Source code for toil.common

# Copyright (C) 2015-2021 Regents of the University of California
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# See the License for the specific language governing permissions and
# limitations under the License.
import json
import logging
import os
import pickle
import re
import signal
import subprocess
import sys
import tempfile
import time
import uuid
import warnings
from argparse import (SUPPRESS,
from distutils.util import strtobool
from functools import lru_cache
from types import TracebackType
from typing import (IO,
from urllib.parse import urlparse, unquote, quote

import requests
from configargparse import ArgParser, YAMLConfigFileParser
from ruamel.yaml import YAML
from ruamel.yaml.comments import CommentedMap

if sys.version_info >= (3, 8):
    from typing import Literal
    from typing_extensions import Literal

from toil import logProcessContext, lookupEnvVar
from toil.batchSystems.options import (add_all_batchsystem_options,
from toil.bus import (ClusterDesiredSizeMessage,
from toil.fileStores import FileID
from import zone_to_region
from toil.lib.compatibility import deprecated
from toil.lib.conversions import bytes2human, human2bytes
from import AtomicFileCreate, try_path
from toil.lib.retry import retry
from toil.provisioners import (add_provisioner_options,
from toil.realtimeLogger import RealtimeLogger
from toil.statsAndLogging import add_logging_options, set_logging_from_options
from toil.version import dockerRegistry, dockerTag, version

    from toil.batchSystems.abstractBatchSystem import AbstractBatchSystem
    from toil.batchSystems.options import OptionSetter
    from toil.job import (AcceleratorRequirement,
    from toil.jobStores.abstractJobStore import AbstractJobStore
    from toil.provisioners.abstractProvisioner import AbstractProvisioner
    from toil.resource import ModuleDescriptor

# aim to pack autoscaling jobs within a 30 minute block before provisioning a new node
defaultTargetTime = 1800
SYS_MAX_SIZE = 9223372036854775807
# sys.max_size on 64 bit systems is 9223372036854775807, so that 32-bit systems
# use the same number
logger = logging.getLogger(__name__)

# TODO: should this use an XDG config directory or ~/.config to not clutter the
# base home directory?
TOIL_HOME_DIR: str = os.path.join(os.path.expanduser("~"), ".toil")
DEFAULT_CONFIG_FILE: str = os.path.join(TOIL_HOME_DIR, "default.yaml")

[docs] def parse_jobstore(jobstore_uri: str) -> str: """ Turn the jobstore string into it's corresponding URI ex: /path/to/jobstore -> file:/path/to/jobstore If the jobstore string already is a URI, return the jobstore: aws:/path/to/jobstore -> aws:/path/to/jobstore :param jobstore_uri: string of the jobstore :return: URI of the jobstore """ name, rest = Toil.parseLocator(jobstore_uri) if name == "file": # We need to resolve relative paths early, on the leader, because the worker process # may have a different working directory than the leader, e.g. under Mesos. return Toil.buildLocator(name, os.path.abspath(rest)) else: return jobstore_uri
[docs] def parse_str_list(s: str) -> List[str]: return [str(x) for x in s.split(",")]
[docs] def parse_int_list(s: str) -> List[int]: return [int(x) for x in s.split(",")]
[docs] class Config: """Class to represent configuration operations for a toil workflow run.""" logFile: Optional[str] logRotating: bool cleanWorkDir: str max_jobs: int max_local_jobs: int manualMemArgs: bool run_local_jobs_on_workers: bool coalesceStatusCalls: bool mesos_endpoint: Optional[str] mesos_framework_id: Optional[str] mesos_role: Optional[str] mesos_name: str kubernetes_host_path: Optional[str] kubernetes_owner: Optional[str] kubernetes_service_account: Optional[str] kubernetes_pod_timeout: float tes_endpoint: str tes_user: str tes_password: str tes_bearer_token: str aws_batch_region: Optional[str] aws_batch_queue: Optional[str] aws_batch_job_role_arn: Optional[str] scale: float batchSystem: str batch_logs_dir: Optional[str] """The backing scheduler will be instructed, if possible, to save logs to this directory, where the leader can read them.""" statePollingWait: int disableAutoDeployment: bool # Core options workflowID: Optional[str] """This attribute uniquely identifies the job store and therefore the workflow. It is necessary in order to distinguish between two consecutive workflows for which self.jobStore is the same, e.g. when a job store name is reused after a previous run has finished successfully and its job store has been clean up.""" workflowAttemptNumber: int jobStore: str logLevel: str workDir: Optional[str] coordination_dir: Optional[str] noStdOutErr: bool stats: bool # Because the stats option needs the jobStore to persist past the end of the run, # the clean default value depends the specified stats option and is determined in setOptions clean: Optional[str] clusterStats: str # Restarting the workflow options restart: bool # Batch system options # File store options caching: Optional[bool] symlinkImports: bool moveOutputs: bool # Autoscaling options provisioner: Optional[str] nodeTypes: List[Tuple[Set[str], Optional[float]]] minNodes: List[int] maxNodes: List[int] targetTime: float betaInertia: float scaleInterval: int preemptibleCompensation: float nodeStorage: int nodeStorageOverrides: List[str] metrics: bool assume_zero_overhead: bool # Parameters to limit service jobs, so preventing deadlock scheduling scenarios maxPreemptibleServiceJobs: int maxServiceJobs: int deadlockWait: Union[float, int] deadlockCheckInterval: Union[float, int] # Resource requirements defaultMemory: int defaultCores: Union[float, int] defaultDisk: int defaultPreemptible: bool # TODO: These names are generated programmatically in # Requirer._fetchRequirement so we can't use snake_case until we fix # that (and add compatibility getters/setters?) defaultAccelerators: List["AcceleratorRequirement"] maxCores: int maxMemory: int maxDisk: int # Retrying/rescuing jobs retryCount: int enableUnlimitedPreemptibleRetries: bool doubleMem: bool maxJobDuration: int rescueJobsFrequency: int # Log management maxLogFileSize: int writeLogs: str writeLogsGzip: str writeLogsFromAllJobs: bool write_messages: Optional[str] realTimeLogging: bool # Misc environment: Dict[str, str] disableChaining: bool disableJobStoreChecksumVerification: bool sseKey: Optional[str] servicePollingInterval: int useAsync: bool forceDockerAppliance: bool statusWait: int disableProgress: bool readGlobalFileMutableByDefault: bool # Debug options debugWorker: bool disableWorkerOutputCapture: bool badWorker: float badWorkerFailInterval: float kill_polling_interval: int # CWL cwl: bool def __init__(self) -> None: # only default options that are not CLI options defined here (thus CLI options are centralized) self.cwl = False # will probably remove later self.workflowID = None self.kill_polling_interval = 5 self.set_from_default_config()
[docs] def set_from_default_config(self) -> None: # get defaults from a config file by simulating an argparse run # as Config often expects defaults to already be instantiated if not os.path.exists(DEFAULT_CONFIG_FILE): # The default config file did not appear to exist when we checked. # It might exist now, though. Try creating it. self.generate_config_file() # Check on the config file to make sure it is sensible config_status = os.stat(DEFAULT_CONFIG_FILE) if config_status.st_size == 0: # If we have an empty config file, someone has to manually delete # it before we will work again. raise RuntimeError( f"Config file {DEFAULT_CONFIG_FILE} exists but is empty. Delete it! Stat says: {config_status}" ) logger.debug("Loading %s byte default configuration", config_status.st_size) try: with open(DEFAULT_CONFIG_FILE, "r") as f: yaml = YAML(typ="safe") s = yaml.load(f) logger.debug("Loaded default configuration: %s", json.dumps(s)) except: # Something went wrong reading the default config, so dump its # contents to the log. "Configuration file contents: %s", open(DEFAULT_CONFIG_FILE, "r").read() ) raise parser = ArgParser() addOptions(parser, jobstore_as_flag=True) ns = parser.parse_args(f"--config={DEFAULT_CONFIG_FILE}") self.setOptions(ns)
