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Resolution theorem proving for predicate logic in pure Python.

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PyProver

PyProver is a resolution theorem prover for first-order predicate logic. PyProver is written in Coconut which compiles to pure, universal Python, allowing PyProver to work on any Python version.

Installing PyProver is as simple as

pip install pyprover

Usage

To use PyProver from a Python interpreter, it is recommended to

from pyprover import *

which will populate the global namespace with capital letters as propositions/predicates, and lowercase letters as constants/variables/functions. When using PyProver from a Python file, however, it is recommended to only import what you need.

Formulas can be constructed using the built-in Python operators on propositions and terms combined with Exists (or EX), ForAll (or FA), Eq, top, and bot. For example:

A & B
A | ~B
~(A | B)
P >> Q
P >> (Q >> P)
(F & G) >> H
E >> top
bot >> E
FA(x, F(x))
TE(x, F(x) | G(x))
FA(x, F(f(x)) >> F(x))
Eq(a, b)

Alternatively, the expr(formula) function can be used, which parses a formula in standard mathematical notation. For example:

F ∧ G ∨ (C → ¬D)
F /\ G \/ (C -> ~D)
F & G | (C -> -D)
⊤ ∧ ⊥
top /\ bot
F -> G -> H
A x. F(x) /\ G(x)
∀x. F(x) /\ G(x)
E x. C(x) \/ D(x)
∃x. C(x) \/ D(x)
∀x. ∃y. G(f(x, y))
a = b
forall x: A, B(x)
exists x: A, B(x)

Note that expr requires propositions/predicates to start with a capital letter and constants/variables/functions to start with a lowercase letter.

Once a formula has been constructed, various functions are provided to work with them. Some of the most important of these are:

  • strict_simplify(expr) finds an equivalent, standardized version of the given expr,
  • simplify(expr) is the same as strict_simplify, but it implicitly assumes TE(x, top) (something exists),
  • strict_proves(givens, concl) determines if concl can be derived from givens, and
  • proves(givens, concl) is the same as strict_proves, but it implicitly assumes TE(x, top) (something exists).

To construct additional propositions/predicates, the function props("name1 name2 name3 ...") will return propositions/predicates for the given names, and to construct additional constants/variables/functions, the function terms("name1 name2 name3 ...") can be used similarly.

Examples

The backtick infix syntax here is from Coconut. If using Python instead simply adjust to standard function call syntax.

from pyprover import *

# constructive propositional logic
assert (E, E>>F, F>>G) `proves` G
assert (E>>F, F>>G) `proves` E>>G

# classical propositional logic
assert ~~E `proves` E
assert top `proves` (E>>F)|(F>>E)

# constructive predicate logic
assert R(j) `proves` TE(x, R(x))
assert (FA(x, R(x) >> S(x)), TE(y, R(y))) `proves` TE(z, S(z))

# classical predicate logic
assert ~FA(x, R(x)) `proves` TE(y, ~R(y))
assert top `proves` TE(x, D(x)) | FA(x, ~D(x))

# use of expr parser
assert expr(r"A x. E y. F(x) \/ G(y)") == FA(x, TE(y, F(x) | G(y)))
assert expr(r"a = b /\ b = c") == Eq(a, b) & Eq(b, c)

Compiling PyProver

If you want to compile PyProver yourself instead of installing it from PyPI with pip, you can

  1. clone the git repository,
  2. run make setup, and
  3. run make install.