Quickstart Guide

First, we create two constants x and y of sort Real , and two constants a and b of sort Integer . Notice that these are symbolic constants, but not actual values.

x, y = Reals('x y')
a, b = Ints('a b')

We define the following constraints regarding x and y :

\[(0 < x) \wedge (0 < y) \wedge (x + y < 1) \wedge (x \leq y)\]

We check whether there is a solution to these constraints:

solve(0 < x, 0 < y, x + y < 1, x <= y)

In this case, there is, so we get output:

[x = 1/6, y = 1/6]

We can also get an explicit model (assignment) for the constraints.

s = Solver()
s.add(0 < x, 0 < y, x + y < 1, x <= y)
assert sat == s.check()
m = s.model()

With the model, we can evaluate variables and terms:

print('x:', m[x])
print('y:', m[y])
print('x - y:', m[x - y])

This will print:

x: 1/6
y: 1/6
x - y: 0

We can also get these values in other forms:

print('string x:', str(m[x]))
print('decimal x:', m[x].as_decimal(4))
print('fraction x:', m[x].as_fraction())
print('float x:', float(m[x].as_fraction()))

Next, we assert the same assertions as above, but with integers. This time, there is no solution, so “no solution” is printed.

solve(0 < a, 0 < b, a + b < 1, a <= b)

