Update .solve() functions with typed time_limit argument

cpmpy/solvers/TEMPLATE.py

@@ -174,7 +174,7 @@ def native_model(self):
         """
         return self.TPL_model
 
-    def solve(self, time_limit=None, **kwargs):
+    def solve(self, time_limit:Optional[float]=None, **kwargs):
         """
             Call the TEMPLATE solver
 
@@ -469,7 +469,7 @@ def add(self, cpm_expr_orig):
     # Other functions from SolverInterface that you can overwrite:
     # solveAll, solution_hint, get_core
 
-    def solveAll(self, display=None, time_limit=None, solution_limit=None, call_from_model=False, **kwargs):
+    def solveAll(self, display=None, time_limit:Optional[float]=None, solution_limit=None, call_from_model=False, **kwargs):
         """
             A shorthand to (efficiently) compute all (optimal) solutions, map them to CPMpy and optionally display the solutions.
 

cpmpy/solvers/choco.py

@@ -152,7 +152,7 @@ def native_model(self):
         """
         return self.chc_model
 
-    def solve(self, time_limit=None, **kwargs):
+    def solve(self, time_limit: Optional[float]=None, **kwargs):
         """
             Call the Choco solver
 
@@ -230,7 +230,7 @@ def solve(self, time_limit=None, **kwargs):
 
         return has_sol
 
-    def solveAll(self, display=None, time_limit=None, solution_limit=None, call_from_model=False, **kwargs):
+    def solveAll(self, display=None, time_limit:Optional[float]=None, solution_limit=None, call_from_model=False, **kwargs):
         """
             Compute all (optimal) solutions, map them to CPMpy and optionally display the solutions.
 

cpmpy/solvers/cplex.py

@@ -157,7 +157,7 @@ def native_model(self):
         """
         return self.cplex_model
 
-    def solve(self, time_limit=None, **kwargs):
+    def solve(self, time_limit:Optional[float]=None, **kwargs):
         """
             Call the cplex solver
 
@@ -509,7 +509,7 @@ def solution_hint(self, cpm_vars, vals):
 
             self.cplex_model.add_mip_start(warmstart)
 
-    def solveAll(self, display=None, time_limit=None, solution_limit=None, call_from_model=False, **kwargs):
+    def solveAll(self, display=None, time_limit: Optional[float]=None, solution_limit=None, call_from_model=False, **kwargs):
         """
             Compute all solutions and optionally display the solutions.
 

cpmpy/solvers/cpo.py

@@ -151,7 +151,7 @@ def native_model(self):
         """
         return self.cpo_model
 
-    def solve(self, time_limit=None, solution_callback=None, **kwargs):
+    def solve(self, time_limit:Optional[float]=None, solution_callback=None, **kwargs):
         """
             Call the CP Optimizer solver
 
@@ -253,7 +253,7 @@ def solve(self, time_limit=None, solution_callback=None, **kwargs):
 
         return has_sol
 
-    def solveAll(self, display=None, time_limit=None, solution_limit=None, call_from_model=False, **kwargs):
+    def solveAll(self, display=None, time_limit:Optional[float]=None, solution_limit=None, call_from_model=False, **kwargs):
         """
             A shorthand to (efficiently) compute all (optimal) solutions, map them to CPMpy and optionally display the solutions.
 

cpmpy/solvers/exact.py

@@ -172,7 +172,7 @@ def _fillVars(self):
         for cpm_var, val in zip(lst_vars,exact_vals):
             cpm_var._value = bool(val) if isinstance(cpm_var, _BoolVarImpl) else val # xct value is always an int
 
-    def solve(self, time_limit=None, assumptions=None, **kwargs):
+    def solve(self, time_limit:Optional[float]=None, assumptions=None, **kwargs):
         """
             Call Exact
 
@@ -274,7 +274,7 @@ def _update_time(self, timelim, start, end):
             if timelim == 0: timelim = -1
         return timelim
 
-    def solveAll(self, display=None, time_limit=None, solution_limit=None, call_from_model=False, **kwargs):
+    def solveAll(self, display=None, time_limit:Optional[float]=None, solution_limit=None, call_from_model=False, **kwargs):
         """
             Compute all solutions and optionally, display the solutions.
 

cpmpy/solvers/gcs.py

@@ -96,6 +96,7 @@ def supported():
         # try to import the package
         try:
             import gcspy
+            pkg_resources.require("gcspy>=0.1.8")
             return True
         except ModuleNotFoundError:
             return False
@@ -148,7 +149,7 @@ def native_model(self):
     def has_objective(self):
         return self.objective_var is not None
 
