Text anonymization in many languages for python3.6+ using Faker.
pip install anonymization
>>> from anonymization import Anonymization, PhoneNumberAnonymizer
>>>
>>> text = "C'est bien le 0611223344 ton numéro ?"
>>> anon = Anonymization('fr_FR')
>>> phoneAnonymizer = PhoneNumberAnonymizer(anon)
>>> phoneAnonymizer.anonymize(text)
"C'est bien le 0144939332 ton numéro ?"
This example use NamedEntitiesAnonymizer which require spacy and a spacy model.
pip install spacy
python -m spacy download en
>>> from anonymization import Anonymization, AnonymizerChain, EmailAnonymizer, NamedEntitiesAnonymizer
>>> text = "Hi John,\nthanks for you for subscribing to Superprogram, feel free to ask me any question at [email protected] \n Superprogram the best program!"
>>> anon = AnonymizerChain(Anonymization('en_US'))
>>> anon.add_anonymizers(EmailAnonymizer, NamedEntitiesAnonymizer('en'))
>>> anon.anonymize(text)
'Hi Holly,\nthanks for you for subscribing to Ariel, feel free to ask me any question at [email protected] \n Ariel the best program!'
name | lang |
---|---|
FilePathAnonymizer | - |
name | lang |
---|---|
EmailAnonymizer | - |
UriAnonymizer | - |
MacAddressAnonymizer | - |
Ipv4Anonymizer | - |
Ipv6Anonymizer | - |
name | lang |
---|---|
PhoneNumberAnonymizer | 47+ |
msisdnAnonymizer | 47+ |
name | lang |
---|---|
NamedEntitiesAnonymizer | 7+ |
Custom anonymizers can be easily created to fit your needs:
class CustomAnonymizer():
def __init__(self, anonymization: Anonymization):
self.anonymization = anonymization
def anonymize(self, text: str) -> str:
return modified_text
# or replace by regex patterns in text using a faker provider
return self.anonymization.regex_anonymizer(text, pattern, provider)
# or replace all occurences using a faker provider
return self.anonymization.replace_all(text, matchs, provider)
You may also add new faker provider with the helper Anonymization.add_provider(FakerProvider)
or access the faker instance directly Anonymization.faker
.
MIT