Update string formatting to f-strings in examples and fix getObjVal()

CHANGELOG.md

@@ -3,14 +3,16 @@
 ## Unreleased
 ### Added
 - Added more type annotations and deprecation markers to the stubs.
+- Added tests for `getObjVal()` and `getVal()`
 ### Fixed
+- Fixed incorrect `getObjVal()` result when called before `getBestSol()` (e.g., in event handlers).
 ### Changed
+- Replaced `format()` with f-strings in examples
 ### Removed
 
 ## 6.3.0 - 2026.10.11
 ### Added
-- Added the following methods with tests: `getNNodesLeft()`, `getNRuns()`, `getNReoptRuns()`, `addNNodes()`, `getDeterministicTime()`, `getAvgDualbound()`, `getMaxTotalDepth()`, `getNBacktracks()`,\
-`getFocusNode()`, `getAvgLowerbound()`, `getFirstPrimalBound()`, `getLowerboundRoot()`, `getUpperbound()`, `getNObjlimLeaves()`
+- Added the following methods with tests: `getNNodesLeft()`, `getNRuns()`, `getNReoptRuns()`, `addNNodes()`, `getDeterministicTime()`, `getAvgDualbound()`, `getMaxTotalDepth()`, `getNBacktracks()`, `getFocusNode()`, `getAvgLowerbound()`, `getFirstPrimalBound()`, `getLowerboundRoot()`, `getUpperbound()`, `getNObjlimLeaves()`
 - Added `addConsCumulative()` for SCIP cumulative constraints (#1222)
 - Added `addConsLogicor()`, `addCoefLogicor()`, `getNVarsLogicor()`, `getVarsLogicor()`, `getDualsolLogicor()` and `getDualfarkasLogicor()` for SCIP logicor constraints (#977)
 - `Expr` and `GenExpr` support `__pos__` magic method like `+Expr` or `+GenExpr`

