PK]Md((b2luigi/__init__.py"""Task scheduling and batch running for basf2 jobs made simple""" __version__ = "0.3.0" from luigi import * from luigi.util import requires, inherits, copies from b2luigi.core.parameter import wrap_parameter, BoolParameter wrap_parameter() from b2luigi.core.task import Task, ExternalTask, WrapperTask from b2luigi.core.temporary_wrapper import on_temporary_files from b2luigi.core.dispatchable_task import DispatchableTask, dispatch from b2luigi.core.settings import get_setting, set_setting, clear_setting from b2luigi.cli.process import process PKn@ M܃4 b2luigi/basf2_helper/__init__.pyfrom b2luigi.basf2_helper.targets import ROOTLocalTarget from b2luigi.basf2_helper.tasks import Basf2Task, Basf2PathTask, Basf2FileMergeTask, SimplifiedOutputBasf2Task, HaddTask, Basf2nTupleMergeTask PKn@ Mccb2luigi/basf2_helper/data.pyfrom collections import namedtuple from glob import glob import enum from b2luigi.core.utils import product_dict, fill_kwargs_with_lists import b2luigi from parse import parse MDST_DIR_STRUCTURE = "/hsm/belle2/bdata/Data/release-{p.release}/DB{p.database:08d}/prod{p.prod:08d}/" + \ "e{p.experiment_number:04d}/4S/r{p.run_number:05d}/all/mdst/sub00/" + \ "mdst.{p.prefix}.{p.experiment_number:04d}.{p.run_number:05d}.{p.file_name}.root" CDST_DIR_STRUCTURE = "/hsm/belle2/bdata/Data/release-{p.release}/DB{p.database:08d}/prod{p.prod:08d}/" + \ "e{p.experiment_number:04d}/4S/r{p.run_number:05d}/all/cdst/sub00/" + \ "cdst.{p.prefix}.{p.experiment_number:04d}.{p.run_number:05d}.{p.file_name}.root" RAW_DIR_STRUCTURE = "/ghi/fs01/belle2/bdata/Data/Raw/e{p.experiment_number:04d}/r{p.run_number:05d}/sub00/" + \ "{p.prefix}.{p.experiment_number:04d}.{p.run_number:05d}.{p.file_name}.root" class DataMode(enum.Enum): raw = "raw" mdst = "mdst" cdst = "cdst" class DataTask(b2luigi.ExternalTask): data_mode = b2luigi.EnumParameter(enum=DataMode) experiment_number = b2luigi.IntParameter() run_number = b2luigi.IntParameter() prefix = b2luigi.Parameter() file_name = b2luigi.Parameter() def output(self): yield {"input.root": b2luigi.LocalTarget(_build_data_path(self))} class RawDataTask(DataTask): data_mode = DataMode.raw class DstDataTask(DataTask): release = b2luigi.Parameter() prod = b2luigi.IntParameter() database = b2luigi.IntParameter() class MdstDataTask(DstDataTask): data_mode = DataMode.mdst class CdstDataTask(DstDataTask): data_mode = DataMode.cdst requires_raw_data = b2luigi.requires(RawDataTask) requires_mdst_data = b2luigi.requires(MdstDataTask) requires_cdst_data = b2luigi.requires(CdstDataTask) def _build_data_path(parameters): mode = parameters.data_mode if mode == DataMode.raw: return RAW_DIR_STRUCTURE.format(p=parameters) elif mode == DataMode.cdst: return CDST_DIR_STRUCTURE.format(p=parameters) elif mode == DataMode.mdst: return MDST_DIR_STRUCTURE.format(p=parameters) def _parse_data_path(data_mode, data_path): extracted_kwargs = None if data_mode == DataMode.mdst: extracted_kwargs = parse(MDST_DIR_STRUCTURE, data_path) elif data_mode == DataMode.cdst: extracted_kwargs = parse(CDST_DIR_STRUCTURE, data_path) elif data_mode == DataMode.raw: extracted_kwargs = parse(RAW_DIR_STRUCTURE, data_path) if not extracted_kwargs: raise ValueError("The path does not fit the given format") extracted_kwargs = {key.replace("p.", ""): value for key, value in extracted_kwargs.named.items()} return extracted_kwargs def _get_data_kwargs(data_mode, experiment_number, run_number, prefix=None, file_name=None, **other_kwargs): if file_name is None: file_name = "*" if prefix is None: prefix = "*" all_kwargs = fill_kwargs_with_lists(data_mode=data_mode, experiment_number=experiment_number, run_number=run_number, prefix=prefix, file_name=file_name, **other_kwargs) for kwargs in product_dict(**all_kwargs): # The build_data_path wants an object, so lets convert the dict to a named tuple kwargs = namedtuple('GenericDict', kwargs.keys())(**kwargs) for data_file in glob(_build_data_path(kwargs)): yield _parse_data_path(data_mode, data_file) def clone_on_mdst(self, task_class, experiment_number, run_number, release, prod, database, prefix=None, file_name=None, **additional_kwargs): # TODO: make database not needed for kwargs in _get_data_kwargs(data_mode=DataMode.mdst, experiment_number=experiment_number, run_number=run_number, release=release, prod=prod, database=database, prefix=prefix, file_name=file_name): yield self.clone(task_class, **kwargs, **additional_kwargs) def clone_on_cdst(self, task_class, experiment_number, run_number, release, prod, database, prefix=None, file_name=None, **additional_kwargs): # TODO: make database not needed for kwargs in _get_data_kwargs(data_mode=DataMode.cdst, experiment_number=experiment_number, run_number=run_number, release=release, prod=prod, database=database, prefix=prefix, file_name=file_name): yield self.clone(task_class, **kwargs, **additional_kwargs) def clone_on_raw(self, task_class, experiment_number, run_number, prefix=None, file_name=None, **additional_kwargs): for kwargs in _get_data_kwargs(data_mode=DataMode.raw, experiment_number=experiment_number, run_number=run_number, prefix=prefix, file_name=file_name): yield self.clone(task_class, **kwargs, **additional_kwargs) PKn@ Mw'!b2luigi/basf2_helper/targets.pyimport b2luigi class ROOTLocalTarget(b2luigi.LocalTarget): def exists(self): if not super().exists(): return False path = self.path import ROOT tfile = ROOT.TFile.Open(path) return tfile and len(tfile.GetListOfKeys()) > 0PKU Mn n b2luigi/basf2_helper/tasks.pyimport collections import os import b2luigi from b2luigi.basf2_helper.targets import ROOTLocalTarget from b2luigi.basf2_helper.utils import get_basf2_git_hash import subprocess from b2luigi.core.utils import create_output_dirs class Basf2Task(b2luigi.DispatchableTask): git_hash = b2luigi.Parameter(default=get_basf2_git_hash()) def get_output_file_target(self, *args, **kwargs): file_name = self.get_output_file_name(*args, **kwargs) if os.path.splitext(file_name)[-1] == ".root": return ROOTLocalTarget(file_name) else: return super().get_output_file_target(*args, **kwargs) def get_serialized_parameters(self): serialized_parameters = super().get_serialized_parameters() # Git