Metadata-Version: 2.1
Name: pynonymizer
Version: 1.6.2
Summary: An anonymization tool for production databases
Home-page: https://gitlab.com/jerometwell/pynonymizer
Author: Jerome Twell
Author-email: jtwell1@gmail.com
License: MIT
Description: # pynonymizer
        
        pynonymizer is a universal tool for translating sensitive production database dumps into anonymized copies.
        
        This can help you support GDPR/Data Protection in your organization without compromizing on quality testing data.
        
        ### Why are anonymized databases important?
        The primary source of information on how your database is used is in _your production database_. In most situations, the production dataset is usually significantly larger than any development copy, and
        would contain a wider range of data.
        
        From time to time, it is prudent to run a new feature or stage a test against this dataset, rather
        than one that is artificially created by developers or by testing frameworks. Anonymized databases allow us to use the structures present in production, while stripping them of any personally identifiable data that would
        consitute a breach of privacy for end-users and subsequently a breach of GDPR. 
        
        With Anonymized databases, copies can be processed regularly, and distributed easily, leaving your developers and testers with a rich source of information on the volume and general makeup of the system in production. It can
        be used to run better staging environments, integration tests, and even simulate database migrations. 
        
        below is an excerpt from an anonymized database:
        
        | id |salutation | firstname | surname | email | dob | 
        | - | - | - | - | - | - | 
        | 1 | Dr. | Bernard | Gough | tnelson@powell.com | 2000-07-03 | 
        | 2 | Mr. | Molly | Bennett | clarkeharriet@price-fry.com | 2014-05-19 | 
        | 3 | Mrs. | Chelsea | Reid | adamsamber@clayton.com | 1974-09-08 | 
        | 4 | Dr. | Grace | Armstrong | tracy36@wilson-matthews.com | 1963-12-15 | 
        | 5 | Dr. | Stanley | James | christine15@stewart.net | 1976-09-16 | 
        | 6 | Dr. | Mark | Walsh | dgardner@ward.biz | 2004-08-28 | 
        | 7 | Mrs. | Josephine | Chambers | hperry@allen.com | 1916-04-04 | 
        | 8 | Dr. | Stephen | Thomas | thompsonheather@smith-stevens.com | 1995-04-17 | 
        | 9 | Ms. | Damian | Thompson | yjones@cox.biz | 2016-10-02 | 
        | 10 | Miss | Geraldine | Harris | porteralice@francis-patel.com | 1910-09-28 | 
        | 11 | Ms. | Gemma | Jones | mandylewis@patel-thomas.net | 1990-06-03 | 
        | 12 | Dr. | Glenn | Carr | garnervalerie@farrell-parsons.biz | 1998-04-19 | 
        
        
        ## How does it work?
        `pynonymizer` replaces personally identifiable data in your database with **realistic** pseudorandom data, from the `Faker` library or from other functions.
        There are a wide variety of data types available which should suit the column in question, for example:
        
        * `unique_email`
        * `company`
        * `file_path`
        * `[...]`
        
        For a full list of data generation strategies, see the docs on [strategyfiles](https://gitlab.com/jerometwell/pynonymizer/blob/master/doc/strategyfiles.md)
        
        ### Process outline
        
        1. Restore from dumpfile to temporary database.
        1. Anonymize temporary database with strategy.
        1. Dump resulting data to file.
        1. Drop temporary database.
        
        If this workflow doesnt work for you, see [process control](https://gitlab.com/jerometwell/pynonymizer/blob/master/doc/process-control.md) to see if it can be adjusted to suit your needs.
        
