okasen/django-profanity-filter

Django profanity template filter and validators

Django Profanity Filter

Django Profanity Filter is a simple Django app that introduces a range of template tags and filters and model validators that remove or censor inappropriate language.

Installation

1. Install via pip

$ pip install django-profanity-filter

2. Add 'profanity', to your INSTALLED_APPS in settings.py

INSTALLED_APPS = (
...
'profanity',
...
)

Usage

Template Tags

At the top of every template you wish to use profanity filters and tags on, make sure to load the profanity tags.

...
{% load profanity %}
...

Censor Filter

Example

{% with string='You are a bitch!' %}
{{ string|censor }}
{% endwith %}

The output will be You are a *****!, instead of You are a bitch!.

Is Profane Tag

Example

{% with string='You are a bitch!' %}
{{ string|is_profane }}
{% endwith %}

The output will be True, since the string contains profanity.

Validators

Is Profane Validator

Example

from profanity.validators import validate_is_profane

class Post(models.Model):
    post = models.TextArea(max_length=150, validators=[validate_is_profane])

You can also now validate text within unbroken strings, i.e. strings with no spaces in them (stringswithnospacesinthem). To do so, use the validate_is_profane_nospace validator as shown below:

from profanity.validators import validate_is_profane_nospace

class Post(models.Model):
    post = models.TextArea(max_length=150, validators=[validate_is_profane_nospace])

Because there are sometimes profane words nested within safe words (e.g. semen in basement), this validator also uses a "good list" of words that will trigger false positives. If you notice that a word is being blocked from use due to it triggering a false positive, simply add the word to goodlist.txt

TODO

Template Tags

• Basic filter
• Advanced filter
  • Keyword argument for custom word filter

Validators

• Basic Censorship Validator
• Nospace Profanity Validator (for usernames and other unbroken strings)
• Advanced validator - perhaps with the ability to find common morphs of words