hash should go to the front return_dict = collections.OrderedDict() return_dict["git_hash"] = serialized_parameters["git_hash"] for key, value in serialized_parameters.items(): return_dict[key] = value return return_dict class Basf2PathTask(Basf2Task): num_processes = b2luigi.IntParameter(significant=False, default=0) max_event = b2luigi.IntParameter(significant=False, default=0) def create_path(self): raise NotImplementedError() @b2luigi.on_temporary_files def process(self): assert get_basf2_git_hash() == self.git_hash try: import basf2 import ROOT except ImportError: raise ImportError("Can not find ROOT or basf2. Can not use the basf2 task.") if self.num_processes: basf2.set_nprocesses(self.num_processes) if self.max_event: ROOT.Belle2.Environment.Instance().setNumberEventsOverride(self.max_event) path = self.create_path() basf2.print_path(path) basf2.process(path) print(basf2.statistics) class SimplifiedOutputBasf2Task(Basf2PathTask): def create_path(self): raise NotImplementedError() def output(self): path = self.create_path() outputs = [] for module in path.modules(): if module.type() == "RootOutput": for param in module.available_params(): if param.name == "outputFileName": outputs.append(ROOTLocalTarget(param.values)) return outputs class MergerTask(Basf2Task): cmd = [] def output(self): for key, _ in self.get_input_file_names().items(): if hasattr(self, "keys") and key not in self.keys: continue yield self.add_to_output(key) @b2luigi.on_temporary_files def process(self): create_output_dirs(self) for key, file_list in self.get_input_file_names().items(): if hasattr(self, "keys") and key not in self.keys: continue args = self.cmd + [self.get_output_file_name(key)] + file_list subprocess.check_call(args) class HaddTask(MergerTask): cmd = ["hadd", "-f"] class Basf2FileMergeTask(MergerTask): cmd = ["b2file-merge", "-f"] class Basf2nTupleMergeTask(MergerTask): cmd = ["fei_merge_files"]PKn@ M3`EEb2luigi/basf2_helper/utils.pyimport os import git def get_basf2_git_hash(): basf2_release = os.getenv("BELLE2_RELEASE") if basf2_release == "head": basf2_release_location = os.getenv("BELLE2_LOCAL_DIR") assert basf2_release_location return git.Repo(basf2_release_location).head.object.hexsha return basf2_releasePKn@ Mb2luigi/batch/__init__.pyPKn@ Mb2luigi/batch/workers.pyimport enum import luigi.interface import luigi.worker from b2luigi.batch.processes.lsf import LSFProcess from b2luigi.batch.processes.test import TestProcess from b2luigi.core.settings import get_setting class BatchSystems(enum.Enum): lsf = "lsf" htcondor = "htcondor" local = "local" test = "test" class SendJobWorker(luigi.worker.Worker): def _create_task_process(self, task): try: batch_system = task.batch_system except AttributeError: batch_system = BatchSystems(get_setting("batch_system", BatchSystems.lsf)) if batch_system == BatchSystems.lsf: process_class = LSFProcess elif batch_system == BatchSystems.htcondor: raise NotImplementedError elif batch_system == BatchSystems.test: process_class = TestProcess elif batch_system == BatchSystems.local: return super()._create_task_process(task) else: raise NotImplementedError return process_class(task=task, scheduler=self._scheduler, result_queue=self._task_result_queue, worker_timeout=self._config.timeout) class SendJobWorkerSchedulerFactory(luigi.interface._WorkerSchedulerFactory): def create_worker(self, scheduler, worker_processes, assistant=False): return SendJobWorker(scheduler=scheduler, worker_processes=worker_processes, assistant=assistant) PKn@ Moo#b2luigi/batch/processes/__init__.pyimport os import sys import time import enum import luigi import luigi.scheduler from b2luigi.core.utils import on_failure, create_cmd_from_task class JobStatus(enum.Enum): running = "running" successful = "successful" aborted = "aborted" class BatchProcess: """ This is the base class for all batch algorithms that allow luigi to run on a specific batch system. This is an abstract base class and inheriting classes need to supply functionalities for * starting a job using the commands in self.task_cmd * getting the job status of a running, finished or failed job * and killing a job All those commands are called from the main process, which is not running on the batch system. Every batch system that is capable of these functions can in principle work together with b2luigi. Implementation note: In principle, using the batch system is transparent to the user. In case of problems, it may however be useful to understand how it is working. When you start your luigi dependency tree with ``process(..., batch=True)``, the normal luigi process is started looking for unfinished tasks and running them etc. Normally, luigi creates a process for each running task and runs them either directly or on a different core (if you have enabled more than one worker). In the batch case, this process is not a normal python multiprocessing process, but this BatchProcess, which has the same interface (one can check the status of the process, start or kill it). The process does not need to wait for the batch job to finish but is asked repeatedly for the job status. By this, most of the core functionality of luigi is kept and reused. This also means, that every batch job only includes a single task and is finished whenever this task is done decreasing the batch runtime. You will need exectly as many batch jobs as you have tasks and no batch job will idle waiting for input data as all are scheduled only when the task they should run is actually runnable (the input files are there). What is the batch command now? In each job, we start the current python interpreter (the one you used to call this main file) to start the very same file again. However, we give it an additional parameter, which tells it to only run one single task. Task can be identified by their task id. A typical task command may look like:: /your-path/venv/bin/python /your-project/some-file.py --batch-runner --task-id MyTask_38dsf879w3 if you are using a virtual environment and the batch job should run the MyTask. The implementation of the abstract functions is responsible for starting a job with exactly this command (which is stored in self.task_cmd) and