[docs] def generate_config_file(self) -> None: """ If the default config file does not exist, create it. Raises an error if the default config file cannot be created. Safe to run simultaneously in multiple processes. If this process runs this function, it will always see the default config file existing with parseable contents, even if other processes are racing to create it. No process will see an empty or partially-written default config file. """ check_and_create_toil_home_dir() generate_config(DEFAULT_CONFIG_FILE)
[docs] def prepare_start(self) -> None: """ After options are set, prepare for initial start of workflow. """ self.workflowAttemptNumber = 0
[docs] def prepare_restart(self) -> None: """ Before restart options are set, prepare for a restart of a workflow. Set up any execution-specific parameters and clear out any stale ones. """ self.workflowAttemptNumber += 1 # We should clear the stored message bus path, because it may have been # auto-generated and point to a temp directory that could no longer # exist and that can't safely be re-made. self.write_messages = None
[docs] def setOptions(self, options: Namespace) -> None: """Creates a config object from the options object.""" def set_option(option_name: str, old_names: Optional[List[str]] = None) -> None: """ Determine the correct value for the given option. Priority order is: 1. options object under option_name 2. options object under old_names 3. environment variables in env 4. provided default value Selected option value is run through parsing_funtion if it is set. Then the parsed value is run through check_function to check it for acceptability, which should raise AssertionError if the value is unacceptable. If the option gets a non-None value, sets it as an attribute in this Config. """ option_value = getattr(options, option_name, None) if old_names is not None: for old_name in old_names: # If the option is already set with the new name and not the old name # prioritize the new name over the old name and break if ( option_value is not None and option_value != [] and option_value != {} ): break # Try all the old names in case user code is setting them # in an options object. # This does assume that all deprecated options have a default value of None if getattr(options, old_name, None) is not None: warnings.warn( f"Using deprecated option field {old_name} to " f"provide value for config field {option_name}", DeprecationWarning, ) option_value = getattr(options, old_name) if option_value is not None or not hasattr(self, option_name): setattr(self, option_name, option_value) # Core options set_option("jobStore") # TODO: LOG LEVEL STRING set_option("workDir") set_option("coordination_dir") set_option("noStdOutErr") set_option("stats") set_option("cleanWorkDir") set_option("clean") set_option("clusterStats") set_option("restart") # Batch system options set_option("batchSystem") set_batchsystem_options( None, cast("OptionSetter", set_option) ) # None as that will make set_batchsystem_options iterate through all batch systems and set their corresponding values # File store options set_option("symlinkImports", old_names=["linkImports"]) set_option("moveOutputs", old_names=["moveExports"]) set_option("caching", old_names=["enableCaching"]) # Autoscaling options set_option("provisioner") set_option("nodeTypes") set_option("minNodes") set_option("maxNodes") set_option("targetTime") set_option("betaInertia") set_option("scaleInterval") set_option("metrics") set_option("assume_zero_overhead") set_option("preemptibleCompensation") set_option("nodeStorage") set_option("nodeStorageOverrides") if self.cwl is False: # Parameters to limit service jobs / detect deadlocks set_option("maxServiceJobs") set_option("maxPreemptibleServiceJobs") set_option("deadlockWait") set_option("deadlockCheckInterval") set_option("defaultMemory") set_option("defaultCores") set_option("defaultDisk") set_option("defaultAccelerators") set_option("maxCores") set_option("maxMemory") set_option("maxDisk") set_option("defaultPreemptible") # Retrying/rescuing jobs set_option("retryCount") set_option("enableUnlimitedPreemptibleRetries") set_option("doubleMem") set_option("maxJobDuration") set_option("rescueJobsFrequency") # Log management set_option("maxLogFileSize") set_option("writeLogs") set_option("writeLogsGzip") set_option("writeLogsFromAllJobs") set_option("write_messages") # Misc set_option("environment") set_option("disableChaining") set_option("disableJobStoreChecksumVerification") set_option("statusWait") set_option("disableProgress") set_option("sseKey") set_option("servicePollingInterval") set_option("forceDockerAppliance") # Debug options set_option("debugWorker") set_option("disableWorkerOutputCapture") set_option("badWorker") set_option("badWorkerFailInterval") set_option("logLevel") self.check_configuration_consistency()
[docs] def check_configuration_consistency(self) -> None: """Old checks that cannot be fit into an action class for argparse""" if self.writeLogs and self.writeLogsGzip: raise ValueError( "Cannot use both --writeLogs and --writeLogsGzip at the same time." ) if self.writeLogsFromAllJobs and not self.writeLogs and not self.writeLogsGzip: raise ValueError( "To enable --writeLogsFromAllJobs, either --writeLogs or --writeLogsGzip must be set." ) for override in self.nodeStorageOverrides: tokens = override.split(":") if not any(tokens[0] in n[0] for n in self.nodeTypes): raise ValueError( "Instance type in --nodeStorageOverrides must be in --nodeTypes" ) if self.stats: if self.clean != "never" and self.clean is not None: logger.warning( "Contradicting options passed: Clean flag is set to %s " "despite the stats flag requiring " "the jobStore to be intact at the end of the run. " "Setting clean to 'never'." % self.clean ) self.clean = "never"
[docs] def __eq__(self, other: object) -> bool: return self.__dict__ == other.__dict__
[docs] def __hash__(self) -> int: return self.__dict__.__hash__() # type: ignore
[docs] def check_and_create_toil_home_dir() -> None: """ Ensure that TOIL_HOME_DIR exists. Raises an error if it does not exist and cannot be created. Safe to run simultaneously in multiple processes. """ dir_path = try_path(TOIL_HOME_DIR) if dir_path is None: raise RuntimeError( f"Cannot create or access Toil configuration directory {TOIL_HOME_DIR}" )
