Anonymizer
Anonymizer is a Python package that generates fake data for you. It internally makes use of the Faker package, and allows you to keep track of the mapping between your original and fake data. This will be especially useful when you are anonymizing data in pandas data frames.
_____ .__
/ _ \ ____ ____ ____ ___.__. _____ |__|________ ____ _______
/ /_\ \ / \ / _ \ / \< | | / \ | |\___ /_/ __ \\_ __ \
/ | \| | \( <_> )| | \\___ || Y Y \| | / / \ ___/ | | \/
\____|__ /|___| / \____/ |___| // ____||__|_| /|__|/_____ \ \___ >|__|
\/ \/ \/ \/ \/ \/ \/
Basic Usage
Initialization
names = ['Kevin Bell', 'Ricky Sheppard', 'James Hill MD']
anonymizer = Anonymizer()
Get Anonymized Name
anonymizer.get_anonymized_name('Ghajinikanth Zuckerberg')
# 'Catherine Parker'
Get Original Name
anonymizer.get_original_name('Catherine Parker')
# 'Ghajinikanth Zuckerberg'
Get Anonymized Name for Same Name
anonymizer.get_anonymized_name('Ghajinikanth Zuckerberg') # First Call
# 'Catherine Parker'
anonymizer.get_anonymized_name('Ghajinikanth Zuckerberg') # Second Call
# 'Catherine Parker'
Fetch list of Anonymized Names
anonymizer.get_anonymized_names(names)
# ['Leslie Adams', 'Michelle Burke', 'Annette Maxwell']
Fetch list of Original Names
anonymizer.get_original_names(anonymizedNames)
# ['Kevin Bell', 'Ricky Sheppard', 'James Hill MD']
Get Anonymized Data for a different Faker Type
address_anonymizer = Anonymizer(faker_type=FakerType.ADDRESS)
address_anonymizer.get_anonymized_name('74437 Alexandra Well\nSouth Jade, CT 40282')
# 'USNS Hernandez\nFPO AA 32353'