writing the log of the job into appropriate locations. Warning: There are a few drawbacks when using the batch system, which you may have to keep in mind: * We are currently assuming that you have the same environment setup on the batch system as locally and we will call the python executable which runs your scheduling job. The currently integrated batch processes (e.g. LSF) use the current environment variables including the cwd and PATH also on the batch. * The ``luigi`` feature to request new dependencies while task running (via yield) is not implemented for the batch mode. * Other drawbacks may come from the implemented batch processes. """ def __init__(self, task, scheduler, result_queue, worker_timeout): self.use_multiprocessing = False self.task = task self.timeout_time = time.time() + worker_timeout if worker_timeout else None self._result_queue = result_queue self._scheduler = scheduler self.task_cmd = create_cmd_from_task(task) @property def exitcode(self): # We cheat here a bit: if the exit code is set to 0 all the time, we can always use the result queue for # delivering the result return 0 def get_job_status(self): """ Implement this function to return the current job status. How you identify exactly your job is dependent on the implementation and needs to be handled by your own child class. Must return one item of the JobStatus enumeration: running, aborted, successful. Will only be called after the job is started already but may also be called when the job is finished already. If the task status is unknown, return aborted. If the task has not started already (but is scheduled), return running nevertheless. No matter if aborted via a call to kill_job, by the batch system or by an exception in the job itself, you should return aborted if the job is not finished successfully. """ raise NotImplementedError def start_job(self): """ Override this function in your child class to start a job on the batch system. It is called exactly once. You need to store any information identifying your batch job on your own. After the start_job function is called by the framework (and no exception is thrown), it is assumed that a batch job running exactly the command in self.task_cmd is started or scheduled. Please make sure to have a proper environment in the batch job (e.g. by copying the current environment) and the same python executable (or a similar one) running in the same working directory. After the job is finished (no matter if aborted or successful) we assume the stdout and stderr is written into the two files given by b2luigi.core.utils.get_log_files(self.task). """ raise NotImplementedError def kill_job(self): """ This command is used to abort a job started by the start_job function. It is only called once to abort a job, so make sure to either block until the job is really gone or be sure that it will go down soon. Especially, do not wait until the job is finished. It is called for example when the user presses Ctrl-C. In some strange corner cases it may happen that this function is called even before the job is started (the start_job function is called). In this case, you do not need to do anything (but not raise an exception). """ raise NotImplementedError def run(self): self.start_job() def terminate(self): self.kill_job() def is_alive(self): job_status = self.get_job_status() if job_status == JobStatus.successful: job_output = "" self._put_to_result_queue(status=luigi.scheduler.DONE, explanation=job_output) return False elif job_status == JobStatus.aborted: job_output = "" self._put_to_result_queue(status=luigi.scheduler.FAILED, explanation=job_output) on_failure(self.task, job_output) return False elif job_status == JobStatus.running: return True raise ValueError("get_job_status() returned an unknown job state!") def _put_to_result_queue(self, status, explanation): missing = [] new_deps = [] self._result_queue.put((self.task.task_id, status, explanation, missing, new_deps)) PKJX MN9w  b2luigi/batch/processes/lsf.pyimport json import re import subprocess from b2luigi.batch.processes import BatchProcess, JobStatus from b2luigi.core.utils import get_log_file_dir class LSFProcess(BatchProcess): """ Reference implementation of the batch process for an LSF batch system. We assume that the batch system shares a file system with the submission node you are currently working on (or at least the current folder is also available there with the same path). We also assume that we can run the same python interpreter there by just copying the current environment and calling it from the same path. Both requirements are fulfilled by a "normal" LSF setup, so you do not keep those in mind typically. """ def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) self._batch_job_id = None def get_job_status(self): assert self._batch_job_id output = subprocess.check_output(["bjobs", "-json", "-o", "stat", self._batch_job_id]) output = output.decode() output = json.loads(output)["RECORDS"][0] if "STAT" not in output: return JobStatus.aborted job_status = output["STAT"] if job_status == "DONE": return JobStatus.successful elif job_status == "EXIT": return JobStatus.aborted return JobStatus.running def start_job(self): prefix = ["bsub", "-env all"] try: prefix += ["-q", self.task.queue] except AttributeError: pass log_file_dir = get_log_file_dir(self.task) stderr_log_file = log_file_dir + "stderr" stdout_log_file = log_file_dir + "stdout" prefix += ["-eo", stderr_log_file, "-oo", stdout_log_file] output = subprocess.check_output(prefix + self.task_cmd) output = output.decode() # Output of the form Job <72065926> is submitted to default queue . match = re.search(r"<[0-9]+>", output) if not match: raise RuntimeError("Batch submission failed with output " + output) self._batch_job_id = match.group(0)[1:-1] def kill_job(self): if not self._batch_job_id: return subprocess.check_call(["bkill", self._batch_job_id], stdout=subprocess.DEVNULL)PKJX M[Hllb2luigi/batch/processes/test.pyimport subprocess from b2luigi.batch.processes import BatchProcess, JobStatus from b2luigi.core.utils import get_log_file_dir class TestProcess(BatchProcess): def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) self._process = None def get_job_status(self): if not self._process: return JobStatus.aborted returncode = self._process.poll() if returncode is None: return JobStatus.running elif returncode: return JobStatus.aborted else: return JobStatus.successful def start_job(self): log_file_dir = get_log_file_dir(self.task) stderr_log_file = log_file_dir + "stderr" stdout_log_file = log_file_dir + "stdout" with open(stdout_log_file, "w") as stdout: with open(stderr_log_file, "w") as stderr: self._process = subprocess.Popen(self.task_cmd, stdout=stdout, stderr=stderr) def kill_job(self): if not self._process: return self._process.kill() def get_job_output(self): return "" PKn@ Mb2luigi/cli/__init__.pyPKn@ M,22b2luigi/cli/arguments.pyimport argparse def get_cli_arguments(): parser = argparse.ArgumentParser() parser.add_argument("--show-output", help="Instead of running the tasks, show which output files will/are created.", action="store_true") parser.add_argument("--test", help="Run the task list in test mode by printing the log directly to the screen instead" "of storing it in a file.", action="store_true") parser.add_argument("--batch", help="Instead of running locally, try to submit the tasks to the batch system.", action="store_true") parser.add_argument("--batch-runner", help="Expert option to mark this worker as a batch runner.", action="store_true") parser.add_argument("--dry-run", help="Do not run any task but set the return value to 0, if the tasks are complete.", action="store_true") parser.add_argument("--scheduler-host", help="If given, use this host as a central scheduler instead of a local one.", default="") parser.add_argument("--scheduler-port", help="If given, use the port on this host as a central scheduler instead of a local one.", type=int, default=0) parser.add_argument("--task-id", help="EXPERT.", default="") args = parser.parse_args() if (args.test or args.dry_run) and (args.scheduler_host or args.scheduler_port): raise AttributeError("Can not test while using a central scheduler!") if args.batch_runner and not args.task_id : raise AttributeError("A batch runner should always have a fully qualified task id.") if args.show_output and (args.scheduler_host or args.scheduler_port or args.batch or args.test): print("Ignoring all other parameters, as you have given the --show-output parameter.") return args PKn@ M_ppb2luigi/cli/process.pyfrom b2luigi.cli.arguments import get_cli_arguments from b2luigi.cli import runner __has_run_already = False def process(task_like_elements, show_output=False, dry_run=False, test=False, batch=False, **kwargs): """ Call this function in your main method to tell ``b2luigi`` where your entry point of the task graph is. It is very similar to ``luigi.build`` with some additional configuration options. Example: This example defines a simple task and tells ``b2luigi`` to execute it 100 times with different parametes:: import b2luigi import random class MyNumberTask(b2luigi.Task): some_parameter = b2luigi.Parameter() def output(self): return b2luigi.LocalTarget(f"results/output_file_{self.some_parameter}.txt") def run(self): random_number = random.random() with self.output().open("w") as f: f.write(f"{random_number}\\n") if __name__ == "__main__": b2luigi.process([MyNumberTask(some_parameter=i) for i in range(100)]) All flag arguments can also be given as command line arguments. This means the call with:: b2luigi.process(tasks, batch=True) is equivalent to calling the script with:: python script.py --batch Args: task_like_elements (:obj:`Task` or list): Task(s) to execute with luigi. Can either be a list of tasks or a task instance. show_output (bool, optional): Instead of running the task(s), write out all output files which will be generated marked in color, if they are present already. Good for testing of your tasks will do, what you think they should. dry_run (bool, optional): Instead od running the task(s), write out which tasks will be executed. This is a simplified form of dependency resolution, so this information may be wrong in some corner cases. Also good for testing. test (bool, optional): Does neither run on the batch system, with multiprocessing or dispatched (see :obj:`DispatchableTask`) but directly on the machine for debugging reasons. Does output all logs to the console. batch (bool, optional): Execute the tasks on the selected batch system. Refer to :ref:`quick-start-label` for more information. The default batch system is LSF, but this can be changed with the `batch_system` settings. See :obj:`get_setting` on how to define settings. **kwargs: Additional keyword arguments passed to ``luigi.build``. """ # Assert, that process is only run once global __has_run_already if __has_run_already: raise RuntimeError( "You are not allowed to call process twice in your code!") __has_run_already = True # Create Task List if not isinstance(task_like_elements, list): task_list = [task_like_elements] else: task_list = task_like_elements # Check the CLI arguments and run as requested cli_args = get_cli_arguments() if cli_args.show_output or show_output: runner.show_all_outputs(task_list) elif cli_args.dry_run or dry_run: runner.dry_run(task_list) elif cli_args.test or test: runner.run_test_mode(task_list, cli_args, kwargs) elif cli_args.batch_runner: runner.run_as_batch_worker(task_list, cli_args, kwargs) elif cli_args.batch or batch: runner.run_batched(task_list, cli_args, kwargs) else: runner.run_local(task_list, cli_args, kwargs) PK]Mj b2luigi/cli/runner.pyimport collections import luigi import luigi.server import luigi.configuration import os from b2luigi.batch.workers import SendJobWorkerSchedulerFactory from b2luigi.core.settings import set_setting from b2luigi.core.utils import task_iterator, get_all_output_files_in_tree def run_as_batch_worker(task_list, cli_args, kwargs): found_task = False for root_task in task_list: for task in task_iterator(root_task): if task.task_id != cli_args.task_id: continue found_task = True set_setting("local_execution", True) # TODO: We do not process the information if (a) we have a new dependency and (b) why the task has failed. # TODO: Would be also nice to run the event handlers try: task.run() task.on_success() except