pganonymize

A commandline tool to anonymize PostgreSQL databases for DSGVO/GDPR purposes.

It uses a YAML file to define which tables and fields should be anonymized and provides various methods of anonymization. The tool requires a direct PostgreSQL connection to perform the anonymization.

PyPI - Python Version

https://raw.githubusercontent.com/rheinwerk-verlag/pganonymize/main/docs/_static/demo.gif

Features

Intentionally compatible with Python 2.7 (for old, productive platforms)
Anonymize PostgreSQL tables on data level entry with various providers (some examples in the table below)
Exclude data for anonymization depending on regular expressions or SQL WHERE clauses
Truncate entire tables for unwanted data

Field	Value	Provider	Output
first_name	John	choice	(Bob\|Larry\|Lisa)
title	Dr.	clear
street	Irving St	faker.street_name	Miller Station
password	dsf82hFxcM	mask	XXXXXXXXXX
credit_card	1234-567-890	partial_mask	1??????????0
email	jane.doe@example.com	md5	0cba00ca3da1b283a57287bcceb17e35
email	jane.doe@example.com	faker.unique.email	alex7@sample.com
phone_num	65923473	md5 as_number: True	3948293448
ip	157.50.1.20	set	127.0.0.1
uuid_col	00010203-0405-……	uuid4	f7c1bd87-4d….

Note: faker.unique.[provider] only supported on Python 3.6+ (Faker library min. supported python version)
Note: uuid4 - only for (native uuid4) columns

See the documentation for a more detailed description of the provided anonymization methods.

Installation

The default installation method is to use pip:

$ pip install pganonymize

Usage

usage: pganonymize [-h] [-v] [-l] [--schema SCHEMA] [--dbname DBNAME]
               [--user USER] [--password PASSWORD] [--host HOST]
               [--port PORT] [--dry-run] [--dump-file DUMP_FILE]

Anonymize data of a PostgreSQL database

optional arguments:
-h, --help            show this help message and exit
-v, --verbose         Increase verbosity
-l, --list-providers  Show a list of all available providers
--schema SCHEMA       A YAML schema file that contains the anonymization
                        rules
--dbname DBNAME       Name of the database
--user USER           Name of the database user
--password PASSWORD   Password for the database user
--host HOST           Database hostname
--port PORT           Port of the database
--dry-run             Don't commit changes made on the database
--dump-file DUMP_FILE
                      Create a database dump file with the given name
--dump-options DUMP_OPTIONS
                      Options to pass to the pg_dump command
--init-sql INIT_SQL   SQL to run before starting anonymization
--parallel            Data anonymization is done in parallel

Despite the database connection values, you will have to define a YAML schema file, that includes all anonymization rules for that database. Take a look at the schema documentation or the YAML sample schema.

Example calls:

$ pganonymize --schema=myschema.yml \
    --dbname=test_database \
    --user=username \
    --password=mysecret \
    --host=db.host.example.com \
    -v

$ pganonymize --schema=myschema.yml \
    --dbname=test_database \
    --user=username \
    --password=mysecret \
    --host=db.host.example.com \
    --init-sql "set search_path to non_public_search_path; set work_mem to '1GB';" \
    -v

Database dump

With the --dump-file argument it is possible to create a dump file after anonymizing the database. Please note, that the pg_dump command from the postgresql-client-common library is necessary to create the dump file for the database, e.g. under Linux:

$ sudo apt-get install postgresql-client-common

Example call:

$ pganonymize --schema=myschema.yml \
    --dbname=test_database \
    --user=username \
    --password=mysecret \
    --host=db.host.example.com \
    --dump-file=/tmp/dump.gz \
    -v

So that the password for dumping does not have to be entered manually, it can also be entered as an environment var PGPASSWORD:

$ PGPASSWORD=password pganonymize --schema=myschema.yml \
    --dbname=test_database \
    --user=username \
    --password=mysecret \
    --host=db.host.example.com \
    --dump-file=/tmp/dump.gz \
    -v

Docker

If you want to run the anonymizer within a Docker container you first have to build the image:

$ docker build -t pganonymize .

