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How to use init_task_params method in autotest

Best Python code snippet using autotest_python

trial.py

Source:trial.py

...107                         "parameters": []}108            for par in self.__class__.parameters:109                task_data[par.name] = getattr(self, par.name)  # parameter values are stored in task_data json object110                task_data["parameters"].append(par.name)  # work processor needs to know list of parameters (names)111            self.init_task_params(task_full_id, task_data)112            self.zk.ensure_path(task_path)113            self.zk.set(task_path, json.dumps(task_data))114            @self.zk.DataWatch(dependent_vars_path)115            def watch_dependent_vars(data, stat_):116                if data is not None and data != "":117                    self.received_tasks_counter += 1118                    # append partial results/dependent vars119                    task_results = json.loads(data)120                    node_id = task_results["node_id"]121                    partial_dependent = task_results["dependent"]122                    self.append_partial_results(partial_dependent)123                    dependent_vars_path = "/experiments/" + str(self.exp_id) + "/trials/" + str(124                        self.trial_id) + "/nodes/" + str(node_id) + "/dependent_variables"125                    self.zk.set(dependent_vars_path, "")  # clearing data126                    if self.received_tasks_counter == self.number_of_hosts: # all subtasks are completed.127                        self.aggregate_results()128                        self.zk.set(self.curr_trial_path + "/status", json.dumps(129                            {"trial_id": self.trial_id, "status": "completed", "dependent": self.results}))130                        self.process_after_run()131                        return False132                return True133            task_number += 1134    def init_task_params(self, task_full_id, data):135        pass136    def init_task_param(self, param_name, value, data):137        data[param_name] = value138        data["parameters"].append(param_name)139    # partial_dependent is a dictionary of dependent vars140    def append_partial_results(self, partial_dependent):141       pass142    def aggregate_results(self):143        pass144    def process_after_agent_action(self, agent, action):  # do any book-keeping needed after each step by an agent145        pass146    def process_after_iteration(self):  # do any book-keeping needed after each iteration completes147        pass148    def process_after_run(self):  # do any book-keeping needed after the trial ends and before agents are disconnected...

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