BaseException as ex: task.on_failure(ex) raise ex return if not found_task: raise ValueError(f"The task id {task.task_id} to be executed by this batch worker " f"does not exist in the locally reproduced task graph.") def run_batched(task_list, cli_args, kwargs): kwargs["worker_scheduler_factory"] = SendJobWorkerSchedulerFactory() run_local(task_list, cli_args, kwargs) def run_local(task_list, cli_args, kwargs): if cli_args.scheduler_host or cli_args.scheduler_port: core_settings = luigi.interface.core() host = cli_args.scheduler_host or core_settings.scheduler_host port = int(cli_args.scheduler_port) or core_settings.scheduler_port kwargs["scheduler_host"] = host kwargs["scheduler_port"] = port else: kwargs["local_scheduler"] = True kwargs.setdefault("log_level", "INFO") luigi.build(task_list, **kwargs) def run_test_mode(task_list, cli_args, kwargs): set_setting("local_execution", True) luigi.build(task_list, log_level="DEBUG", local_scheduler=True, **kwargs) def show_all_outputs(task_list, *args, **kwargs): from colorama import Fore, Style all_output_files = collections.defaultdict(list) for task in task_list: output_files = get_all_output_files_in_tree(task) for key, file_names in output_files.items(): all_output_files[key] += file_names for key, file_names in all_output_files.items(): print(key) file_names = {d["file_name"]: d["exists"] for d in file_names} for file_name, exists in file_names.items(): # TODO: this is not correct as it does not check the task status! if exists: print("\t", Fore.GREEN, file_name, Style.RESET_ALL) else: print("\t", Fore.RED, file_name, Style.RESET_ALL) print() def dry_run(task_list): nonfinished_task_list = collections.defaultdict(set) for root_task in task_list: for task in task_iterator(root_task, only_non_complete=True): nonfinished_task_list[task.__class__.__name__].add(task) non_completed_tasks = 0 for task_class in sorted(nonfinished_task_list): print(task_class) for task in nonfinished_task_list[task_class]: print("\tWould run", task) print() non_completed_tasks += 1 if non_completed_tasks: print("In total", non_completed_tasks) exit(1) else: print("All tasks are finished!") exit(0) PKn@ Mb2luigi/core/__init__.pyPKJX M@G?} } !b2luigi/core/dispatchable_task.pyimport os import subprocess import functools import sys from b2luigi.core.settings import get_setting from b2luigi.core.task import Task from b2luigi.core.utils import get_log_file_dir, add_on_failure_function, create_cmd_from_task, create_output_dirs def _run_task_locally(task, run_function): create_output_dirs(task) run_function(task) def _run_task_remote(task): add_on_failure_function(task) filename = os.path.realpath(sys.argv[0]) log_file_dir = get_log_file_dir(task) stderr_file_name = log_file_dir + "stderr" stdout_file_name = log_file_dir + "stdout" cmd = create_cmd_from_task(task) with open(stdout_file_name, "w") as stdout_file: with open(stderr_file_name, "w") as stderr_file: return_code = subprocess.call(cmd, stdout=stdout_file, stderr=stderr_file, cwd=os.path.dirname(filename)) if return_code: raise RuntimeError(f"Execution failed with return code {return_code}") def dispatch(run_function): """ In cases you have a run function calling external, probably insecure functionalities, use this function wrapper around your run function. Example: The run function can include any code you want. When the task runs, it is started in a subprocess and monitored by the parent process. When it dies unexpectedly (e.g. because of a segfault etc.) the task will be marked as failed. If not, it is successful. The log output will be written to two files in the log folder (marked with the parameters of the task), which you can check afterwards:: import b2luigi class MyTask(b2luigi.Task): @b2luigi.dispatch def run(self): call_some_evil_function() Implementation note: In the subprocess we are calling the current sys.executable (which should by python hopefully) with the current input file as a parameter, but let it only run this specific task (by handing over the task id and the `--batch-worker` option). The run function notices this and actually runs the task instead of dispatching again. You have the possibility to control what exactly is used as executable by setting the "executable" setting, which needs to be a list of strings. Additionally, you can add a ``cmd_prefix`` parameter to your class, which also needs to be a list of strings, which are prefixed to the current command (e.g. if you want to add a profiler to all your tasks) """ @functools.wraps(run_function) def wrapped_run_function(self): if get_setting("local_execution", False): _run_task_locally(self, run_function) else: _run_task_remote(self) return wrapped_run_function class DispatchableTask(Task): """ Instead of using the :obj:`dispatch` function wrapper, you can also inherit from this class. Except that, it has exactly the same functionality as a normal :obj:`Task`. Important: You need to overload the process function instead of the run function in this case! """ def process(self): """ Override this method with your normal run function. Do not touch the run function itself! """ raise NotImplementedError def run(self): dispatch(self.__class__.process)(self) PKn@ M)=b2luigi/core/parameter.pyimport hashlib import luigi from luigi.parameter import _no_value def wrap_parameter(): """ Monkey patch the parameter base class (and with it all other parameters( of luigi to include an additional "hashed" parameter in its constructor. Enabling this parameter will use a hashed version of the parameter value when creating file paths our of the parameters of a task instead of the value itself. This is especially useful when you have list, string or dict parameters, where the resulting file path may include "/" or "{}". """ import b2luigi parameter_class = b2luigi.Parameter def serialize_hashed(self, x): return "hashed_" + hashlib.md5(str(x).encode()).hexdigest() old_init = parameter_class.__init__ def __init__(self, hashed=False, *args, **kwargs): old_init(self, *args, **kwargs) if hashed: self.serialize_hashed = lambda x: serialize_hashed(self, x) parameter_class.