[docs] def generate_config(filepath: str) -> None: """ Write a Toil config file to the given path. Safe to run simultaneously in multiple processes. No process will see an empty or partially-written file at the given path. """ # this is placed in rather than to prevent circular imports # configargparse's write_config function does not write options with a None value # Thus, certain CLI options that use None as their default won't be written to the config file. # it also does not support printing config elements in nonalphabetical order # Instead, mimic configargparser's write_config behavior and also make it output arguments with # a default value of None # To do this, iterate through the options # Skip --help and --config as they should not be included in the config file # Skip deprecated/redundant options # Various log options are skipped as they are store_const arguments that are redundant to --logLevel # linkImports, moveExports, disableCaching, are deprecated in favor of --symlinkImports, --moveOutputs, # and --caching respectively # Skip StoreTrue and StoreFalse options that have opposite defaults as including it in the config would # override those defaults deprecated_or_redundant_options = ( "help", "config", "logCritical", "logDebug", "logError", "logInfo", "logOff", "logWarning", "linkImports", "noLinkImports", "moveExports", "noMoveExports", "enableCaching", "disableCaching", ) parser = ArgParser(YAMLConfigFileParser()) addOptions(parser, jobstore_as_flag=True) data = CommentedMap() # to preserve order group_title_key: Dict[str, str] = dict() for action in parser._actions: if any( s.replace("-", "") in deprecated_or_redundant_options for s in action.option_strings ): continue # if action is StoreFalse and default is True then don't include if isinstance(action, _StoreFalseAction) and action.default is True: continue # if action is StoreTrue and default is False then don't include if isinstance(action, _StoreTrueAction) and action.default is False: continue option_string = ( action.option_strings[0] if action.option_strings[0].find("--") != -1 else action.option_strings[1] ) option = option_string[2:] default = action.default data[option] = default # store where each argparse group starts group_title = action.container.title # type: ignore[attr-defined] group_title_key.setdefault(group_title, option) # add comment for when each argparse group starts for group_title, key in group_title_key.items(): data.yaml_set_comment_before_after_key(key, group_title) # Now we need to put the config file in place at filepath. # But someone else may have already created a file at that path, or may be # about to open the file at that path and read it before we can finish # writing the contents. So we write the config file at a temporary path and # atomically move it over. There's still a race to see which process's # config file actually is left at the name in the end, but nobody will ever # see an empty or partially-written file at that name (if there wasn't one # there to begin with). with AtomicFileCreate(filepath) as temp_path: with open(temp_path, "w") as f: yaml = YAML() yaml.dump(data, f)
JOBSTORE_HELP = ( "The location of the job store for the workflow. " "A job store holds persistent information about the jobs, stats, and files in a " "workflow. If the workflow is run with a distributed batch system, the job " "store must be accessible by all worker nodes. Depending on the desired " "job store implementation, the location should be formatted according to " "one of the following schemes:\n\n" "file:<path> where <path> points to a directory on the file systen\n\n" "aws:<region>:<prefix> where <region> is the name of an AWS region like " "us-west-2 and <prefix> will be prepended to the names of any top-level " "AWS resources in use by job store, e.g. S3 buckets.\n\n " "google:<project_id>:<prefix> TODO: explain\n\n" "For backwards compatibility, you may also specify ./foo (equivalent to " "file:./foo or just file:foo) or /bar (equivalent to file:/bar)." )
[docs] def parser_with_common_options( provisioner_options: bool = False, jobstore_option: bool = True ) -> ArgParser: parser = ArgParser(prog="Toil", formatter_class=ArgumentDefaultsHelpFormatter) if provisioner_options: add_provisioner_options(parser) if jobstore_option: parser.add_argument("jobStore", type=str, help=JOBSTORE_HELP) # always add these add_logging_options(parser) parser.add_argument("--version", action="version", version=version) parser.add_argument( "--tempDirRoot", dest="tempDirRoot", type=str, default=tempfile.gettempdir(), help="Path to where temporary directory containing all temp files are created, " "by default generates a fresh tmp dir with 'tempfile.gettempdir()'.", ) return parser
# This is kept in the outer scope as multiple batchsystem files use this
[docs] def make_open_interval_action( min: Union[int, float], max: Optional[Union[int, float]] = None ) -> Type[Action]: """ Returns an argparse action class to check if the input is within the given half-open interval. ex: Provided value to argparse must be within the interval [min, max) Types of min and max must be the same (max may be None) :param min: float/int :param max: optional float/int :return: argparse action class """ class IntOrFloatOpenAction(Action): def __call__( self, parser: Any, namespace: Any, values: Any, option_string: Any = None ) -> None: if isinstance(min, int): if max is not None: # for mypy assert isinstance(max, int) func = iC(min, max) else: func = fC(min, max) try: if not func(values): raise parser.error( f"{option_string} ({values}) must be within the range: [{min}, {'infinity' if max is None else max})" ) except AssertionError: raise RuntimeError( f"The {option_string} option has an invalid value: {values}" ) setattr(namespace, self.dest, values) return IntOrFloatOpenAction
[docs] def addOptions( parser: ArgumentParser, jobstore_as_flag: bool = False, cwl: bool = False ) -> None: """ Add Toil command line options to a parser. Support for config files. :param config: If specified, take defaults from the given Config. :param jobstore_as_flag: make the job store option a --jobStore flag instead of a required jobStore positional argument. """ if not (isinstance(parser, ArgumentParser) or isinstance(parser, _ArgumentGroup)): raise ValueError( f"Unanticipated class: {parser.__class__}. Must be: argparse.ArgumentParser or ArgumentGroup." ) if isinstance(parser, ArgParser): # in case the user passes in their own configargparse instance instead of calling getDefaultArgumentParser() # this forces configargparser to process the config file in YAML rather than in it's own format parser._config_file_parser = YAMLConfigFileParser() # type: ignore[misc] else: # configargparse advertises itself as a drag and drop replacement, and running the normal argparse ArgumentParser # through this code still seems to work (with the exception of --config and environmental variables) warnings.warn( f"Using deprecated library argparse for options parsing." f"This will not parse config files or use environment variables." f"Use configargparse instead or call Job.Runner.getDefaultArgumentParser()", DeprecationWarning, ) opt_strtobool = lambda b: b if b is None else bool(strtobool(b)) convert_bool = lambda b: bool(strtobool(b)) add_logging_options(parser) parser.register("type", "bool", parseBool) # Custom type for arg=True/False. # Core options core_options = parser.add_argument_group( title="Toil core options.", description="Options to specify the location of the Toil workflow and " "turn on stats collation about the performance of jobs.", ) if jobstore_as_flag: core_options.add_argument( "--jobstore", "--jobStore", dest="jobStore", type=parse_jobstore, default=None, help=JOBSTORE_HELP, ) else: core_options.add_argument("jobStore", type=parse_jobstore, help=JOBSTORE_HELP) class WorkDirAction(Action): """ Argparse action class to check that the provided --workDir exists """ def __call__( self, parser: Any, namespace: Any, values: Any, option_string: Any = None ) -> None: workDir = values if workDir is not None: workDir = os.path.abspath(workDir) if not