-    def solve(self, time_limit=None, prove=False, proof_name=None, proof_location=".", 
+    def solve(self, time_limit:Optional[float]=None, prove=False, proof_name=None, proof_location=".",
               verify=False, verify_time_limit=None, veripb_args = [], display_verifier_output=True, **kwargs):
         """
             Run the Glasgow Constraint Solver, get just one (optimal) solution.
@@ -250,7 +251,7 @@ def solve(self, time_limit=None, prove=False, proof_name=None, proof_location=".
 
         return has_sol
 
-    def solveAll(self, time_limit=None, display=None, solution_limit=None, call_from_model=False, 
+    def solveAll(self, time_limit:Optional[float]=None, display=None, solution_limit=None, call_from_model=False,
                  prove=False, proof_name=None, proof_location=".", verify=False, verify_time_limit=None, veripb_args = [], 
                  display_verifier_output=True, **kwargs):
         """

cpmpy/solvers/gurobi.py

@@ -151,7 +151,7 @@ def native_model(self):
         return self.grb_model
 
 
-    def solve(self, time_limit=None, solution_callback=None, **kwargs):
+    def solve(self, time_limit:Optional[float]=None, solution_callback=None, **kwargs):
         """
             Call the gurobi solver
 
@@ -499,7 +499,7 @@ def solution_hint(self, cpm_vars, vals):
         for cpm_var, val in zip(cpm_vars, vals):
             self.solver_var(cpm_var).setAttr("VarHintVal", val)
 
-    def solveAll(self, display=None, time_limit=None, solution_limit=None, call_from_model=False, **kwargs):
+    def solveAll(self, display=None, time_limit:Optional[float]=None, solution_limit=None, call_from_model=False, **kwargs):
         """
             Compute all solutions and optionally display the solutions.
 

cpmpy/solvers/hexaly.py

@@ -114,7 +114,7 @@ def __init__(self, cpm_model=None, subsolver=None):
     def native_model(self):
         return self.hex_model
 
-    def solve(self, time_limit=None, **kwargs):
+    def solve(self, time_limit:Optional[float]=None, **kwargs):
         """
             Call the Hexaly solver
 
@@ -397,7 +397,7 @@ def _hex_expr(self, cpm_expr):
         raise NotImplementedError(f"Unexpected expression {cpm_expr}")
 
 
-    def solveAll(self, display=None, time_limit=None, solution_limit=None, call_from_model=False, **kwargs):
+    def solveAll(self, display=None, time_limit:Optional[float]=None, solution_limit=None, call_from_model=False, **kwargs):
         """
             A shorthand to (efficiently) compute all solutions, map them to CPMpy and optionally display the solutions.
 

cpmpy/solvers/minizinc.py

@@ -289,7 +289,7 @@ def native_model(self):
         return self.mzn_model
 
 
-    def _pre_solve(self, time_limit=None, **kwargs):
+    def _pre_solve(self, time_limit:Optional[float]=None, **kwargs):
         """ shared by solve() and solveAll() """
         import minizinc
 
@@ -306,7 +306,7 @@ def _pre_solve(self, time_limit=None, **kwargs):
         kwargs['output-time'] = True  # required for time getting
         return (kwargs, mzn_inst)
 
-    def solve(self, time_limit=None, **kwargs):
+    def solve(self, time_limit:Optional[float]=None, **kwargs):
         """
             Call the MiniZinc solver
 
@@ -439,7 +439,7 @@ def mzn_time_to_seconds(self, time):
         else:
             raise NotImplementedError  # unexpected type for time
 
-    async def _solveAll(self, display=None, time_limit=None, solution_limit=None, **kwargs):
+    async def _solveAll(self, display=None, time_limit:Optional[float]=None, solution_limit=None, **kwargs):
         """ Special 'async' function because mzn.solutions() is async """
 
         # ensure all vars are known to solver
@@ -813,7 +813,7 @@ def zero_based(array):
         # default (incl name-compatible global constraints...)
         return "{}([{}])".format(expr.name, ",".join(args_str))
 
-    def solveAll(self, display=None, time_limit=None, solution_limit=None, call_from_model=False, **kwargs):
+    def solveAll(self, display=None, time_limit:Optional[float]=None, solution_limit=None, call_from_model=False, **kwargs):
         """
             Compute all solutions and optionally display the solutions.
 

