How to use the pyscipopt.SCIP_RESULT function in PySCIPOpt

#SCIPdebugMessage(" -> found gomory cut <%s>: act=%f, rhs=%f, norm=%f, eff=%f, min=%f, max=%f (range=%f)\n",
                    #   cutname, SCIPgetRowLPActivity(scip, cut), SCIProwGetRhs(cut), SCIProwGetNorm(cut),
                    #   SCIPgetCutEfficacy(scip, NULL, cut),
                    #   SCIPgetRowMinCoef(scip, cut), SCIPgetRowMaxCoef(scip, cut),
                    #   SCIPgetRowMaxCoef(scip, cut)/SCIPgetRowMinCoef(scip, cut))

                    # flush all changes before adding the cut
                    scip.flushRowExtensions(cut)

                    infeasible = scip.addCut(cut, forcecut=True)
                    self.ncuts += 1

                    if infeasible:
                       result = SCIP_RESULT.CUTOFF
                    else:
                       result = SCIP_RESULT.SEPARATED
                scip.releaseRow(cut)

        return {"result": result}

'node_depth': self.model.getCurrentNode().getDepth(),
                    'filename': filename,
                })

                self.sample_counter += 1

        # if exploration and expert policies are the same, prevent running it twice
        if not query_expert or (not self.follow_expert and self.exploration_policy != 'vanillafullstrong'):
            result = self.model.executeBranchRule(self.exploration_policy, allowaddcons)

        # apply 'vanillafullstrong' branching decision if needed
        if query_expert and self.follow_expert or self.exploration_policy == 'vanillafullstrong':
            assert result == scip.SCIP_RESULT.DIDNOTRUN
            cands, scores, npriocands, bestcand = self.model.getVanillafullstrongData()
            self.model.branchVar(cands[bestcand])
            result = scip.SCIP_RESULT.BRANCHED

        return {"result": result}

def conscheck(self, constraints, solution, checkintegrality, checklprows, printreason):
        if self.addCuts(checkonly = True):
            return {"result": SCIP_RESULT.INFEASIBLE}
        else:
            return {"result": SCIP_RESULT.FEASIBLE}