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How to use _reset_awaitable_timer method in lisa

Best Python code snippet using lisa_python

lisa_runner.py

Source:lisa_runner.py

...241                self.platform.deploy_environment(environment)242                assert (243                    environment.status == EnvironmentStatus.Deployed244                ), f"actual: {environment.status}"245                self._reset_awaitable_timer("deploy")246            except ResourceAwaitableException as identifier:247                if self._is_awaitable_timeout("deploy"):248                    self._log.info(249                        f"[{environment.name}] timeout on waiting for more resource: "250                        f"{identifier}, skip assigning case."251                    )252                    raise SkippedException(identifier)253                else:254                    # rerun prepare to calculate resource again.255                    environment.status = EnvironmentStatus.New256        except Exception as identifier:257            self._attach_failed_environment_to_result(258                environment=environment,259                result=test_results[0],260                exception=identifier,261            )262            self._delete_environment_task(environment=environment, test_results=[])263    def _initialize_environment_task(264        self, environment: Environment, test_results: List[TestResult]265    ) -> None:266        self._log.debug(f"start initializing task on '{environment.name}'")267        assert test_results268        try:269            environment.initialize()270            assert (271                environment.status == EnvironmentStatus.Connected272            ), f"actual: {environment.status}"273        except Exception as identifier:274            self._attach_failed_environment_to_result(275                environment=environment,276                result=test_results[0],277                exception=identifier,278            )279            self._delete_environment_task(environment=environment, test_results=[])280    def _run_test_task(281        self,282        environment: Environment,283        test_results: List[TestResult],284        case_variables: Dict[str, VariableEntry],285    ) -> None:286        self._log.debug(287            f"start running cases on '{environment.name}', "288            f"case count: {len(test_results)}, "289            f"status {environment.status.name}"290        )291        assert test_results292        assert len(test_results) == 1, (293            f"single test result to run, " f"but {len(test_results)} found."294        )295        test_result = test_results[0]296        suite_metadata = test_result.runtime_data.metadata.suite297        test_suite: TestSuite = suite_metadata.test_class(298            suite_metadata,299        )300        test_suite.start(301            environment=environment,302            case_results=test_results,303            case_variables=case_variables,304        )305        # release environment reference to optimize memory.306        test_result.environment = None307        # Some test cases may break the ssh connections. To reduce side effects308        # on next test cases, close the connection after each test run. It will309        # be connected on the next command automatically.310        environment.nodes.close()311        # Try to connect node(s), if cannot access node(s) of this environment,312        # set the current environment as Bad. So that this environment won't be reused.313        if not is_unittest() and not environment.nodes.test_connections():314            environment.status = EnvironmentStatus.Bad315            self._log.debug(316                f"set environment '{environment.name}' as bad, "317                f"because after test case '{test_result.name}', "318                f"node(s) cannot be accessible."319            )320        environment.nodes.close()321        # keep failed environment, not to delete322        if (323            test_result.status == TestStatus.FAILED324            and self.platform.runbook.keep_environment325            == constants.ENVIRONMENT_KEEP_FAILED326        ):327            self._log.debug(328                f"keep environment '{environment.name}', "329                f"because keep_environment is 'failed', "330                f"and test case '{test_result.name}' failed on it."331            )332            environment.status = EnvironmentStatus.Deleted333        # if an environment is in bad status, it will be deleted, not run more334        # test cases. But if the setting is to keep failed environment, it may335        # be kept in above logic.336        if environment.status == EnvironmentStatus.Bad or environment.is_dirty:337            self._log.debug(338                f"delete environment '{environment.name}', "339                f"because it's in Bad status or marked as dirty."340            )341            self._delete_environment_task(342                environment=environment, test_results=test_results343            )344    def _delete_environment_task(345        self, environment: Environment, test_results: List[TestResult]346    ) -> None:347        """348        May be called async349        """350        # the predefined environment shouldn't be deleted, because it351        # serves all test cases.352        if environment.status == EnvironmentStatus.Deleted or (353            environment.status == EnvironmentStatus.Prepared354            and not environment.is_in_use355        ):356            # The prepared only environment doesn't need to be deleted.357            # It may cause platform fail to delete non-existing environment.358            environment.status = EnvironmentStatus.Deleted359        else:360            try:361                self.platform.delete_environment(environment)362            except Exception as identifier:363                self._log.debug(364                    f"error on deleting environment '{environment.name}': {identifier}"365                )366    def _prepare_environment(self, environment: Environment) -> bool:367        success = True368        try:369            try:370                self.platform.prepare_environment(environment)371                self._reset_awaitable_timer("prepare")372            except ResourceAwaitableException as identifier:373                # if timed out, raise the exception and skip the test case. If374                # not, do nothing to keep env as new to try next time.375                if self._is_awaitable_timeout("prepare"):376                    raise SkippedException(identifier)377        except Exception as identifier:378            success = False379            matched_result = self._match_failed_environment_with_result(380                environment=environment,381                candidate_results=self.test_results,382                exception=identifier,383            )384            self._attach_failed_environment_to_result(385                environment=environment,...

runner.py

Source:runner.py

...139            return False140        else:141            self._log.info(f"{name} timeout on waiting for more resource...")142            return True143    def _reset_awaitable_timer(self, name: str) -> None:144        _wait_resource_timer = self._wait_resource_timers.get(name, create_timer())145        _wait_resource_timer.reset()146        self._wait_resource_logged = False147        self._wait_resource_timers[name] = _wait_resource_timer148class RootRunner(Action):149    """150    The entry root runner, which starts other runners.151    """152    def __init__(self, runbook_builder: RunbookBuilder) -> None:153        super().__init__()154        self.exit_code: int = 0155        self._runbook_builder = runbook_builder156        self._log = get_logger("RootRunner")157        # this is to hold active runners, and will close them, if there is any...

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