        ## Requirements
        * Python >= 3.6
        
        ### mysql
        * `mysql`/`mysqldump` Must be in $PATH
        * backup file in plain .sql/sql.gz (schema and data)
        * Local or remote mysql >= 5.5
        
        ### mssql
        * Requires extra dependencies: install package `pynonymizer[mssql]`
        * MSSQL >= 2008
        * Due to backup/restore limitations, you must be running pynonymizer on the *same server* as the database engine.
        * A backup in `.bak` format
        
        ### postgres
        * `psql`/`pg_dump` Must be in $PATH
        * backup file in plain .sql/sql.gz (schema and data)
        * Local or remote postgres server
        
        # Getting Started
        
        ## Usage
        1. Write a [strategyfile](https://gitlab.com/jerometwell/pynonymizer/blob/master/doc/strategyfiles.md) for your database
        1. See below:
        ```
        usage: pynonymizer [-h] [--input INPUT] [--strategy STRATEGYFILE]
                           [--output OUTPUT] [--db-type DB_TYPE] [--db-host DB_HOST]
                           [--db-name DB_NAME] [--db-user DB_USER]
                           [--db-password DB_PASSWORD] [--fake-locale FAKE_LOCALE]
                           [--start-at STEP] [--skip-steps STEP [STEP ...]]
                           [--stop-at STEP] [--seed-rows SEED_ROWS]
                           [--mssql-backup-compression] [-v]
        
        A tool for writing better anonymization strategies for your production
        databases.
        
        optional arguments:
          -h, --help            show this help message and exit
          --input INPUT, -i INPUT
                                The source dumpfile to read from. [$PYNONYMIZER_INPUT]
          --strategy STRATEGYFILE, -s STRATEGYFILE
                                A strategyfile to use during anonymization.
                                [$PYNONYMIZER_STRATEGY]
          --output OUTPUT, -o OUTPUT
                                The destination to write the dumped output to.
                                [$PYNONYMIZER_OUTPUT]
          --db-type DB_TYPE, -t DB_TYPE
                                Type of database to interact with. More databases will
                                be supported in future versions. default: mysql
                                [$PYNONYMIZER_DB_TYPE]
          --db-host DB_HOST, -d DB_HOST
                                Database hostname or IP address.
                                [$PYNONYMIZER_DB_HOST]
          --db-name DB_NAME, -n DB_NAME
                                Name of database to restore and anonymize in. If not
                                provided, a unique name will be generated from the
                                strategy name. This will be dropped at the end of the
                                run. [$PYNONYMIZER_DB_NAME]
          --db-user DB_USER, -u DB_USER
                                Database credentials: username. [$PYNONYMIZER_DB_USER]
          --db-password DB_PASSWORD, -p DB_PASSWORD
                                Database credentials: password. Recommended: use
                                environment variables to avoid exposing secrets in
                                production environments. [$PYNONYMIZER_DB_PASSWORD]
          --fake-locale FAKE_LOCALE, -l FAKE_LOCALE
                                Locale setting to initialize fake data generation.
                                Affects Names, addresses, formats, etc.
                                [$PYNONYMIZER_FAKE_LOCALE]
          --start-at STEP       Choose a step to begin the process (inclusive).
                                [$PYNONYMIZER_START_AT]
          --skip-steps STEP [STEP ...]
                                Choose one or more steps to skip.
                                [$PYNONYMIZER_SKIP_STEPS]
          --stop-at STEP        Choose a step to stop at (inclusive).
                                [$PYNONYMIZER_STOP_AT]
          --seed-rows SEED_ROWS
                                Specify a number of rows to populate the fake data
                                table used during anonymization.
                                [$PYNONYMIZER_SEED_ROWS]
          --mssql-backup-compression
                                [MSSQL] Use compression when backing up the database.
                                [$PYNONYMIZER_MSSQL_BACKUP_COMPRESSION]
          -v, --version         show program's version number and exit
        ```
        
        ## License
        
        [MIT](https://gitlab.com/jerometwell/pynonymizer/blob/master/LICENSE)
        
Keywords: anonymization gdpr database mysql
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: License :: OSI Approved :: MIT License
Classifier: Topic :: Database
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python :: 3.6
Description-Content-Type: text/markdown
Provides-Extra: mssql
