PyExpert 0.0.1

This is a small embeddable Prolog interpreter in Python3, designed primarily for implementing explainable expert systems.

Usage:

# Imports
from weak.prolog import prolog_driver,prolog_default_env,prolog_next_solution,prolog_core_library

# Initialise environment
env = prolog_default_env()

# Execute query
ret,vars = prolog_driver(env, '? append(A, B, [x,y]).')
print(vars)

# Inspect all the remaining solutions
while prolog_next_solution(env):
    print(vars)

Weak sets

The main feature of this implementation is a weak set - a value that unifies with any other weak set, resulting in a new set containing elements of both sets. This is useful for implementing certain kinds of type systems and for higher level hacks, such as tracing a Prolog execution (e.g., for a human-readable narration of an expert system decision), implementing constraints, etc.

For example:

? weak(a,W1), weak(b,W1), weak(c,W2), W1=W2.

results in W1=W2=[a,b,c]

See weak/narrate.py for an example of an instrumentation of a Prolog code for producing execution traces, or a "narration", which can then be used to generate, for example, a plain English narration of the expert system thought process.

See tests/demo.py for an example of constructing an explainable expert system.