tinybook

Minimal pure-Python library that demonstrates a basic workflow for an encrypted order book by leveraging a secure multi-party computation (MPC) protocol.

Purpose

This library demonstrates how a functionality can be implemented using a secure multi-party computation (MPC) protocol for evaluating arithmetic sum-of-products expressions (as implemented in tinynmc). The approach used in this library can serve as a template for any workflow that relies on multiple simultaneous instances of such a protocol.

Installation and Usage

This library is available as a package on PyPI:

python -m pip install tinybook

The library can be imported in the usual way:

import tinybook
from tinybook import *

Basic Example

Suppose that a secure decentralized voting workflow is supported by three parties. The node objects would be instantiated locally by each of these three parties:

>>> nodes = [node(), node(), node()]

The preprocessing workflow that the nodes must execute can be simulated. It is assumed that all permitted prices are integers greater than or equal to 0 and strictly less than a fixed maximum value. The number of distinct prices can be supplied to the preprocessing simulation:

>>> preprocess(nodes, prices=16)

A request must be submitted for the opportunity to submit an order. Below, two clients each create their request (one for an ask order and the other for a bid order):

>>> request_ask = request.ask()
>>> request_bid = request.bid()

Each client can deliver their request to each node, and each node can then locally generate masks that can be returned to the requesting client:

>>> masks_ask = [node.masks(request_ask) for node in nodes]
>>> masks_bid = [node.masks(request_bid) for node in nodes]

Each client can then generate locally an order instance (i.e., a masked representation of the order):

>>> order_ask = order(masks_ask, 4)
>>> order_bid = order(masks_bid, 9)

Each client can broadcast its masked order to all the nodes. Each node can locally assemble these as they arrive. Once a node has received both masked orders, it can determine its shares of the overall outcome:

>>> shares = [node.outcome(order_ask, order_bid) for node in nodes]

The overall outcome can be reconstructed from the shares by the workflow operator. The outcome is either None (if the bid price does not equal or exceed the ask price) or a range instance representing the bid-ask spread (where for a range instance r, the ask price is min(r) and the bid price is max(r)):

>>> reveal(shares)
range(4, 10)
>>> min(reveal(shares))
4
>>> max(reveal(shares))
9

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/tinybook/tinybook.py -v

Style conventions are enforced using Pylint:

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

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/*