Unlock 30% off on Manual Testing Annual Plans this Holiday Season.

Copied to Clipboard!

How to use _prepare_environments method in lisa

Best Python code snippet using lisa_python

lisa_runner.py

Source:lisa_runner.py

...77            for env in self.environments78        )79        return is_all_results_completed and is_all_environment_completed80    def fetch_task(self) -> Optional[Task[None]]:81        self._prepare_environments()82        self._cleanup_deleted_environments()83        self._cleanup_done_results()84        # sort environments by status85        available_environments = self._sort_environments(self.environments)86        available_results = self._sort_test_results(87            [x for x in self.test_results if x.can_run]88        )89        # check deletable environments90        delete_task = self._delete_unused_environments()91        if delete_task:92            return delete_task93        if available_results and available_environments:94            for priority in range(6):95                can_run_results = self._get_results_by_priority(96                    available_results, priority97                )98                if not can_run_results:99                    continue100                # it means there are test cases and environment, so it needs to101                # schedule task.102                for environment in available_environments:103                    if environment.is_in_use:104                        # skip in used environments105                        continue106                    # try to pick the designated test result.107                    environment_results = [108                        x109                        for x in can_run_results110                        if environment.source_test_result111                        and x.id_ == environment.source_test_result.id_112                    ]113                    if not environment_results:114                        environment_results = self._get_runnable_test_results(115                            test_results=can_run_results, environment=environment116                        )117                    if not environment_results:118                        continue119                    task = self._dispatch_test_result(120                        environment=environment, test_results=environment_results121                    )122                    # there is more checking conditions. If some conditions doesn't123                    # meet, the task is None. If so, not return, and try next124                    # conditions or skip this test case.125                    if task:126                        return task127                if not any(128                    x.is_in_use or x.status == EnvironmentStatus.New129                    for x in available_environments130                ):131                    # if there is no environment in used, new, and results are132                    # not fit envs. those results cannot be run.133                    self._skip_test_results(can_run_results)134        elif available_results:135            # no available environments, so mark all test results skipped.136            self._skip_test_results(available_results)137            self.status = ActionStatus.SUCCESS138        return None139    def close(self) -> None:140        if hasattr(self, "environments") and self.environments:141            for environment in self.environments:142                self._delete_environment_task(environment, [])143        super().close()144    def _dispatch_test_result(145        self, environment: Environment, test_results: List[TestResult]146    ) -> Optional[Task[None]]:147        check_cancelled()148        assert test_results149        can_run_results = test_results150        # deploy151        if environment.status == EnvironmentStatus.Prepared and can_run_results:152            return self._generate_task(153                task_method=self._deploy_environment_task,154                environment=environment,155                test_results=can_run_results[:1],156            )157        # run on deployed environment158        can_run_results = [x for x in can_run_results if x.can_run]159        if environment.status == EnvironmentStatus.Deployed and can_run_results:160            selected_test_results = self._get_test_results_to_run(161                test_results=test_results, environment=environment162            )163            if selected_test_results:164                return self._generate_task(165                    task_method=self._run_test_task,166                    environment=environment,167                    test_results=selected_test_results,168                    case_variables=self._case_variables,169                )170            # Check if there is case to run in a connected environment. If so,171            # initialize the environment172            initialization_results = self._get_runnable_test_results(173                test_results=test_results,174                environment_status=EnvironmentStatus.Connected,175                environment=environment,176            )177            if initialization_results:178                return self._generate_task(179                    task_method=self._initialize_environment_task,180                    environment=environment,181                    test_results=initialization_results,182                )183        # run on connected environment184        can_run_results = [x for x in can_run_results if x.can_run]185        if environment.status == EnvironmentStatus.Connected and can_run_results:186            selected_test_results = self._get_test_results_to_run(187                test_results=test_results, environment=environment188            )189            if selected_test_results:190                return self._generate_task(191                    task_method=self._run_test_task,192                    environment=environment,193                    test_results=selected_test_results,194                    case_variables=self._case_variables,195                )196        return None197    def _delete_unused_environments(self) -> Optional[Task[None]]:198        available_environments = self._sort_environments(self.environments)199        # check deletable environments200        for environment in available_environments:201            # if an environment is in using, or not deployed, they won't be202            # deleted until end of runner.203            if environment.is_in_use or environment.status in [204                EnvironmentStatus.New,205                EnvironmentStatus.Prepared,206            ]:207                continue208            can_run_results = self._get_runnable_test_results(209                self.test_results, environment=environment210            )211            if not can_run_results:212                # no more test need this environment, delete it.213                self._log.debug(214                    f"generating delete environment task on '{environment.name}'"215                )216                return self._generate_task(217                    task_method=self._delete_environment_task,218                    environment=environment,219                    test_results=[],220                )221        return None222    def _prepare_environments(self) -> None:223        if all(x.status != EnvironmentStatus.New for x in self.environments):224            return225        proceeded_environments: List[Environment] = []226        for candidate_environment in self.environments:227            success = True228            if candidate_environment.status == EnvironmentStatus.New:229                success = self._prepare_environment(candidate_environment)230            if success:231                proceeded_environments.append(candidate_environment)232        # sort by environment source and cost cases233        # user defined should be higher priority than test cases' requirement234        proceeded_environments.sort(key=lambda x: (not x.is_predefined, x.cost))235        self.environments = proceeded_environments236    def _deploy_environment_task(...

