datamasque-python
Official Python client for the DataMasque platform.
DataMasque is a data masking platform that replaces sensitive data with realistic but non-production values, so teams can use production-shaped data in non-production environments without exposing PII. This package is a thin Python wrapper around the DataMasque server’s HTTP API, covering connection management, ruleset and ruleset-library CRUD, masking run lifecycle, discovery results, user administration, and license management.
Installation
pip install datamasque-pythonPython 3.9 or newer is required.
Quickstart
from datamasque.client import DataMasqueClient
from datamasque.client.models.dm_instance import DataMasqueInstanceConfig
config = DataMasqueInstanceConfig(
base_url="https://datamasque.example.com",
username="api_user",
password="api_password",
)
client = DataMasqueClient(config)
client.authenticate()
for connection in client.list_connections():
print(connection.name)Authentication is performed on the first request if authenticate() is not called explicitly, and is automatically retried once on a 401 response. client.healthcheck() is available as a lightweight readiness probe that does not consume credentials.
For a DataMasque instance hosted on Snowpark Container Services (SPCS) (a *.snowflakecomputing.app base_url), pass a Snowflake Programmatic Access Token as spcs_pat on DataMasqueInstanceConfig. See the usage docs for details.
Error handling
All methods raise subclasses of DataMasqueException on failure:
DataMasqueApiError — the server responded with a non-2xx status (excluding 502). The triggering Response is available on the .response attribute.
DataMasqueNotReadyError — the server responded with 502, typically because it is still starting up.
DataMasqueTransportError — the request failed before any response was received (connection refused, timeout, DNS failure, SSL handshake failure, etc.).
FailedToStartError / InvalidRulesetError / InvalidLibraryError — raised by start_masking_run when the server rejects the run.
DataMasqueUserError — raised by user-management methods when the input is invalid.
Documentation
All classes and functions have docstrings and type hints.
Compiled docs are hosted at Read the Docs: datamasque-python.
Documentation for the DataMasque product, including a full API reference, can be found on the DataMasque portal.
Contributing
See CONTRIBUTING.rst for development setup, testing, and the pull request flow.
License
Apache License 2.0. See LICENSE.
1 maintainer
Metadata
1 maintainer
Release files for datamasque-python 1.3.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| datamasque_python-1.3.1.tar.gz | 211.1 kB | With provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| datamasque_python-1.3.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 289.0 kB
Release files / datamasque_python-1.3.1.tar.gz
| Download URL | datamasque_python-1.3.1.tar.gz |
|---|---|
| Size | 211.1 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
c6ec9ef4e857172ce51fe8443b0c179411f12be9d765103566b7c690c0d848bf
|
|
BLAKE2b-256 checksum How to use checksums |
e05201dbcc78afc2eef1a110da941c2801e7b02210110acccd5a993cd4fe915f
|
| Upload date | |
|
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.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Sep 9, 2026.
Transparency logRelease files / datamasque_python-1.3.1-py3-none-any.whl
| Download URL | datamasque_python-1.3.1-py3-none-any.whl |
|---|---|
| Size | 77.9 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
61139f8162c85cef8b4aff4a4c2583f16fa6c48ab98798f7649e822430a54668
|
|
BLAKE2b-256 checksum How to use checksums |
826c8f1536a6b26d64a49686e2b5c3c86729fb1542ab885d4eb64b817e557dec
|
| Upload date | |
|
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.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Sep 9, 2026.
Transparency logSecurity for datamasque-python 1.3.1
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.
Full provenance
All 2 files in this release have been uploaded with provenance metadata.
Attestation for datamasque_python-1.3.1.tar.gz
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Sep 9, 2026.
Transparency logA note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
