profanity-filter: A Python library for detecting and filtering profanity

Changes

• Updated outdated packages
• Fixed dependecies
• Bumped python version up-to 3.11

Table of contents

• profanity-filter: A Python library for detecting and filtering profanity
  • Table of contents
  • Overview
    • Features
    • Caveats
  • Usage
    • Basics
    • Deep analysis
    • Multilingual analysis
    • Using as a part of Spacy pipeline
    • Customizations
    • Console Executable
    • RESTful web service
  • Installation
    • Basic installation
    • Deep analysis
    • Other language support
      • Russian language support
        • Pymorphy2
    • Multilingual support
    • RESTful web service
  • Troubleshooting
  • Credits

Overview

profanity-filter is a universal library for detecting and filtering profanity. Support for English and Russian is included.

Features

1. Full text or individual words censoring.
2. Multilingual support, including profanity filtering in texts written in mixed languages.
3. Deep analysis. The library detects not only the exact profane word matches but also derivative and distorted profane words using the Levenshtein automata, ignoring dictionary words, containing profane words as a part.
4. Spacy component for using the library as a part of the pipeline.
5. Explanation of decisions (attribute original_profane_word).
6. Partial word censoring.
7. Extensibility support. New languages can be added by supplying dictionaries.
8. RESTful web service.

Caveats

1. Context-free. The library cannot detect using profane phrases consisted of decent words. Vice versa, the library cannot detect appropriate usage of a profane word.

Usage

Here are the basic examples of how to use the library. For more examples please see tests folder.

Basics

from profanity_filter import ProfanityFilter

pf = ProfanityFilter()

pf.censor("That's bullshit!")
# "That's ********!"

pf.censor_word('fuck')
# Word(uncensored='fuck', censored='****', original_profane_word='fuck')

Deep analysis

from profanity_filter import ProfanityFilter

pf = ProfanityFilter()

pf.censor("fuckfuck")
# "********"

pf.censor_word('oofuko')
# Word(uncensored='oofuko', censored='******', original_profane_word='fuck')

pf.censor_whole_words = False
pf.censor_word('h0r1h0r1')
# Word(uncensored='h0r1h0r1', censored='***1***1', original_profane_word='h0r')

Multilingual analysis

from profanity_filter import ProfanityFilter

pf = ProfanityFilter(languages=['ru', 'en'])

pf.censor("Да бля, это просто shit какой-то!")
# "Да ***, это просто **** какой-то!"

Using as a part of Spacy pipeline

import spacy
from profanity_filter import ProfanityFilter

nlp = spacy.load('en')
profanity_filter = ProfanityFilter(nlps={'en': nlp})  # reuse spacy Language (optional)
nlp.add_pipe(profanity_filter.spacy_component, last=True)

doc = nlp('This is shiiit!')

doc._.is_profane
# True

doc[:2]._.is_profane
# False

for token in doc:
    print(f'{token}: '
          f'censored={token._.censored}, '
          f'is_profane={token._.is_profane}, '
          f'original_profane_word={token._.original_profane_word}'
    )
# This: censored=This, is_profane=False, original_profane_word=None
# is: censored=is, is_profane=False, original_profane_word=None
# shiiit: censored=******, is_profane=True, original_profane_word=shit
# !: censored=!, is_profane=False, original_profane_word=None

Customizations

from profanity_filter import ProfanityFilter

pf = ProfanityFilter()

pf.censor_char = '@'
pf.censor("That's bullshit!")
# "That's @@@@@@@@!"

pf.censor_char = '*'
pf.custom_profane_word_dictionaries = {'en': {'love', 'dog'}}
pf.censor("I love dogs and penguins!")
# "I **** **** and penguins"

pf.restore_profane_word_dictionaries()
pf.is_clean("That's awesome!")
# True

pf.is_clean("That's bullshit!")
# False

pf.is_profane("That's bullshit!")
# True

pf.extra_profane_word_dictionaries = {'en': {'chocolate', 'orange'}}
pf.censor("Fuck orange chocolates")
# "**** ****** **********"

Console Executable

$ profanity_filter -h
usage: profanity_filter [-h] [-t TEXT | -f PATH] [-l LANGUAGES] [-o OUTPUT_FILE] [--show]

Profanity filter console utility

optional arguments:
  -h, --help            show this help message and exit
  -t TEXT, --text TEXT  Test the given text for profanity
  -f PATH, --file PATH  Test the given file for profanity
  -l LANGUAGES, --languages LANGUAGES
                        Test for profanity using specified languages (comma
                        separated)
  -o OUTPUT_FILE, --output OUTPUT_FILE
                        Write the censored output to a file
  --show                Print the censored text

RESTful web service

Run:

$ uvicorn profanity_filter.web:app --reload
INFO: Uvicorn running on http://127.0.0.1:8000
...