__init__ = __init__ class BoolParameter(luigi.BoolParameter): """Copied BoolParameter without default value""" def __init__(self, **kwargs): kwargs.setdefault("default", _no_value) luigi.Parameter.__init__(self, **kwargs) PKn@ MWtl  b2luigi/core/settings.pyimport json import os # The global object hosting the current settings _current_global_settings = {} def get_setting(key, default=None): """ ``b2luigi`` adds a settings management to ``luigi`` and also uses it at various places. With this function, you can get the current value of a specific setting with the given key. If there is no setting defined with this name, either the default is returned or, if you did not supply any default, a value error is raised. For information on how settings are set, please see :obj:`set_setting`. Settings can be of any type, but are mostly strings. Parameters: key (:obj:`str`): The name of the parameter to query. default (optional): If there is no setting which the name, either return this default or if it is not set, raise a ValueError. """ try: return _current_global_settings[key] except KeyError: for settings_file in _setting_file_iterator(): try: with open(settings_file , "r") as f: return json.load(f)[key] except KeyError: pass if default is None: raise ValueError(f"No settings found for {key}!") return default def set_setting(key, value): """ There are two possibilities to set a setting with a given name: * Either you use this function and supply the key and the value. The setting is then defined globally for all following calls to :obj:`get_setting` with the specific key. * Or you add a file called ``settings.json`` the the current working directory *or any folder above that*. In the json file, you need to supply a key and a value for each setting you want to have, e.g:: { "result_path": "results", "some_setting": "some_value" } By looking also in the parent folders for setting files, you can define project settings in a top folder and specific settings further down in your local folders. """ _current_global_settings[key] = value def clear_setting(key): """ Clear the setting with the given key """ try: del _current_global_settings[key] except KeyError: pass def _setting_file_iterator(): path = os.getcwd() while True: json_file = os.path.join(path, "settings.json") if os.path.exists(json_file): yield json_file path = os.path.split(path)[0] if path == "/": break PKU ML3b2luigi/core/task.pyfrom b2luigi.core import utils import luigi from b2luigi.core.utils import create_output_file_name class Task(luigi.Task): """ Drop in replacement for ``luigi.Task`` which is 100% API compatible. It just adds some useful methods for handling output file name generation using the parameters of the task. See :ref:`quick-start-label` on information on how to use the methods. Example:: class MyAverageTask(b2luigi.Task): def requires(self): for i in range(100): yield self.clone(MyNumberTask, some_parameter=i) def output(self): yield self.add_to_output("average.txt") def run(self): # Build the mean summed_numbers = 0 counter = 0 for input_file in self.get_input_file_names("output_file.txt"): with open(input_file, "r") as f: summed_numbers += float(f.read()) counter += 1 average = summed_numbers / counter with self.get_output_file("average.txt").open("w") as f: f.write(f"{average}\\n") """ def add_to_output(self, output_file_name): """ Call this in your output() function to add a target to the list of files, this task will output. Always use in combination with `yield`. This function will automatically add all current parameter values to the file name when used in the form ``result_path/param_1=value/param_2=value/output_file_name`` This function will automatically use a ``LocalTarget``. If you do not want this, you can override the :obj:`_get_output_file_target` function. Example: This adds two files called ``some_file.txt`` and ``some_other_file.txt`` to the output:: def output(self): yield self.add_to_output("some_file.txt") yield self.add_to_output("some_other_file.txt") Args: output_file_name (:obj:`str`): the file name of the output file. Refer to this file name as a key when using :obj:`get_input_file_names`, :obj:`get_output_file_names` or :obj:`get_output_file`. """ return {output_file_name: self._get_output_file_target(output_file_name, create_folder=True)} def get_input_file_names(self, key=None): """ Get a dictionary of input file names of the tasks, which are defined in our requirements. Either use the key argument or dictionary indexing with the key given to :obj:`add_to_output` to get back a list (!) of file paths. Args: key (:obj:`str`, optional): If given, only return a list of file paths with this given key. Return: If key is none, returns a dictionary of keys to list of file paths. Else, returns only the list of file paths for this given key. """ input_list = utils.flatten_to_list_of_dicts(self.input()) file_paths = utils.flatten_to_file_paths(input_list) if key is not None: return file_paths[key] else: return file_paths def get_output_file_name(self, key): """ Analogous to :obj:`get_input_file_names` this function returns a an output file defined in out output function with the given key. In contrast to :obj:`get_input_file_names`, only a single file name will be returned (as there can only be a single output file with a given name). Args: key (:obj:`str`): Return the file path with this given key. Return: Returns only the file path for this given key. """ target = self._get_output_target(key) file_paths = utils.flatten_to_file_paths(target) return file_paths def _get_input_targets(self, key): """Shortcut to get the input targets for a given key. Will return a luigi target.""" input_dict = utils.flatten_to_list_of_dicts(self.input()) return input_dict[key] def _get_output_target(self, key): """Shortcut to get the output target for a given key. Will return a luigi target.""" output_dict = utils.flatten_to_dict(self.output()) return output_dict[key] def _get_output_file_target(self, base_filename, **kwargs): file_name = create_output_file_name(self, base_filename, **kwargs) return luigi.LocalTarget(file_name) class ExternalTask(Task, luigi.ExternalTask): """Direct copy of :obj:`luigi.ExternalTask`, but with the capabilities of :obj:`Task` added.""" pass class WrapperTask(Task, luigi.WrapperTask): """Direct copy of :obj:`luigi.WrapperTask`, but with the capabilities of :obj:`Task` added.""" pass class NotCompletedTask(Task): def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) self.check_complete = True def complete(self): """Custom complete function checking also the child tasks until a check_complete = False is reached""" if not super().complete(): return False if not self.check_complete: return True requires = self.requires() try: if not requires.complete(): return False except AttributeError: for task in requires: if not task.complete(): return False return True PKn@ M] !b2luigi/core/temporary_wrapper.pyfrom contextlib import ExitStack from functools import wraps class TemporaryFileContextManager(ExitStack): def __init__(self, task): super().