Anonymize data in your PostgreSQL dababase with ease. Anonymization is handy if you need to provide data to people that should not have access to the personal information of the users. Importing the data to third-party tools where you cannot guarantee what will happen to the data is also a common use case.

The rules for anonynimization are written in a single YAML file. Columns that should be left in the raw form without anonymization must be explicitly marked in the schema. This ensures that adding the new column in the DB without thinking about its sensitivity does not leak the data. The default name of the primary key is id but a custom one can be specified form the table in the schema.

A sample YAML schema can be examined below.

user:
    raw: []
customer:
    raw: [user_ptr_id, language, currency, citizenship]
    pk: user_ptr_id
customeraddress:
    raw: [country, customer_id]

pgantomizer_dump is a helper script that dumps tables specified in the YAML schema file to a compressed file.

pgantomizer is the main script that loads the PostgreSQL dump into a specified instance and then all columns except primary keys and the ones specified in the schema as raw are anonymized according to their data type. Finally, the dump file is deleted by default to reduce risk of leakage of unanonymized data.

You can call the functions to dump anonymize the data from Python. Please, look at the dump_db and load_anonymize_remove in the code. To help integrating the code in complex environments such as a horde of Docker containers, all database-related arguments can be supplied as environmental variables.

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