eta_x.py

Source:eta_x.py

...73            path_results=self.config.path_results,74            path_scenarios=self.config.path_scenarios,75        )76        self.config_run.create_results_folders()77        self._prepare_environments(training)78        self._prepare_model(reset)79        log.info("Run prepared successfully.")80    def _prepare_model(self, reset: bool = False) -> None:81        """Check for existing model and load it or back it up and create a new model.82        :param reset: Flag to determine whether an existing model should be reset.83        """84        assert self.config_run is not None, (85            "Set the config_run attribute before trying to initialize the model "86            "(for example by calling prepare_run)."87        )88        assert self.environments is not None, (89            "Initialize the environments before trying to initialize the model" "(for example by calling prepare_run)."90        )91        path_model = self.config_run.path_run_model92        if path_model.is_file() and reset:93            log.info(f"Existing model detected: {path_model}")94            bak_name = path_model / f"_{datetime.fromtimestamp(path_model.stat().st_mtime).strftime('%Y%m%d_%H%M')}.bak"95            path_model.rename(bak_name)96            log.info(f"Reset is active. Existing model will be backed up. Backup file name: {bak_name}")97        elif path_model.is_file():98            log.info(f"Existing model detected: {path_model}. Loading model.")99            self.model = load_model(100                self.config.setup.agent_class,101                self.environments,102                self.config.settings.agent,103                self.config_run.path_run_model,104                tensorboard_log=self.config.setup.tensorboard_log,105                log_path=self.config_run.path_series_results,106            )107            return108        # Initialize the model if it wasn't loaded from a file109        self.model = initialize_model(110            self.config.setup.agent_class,111            self.config.setup.policy_class,112            self.environments,113            self.config.settings.agent,114            self.config.settings.seed,115            tensorboard_log=self.config.setup.tensorboard_log,116            log_path=self.config_run.path_series_results,117        )118    def _prepare_environments(self, training: bool = True) -> None:119        """Vectorize and prepare the environments and potentially the interaction environments.120        :param training: Should preparation be done for training (alternative: playing)?121        """122        assert self.config_run is not None, (123            "Set the config_run attribute before trying to initialize the environments "124            "(for example by calling prepare_run)."125        )126        env_class = self.config.setup.environment_class127        self.config_run.set_env_info(env_class)128        legacy_signature = {129            "env_id",130            "run_name",131            "general_settings",132            "path_settings",...