os.path.exists(workDir): raise RuntimeError( f"The path provided to --workDir ({workDir}) does not exist." ) if len(workDir) > 80: logger.warning( f'Length of workDir path "{workDir}" is {len(workDir)} characters. ' f"Consider setting a shorter path with --workPath or setting TMPDIR to something " f'like "/tmp" to avoid overly long paths.' ) setattr(namespace, self.dest, workDir) class CoordinationDirAction(Action): """ Argparse action class to check that the provided --coordinationDir exists """ def __call__( self, parser: Any, namespace: Any, values: Any, option_string: Any = None ) -> None: coordination_dir = values if coordination_dir is not None: coordination_dir = os.path.abspath(coordination_dir) if not os.path.exists(coordination_dir): raise RuntimeError( f"The path provided to --coordinationDir ({coordination_dir}) does not exist." ) setattr(namespace, self.dest, coordination_dir) def make_closed_interval_action( min: Union[int, float], max: Optional[Union[int, float]] = None ) -> Type[Action]: """ Returns an argparse action class to check if the input is within the given half-open interval. ex: Provided value to argparse must be within the interval [min, max] :param min: int/float :param max: optional int/float :return: argparse action """ class ClosedIntOrFloatAction(Action): def __call__( self, parser: Any, namespace: Any, values: Any, option_string: Any = None, ) -> None: def is_within(x: Union[int, float]) -> bool: if max is None: return min <= x else: return min <= x <= max try: if not is_within(values): raise parser.error( f"{option_string} ({values}) must be within the range: [{min}, {'infinity' if max is None else max}]" ) except AssertionError: raise RuntimeError( f"The {option_string} option has an invalid value: {values}" ) setattr(namespace, self.dest, values) return ClosedIntOrFloatAction core_options.add_argument( "--workDir", dest="workDir", default=None, env_var="TOIL_WORKDIR", action=WorkDirAction, help="Absolute path to directory where temporary files generated during the Toil " "run should be placed. Standard output and error from batch system jobs " "(unless --noStdOutErr is set) will be placed in this directory. A cache directory " "may be placed in this directory. Temp files and folders will be placed in a " "directory toil-<workflowID> within workDir. The workflowID is generated by " "Toil and will be reported in the workflow logs. Default is determined by the " "variables (TMPDIR, TEMP, TMP) via mkdtemp. This directory needs to exist on " "all machines running jobs; if capturing standard output and error from batch " "system jobs is desired, it will generally need to be on a shared file system. " "When sharing a cache between containers on a host, this directory must be " "shared between the containers.", ) core_options.add_argument( "--coordinationDir", dest="coordination_dir", default=None, env_var="TOIL_COORDINATION_DIR", action=CoordinationDirAction, help="Absolute path to directory where Toil will keep state and lock files." "When sharing a cache between containers on a host, this directory must be " "shared between the containers.", ) core_options.add_argument( "--noStdOutErr", dest="noStdOutErr", default=False, action="store_true", help="Do not capture standard output and error from batch system jobs.", ) core_options.add_argument( "--stats", dest="stats", default=False, action="store_true", help="Records statistics about the toil workflow to be used by 'toil stats'.", ) clean_choices = ["always", "onError", "never", "onSuccess"] core_options.add_argument( "--clean", dest="clean", choices=clean_choices, default="onSuccess", help=f"Determines the deletion of the jobStore upon completion of the program. " f"Choices: {clean_choices}. The --stats option requires information from the " f"jobStore upon completion so the jobStore will never be deleted with that flag. " f"If you wish to be able to restart the run, choose 'never' or 'onSuccess'. " f"Default is 'never' if stats is enabled, and 'onSuccess' otherwise.", ) core_options.add_argument( "--cleanWorkDir", dest="cleanWorkDir", choices=clean_choices, default="always", help=f"Determines deletion of temporary worker directory upon completion of a job. " f"Choices: {clean_choices}. Default = always. WARNING: This option should be " f"changed for debugging only. Running a full pipeline with this option could " f"fill your disk with excessive intermediate data.", ) core_options.add_argument( "--clusterStats", dest="clusterStats", nargs="?", action="store", default=None, const=os.getcwd(), help="If enabled, writes out JSON resource usage statistics to a file. " "The default location for this file is the current working directory, but an " "absolute path can also be passed to specify where this file should be written. " "This options only applies when using scalable batch systems.", ) # Restarting the workflow options restart_options = parser.add_argument_group( title="Toil options for restarting an existing workflow.", description="Allows the restart of an existing workflow", ) restart_options.add_argument( "--restart", dest="restart", default=False, action="store_true", help="If --restart is specified then will attempt to restart existing workflow " "at the location pointed to by the --jobStore option. Will raise an exception " "if the workflow does not exist", ) # Batch system options batchsystem_options = parser.add_argument_group( title="Toil options for specifying the batch system.", description="Allows the specification of the batch system.", ) add_all_batchsystem_options(batchsystem_options) # File store options file_store_options = parser.add_argument_group( title="Toil options for configuring storage.", description="Allows configuring Toil's data storage.", ) link_imports = file_store_options.add_mutually_exclusive_group() link_imports_help = ( "When using a filesystem based job store, CWL input files are by default symlinked in. " "Setting this option to True instead copies the files into the job store, which may protect " "them from being modified externally. When set to False, as long as caching is enabled, " "Toil will protect the file automatically by changing the permissions to read-only." "default=%(default)s" ) link_imports.add_argument( "--symlinkImports", dest="symlinkImports", type=convert_bool, default=True, help=link_imports_help, ) move_exports = file_store_options.add_mutually_exclusive_group() move_exports_help = ( "When using a filesystem based job store, output files are by default moved to the " "output directory, and a symlink to the moved exported file is created at the initial " "location. Setting this option to True instead copies the files into the output directory. " "Applies to filesystem-based job stores only." "default=%(default)s" ) move_exports.add_argument( "--moveOutputs", dest="moveOutputs", type=convert_bool, default=False, help=move_exports_help, ) caching = file_store_options.add_mutually_exclusive_group() caching_help = "Enable or disable caching for your workflow, specifying this overrides default from job store" caching.add_argument( "--caching", dest="caching", type=opt_strtobool, default=None, help=caching_help ) # default is None according to PR 4299, seems to be generated at runtime # Auto scaling options autoscaling_options = parser.add_argument_group( title="Toil options for autoscaling the cluster of worker nodes.", description="Allows the specification of the minimum and maximum number of nodes in an autoscaled cluster, " "as well as parameters to control the level of provisioning.", ) provisioner_choices = ["aws", "gce", None] # TODO: Better consolidate this provisioner arg and the one in provisioners/ autoscaling_options.add_argument( "--provisioner", "-p", dest="provisioner", choices=provisioner_choices, default=None, help=f"The provisioner for cluster auto-scaling. This is the main Toil " f"'--provisioner' option, and defaults to None for running on single " f"machine and non-auto-scaling batch systems. The currently supported " f"choices are {provisioner_choices}. The default is %(default)s.", ) autoscaling_options.add_argument( "--nodeTypes", default=[], dest="nodeTypes", type=parse_node_types, action="extend", help="Specifies a list of comma-separated node types, each of which is " "composed of slash-separated instance types, and an optional spot " "bid set off by a colon, making the node type preemptible. Instance " "types may appear in multiple node types, and the same node type " "may appear as both preemptible and non-preemptible.