate speech or offensive language
cleaned_text = remove_hate_speech(sample_text)