AbstractDatasetCreator.py

Source:AbstractDatasetCreator.py

...74        self.track_offsets = track_offsets75        self.remove_type_annotations = remove_type_annotations76        self.recompute_l2g = recompute_l2g77        self.path = path78        self._prepare_environments()79        self._init_cache()80    def _init_cache(self):81        # TODO this is wrong, use standard utilities82        rnd_name = get_random_name()83        self.tmp_dir = os.path.join(tempfile.gettempdir(), rnd_name)84        if os.path.isdir(self.tmp_dir):85            shutil.rmtree(self.tmp_dir)86        os.mkdir(self.tmp_dir)87        self.local2global_cache_filename = os.path.join(self.tmp_dir, "local2global_cache.db")88        self.local2global_cache = shelve.open(self.local2global_cache_filename)89    def __del__(self):90        self.local2global_cache.close()91        shutil.rmtree(self.tmp_dir)92        # os.remove(self.local2global_cache_filename) # TODO nofile on linux, need to check93    def handle_parallel_edges(self, edges_path):94        logging.info("Handle parallel edges")95        last_id = 096        global_edge_types = set(special_mapping.keys()) | set(special_mapping.values())97        existing_global_edges = set()98        temp_edges = join(os.path.dirname(edges_path), "temp_" + os.path.basename(edges_path))99        for ind, edges in enumerate(read_edges(edges_path, as_chunks=True)):100            edges["id"] = range(last_id, len(edges) + last_id)101            edge_bank = defaultdict(list)102            ids_to_remove = set()103            for id_, type_, src, dst in edges[["id", "type", "source_node_id", "target_node_id"]].values:104                if type_ in global_edge_types:105                    global_edge = (type_, src, dst)106                    if global_edge not in existing_global_edges:107                        existing_global_edges.add(global_edge)108                    else:109                        ids_to_remove.add(id_)110                else:111                    edge_bank[(src, dst)].append((id_, type_))112            for key, parallel_edges in edge_bank.items():113                if len(parallel_edges) > 1:114                    parallel_edges = sorted(parallel_edges, key=lambda x: self.edge_priority.get(x[1], 3))115                    ids_to_remove.update(pe[0] for pe in parallel_edges[1:])116            edges = edges[117                edges["id"].apply(lambda id_: id_ not in ids_to_remove)118            ]119            edges["id"] = range(last_id, len(edges) + last_id)120            last_id = len(edges) + last_id121            kwargs = self.get_writing_mode(temp_edges.endswith("csv"), first_written=ind != 0)122            persist(edges, temp_edges, **kwargs)123        os.remove(edges_path)124        os.rename(temp_edges, edges_path)125    def post_pruning(self, nodes_path, edges_path):126        logging.info("Post pruning")127        restricted_nodes = set()128        for nodes in read_nodes(nodes_path, as_chunks=True):129            restricted_nodes.update(130                nodes[131                    nodes["type"].apply(lambda type_: type_ in self.restricted_in_types)132                ]["id"]133            )134        temp_edges = join(os.path.dirname(edges_path), "temp_" + os.path.basename(edges_path))135        for ind, edges in enumerate(read_edges(edges_path, as_chunks=True)):136            edges = edges[137                edges["type"].apply(lambda type_: type_ not in self.restricted_edges)138            ]139            edges = edges[140                edges["target_node_id"].apply(lambda type_: type_ not in restricted_nodes)141            ]142            kwargs = self.get_writing_mode(temp_edges.endswith("csv"), first_written=ind != 0)143            persist(edges, temp_edges, **kwargs)144        os.remove(edges_path)145        os.rename(temp_edges, edges_path)146    def compact_mapping_for_l2g(self, global_nodes, filename):147        if len(global_nodes) > 0:148            self.update_l2g_file(149                mapping=self.create_compact_mapping(global_nodes), filename=filename150            )151    @staticmethod152    def create_compact_mapping(node_ids):153        return dict(zip(node_ids, range(len(node_ids))))154    def update_l2g_file(self, mapping, filename):155        for env_path in tqdm(self.environments, desc=f"Fixing {filename}"):156            filepath = os.path.join(env_path, filename)157            if not os.path.isfile(filepath):158                continue159            l2g = unpersist(filepath)160            l2g["global_id"] = l2g["global_id"].apply(lambda id_: mapping.get(id_, None))161            persist(l2g, filepath)162    def get_local2global(self, path):163        if path in self.local2global_cache:164            return self.local2global_cache[path]165        