\n" "Valid argument specifying two node types:\n" "\tc5.4xlarge/c5a.4xlarge:0.42,t2.large\n" "Node types:\n" "\tc5.4xlarge/c5a.4xlarge:0.42 and t2.large\n" "Instance types:\n" "\tc5.4xlarge, c5a.4xlarge, and t2.large\n" "Semantics:\n" "\tBid $0.42/hour for either c5.4xlarge or c5a.4xlarge instances,\n" "\ttreated interchangeably, while they are available at that price,\n" "\tand buy t2.large instances at full price.\n" "default=%(default)s", ) class NodeExtendAction(_AppendAction): """ argparse Action class to remove the default value on first call, and act as an extend action after """ # with action=append/extend, the argparse default is always prepended to the option # so make the CLI have priority by rewriting the option on the first run def __init__(self, option_strings: Any, dest: Any, **kwargs: Any): super().__init__(option_strings, dest, **kwargs) self.is_default = True def __call__( self, parser: Any, namespace: Any, values: Any, option_string: Any = None ) -> None: if self.is_default: setattr(namespace, self.dest, values) self.is_default = False else: super().__call__(parser, namespace, values, option_string) autoscaling_options.add_argument( "--maxNodes", default=[10], dest="maxNodes", type=parse_int_list, action=NodeExtendAction, help=f"Maximum number of nodes of each type in the cluster, if using autoscaling, " f"provided as a comma-separated list. The first value is used as a default " f"if the list length is less than the number of nodeTypes. " f"default=%(default)s", ) autoscaling_options.add_argument( "--minNodes", default=[0], dest="minNodes", type=parse_int_list, action=NodeExtendAction, help="Mininum number of nodes of each type in the cluster, if using " "auto-scaling. This should be provided as a comma-separated list of the " "same length as the list of node types. default=%(default)s", ) autoscaling_options.add_argument( "--targetTime", dest="targetTime", default=defaultTargetTime, type=int, action=make_closed_interval_action(0), help=f"Sets how rapidly you aim to complete jobs in seconds. Shorter times mean " f"more aggressive parallelization. The autoscaler attempts to scale up/down " f"so that it expects all queued jobs will complete within targetTime " f"seconds. default=%(default)s", ) autoscaling_options.add_argument( "--betaInertia", dest="betaInertia", default=0.1, type=float, action=make_closed_interval_action(0.0, 0.9), help=f"A smoothing parameter to prevent unnecessary oscillations in the number " f"of provisioned nodes. This controls an exponentially weighted moving " f"average of the estimated number of nodes. A value of 0.0 disables any " f"smoothing, and a value of 0.9 will smooth so much that few changes will " f"ever be made. Must be between 0.0 and 0.9. default=%(default)s", ) autoscaling_options.add_argument( "--scaleInterval", dest="scaleInterval", default=60, type=int, help=f"The interval (seconds) between assessing if the scale of " f"the cluster needs to change. default=%(default)s", ) autoscaling_options.add_argument( "--preemptibleCompensation", "--preemptableCompensation", dest="preemptibleCompensation", default=0.0, type=float, action=make_closed_interval_action(0.0, 1.0), help=f"The preference of the autoscaler to replace preemptible nodes with " f"non-preemptible nodes, when preemptible nodes cannot be started for some " f"reason. This value must be between 0.0 and 1.0, inclusive. " f"A value of 0.0 disables such " f"compensation, a value of 0.5 compensates two missing preemptible nodes " f"with a non-preemptible one. A value of 1.0 replaces every missing " f"pre-emptable node with a non-preemptible one. default=%(default)s", ) autoscaling_options.add_argument( "--nodeStorage", dest="nodeStorage", default=50, type=int, help="Specify the size of the root volume of worker nodes when they are launched " "in gigabytes. You may want to set this if your jobs require a lot of disk " f"space. (default=%(default)s).", ) autoscaling_options.add_argument( "--nodeStorageOverrides", dest="nodeStorageOverrides", default=[], type=parse_str_list, action="extend", help="Comma-separated list of nodeType:nodeStorage that are used to override " "the default value from --nodeStorage for the specified nodeType(s). " "This is useful for heterogeneous jobs where some tasks require much more " "disk than others.", ) autoscaling_options.add_argument( "--metrics", dest="metrics", default=False, type=convert_bool, help="Enable the prometheus/grafana dashboard for monitoring CPU/RAM usage, " "queue size, and issued jobs.", ) autoscaling_options.add_argument( "--assumeZeroOverhead", dest="assume_zero_overhead", default=False, type=convert_bool, help="Ignore scheduler and OS overhead and assume jobs can use every last byte " "of memory and disk on a node when autoscaling.", ) # Parameters to limit service jobs / detect service deadlocks service_options = parser.add_argument_group( title="Toil options for limiting the number of service jobs and detecting service deadlocks", description="Allows the specification of the maximum number of service jobs in a cluster. By keeping " "this limited we can avoid nodes occupied with services causing deadlocks.", ) service_options.add_argument( "--maxServiceJobs", dest="maxServiceJobs", default=SYS_MAX_SIZE, type=int, help=SUPPRESS if cwl else f"The maximum number of service jobs that can be run concurrently, " f"excluding service jobs running on preemptible nodes. " f"default=%(default)s", ) service_options.add_argument( "--maxPreemptibleServiceJobs", dest="maxPreemptibleServiceJobs", default=SYS_MAX_SIZE, type=int, help=SUPPRESS if cwl else f"The maximum number of service jobs that can run concurrently on " f"preemptible nodes. default=%(default)s", ) service_options.add_argument( "--deadlockWait", dest="deadlockWait", default=60, type=int, help=SUPPRESS if cwl else f"Time, in seconds, to tolerate the workflow running only the same service " f"jobs, with no jobs to use them, before declaring the workflow to be " f"deadlocked and stopping. default=%(default)s", ) service_options.add_argument( "--deadlockCheckInterval", dest="deadlockCheckInterval", default=30, type=int, help=SUPPRESS if cwl else "Time, in seconds, to wait between checks to see if the workflow is stuck " "running only service jobs, with no jobs to use them. Should be shorter " "than --deadlockWait. May need to be increased if the batch system cannot " "enumerate running jobs quickly enough, or if polling for running jobs is " "placing an unacceptable load on a shared cluster. " f"default=%(default)s", ) # Resource