LogPy now supports commutative and associative pattern matching on expression trees. This is a standard requirement for computer algebra systems like SymPy but not a traditional feature of logic programming systems.

Pattern-matching in LogPy is expressed by the eq goal. This goal relies on unification to match trees of tuples. Unification is a computational cornerstone of LogPy. Traditionally eq performs exact structural pattern matching. For example

(1, x, (5, y, 7))  matches  (1, (2, 3, 4), (5, 6, 7))

with the following substitution

{x: (2, 3, 4), y: 6}

Expression Trees

We traditionally represent both mathematical expressions and computer programs with expression trees. For example \(y * (1 + x)\) can be visualized as follows

We represent this expression in LogPy with tuples. The head/first element of each tuple is an operation like add or mul. All subsequent elements (the tail) are the arguments/children of that expression.

y * (x + 1) -> (mul, y, (add, x, 1))

Matching Expression Trees

This form is exactly what we use for unification. We could match this pattern against the following expression, treating x and y as wildcard logic variables

(mul, y, (add, x, 1))  matches  (mul, (pow, 2, 10), (add, 3, 1))

with the following substitution

{x: 3, y: (pow, 2, 10)}

But what about the following?

(add, x, 1)  matches?  (add, 1, 3)

This doesn’t unify. While the first (add, add) and second (x, 1) elements can match (if {x: 1}) the third elements (1, 3) will not.

As mathematicians however we know that because add is commutative these expressions should match if we are allowed to rearrange the terms in the tail and match 1 to 1 and x to 3. LogPy doesn’t know this by default. LogPy is not a math library.

Building Commutative Equality

Given the goal seteq for set unification and a goal conso for head-tail pattern matching we build eq_commutative for commutative matching.

Example of seteq

run(0, x, seteq((1, 2, x), (3, 1, 2)))  # seteq matches within sets

Example of conso

run(0, head,  conso(head, tail, (1, 2, 3, 4)))
run(0, tail,  conso(head, tail, (1, 2, 3, 4)))
((2, 3, 4),)

Given these two it is easy to build eq_commutative

def eq_commutative(u, v):
    operation, utail, vtail = var(), var(), var()
    return lall(conso(operation, utail, u),
                conso(operation, vtail, v),
                seteq(utail, vtail))

That is we require all of the following (lall is logical all).

  • u must be of the form (operation, utail....)
  • v must be of the form (operation, vtail....). Note that the same variable operation must be the same in both expressions.
  • The operation must be commutative (operations register themselves beforehand, see example below)
  • utail and vtail must unify under set equality.

I am glossing over some details here, like “what about associative matching” and “how does seteq work?” but this should give a high-level view of how logic programs are made. Lets see an example of associative/commutative matching


This is the standard example for commutative matching found in the repository

from logpy import run, var, fact
from logpy.assoccomm import eq_assoccomm as eq
from logpy.assoccomm import commutative, associative

# Define some dummy Operationss
add = 'add'
mul = 'mul'

# Register that these ops are commutative using the facts system
fact(commutative, mul)
fact(commutative, add)
fact(associative, mul)
fact(associative, add)

# Define some wild variables
x, y = var('x'), var('y')

# Two expressions to match
pattern = (mul, (add, 1, x), y)                # (1 + x) * y
expr    = (mul, 2, (add, 3, 1))                # 2 * (3 + 1)
print run(0, (x,y), eq(pattern, expr))
# ((3, 2),) #  meaning one result with x matches to 3 and y matches to 2


With this LogPy contains all of the functionality of SymPy’s old unify module but in a cleaner and much more extensible form.

blog comments powered by Disqus