else:166            local2global_df = unpersist_if_present(path)167            if local2global_df is None:168                return None169            else:170                local2global = dict(zip(local2global_df['id'], local2global_df['global_id']))171                self.local2global_cache[path] = local2global172                return local2global173    @staticmethod174    def persist_if_not_none(table, dir, name):175        if table is not None:176            path = os.path.join(dir, name)177            persist(table, path)178    def write_type_annotation_flag(self, edges, output_dir):179        if len(self.type_annotation_edge_types) > 0:180            query_str = " or ".join(f"type == '{edge_type}'" for edge_type in self.type_annotation_edge_types)181            if len(edges.query(query_str)) > 0:182                with open(os.path.join(output_dir, "has_annotations"), "w") as has_annotations:183                    pass184    def write_local(self, dir, local2global=None, local2global_with_ast=None, **kwargs):185        if not self.recompute_l2g:186            for var_name, var_ in kwargs.items():187                self.persist_if_not_none(var_, dir, var_name + ".bz2")188        self.persist_if_not_none(local2global, dir, "local2global.bz2")189        self.persist_if_not_none(local2global_with_ast, dir, "local2global_with_ast.bz2")190    def merge_files(self, env_path, filename, map_filename, columns_to_map, original, columns_special=None):191        input_table_path = join(env_path, filename)192        local2global = self.get_local2global(join(env_path, map_filename))193        if os.path.isfile(input_table_path) and local2global is not None:194            input_table = unpersist(input_table_path)195            if self.only_with_annotations:196                if not os.path.isfile(join(env_path, "has_annotations")):197                    return original198            new_table = map_columns(input_table, local2global, columns_to_map, columns_special=columns_special)199            if original is None:200                return new_table201            else:202                return original.append(new_table)203        else:204            return original205    def read_mapped_local(self, env_path, filename, map_filename, columns_to_map, columns_special=None):206        input_table_path = join(env_path, filename)207        local2global = self.get_local2global(join(env_path, map_filename))208        if os.path.isfile(input_table_path) and local2global is not None:209            if self.only_with_annotations:210                if not os.path.isfile(join(env_path, "has_annotations")):211                    return None212            input_table = unpersist(input_table_path)213            new_table = map_columns(input_table, local2global, columns_to_map, columns_special=columns_special)214            return new_table215        else:216            return None217    def get_writing_mode(self, is_csv, first_written):218        kwargs = {}219        if first_written is True:220            kwargs["mode"] = "a"221            if is_csv:222                kwargs["header"] = False223        return kwargs224    def create_global_file(225            self, local_file, local2global_file, columns, output_path, message, ensure_unique_with=None,226            columns_special=None227    ):228        assert output_path.endswith("json") or output_path.endswith("csv")229        if ensure_unique_with is not None:230            unique_values = set()231        else:232            unique_values = None233        first_written = False234        for ind, env_path in tqdm(235                enumerate(self.environments), desc=message, leave=True,236                dynamic_ncols=True, total=len(self.environments)237        ):238            mapped_local = self.read_mapped_local(239                env_path, local_file, local2global_file, columns, columns_special=columns_special240            )241            if mapped_local is not None:242                if unique_values is not None:243                    unique_verify = list(zip(*(mapped_local[col_name] for col_name in ensure_unique_with)))244                    mapped_local = mapped_local.loc[245                        map(lambda x: x not in unique_values, unique_verify)246                    ]247                    unique_values.update(unique_verify)248                kwargs = self.get_writing_mode(output_path.endswith("csv"), first_written)249                persist(mapped_local, output_path, **kwargs)250                first_written = True251    # def create_global_file(252    #         self, local_file, local2global_file, columns, output_path, message, ensure_unique_with=None,253    #         columns_special=None254    # ):255    #     global_table = None256    #     for ind, env_path