Example

examples/api/python/quickstart.py

  1 #!/usr/bin/env python
  2 ###############################################################################
  3 # Top contributors (to current version):
  4 #   Yoni Zohar, Aina Niemetz, Alex Ozdemir
  5 #
  6 # This file is part of the cvc5 project.
  7 #
  8 # Copyright (c) 2009-2022 by the authors listed in the file AUTHORS
  9 # in the top-level source directory and their institutional affiliations.
 10 # All rights reserved.  See the file COPYING in the top-level source
 11 # directory for licensing information.
 12 # #############################################################################
 13 #
 14 # A simple demonstration of the api capabilities of cvc5, adapted from quickstart.cpp
 15 ##
 16 
 17 import cvc5
 18 from cvc5 import Kind
 19 
 20 if __name__ == "__main__":
 21   # Create a solver
 22   #! [docs-python-quickstart-1 start]
 23   solver = cvc5.Solver()
 24   #! [docs-python-quickstart-1 end]
 25 
 26   # We will ask the solver to produce models and unsat cores,
 27   # hence these options should be turned on.
 28   #! [docs-python-quickstart-2 start]
 29   solver.setOption("produce-models", "true");
 30   solver.setOption("produce-unsat-cores", "true");
 31   #! [docs-python-quickstart-2 end]
 32 
 33   # The simplest way to set a logic for the solver is to choose "ALL".
 34   # This enables all logics in the solver.
 35   # Alternatively, "QF_ALL" enables all logics without quantifiers.
 36   # To optimize the solver's behavior for a more specific logic,
 37   # use the logic name, e.g. "QF_BV" or "QF_AUFBV".
 38 
 39   # Set the logic
 40   #! [docs-python-quickstart-3 start]
 41   solver.setLogic("ALL");
 42   #! [docs-python-quickstart-3 end]
 43 
 44   # In this example, we will define constraints over reals and integers.
 45   # Hence, we first obtain the corresponding sorts.
 46   #! [docs-python-quickstart-4 start]
 47   realSort = solver.getRealSort();
 48   intSort = solver.getIntegerSort();
 49   #! [docs-python-quickstart-4 end]
 50 
 51   # x and y will be real variables, while a and b will be integer variables.
 52   # Formally, their python type is Term,
 53   # and they are called "constants" in SMT jargon:
 54   #! [docs-python-quickstart-5 start]
 55   x = solver.mkConst(realSort, "x");
 56   y = solver.mkConst(realSort, "y");
 57   a = solver.mkConst(intSort, "a");
 58   b = solver.mkConst(intSort, "b");
 59   #! [docs-python-quickstart-5 end]
 60 
 61   # Our constraints regarding x and y will be:
 62   #
 63   #   (1)  0 < x
 64   #   (2)  0 < y
 65   #   (3)  x + y < 1
 66   #   (4)  x <= y
 67   #
 68 
 69   #! [docs-python-quickstart-6 start]
 70   # Formally, constraints are also terms. Their sort is Boolean.
 71   # We will construct these constraints gradually,
 72   # by defining each of their components.
 73   # We start with the constant numerals 0 and 1:
 74   zero = solver.mkReal(0);
 75   one = solver.mkReal(1);
 76 
 77   # Next, we construct the term x + y
 78   xPlusY = solver.mkTerm(Kind.ADD, x, y);
 79 
 80   # Now we can define the constraints.
 81   # They use the operators +, <=, and <.
 82   # In the API, these are denoted by Plus, Leq, and Lt.
 83   constraint1 = solver.mkTerm(Kind.LT, zero, x);
 84   constraint2 = solver.mkTerm(Kind.LT, zero, y);
 85   constraint3 = solver.mkTerm(Kind.LT, xPlusY, one);
 86   constraint4 = solver.mkTerm(Kind.LEQ, x, y);
 87 
 88   # Now we assert the constraints to the solver.
 89   solver.assertFormula(constraint1);
 90   solver.assertFormula(constraint2);
 91   solver.assertFormula(constraint3);
 92   solver.assertFormula(constraint4);
 93   #! [docs-python-quickstart-6 end]
 94 
 95   # Check if the formula is satisfiable, that is,
 96   # are there real values for x and y that satisfy all the constraints?
 97   #! [docs-python-quickstart-7 start]
 98   r1 = solver.checkSat();
 99   #! [docs-python-quickstart-7 end]
100 
101   # The result is either SAT, UNSAT, or UNKNOWN.
102   # In this case, it is SAT.
103   #! [docs-python-quickstart-8 start]
104   print("expected: sat")
105   print("result: ", r1)
106   #! [docs-python-quickstart-8 end]
107 
108   # We can get the values for x and y that satisfy the constraints.
109   #! [docs-python-quickstart-9 start]
110   xVal = solver.getValue(x);
111   yVal = solver.getValue(y);
112   #! [docs-python-quickstart-9 end]
113 
114   # It is also possible to get values for compound terms,
115   # even if those did not appear in the original formula.
116   #! [docs-python-quickstart-10 start]
117   xMinusY = solver.mkTerm(Kind.SUB, x, y);
118   xMinusYVal = solver.getValue(xMinusY);
119   #! [docs-python-quickstart-10 end]
120 
121   # We can now obtain the values as python values
122   #! [docs-python-quickstart-11 start]
123   xPy = xVal.getRealValue();
124   yPy = yVal.getRealValue();
125   xMinusYPy = xMinusYVal.getRealValue();
126 
127   print("value for x: ", xPy)
128   print("value for y: ", yPy)
129   print("value for x - y: ", xMinusYPy)
130   #! [docs-python-quickstart-11 end]
131 
132   # Another way to independently compute the value of x - y would be
133   # to use the python minus operator instead of asking the solver.
134   # However, for more complex terms,
135   # it is easier to let the solver do the evaluation.
136   #! [docs-python-quickstart-12 start]
137   xMinusYComputed = xPy - yPy;
138   if xMinusYComputed == xMinusYPy:
139     print("computed correctly")
140   else:
141     print("computed incorrectly")
142   #! [docs-python-quickstart-12 end]
143 
144   # Further, we can convert the values to strings
145   #! [docs-python-quickstart-13 start]
146   xStr = str(xPy);
147   yStr = str(yPy);
148   xMinusYStr = str(xMinusYPy);
149   #! [docs-python-quickstart-13 end]
150 
151   # Next, we will check satisfiability of the same formula,
152   # only this time over integer variables a and b.
153 
154   # We start by resetting assertions added to the solver.
155   #! [docs-python-quickstart-14 start]
156   solver.resetAssertions();
157   #! [docs-python-quickstart-14 end]
158 
159   # Next, we assert the same assertions above with integers.
160   # This time, we inline the construction of terms
161   # to the assertion command.
162   #! [docs-python-quickstart-15 start]
163   solver.assertFormula(solver.mkTerm(Kind.LT, solver.mkInteger(0), a));
164   solver.assertFormula(solver.mkTerm(Kind.LT, solver.mkInteger(0), b));
165   solver.assertFormula(
166       solver.mkTerm(
167           Kind.LT, solver.mkTerm(Kind.ADD, a, b), solver.mkInteger(1)));
168   solver.assertFormula(solver.mkTerm(Kind.LEQ, a, b));
169   #! [docs-python-quickstart-15 end]
170 
171   # We check whether the revised assertion is satisfiable.
172   #! [docs-python-quickstart-16 start]
173   r2 = solver.checkSat();
174   #! [docs-python-quickstart-16 end]
175 
176   # This time the formula is unsatisfiable
177   #! [docs-python-quickstart-17 start]
178   print("expected: unsat")
179   print("result:", r2)
180   #! [docs-python-quickstart-17 end]
181 
182   # We can query the solver for an unsatisfiable core, i.e., a subset
183   # of the assertions that is already unsatisfiable.
184   #! [docs-python-quickstart-18 start]
185   unsatCore = solver.getUnsatCore();
186   print("unsat core size:", len(unsatCore))
187   print("unsat core:", unsatCore)
188   #! [docs-python-quickstart-18 end]