Go to the {BASE_URL}/docs for interactive documentation.

Installation

First two parts of installation instructions are designed for the users who want to filter English profanity. If you want to filter profanity in another language you still need to read it.

Basic installation

For minimal setup you need to install profanity-filter with is bundled with spacy and download spacy model for tokenization and lemmatization:

$ pip install profanity-filter
$ # Skip next line if you want to filter profanity in another language
$ python -m spacy download en

For more info about Spacy models read: https://spacy.io/usage/models/.

Deep analysis

To get deep analysis functionality install additional libraries and dictionary for your language.

Firstly, install hunspell and hunspell-devel packages with your system package manager.

For Amazon Linux AMI run:

$ sudo yum install hunspell

For openSUSE run:

$ sudo zypper install hunspell hunspell-devel

Then run:

$ pip install -U profanity-filter[deep-analysis] git+https://github.com/rominf/hunspell_serializable@49c00fabf94cacf9e6a23a0cd666aac10cb1d491#egg=hunspell_serializable git+https://github.com/rominf/pyffs@6c805fbfd7771727138b169b32484b53c0b0fad1#egg=pyffs
$ # Skip next lines if you want deep analysis support for another language (will be covered in next section)
$ cd profanity_filter/data
$ wget https://cgit.freedesktop.org/libreoffice/dictionaries/plain/en/en_US.aff
$ wget https://cgit.freedesktop.org/libreoffice/dictionaries/plain/en/en_US.dic
$ mv en_US.aff en.aff
$ mv en_US.dic en.dic

Other language support

Let's take Russian for example on how to add new language support.

Russian language support

Firstly, we need to provide file profanity_filter/data/ru_badwords.txt which contains a newline separated list of profane words. For Russian it's already present, so we skip file generation.

Next, we need to download the appropriate Spacy model. Unfortunately, Spacy model for Russian is not yet ready, so we will use an English model for tokenization. If you had not install Spacy model for English, it's the right time to do so. As a consequence, even if you want to filter just Russian profanity, you need to specify English in ProfanityFilter constructor as shown in usage examples.

Next, we download dictionaries in Hunspell format for deep analysis from the site https://cgit.freedesktop.org/libreoffice/dictionaries/plain/:

> cd profanity_filter/data
> wget https://cgit.freedesktop.org/libreoffice/dictionaries/plain/ru_RU/ru_RU.aff
> wget https://cgit.freedesktop.org/libreoffice/dictionaries/plain/ru_RU/ru_RU.dic
> mv ru_RU.aff ru.aff
> mv ru_RU.dic ru.dic

Pymorphy2

For Russian and Ukrainian languages to achieve better results we suggest you to install pymorphy2. To install pymorphy2 with Russian dictionary run:

$ pip install -U profanity-filter[pymorphy2-ru] git+https://github.com/kmike/pymorphy2@ca1c13f6998ae2d835bdd5033c17197dcba84cf4#egg=pymorphy2

Multilingual support

You need to install polyglot package and it's requirements for language detection. See https://polyglot.readthedocs.io/en/latest/Installation.html for more detailed instructions.

For Amazon Linux AMI run:

$ sudo yum install libicu-devel

For openSUSE run:

$ sudo zypper install libicu-devel

Then run:

$ pip install -U profanity-filter[multilingual]

RESTful web service

Run:

$ pip install -U profanity-filter[web]

Troubleshooting

You can always check will deep, morphological, and multilingual analyses work by inspecting the value of module variable AVAILABLE_ANALYSES. If you've followed all steps and installed support for all analyses you will see the following:

from profanity_filter import AVAILABLE_ANALYSES

print(', '.join(sorted(analysis.value for analysis in AVAILABLE_ANALYSES)))
# deep, morphological, multilingual

If something is not right, you can import dependencies yourself to see the import exceptions:

from profanity_filter.analysis.deep import *
from profanity_filter.analysis.morphological import *
from profanity_filter.analysis.multilingual import *

Credits

English profane word dictionary: https://github.com/areebbeigh/profanityfilter/ (author Areeb Beigh).

Russian profane word dictionary: https://github.com/PixxxeL/djantimat (author Ivan Sergeev).