__init__() self._task = task self._task_output_function = task.get_output_file_name self._open_files = {} def __enter__(self): def get_output_file_name(key): if key not in self._open_files: target = self._task._get_output_target(key) temporary_path = target.temporary_path() self._open_files[key] = self.enter_context(temporary_path) return self._open_files[key] self._task.get_output_file_name = get_output_file_name def __exit__(self, *exc_details): super().__exit__(*exc_details) self._task.get_output_file_name = self._task_output_function def on_temporary_files(run_function): """ Wrapper for decorating a task's run function to use temporary files as outputs. A common problem when using long running tasks in luigi is the thanksgiving bug. It occurs, when you define an output of a task and in its run function you create this output and fill it with content during a long lasting calculation. It may happen, that during the creation of the output and the finish of the calculation some other tasks look if the output is already there, find it existing and assume, that the task is already finished (although there is probably only nonsense in the file). A solution is already given by luigi itself, when using the temporary_path() function of the file system targets, which is really nice! Unfortunately, this means you have to open all your output files with a context manager and this is very hard to do if you have external tasks also (because they will probably use the output file directly instead of the temporary file version of if). This wrapper simplifies the usage of the temporary files:: import b2luigi class MyTask(b2luigi.Task): def output(self): yield self.add_to_output("test.txt") @b2luigi.on_temporary_files def run(self): with open(self.get_output_file_name("test.txt"), "w") as f: raise ValueError() f.write("Test") Instead of creating the file "test.txt" at the beginning and filling it with content later (which will never happen because of the exception thrown, mich makes the file existing but the task actually not finished), the file will be written to a temporary file first and copied to its final location at the end of the run function (but only if there was no error). *Attention*: The decorator only edits the function get_output_file_name. If you are using the output directly, you have to take care of using the temporary path correctly by yourself! """ @wraps(run_function) def run(self): with TemporaryFileContextManager(self): run_function(self) return runPK]MO"1#1#b2luigi/core/utils.pyimport contextlib import importlib import itertools import os import collections import sys import types import colorama from b2luigi.core.settings import set_setting, get_setting @contextlib.contextmanager def remember_cwd(): """Helper contextmanager to stay in the same cwd""" old_cwd = os.getcwd() try: yield finally: os.chdir(old_cwd) def product_dict(**kwargs): """ Cross-product the given parameters and return a list of dictionaries. Example: .. code-block:: python >>> list(product_dict(arg_1=[1, 2], arg_2=[3, 4])) [{'arg_1': 1, 'arg_2': 3}, {'arg_1': 1, 'arg_2': 4}, {'arg_1': 2, 'arg_2': 3}, {'arg_1': 2, 'arg_2': 4}] :param kwargs: Each keyword argument should be an iterable :return: A list of kwargs where each list of input keyword arguments is cross-multiplied with every other. """ keys = kwargs.keys() vals = kwargs.values() for instance in itertools.product(*vals): yield dict(zip(keys, instance)) def fill_kwargs_with_lists(**kwargs): """ Return the kwargs with each value mapped to [value] if not a list already. Example: .. code-block:: python >>> fill_kwargs_with_lists(arg_1=[1, 2], arg_2=3) {'arg_1': [1, 2], 'arg_2': [3]} :param kwargs: The input keyword arguments :return: Same as kwargs, but each value mapped to a list if not a list already """ return_kwargs = {} for key, value in kwargs.items(): if value is None: value = [] if isinstance(value, str) or not isinstance(value, collections.Iterable): value = [value] return_kwargs[key] = value return return_kwargs def flatten_to_file_paths(inputs): """ Take in a structure of something and replace each luigi target by its corresponding path. For dicts, it will replace the value as well as the key. The key will however only by the basename of the path. :param inputs: A dict or a luigi target :return: A dict with the keys replaced by the basename of the targets and the values by the full path """ if not inputs: return None try: return inputs.path except AttributeError: pass if isinstance(inputs, dict): return {os.path.basename(flatten_to_file_paths(key)): flatten_to_file_paths(value) for key, value in inputs.items()} elif isinstance(inputs, list): return [flatten_to_file_paths(value) for value in inputs] else: return inputs def flatten_to_dict(inputs): """ Return a whatever input structure into a dictionary. If it is a dict already, return this. If is is an iterable of dict or dict-like objects, return the merged dictionary. All non-dict values will be turned into a dictionary with value -> {value: value} Example: .. code-block:: python >>> flatten_to_dict([{"a": 1, "b": 2}, {"c": 3}, "d"]) {'a': 1, 'b': 2, 'c': 3, 'd': 'd'} :param inputs: The input structure :return: A dict constructed as described above. """ inputs = _flatten(inputs) inputs = map(_to_dict, inputs) joined_dict = {} for i in inputs: for key, value in i.items(): joined_dict[key] = value