requirements resource_options = parser.add_argument_group( title="Toil options for cores/memory requirements.", description="The options to specify default cores/memory requirements (if not specified by the jobs " "themselves), and to limit the total amount of memory/cores requested from the batch system.", ) resource_help_msg = ( "The {} amount of {} to request for a job. " "Only applicable to jobs that do not specify an explicit value for this requirement. " "{}. " "Default is {}." ) cpu_note = "Fractions of a core (for example 0.1) are supported on some batch systems [mesos, single_machine]" disk_mem_note = "Standard suffixes like K, Ki, M, Mi, G or Gi are supported" accelerators_note = ( "Each accelerator specification can have a type (gpu [default], nvidia, amd, cuda, rocm, opencl, " "or a specific model like nvidia-tesla-k80), and a count [default: 1]. If both a type and a count " "are used, they must be separated by a colon. If multiple types of accelerators are " "used, the specifications are separated by commas" ) h2b = lambda x: human2bytes(str(x)) resource_options.add_argument( "--defaultMemory", dest="defaultMemory", default="2.0 Gi", type=h2b, action=make_open_interval_action(1), help=resource_help_msg.format( "default", "memory", disk_mem_note, bytes2human(2147483648) ), ) resource_options.add_argument( "--defaultCores", dest="defaultCores", default=1, metavar="FLOAT", type=float, action=make_open_interval_action(1.0), help=resource_help_msg.format("default", "cpu", cpu_note, str(1)), ) resource_options.add_argument( "--defaultDisk", dest="defaultDisk", default="2.0 Gi", metavar="INT", type=h2b, action=make_open_interval_action(1), help=resource_help_msg.format( "default", "disk", disk_mem_note, bytes2human(2147483648) ), ) resource_options.add_argument( "--defaultAccelerators", dest="defaultAccelerators", default=[], metavar="ACCELERATOR[,ACCELERATOR...]", type=parse_accelerator_list, action="extend", help=resource_help_msg.format("default", "accelerators", accelerators_note, []), ) resource_options.add_argument( "--defaultPreemptible", "--defaultPreemptable", dest="defaultPreemptible", metavar="BOOL", type=convert_bool, nargs="?", const=True, default=False, help="Make all jobs able to run on preemptible (spot) nodes by default.", ) resource_options.add_argument( "--maxCores", dest="maxCores", default=SYS_MAX_SIZE, metavar="INT", type=int, action=make_open_interval_action(1), help=resource_help_msg.format("max", "cpu", cpu_note, str(SYS_MAX_SIZE)), ) resource_options.add_argument( "--maxMemory", dest="maxMemory", default=SYS_MAX_SIZE, metavar="INT", type=h2b, action=make_open_interval_action(1), help=resource_help_msg.format( "max", "memory", disk_mem_note, bytes2human(SYS_MAX_SIZE) ), ) resource_options.add_argument( "--maxDisk", dest="maxDisk", default=SYS_MAX_SIZE, metavar="INT", type=h2b, action=make_open_interval_action(1), help=resource_help_msg.format( "max", "disk", disk_mem_note, bytes2human(SYS_MAX_SIZE) ), ) # Retrying/rescuing jobs job_options = parser.add_argument_group( title="Toil options for rescuing/killing/restarting jobs.", description="The options for jobs that either run too long/fail or get lost (some batch systems have issues!).", ) job_options.add_argument( "--retryCount", dest="retryCount", default=1, type=int, action=make_open_interval_action(0), help=f"Number of times to retry a failing job before giving up and " f"labeling job failed. default={1}", ) job_options.add_argument( "--enableUnlimitedPreemptibleRetries", "--enableUnlimitedPreemptableRetries", dest="enableUnlimitedPreemptibleRetries", type=convert_bool, default=False, help="If set, preemptible failures (or any failure due to an instance getting " "unexpectedly terminated) will not count towards job failures and --retryCount.", ) job_options.add_argument( "--doubleMem", dest="doubleMem", type=convert_bool, default=False, help="If set, batch jobs which die to reaching memory limit on batch schedulers " "will have their memory doubled and they will be retried. The remaining " "retry count will be reduced by 1. Currently supported by LSF.", ) job_options.add_argument( "--maxJobDuration", dest="maxJobDuration", default=SYS_MAX_SIZE, type=int, action=make_open_interval_action(1), help=f"Maximum runtime of a job (in seconds) before we kill it (this is a lower bound, " f"and the actual time before killing the job may be longer). " f"default=%(default)s", ) job_options.add_argument( "--rescueJobsFrequency", dest="rescueJobsFrequency", default=60, type=int, action=make_open_interval_action(1), help=f"Period of time to wait (in seconds) between checking for missing/overlong jobs, " f"that is jobs which get lost by the batch system. Expert parameter. " f"default=%(default)s", ) # Log management options log_options = parser.add_argument_group( title="Toil log management options.", description="Options for how Toil should manage its logs.", ) log_options.add_argument( "--maxLogFileSize", dest="maxLogFileSize", default=64000, type=h2b, action=make_open_interval_action(1), help=f"The maximum size of a job log file to keep (in bytes), log files larger than " f"this will be truncated to the last X bytes. Setting this option to zero will " f"prevent any truncation. Setting this option to a negative value will truncate " f"from the beginning. Default={bytes2human(64000)}", ) log_options.add_argument( "--writeLogs", dest="writeLogs", nargs="?", action="store", default=None, const=os.getcwd(), help="Write worker logs received by the leader into their own files at the specified " "path. Any non-empty standard output and error from failed batch system jobs will " "also be written into files at this path. The current working directory will be " "used if a path is not specified explicitly. Note: By default only the logs of " "failed jobs are returned to leader. Set log level to 'debug' or enable " "'--writeLogsFromAllJobs' to get logs back from successful jobs, and adjust " "'maxLogFileSize' to control the truncation limit for worker logs.", ) log_options.add_argument( "--writeLogsGzip", dest="writeLogsGzip", nargs="?", action="store", default=None, const=os.getcwd(), help="Identical to --writeLogs except the logs files are gzipped on the leader.", ) log_options.add_argument( "--writeLogsFromAllJobs", dest="writeLogsFromAllJobs", type=convert_bool, default=False, help="Whether to write logs from all jobs (including the successful ones) without " "necessarily setting the log level to 'debug'. Ensure that either --writeLogs " "or --writeLogsGzip is set if enabling this option.", ) log_options.add_argument( "--writeMessages", dest="write_messages", default=None, type=lambda x: None if x is None else os.path.abspath(x), help="File to send messages from the leader's message bus to.", ) log_options.add_argument( "--realTimeLogging", dest="realTimeLogging", type=convert_bool, default=False, help="Enable real-time logging from workers to leader", ) # Misc options misc_options = parser.add_argument_group( title="Toil miscellaneous options.", description="Everything else." ) misc_options.add_argument( "--disableChaining", dest="disableChaining", type=convert_bool, default=False, help="Disables chaining of jobs (chaining uses one job's resource allocation " "for its successor job if possible).", ) misc_options.add_argument( "--disableJobStoreChecksumVerification", dest="disableJobStoreChecksumVerification", default=False, type=convert_bool, help="Disables checksum verification for files transferred to/from the