oprf 5.0.0

Oblivious pseudo-random function (OPRF) protocol functionality implementations based on Curve25519 and the Ristretto group.

Oblivious pseudo-random function (OPRF) protocol functionality implementations based on Curve25519 and the Ristretto group.

Purpose

This library provides data structures and methods for a basic oblivious pseudo-random function (OPRF) protocol. Method implementations rely on cryptographic primitives involving the Ristretto group that are exported by the oblivious library. By default, these are wrappers for functions found in the subset of the libsodium library that is bundled with the rbcl library.

Installation and Usage

This library is available as a package on PyPI:

python -m pip install oprf

By default, this library indirectly relies on rbcl (which bundles a subset of the libsodium library that is compiled for common architectures). However, it is possible to install a fully working pure-Python version of this library by installing only the pure-Python subset of the oblivious dependency (i.e., within an environment where rbcl is not a required dependency of other installed packages). This approach makes it possible to use this library for rapid prototyping on exotic architectures (with the caveat that pure-Python implementations of primitives are much slower):

python -m pip install oblivious~=7.0
python -m pip install oprf --no-dependencies

The library can be imported in the usual ways:

import oprf
from oprf import *

Examples

This library makes it possible to concisely prepare binary or string data for masking:

>>> from oprf import data, mask
>>> d = data.hash('abc')

A random mask can be constructed and applied to the data. A number of distinct notations is supported for masking in order to minimize differences between the notation within a protocol definition and its implementation:

>>> m = mask() # Create random mask.
>>> m.mask(d) == m(d) == m * d
True
>>> m(d) == d
False

Mask inversion and unmasking are also supported:

>>> c = m(d)
>>> m.unmask(c) == (~m)(c) == c / m == d
True

Masks can also be constructed deterministically from a bytes-like object or string:

>>> m = mask.hash('123')

Because the classes data and mask are derived from bytes, all methods and other operators supported by bytes objects are supported by data and mask objects:

>>> hex = 'a665a45920422f9d417e4867efdc4fb8a04a1f3fff1fa07e998e86f7f7a27a03'
>>> m = mask.fromhex(hex)
>>> m.hex()
'a665a45920422f9d417e4867efdc4fb8a04a1f3fff1fa07e998e86f7f7a27a03'

In addition, Base64 conversion methods are included to support concise encoding and decoding of data and mask objects:

>>> d.from_base64(d.to_base64()) == d
True
>>> m.from_base64(m.to_base64()) == m
True

Development

All installation and development dependencies are fully specified in pyproject.toml. The project.optional-dependencies object is used to specify optional requirements for various development tasks. This makes it possible to specify additional options (such as docs, lint, and so on) when performing installation using pip:

python -m pip install .[docs,lint]

Documentation

The documentation can be generated automatically from the source files using Sphinx:

python -m pip install .[docs]
cd docs
sphinx-apidoc -f -E --templatedir=_templates -o _source .. && make html

Testing and Conventions

All unit tests are executed and their coverage is measured when using pytest (see the pyproject.toml file for configuration details):

python -m pip install .[test]
python -m pytest

Alternatively, all unit tests are included in the module itself and can be executed using doctest:

python src/oprf/oprf.py -v

Style conventions are enforced using Pylint:

python -m pip install .[lint]
python -m pylint src/oprf

Contributions

In order to contribute to the source code, open an issue or submit a pull request on the GitHub page for this library.

Versioning

The version number format for this library and the changes to the library associated with version number increments conform with Semantic Versioning 2.0.0.

Publishing

This library can be published as a package on PyPI by a package maintainer. First, install the dependencies required for packaging and publishing:

python -m pip install .[publish]

Ensure that the correct version number appears in pyproject.toml, and that any links in this README document to the Read the Docs documentation of this package (or its dependencies) have appropriate version numbers. Also ensure that the Read the Docs project for this library has an automation rule that activates and sets as the default all tagged versions. Create and push a tag for this version (replacing ?.?.? with the version number):

git tag ?.?.?
git push origin ?.?.?

Remove any old build/distribution files. Then, package the source into a distribution archive:

rm -rf build dist src/*.egg-info
python -m build --sdist --wheel .

Finally, upload the package distribution archive to PyPI:

python -m twine upload dist/*