After that you can pass a schema file to the container, using Docker volumes, and call the anonymizer:

$ docker run \
    -v <path to your schema>:/schema.yml \
    -it pganonymize \
    /usr/local/bin/pganonymize \
    --schema=/schema.yml \
    --dbname=<database> \
    --user=<user> \
    --password=<password> \
    --host=<host> \
    -v

Release files for pganonymize 0.13.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for pganonymize 0.13.0
File	Size	Uploaded
pganonymize-0.13.0.tar.gz	24.8 kB	Aug 6, 2026	Details

Built distribution (wheel)

Table of built distributions (wheels) for pganonymize 0.13.0
File	Interpreter	ABI	Platform	Reset
pganonymize-0.13.0-py2.py3-none-any.whl 16.1 kB Aug 6, 2026	Python 2, Python 3	none	any	Details

Total release size: 41.0 kB

Release files / pganonymize-0.13.0.tar.gz

Download URL	pganonymize-0.13.0.tar.gz
Size	24.8 kB
Tags	Source
SHA-256 checksum How to use checksums	`9dc1d7b6fca93de2c3b189198b0344234f0c0ee1385ec7bd48e97d4ef05af5cf`
BLAKE2b-256 checksum How to use checksums	`047b3f72694cf96462a37bf5682e69fb8a9f431f64dbdca21c6eb293e4bb540b`
Upload date	Aug 6, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/7.0.0 CPython/3.13.14`

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

Identity

Publishing platform: GitHub Actions
Publishing repository: github.com/rheinwerk-verlag/pganonymize
Publishing commit: github.com/rheinwerk-verlag/pganonymize/tree/e5a59e59591b6c85a3c007bac5710df37f7442e0

Workflow

Publishing configuration: github.com/rheinwerk-verlag/pganonymize/blob/e5a59e59591b6c85a3c007bac5710df37f7442e0/.github/workflows/publish.yml
Publishing logs: github.com/rheinwerk-verlag/pganonymize/actions/runs/31107426378/attempts/1

Artifact

Subject: pganonymize-0.13.0.tar.gz
SHA-256 checksum: 9dc1d7b6fca93de2c3b189198b0344234f0c0ee1385ec7bd48e97d4ef05af5cf Verifying attestations

Release files / pganonymize-0.13.0-py2.py3-none-any.whl

Download URL	pganonymize-0.13.0-py2.py3-none-any.whl
Size	16.1 kB
Tags	Python 2 Python 3
SHA-256 checksum How to use checksums	`0f81d2ad4cc18bd5cccfaed327716071ccaa34a6319bb62c5bc3144f14df00b8`
BLAKE2b-256 checksum How to use checksums	`a228bcad30cd42e74c6c9b8b96ac8f40a4a860564077adf14e8704a2fe848a99`
Upload date	Aug 6, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/7.0.0 CPython/3.13.14`

Provenance

Identity

Publishing platform: GitHub Actions
Publishing repository: github.com/rheinwerk-verlag/pganonymize
Publishing commit: github.com/rheinwerk-verlag/pganonymize/tree/e5a59e59591b6c85a3c007bac5710df37f7442e0

Workflow

Publishing configuration: github.com/rheinwerk-verlag/pganonymize/blob/e5a59e59591b6c85a3c007bac5710df37f7442e0/.github/workflows/publish.yml
Publishing logs: github.com/rheinwerk-verlag/pganonymize/actions/runs/31107426378/attempts/1

Artifact

Subject: pganonymize-0.13.0-py2.py3-none-any.whl
SHA-256 checksum: 0f81d2ad4cc18bd5cccfaed327716071ccaa34a6319bb62c5bc3144f14df00b8 Verifying attestations