job store. " "Checksum verification is a safety check to ensure the data is not corrupted " "during transfer. Currently only supported for non-streaming AWS files.", ) class SSEKeyAction(Action): def __call__( self, parser: Any, namespace: Any, values: Any, option_string: Any = None ) -> None: if values is not None: sse_key = values if sse_key is None: return with open(sse_key) as f: assert ( len(f.readline().rstrip()) == 32 ), "SSE key appears to be invalid." setattr(namespace, self.dest, values) misc_options.add_argument( "--sseKey", dest="sseKey", default=None, action=SSEKeyAction, help="Path to file containing 32 character key to be used for server-side encryption on " "awsJobStore or googleJobStore. SSE will not be used if this flag is not passed.", ) # yaml.safe_load is being deprecated, this is the suggested workaround def yaml_safe_load(stream: Any) -> Any: yaml = YAML(typ="safe", pure=True) d = yaml.load(stream) if isinstance(d, dict): # this means the argument was a dictionary and is valid yaml (for configargparse) return d else: # this means the argument is likely in it's string format (for CLI) return parseSetEnv(parse_str_list(stream)) class ExtendActionDict(Action): """ Argparse action class to implement the action="extend" functionality on dictionaries """ def __call__( self, parser: Any, namespace: Any, values: Any, option_string: Any = None ) -> None: items = getattr(namespace, self.dest, None) assert ( items is not None ) # for mypy. This should never be None, esp. if called in setEnv # note: this will overwrite existing entries items.update(values) misc_options.add_argument( "--setEnv", "-e", metavar="NAME=VALUE or NAME", dest="environment", default={}, type=yaml_safe_load, action=ExtendActionDict, help="Set an environment variable early on in the worker. If VALUE is null, it will " "be looked up in the current environment. Independently of this option, the worker " "will try to emulate the leader's environment before running a job, except for " "some variables known to vary across systems. Using this option, a variable can " "be injected into the worker process itself before it is started.", ) misc_options.add_argument( "--servicePollingInterval", dest="servicePollingInterval", default=60.0, type=float, action=make_open_interval_action(0.0), help=f"Interval of time service jobs wait between polling for the existence of the " f"keep-alive flag. Default: {60.0}", ) misc_options.add_argument( "--forceDockerAppliance", dest="forceDockerAppliance", type=convert_bool, default=False, help="Disables sanity checking the existence of the docker image specified by " "TOIL_APPLIANCE_SELF, which Toil uses to provision mesos for autoscaling.", ) misc_options.add_argument( "--statusWait", dest="statusWait", type=int, default=3600, help="Seconds to wait between reports of running jobs.", ) misc_options.add_argument( "--disableProgress", dest="disableProgress", type=convert_bool, default=False, help="Disables the progress bar shown when standard error is a terminal.", ) # If using argparse instead of configargparse, this should just not parse when calling parse_args() # default config value is set to none as defaults should already be populated at config init misc_options.add_argument( "--config", dest="config", is_config_file_arg=True, default=None, help="Get options from a config file.", ) # Debug options debug_options = parser.add_argument_group( title="Toil debug options.", description="Debug options for finding problems or helping with testing.", ) debug_options.add_argument( "--debugWorker", dest="debugWorker", default=False, action="store_true", help="Experimental no forking mode for local debugging. Specifically, workers " "are not forked and stderr/stdout are not redirected to the log.", ) debug_options.add_argument( "--disableWorkerOutputCapture", dest="disableWorkerOutputCapture", default=False, action="store_true", help="Let worker output go to worker's standard out/error instead of per-job logs.", ) debug_options.add_argument( "--badWorker", dest="badWorker", default=0.0, type=float, action=make_closed_interval_action(0.0, 1.0), help=f"For testing purposes randomly kill --badWorker proportion of jobs using " f"SIGKILL. default={0.0}", ) debug_options.add_argument( "--badWorkerFailInterval", dest="badWorkerFailInterval", default=0.01, type=float, action=make_open_interval_action(0.0), help=f"When killing the job pick uniformly within the interval from 0.0 to " f"--badWorkerFailInterval seconds after the worker starts. " f"default={0.01}", ) # All deprecated options: # These are deprecated in favor of a simpler option # ex: noLinkImports and linkImports can be simplified into a single link_imports argument link_imports.add_argument( "--noLinkImports", dest="linkImports", action="store_false", help=SUPPRESS ) link_imports.add_argument( "--linkImports", dest="linkImports", action="store_true", help=SUPPRESS ) link_imports.set_defaults(linkImports=None) move_exports.add_argument( "--moveExports", dest="moveExports", action="store_true", help=SUPPRESS ) move_exports.add_argument( "--noMoveExports", dest="moveExports", action="store_false", help=SUPPRESS ) link_imports.set_defaults(moveExports=None) # dest is set to enableCaching to not conflict with the current --caching destination caching.add_argument( "--disableCaching", dest="enableCaching", action="store_false", help=SUPPRESS ) caching.set_defaults(disableCaching=None)
[docs] def parseBool(val: str) -> bool: if val.lower() in ["true", "t", "yes", "y", "on", "1"]: return True elif val.lower() in ["false", "f", "no", "n", "off", "0"]: return False else: raise RuntimeError('Could not interpret "%s" as a boolean value' % val)
[docs] @lru_cache(maxsize=None) def getNodeID() -> str: """ Return unique ID of the current node (host). The resulting string will be convertable to a uuid.UUID. Tries several methods until success. The returned ID should be identical across calls from different processes on the same node at least until the next OS reboot. The last resort method is uuid.getnode() that in some rare OS configurations may return a random ID each time it is called. However, this method should never be reached on a Linux system, because reading from /proc/sys/kernel/random/boot_id will be tried prior to that. If uuid.getnode() is reached, it will be called twice, and exception raised if the values are not identical. """ for idSourceFile in ["/var/lib/dbus/machine-id", "/proc/sys/kernel/random/boot_id"]: if os.path.exists(idSourceFile): try: with open(idSourceFile) as inp: nodeID = inp.readline().strip() except OSError: logger.warning( f"Exception when trying to read ID file {idSourceFile}. " f"Will try next method to get node ID.", exc_info=True, ) else: if len(nodeID.split()) == 1: logger.debug(f"Obtained node ID {nodeID} from file {idSourceFile}") break else: logger.warning( f"Node ID {nodeID} from file {idSourceFile} contains spaces. " f"Will try next method to get node ID." ) else: nodeIDs = [] for i_call in range(2): nodeID = str(uuid.getnode()).strip() if len(nodeID.split()) == 1: nodeIDs.append(nodeID) else: logger.warning(f"Node ID {nodeID} from uuid.getnode() contains spaces") nodeID = "" if len(nodeIDs) == 2: if nodeIDs[0] == nodeIDs[1]: nodeID = nodeIDs[0] else: logger.warning( f"Different node IDs {nodeIDs} received from repeated calls to uuid.getnode(). " f"You should use another method to generate node ID." ) logger.debug(f"Obtained node ID {nodeID} from uuid.getnode()") if not nodeID: logger.warning( "Failed to generate stable node ID, returning empty string. If you see this message with a " "work dir on a shared file system when using workers running on multiple nodes, you might " "experience cryptic job failures" ) if len(nodeID.replace("-", "")) < UUID_LENGTH: # Some platforms (Mac) give us not enough actual hex characters. # Repeat them so the result is convertable to a uuid.UUID nodeID = nodeID.replace("-", "") num_repeats = UUID_LENGTH // len(nodeID) + 1 nodeID = nodeID * num_repeats nodeID = nodeID[:UUID_LENGTH] return nodeID