in tqdm(257    #             enumerate(self.environments), desc=message, leave=True,258    #             dynamic_ncols=True, total=len(self.environments)259    #     ):260    #         global_table = self.merge_files(261    #             env_path, local_file, local2global_file, columns, global_table, columns_special=columns_special262    #         )263    #264    #     if ensure_unique_with is not None:265    #         global_table = global_table.drop_duplicates(subset=ensure_unique_with)266    #267    #     if global_table is not None:268    #         global_table.reset_index(drop=True, inplace=True)269    #         assert len(global_table) == len(global_table.index.unique())270    #271    #         persist(global_table, output_path)272    def filter_orphaned_nodes(self, nodes_path, edges_path):273        logging.info("Filter orphaned nodes")274        active_nodes = set()275        for edges in read_edges(edges_path, as_chunks=True):276            active_nodes.update(edges['source_node_id'])277            active_nodes.update(edges['target_node_id'])278        temp_nodes = join(os.path.dirname(nodes_path), "temp_" + os.path.basename(nodes_path))279        for ind, nodes in enumerate(read_nodes(nodes_path, as_chunks=True)):280            nodes = nodes[281                nodes['id'].apply(lambda id_: id_ in active_nodes)282            ]283            kwargs = self.get_writing_mode(temp_nodes.endswith("csv"), first_written=ind != 0)284            persist(nodes, temp_nodes, **kwargs)285        os.remove(nodes_path)286        os.rename(temp_nodes, nodes_path)287    def join_files(self, files, local2global_filename, output_dir):288        for file in files:289            params = copy(self.merging_specification[file])290            params["output_path"] = join(output_dir, params.pop("output_path"))291            self.create_global_file(file, local2global_filename, message=f"Merging {file}", **params)292    def merge_graph_without_ast(self, output_path):293        self.join_files(self.files_for_merging, "local2global.bz2", output_path)294        get_path = partial(join, output_path)295        nodes_path = get_path("common_nodes.json")296        edges_path = get_path("common_edges.json")297        self.filter_orphaned_nodes(298            nodes_path,299            edges_path,300        )301        node_names = self.extract_node_names(302            nodes_path, min_count=2303        )304        if node_names is not None:305            persist(node_names, get_path("node_names.json"))306        self.handle_parallel_edges(edges_path)307        if self.visualize:308            self.visualize_func(309                read_nodes(nodes_path),310                read_edges(edges_path),311                get_path("visualization.pdf")312            )313    def merge_graph_with_ast(self, output_path):314        self.join_files(self.files_for_merging_with_ast, "local2global_with_ast.bz2", output_path)315        get_path = partial(join, output_path)316        nodes_path = get_path("common_nodes.json")317        edges_path = get_path("common_edges.json")318        if self.remove_type_annotations:319            self.filter_type_edges(nodes_path, edges_path)320        self.handle_parallel_edges(edges_path)321        self.post_pruning(nodes_path, edges_path)322        self.filter_orphaned_nodes(323            nodes_path,324            edges_path,325        )326        # persist(global_nodes, get_path("common_nodes.json"))327        node_names = self.extract_node_names(328            nodes_path, min_count=2329        )330        if node_names is not None:331            persist(node_names, get_path("node_names.json"))332        if self.visualize:333            self.visualize_func(334                read_nodes(nodes_path),335                read_edges(edges_path),336                get_path("visualization.pdf")337            )338    @abstractmethod339    def create_output_dirs(self, output_path):340        pass341    @abstractmethod342    def _prepare_environments(self):343        pass344    @staticmethod345    @abstractmethod346    def filter_type_edges(nodes, edges):347        pass348    @staticmethod349    @abstractmethod350    def extract_node_names(nodes, min_count):351        pass352    @abstractmethod353    def do_extraction(self):354        pass355    @abstractmethod356    def merge(self, output_directory):...

Automation Testing Tutorials

Learn to execute automation testing from scratch with LambdaTest Learning Hub. Right from setting up the prerequisites to run your first automation test, to following best practices and diving deeper into advanced test scenarios. LambdaTest Learning Hubs compile a list of step-by-step guides to help you be proficient with different test automation frameworks i.e. Selenium, Cypress, TestNG etc.