cpmpy/solvers/ortools.py

@@ -142,7 +142,7 @@ def native_model(self):
         return self.ort_model
 
 
-    def solve(self, time_limit=None, assumptions=None, solution_callback=None, **kwargs):
+    def solve(self, time_limit:Optional[float]=None, assumptions=None, solution_callback=None, **kwargs):
         """
             Call the CP-SAT solver
 
@@ -277,7 +277,7 @@ def solve(self, time_limit=None, assumptions=None, solution_callback=None, **kwa
                 cpm_var._value = None
         return has_sol
 
-    def solveAll(self, display=None, time_limit=None, solution_limit=None, call_from_model=False, **kwargs):
+    def solveAll(self, display=None, time_limit:Optional[float]=None, solution_limit=None, call_from_model=False, **kwargs):
         """
             A shorthand to (efficiently) compute all solutions, map them to CPMpy and optionally display the solutions.
 

cpmpy/solvers/pindakaas.py

@@ -121,7 +121,7 @@ def __init__(self, cpm_model=None, subsolver=None):
     def native_model(self):
         return self.pdk_solver
 
-    def solve(self, time_limit=None, assumptions=None):
+    def solve(self, time_limit:Optional[float]=None, assumptions=None):
         """
         Solve the encoded CPMpy model given optional time limit and assumptions, returning whether a solution was found.
 

cpmpy/solvers/pumpkin.py

@@ -126,7 +126,7 @@ def native_model(self):
         return self.pum_solver
 
 
-    def solve(self, time_limit=None, prove=False, proof_name="proof.drcp", proof_location=".", assumptions=None):
+    def solve(self, time_limit:Optional[float]=None, prove=False, proof_name="proof.drcp", proof_location=".", assumptions=None):
         """
         Call the Pumpkin solver
 

cpmpy/solvers/pysat.py

@@ -212,7 +212,7 @@ def native_model(self):
         return self.pysat_solver
 
 
-    def solve(self, time_limit=None, assumptions=None):
+    def solve(self, time_limit:Optional[float]=None, assumptions=None):
         """
             Call the PySAT solver
 

cpmpy/solvers/pysdd.py

@@ -130,7 +130,7 @@ def native_model(self):
         """
         return self.pysdd_root
 
-    def solve(self, time_limit=None, assumptions=None):
+    def solve(self, time_limit:Optional[float]=None, assumptions=None):
         """
             See if an arbitrary model exists
 
@@ -181,7 +181,7 @@ def solve(self, time_limit=None, assumptions=None):
 
         return has_sol
 
-    def solveAll(self, display=None, time_limit=None, solution_limit=None, call_from_model=False, **kwargs):
+    def solveAll(self, display=None, time_limit:Optional[float]=None, solution_limit=None, call_from_model=False, **kwargs):
         """
             Compute all solutions and optionally display the solutions.
 

cpmpy/solvers/solver_interface.py

@@ -138,19 +138,12 @@ def objective(self, expr, minimize):
     def status(self):
         return self.cpm_status
 
-    def solve(self, model, time_limit=None):
+    def solve(self,time_limit:Optional[float]=None):
         """
-            Build the CPMpy model into solver-supported model ready for solving
-            and returns the answer (True/False/objective.value())
+            Call the underlying solver.
 
             Overwrites self.cpm_status
 
-            :param model: CPMpy model to be parsed.
-            :type model: Model
-
-            :param time_limit: optional, time limit in seconds
-            :type time_limit: int or float
-
             :return: Bool:
                 - True      if a solution is found (not necessarily optimal, e.g. could be after timeout)
                 - False     if no solution is found
@@ -236,7 +229,7 @@ def __add__(self, cpm_expr):
 
     # OPTIONAL functions
 
-    def solveAll(self, display=None, time_limit=None, solution_limit=None, call_from_model=False, **kwargs):
+    def solveAll(self, display=None, time_limit:Optional[float]=None, solution_limit=None, call_from_model=False, **kwargs):
         """
             Compute all solutions and optionally display the solutions.
 

cpmpy/solvers/z3.py

@@ -139,7 +139,7 @@ def native_model(self):
         return self.z3_solver
 
 
-    def solve(self, time_limit=None, assumptions=[], **kwargs):
+    def solve(self, time_limit:Optional[float]=None, assumptions=[], **kwargs):
         """
             Call the z3 solver