circuitry 1.0.0

Embedded domain-specific combinator library for the abstract assembly and automated synthesis of logical circuits.

Embedded domain-specific combinator library for the abstract assembly and automated synthesis of logical circuits.

Purpose

This embedded domain-specific language (DSL) makes it possible to write an algorithm in Python that operates on bit values and/or bit vectors, and then to interpret that algorithm implementation as a circuit definition in order to synthesize automatically a logical circuit represented using the circuit library. Additional background information and examples can be found in a relevant report.

Package Installation and Usage

The package is available on PyPI:

python -m pip install circuitry

The library can be imported in the usual ways:

import circuitry
from circuitry import *

Examples

This library makes it possible to embed within Python a function that operates on individual bits and/or bit vectors (subject to specific limitations) and then to automatically synthesize a logical circuit that implements that function. In the simple example below, the defined bit equality function takes two bit objects as its inputs and returns one bit object as its output. Because nearly all built-in Python operators are supported by the bit class via appropriate method definitions (e.g., see the __or__ method), the statements and expressions in the function can employ a straightforward and familiar syntax:

>>> from circuitry import *
>>> @synthesize
... def equal(x: bit, y: bit) -> bit:
...     return (x & y) | ((1 - x) & (1 - y))

The function itself can be invoked in the usual manner if the supplied inputs are integers or instances of the bit class:

>>> equal(0, 1)
0
>>> b = equal(bit(0), bit(1))
>>> isinstance(b, bit)
True
>>> int(b)
0

The synthesize decorator automatically synthesizes the corresponding circuit (as an instance of the circuit class defined in the circuit library). The synthesized circuit object is stored within an attribute of the function itself and can be evaluated on two bit values (as specified by the function’s type annotation). See the documentation of the circuit library for more information on how input bit vectors should be structured when evaluating a circuit:

>>> equal.circuit.evaluate([[0], [1]])
[[0]]

The synthesize decorator can also be applied to functions that are defined explicitly as operating on bit vectors (where bit vectors can be represented as lists of integers or as bits objects). Furthermore, functions can be invoked in other functions, making it possible to reuse modular algorithm components. In the example below, the bit vector equality function invokes the bit equality function defined above:

>>> @synthesize
... def equals(xs: bits(8), ys: bits(8)) -> bit:
...     z = 1
...     for i in range(8):
...         z = z & equal(xs[i], ys[i])
...     return z
>>> bs = [0, 1, 1, 0, 1, 0, 1, 0]
>>> equals.circuit.evaluate([bs, bs])
[[1]]
>>> equals.circuit.count() # Number of gates in circuit.
66

Because a circuit is synthesized via standard execution of a decorated Python function, all native Python language features (and even external libraries) can be employed. The most important constraint (which is the responsibility of the programmer to maintain) is that the execution of the function (i.e., the flow of control) should not depend on the values of the inputs bits. The alternative implementation below demonstrates that recursion and higher-order functions can be used within decorated functions:

>>> from functools import reduce
>>> @synthesize
... def equals(xs: bits(8), ys: bits(8)) -> bit:
...     es = [equal(x, y) for (x, y) in zip(xs, ys)]
...     return reduce((lambda e0, e1: e0 & e1), es)
>>> bs = [0, 1, 1, 0, 1, 0, 1, 0]
>>> equals.circuit.evaluate([bs, list(reversed(bs))])
[[0]]
>>> equals.circuit.count() # Number of gates in circuit.
64

A more complex example involving an implementation of SHA-265 that conforms to the FIPS 180-4 specification is found in the testing script that accompanies this library. The SHA-256 example is also described in a relevant report.

Documentation

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

cd docs
python -m pip install -r requirements.txt
sphinx-apidoc -f -E --templatedir=_templates -o _source .. ../setup.py && make html

Testing and Conventions

All unit tests are executed and their coverage is measured when using pytest (see setup.cfg for configuration details):

python -m pip install pytest pytest-cov
python -m pytest

The subset of the unit tests included in the module itself and the documentation examples that appear in the testing script can be executed separately using doctest:

python circuitry/circuitry.py -v
python test/test_circuitry.py -v

Style conventions are enforced using Pylint:

python -m pip install pylint
python -m pylint circuitry ./test/test_circuitry.py

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

Beginning with version 0.1.0, 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. Install the wheel package, remove any old build/distribution files, and package the source into a distribution archive:

python -m pip install wheel
rm -rf dist *.egg-info
python setup.py sdist bdist_wheel

Next, install the twine package and upload the package distribution archive to PyPI:

python -m pip install twine
python -m twine upload dist/*