README.md

@@ -75,8 +75,8 @@ model.setObjective(x + y)
 model.addCons(2*x - y*y >= 0)
 model.optimize()
 sol = model.getBestSol()
-print("x: {}".format(sol[x]))
-print("y: {}".format(sol[y]))
+print(f"x: {sol[x]}")
+print(f"y: {sol[y]}")
 ```
 
 Writing new plugins

docs/tutorials/eventhandler.rst

@@ -37,7 +37,7 @@ The following is an example the prints the value of the objective function whene
   from pyscipopt import Model, SCIP_EVENTTYPE
 
   def print_obj_value(model, event):
-      print("New best solution found with objective value: {}".format(model.getObjVal()))
+      print(f"New best solution found with objective value: {model.getObjVal()}")
 
   m = Model()
   m.attachEventHandlerCallback(print_obj_value, [SCIP_EVENTTYPE.BESTSOLFOUND])
@@ -72,7 +72,7 @@ and then include it in the model using the :code:`Model.includeEventHandler` met
 
         def eventexec(self, event):
             self.count += 1
-            print("!!!![@BestSolCounter] New best solution found. Total best solutions found: {}".format(self.count))
+            print(f"!!!![@BestSolCounter] New best solution found. Total best solutions found: {self.count}")
 
 
     m = Model()

examples/finished/diet.py

@@ -88,7 +88,7 @@ def make_inst():
 
     for b["Cal"] in [None, 3500, 3000, 2500]:
 
-        print("\nDiet for a maximum of {0} calories".format(b["Cal"] if b["Cal"] != None else "unlimited"))
+        print(f"\nDiet for a maximum of {b['Cal'] if b['Cal'] != None else 'unlimited'} calories")
         model = diet(F, N, a, b, c, d)
         model.hideOutput()  # silent mode
         model.optimize()
@@ -97,10 +97,9 @@ def make_inst():
         x, y, z, v = model.data
         for j in x:
             if model.getVal(x[j]) > 0:
-                print("{0:30s}: {1:3.1f} dishes --> {2:4.2f} added to objective".format(j, model.getVal(x[j]),
-                                                                                        model.getVal(y[j])))
+                print(f"{j:30s}: {model.getVal(x[j]):3.1f} dishes --> {model.getVal(y[j]):4.2f} added to objective")
         print("amount spent:", model.getObjVal())
 
         print("amount of nutrients:")
         for i in z:
-            print("{0:30s}: {1:4.2f}".format(i, model.getVal(z[i])))
+            print(f"{i:30s}: {model.getVal(z[i]):4.2f}")

src/pyscipopt/scip.pxi

@@ -1255,9 +1255,7 @@ cdef class BoundChange:
         return SCIPboundchgIsRedundant(self.scip_boundchg)
 
     def __repr__(self):
-        return "{} {} {}".format(self.getVar(),
-                                 _SCIP_BOUNDTYPE_TO_STRING[self.getBoundtype()],
-                                 self.getNewBound())
+        return f"{self.getVar()} {_SCIP_BOUNDTYPE_TO_STRING[self.getBoundtype()]} {self.getNewBound()}"
 
 cdef class DomainChanges:
     """Set of domain changes."""
@@ -11626,6 +11624,11 @@ cdef class Model:
 
         """
 
+        # Ensure _bestSol is up-to-date (cheap pointer comparison)
+        cdef SCIP_SOL* current_best_sol = SCIPgetBestSol(self._scip)
+        if self._bestSol is None or self._bestSol.sol != current_best_sol:
+            self._bestSol = Solution.create(self._scip, current_best_sol)
+
         if SCIPgetNSols(self._scip) == 0:
             if self.getStage() != SCIP_STAGE_SOLVING:
                 raise Warning("Without a solution, method can only be called in stage SOLVING.")

tests/test_model.py

@@ -486,6 +486,82 @@ def test_getObjVal():
     assert m.getObjVal() == 16 
     assert m.getVal(x) == 0
 
+def test_getObjVal_missing_bestSol():
+    m = Model()
+    m.hideOutput()
+
+    x = m.addVar("x", obj=2.0)
+    m.addCons(x >= 1.0)
+
+    # Add a solution 
+    sol = m.createSol()
+    m.setSolVal(sol, x, 10.0)
+    m.addSol(sol)
+
+    # Without the fix from #1272, m._bestSol remained NULL,
+    # causing an assertion failure: assert self._bestSol.sol != NULL
+    assert m.getObjVal() == 20.0
+
+def test_getObjVal_outdated_bestSol():
+    m = Model()
+    m.hideOutput()
+
+    x = m.addVar("x", obj=2.0)
+    m.addCons(x >= 1.0)
+
+    # Add initial solution and populate _bestSol
+    sol1 = m.createSol()
+    m.setSolVal(sol1, x, 10.0)
+    m.addSol(sol1)
+    m.getBestSol()  # populates m._bestSol with sol1
+
+    # Add a better solution
+    sol2 = m.createSol()
+    m.setSolVal(sol2, x, 3.0)
+    m.addSol(sol2)
+
+    # Without the fix from #1272, _bestSol remained stuck
+    # on sol1 and incorrectly returned 20.0 instead of 6.0
+    assert m.getObjVal() == 6.0
+
+def test_getVal_missing_bestSol():
+    m = Model()
+    m.hideOutput()
+
+    x = m.addVar("x", obj=2.0)
+    m.addCons(x >= 1.0)
+
+    # Add a solution 
+    sol = m.createSol()
+    m.setSolVal(sol, x, 10.0)
+    m.addSol(sol)
+
+    # Without the fix from #993, m._bestSol was None here
+    # causing "No solution available" warning
+    assert m.getVal(x) == 10.0
+
+def test_getVal_outdated_bestSol():
+    m = Model()
+    m.hideOutput()
+
+    x = m.addVar("x", obj=2.0)
+    m.addCons(x >= 1.0)
+
+    # Add initial solution and populate _bestSol
+    sol1 = m.createSol()
+    m.setSolVal(sol1, x, 10.0)
+    m.addSol(sol1)
+    m.getBestSol()  # populates m._bestSol with sol1
+
+    # Add a better solution
+    sol2 = m.createSol()
+    m.setSolVal(sol2, x, 3.0)
+    m.addSol(sol2)
+
+    # Without the fix from #993, _bestSol remained stuck
+    # on sol1 and incorrectly returned 10.0 instead of 3.0
+    assert m.getVal(x) == 3.0
+
 # tests writeProblem() after redirectOutput()
 def test_redirection():