return joined_dict def flatten_to_list_of_dicts(inputs): inputs = _flatten(inputs) inputs = map(_to_dict, inputs) joined_dict = collections.defaultdict(list) for i in inputs: for key, value in i.items(): joined_dict[key].append(value) return dict(joined_dict) def task_iterator(task, only_non_complete=False): if not only_non_complete or not task.complete(): yield task for dep in task.deps(): yield from task_iterator(dep, only_non_complete=only_non_complete) def get_all_output_files_in_tree(root_module, key=None): if key: return get_all_output_files_in_tree(root_module)[key] all_output_files = collections.defaultdict(list) for task in task_iterator(root_module): output_dict = flatten_to_dict(task.output()) if not output_dict: continue for target_key, target in output_dict.items(): converted_dict = flatten_to_file_paths({target_key: target}) file_key, file_name = converted_dict.popitem() all_output_files[file_key].append(dict(exists=target.exists(), parameters=get_serialized_parameters(task), file_name=os.path.abspath(file_name))) return all_output_files def filter_from_params(output_files, **kwargs): kwargs_list = fill_kwargs_with_lists(**kwargs) if not kwargs_list: return output_files file_names = [] for kwargs in product_dict(**kwargs_list): for output_dict in output_files: parameters = output_dict["parameters"] not_use = False for key, value in kwargs.items(): if key in parameters and str(parameters[key]) != str(value): not_use = True break if not_use: continue file_names.append(output_dict) return {x["file_name"]: x for x in file_names}.values() def get_task_from_file(file_name, task_name, settings=None, **kwargs): with remember_cwd(): os.chdir(os.path.dirname(file_name)) spec = importlib.util.spec_from_file_location("module.name", os.path.basename(file_name)) task_module = importlib.util.module_from_spec(spec) spec.loader.exec_module(task_module) if settings: for key, value in settings.items(): set_setting(key, value) m = getattr(task_module, task_name)(**kwargs) return m def get_serialized_parameters(task): """Get a string-typed ordered dict of key=value for the significant parameters""" serialized_parameters = collections.OrderedDict() for key, parameter in task.get_params(): if not parameter.significant: continue value = getattr(task, key) if hasattr(parameter, "serialize_hashed"): value = parameter.serialize_hashed(value) else: value = parameter.serialize(value) serialized_parameters[key] = value return serialized_parameters def create_output_file_name(task, base_filename, create_folder=False, result_path=None): serialized_parameters = get_serialized_parameters(task) if not result_path: result_path = get_setting("result_path", ".") param_list = [f"{key}={value}" for key, value in serialized_parameters.items()] filename = os.path.join(result_path, *param_list, base_filename) if create_folder: os.makedirs(os.path.dirname(filename), exist_ok=True) return filename def get_log_file_dir(task): if hasattr(task, 'get_log_file_dir'): log_file_dir = task.get_log_file_dir() return log_file_dir filename = os.path.realpath(sys.argv[0]) base_log_file_dir = get_setting("log_folder", default=os.path.join(os.path.dirname(filename), "logs")) log_file_dir = create_output_file_name(task, task.get_task_family() + "/", create_folder=True, result_path=base_log_file_dir) return log_file_dir def _to_dict(d): if isinstance(d, dict): return d return {d: d} def _flatten(struct): if isinstance(struct, dict) or isinstance(struct, str): return [struct] result = [] try: iterator = iter(struct) except TypeError: return [struct] for f in iterator: result += _flatten(f) return result def on_failure(self, exception): log_file_dir = get_log_file_dir(self) print(colorama.Fore.RED) print("Task", self.task_family, "failed!") print("Parameters") for key, value in get_filled_params(self).items(): print("\t", key, "=", value) print("Please have a look into the log files in") print(log_file_dir) print(colorama.Style.RESET_ALL) def add_on_failure_function(task): task.on_failure = types.MethodType(on_failure, task) def create_cmd_from_task(task): filename = os.path.realpath(sys.argv[0]) cmd = [] if hasattr(task, "cmd_prefix"): cmd = task.cmd_prefix executable = get_setting("executable", [sys.executable]) cmd += executable cmd += [os.path.abspath(filename), "--batch-runner", "--task-id", task.task_id] return cmd def create_output_dirs(task): """Create all output dicts if needed. Normally only used internally.""" output_list = flatten_to_dict(task.output()) output_list = output_list.values() for output in output_list: output.makedirs() def get_filled_params(task): """Helper function for getting the parameter list with each parameter set to its current value""" return {key: getattr(task, key) for key, _ in task.get_params()}PKn@ M ~~b2luigi-0.3.0.dist-info/LICENSE GNU GENERAL PUBLIC LICENSE Version 3, 29 June 2007 Copyright (C) 2007 Free Software Foundation, Inc. Everyone is permitted to copy and distribute verbatim copies of this license document, but changing it is not allowed. Preamble The GNU General Public License is a free, copyleft license for software and other kinds of works. The licenses for most software and other practical works are designed to take away your freedom to share and change the works. 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IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS), EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES. 17. Interpretation of Sections 15 and 16. If the disclaimer of warranty and limitation of liability provided above cannot be given local legal effect according to their terms, reviewing courts shall apply local law that most closely approximates an absolute waiver of all civil liability in connection with the Program, unless a warranty or assumption of liability accompanies a copy of the Program in return for a fee. PK!Hp!Qab2luigi-0.3.0.dist-info/WHEEL HM K-*ϳR03rOK-J,/RH,zd&Y)r$[)T&UD"PK!H)W ^ b2luigi-0.3.0.dist-info/METADATA]KO@ +|$R@N$J=xJ[ }ly~+*$=4Ll7QM 5fHg]"×=hl wK2: U=40!w{y)zS;>r=P;e 9T>, =0r:,n}GvGA_ 8t Kcl.*PPK!HG͘rFb2luigi-0.3.0.dist-info/RECORDɒH} $ ,z(!e$搜{jEզ_sΟdHCd?}?Ci@1_Nsou$oYF!B3Xrt)jYk[)cG t-ru#.\'uQ7-5֙QRp8cA~Aaj.fꂶ}-#qED ƫCΗm