[docs] class Toil(ContextManager["Toil"]): """ A context manager that represents a Toil workflow. Specifically the batch system, job store, and its configuration. """ config: Config _jobStore: "AbstractJobStore" _batchSystem: "AbstractBatchSystem" _provisioner: Optional["AbstractProvisioner"]
[docs] def __init__(self, options: Namespace) -> None: """ Initialize a Toil object from the given options. Note that this is very light-weight and that the bulk of the work is done when the context is entered. :param options: command line options specified by the user """ super().__init__() self.options = options self._jobCache: Dict[Union[str, "TemporaryID"], "JobDescription"] = {} self._inContextManager: bool = False self._inRestart: bool = False
[docs] def __enter__(self) -> "Toil": """ Derive configuration from the command line options. Then load the job store and, on restart, consolidate the derived configuration with the one from the previous invocation of the workflow. """ set_logging_from_options(self.options) config = Config() config.setOptions(self.options) if config.jobStore is None: raise RuntimeError("No jobstore provided!") jobStore = self.getJobStore(config.jobStore) if config.caching is None: config.caching = jobStore.default_caching() # Set the caching option because it wasn't set originally, resuming jobstore rebuilds config from CLI options self.options.caching = config.caching if not config.restart: config.prepare_start() jobStore.initialize(config) else: jobStore.resume() # Merge configuration from job store with command line options config = jobStore.config config.prepare_restart() config.setOptions(self.options) jobStore.write_config() self.config = config self._jobStore = jobStore self._inContextManager = True # This will make sure `self.__exit__()` is called when we get a SIGTERM signal. signal.signal(signal.SIGTERM, lambda *_: sys.exit(1)) return self
[docs] def __exit__( self, exc_type: Optional[Type[BaseException]], exc_val: Optional[BaseException], exc_tb: Optional[TracebackType], ) -> Literal[False]: """ Clean up after a workflow invocation. Depending on the configuration, delete the job store. """ try: if ( exc_type is not None and self.config.clean == "onError" or exc_type is None and self.config.clean == "onSuccess" or self.config.clean == "always" ): try: if self.config.restart and not self._inRestart: pass else: self._jobStore.destroy() "Successfully deleted the job store: %s" % str(self._jobStore) ) except: "Failed to delete the job store: %s" % str(self._jobStore) ) raise except Exception as e: if exc_type is None: raise else: logger.exception("The following error was raised during clean up:") self._inContextManager = False self._inRestart = False return False # let exceptions through
[docs] def start(self, rootJob: "Job") -> Any: """ Invoke a Toil workflow with the given job as the root for an initial run. This method must be called in the body of a ``with Toil(...) as toil:`` statement. This method should not be called more than once for a workflow that has not finished. :param rootJob: The root job of the workflow :return: The root job's return value """ self._assertContextManagerUsed() # Write shared files to the job store self._jobStore.write_leader_pid() self._jobStore.write_leader_node_id() if self.config.restart: raise ToilRestartException( "A Toil workflow can only be started once. Use " "Toil.restart() to resume it." ) self._batchSystem = self.createBatchSystem(self.config) self._setupAutoDeployment(rootJob.getUserScript()) try: self._setBatchSystemEnvVars() self._serialiseEnv() self._cacheAllJobs() # Pickle the promised return value of the root job, then write the pickled promise to # a shared file, where we can find and unpickle it at the end of the workflow. # Unpickling the promise will automatically substitute the promise for the actual # return value. with self._jobStore.write_shared_file_stream("rootJobReturnValue") as fH: rootJob.prepareForPromiseRegistration(self._jobStore) promise = rootJob.rv() pickle.dump(promise, fH, protocol=pickle.HIGHEST_PROTOCOL) # Setup the first JobDescription and cache it rootJobDescription = rootJob.saveAsRootJob(self._jobStore) self._cacheJob(rootJobDescription) self._setProvisioner() return self._runMainLoop(rootJobDescription) finally: self._shutdownBatchSystem()
[docs] def restart(self) -> Any: """ Restarts a workflow that has been interrupted. :return: The root job's return value """ self._inRestart = True self._assertContextManagerUsed() # Write shared files to the job store self._jobStore.write_leader_pid() self._jobStore.write_leader_node_id() if not self.config.restart: raise ToilRestartException( "A Toil workflow must be initiated with Toil.start(), " "not restart()." ) from toil.job import JobException try: self._jobStore.load_root_job() except JobException: logger.warning( "Requested restart but the workflow has already been completed; allowing exports to rerun." ) return self._jobStore.get_root_job_return_value() self._batchSystem = self.createBatchSystem(self.config) self._setupAutoDeployment() try: self._setBatchSystemEnvVars() self._serialiseEnv() self._cacheAllJobs() self._setProvisioner() rootJobDescription = self._jobStore.clean(jobCache=self._jobCache) return self._runMainLoop(rootJobDescription) finally: self._shutdownBatchSystem()
def _setProvisioner(self) -> None: if self.config.provisioner is None: self._provisioner = None else: self._provisioner = cluster_factory( provisioner=self.config.provisioner, clusterName=None, zone=None, # read from instance meta-data nodeStorage=self.config.nodeStorage, nodeStorageOverrides=self.config.nodeStorageOverrides, sseKey=self.config.sseKey, ) self._provisioner.setAutoscaledNodeTypes(self.config.nodeTypes)
[docs] @classmethod def getJobStore(cls, locator: str) -> "AbstractJobStore": """ Create an instance of the concrete job store implementation that matches the given locator. :param str locator: The location of the job store to be represent by the instance :return: an instance of a concrete subclass of AbstractJobStore """ name, rest = cls.parseLocator(locator) if name == "file": from toil.jobStores.fileJobStore import FileJobStore return FileJobStore(rest) elif name == "aws": from import AWSJobStore return AWSJobStore(rest) elif name == "google": from toil.jobStores.googleJobStore import GoogleJobStore return GoogleJobStore(rest) else: raise RuntimeError("Unknown job store implementation '%s'" % name)
[docs] @staticmethod def parseLocator(locator: str) -> Tuple[str, str]: if locator[0] in "/." or ":" not in locator: return "file", locator else: try: name, rest = locator.split(":", 1) except ValueError: raise RuntimeError("Invalid job store locator syntax.") else: return name, rest
[docs] @staticmethod def buildLocator(name: str, rest: str) -> str: if ":" in name: raise ValueError(f"Can't have a ':' in the name: '{name}'.") return f"{name}:{rest}"
[docs] @classmethod def resumeJobStore(cls, locator: str) -> "AbstractJobStore": jobStore = cls.getJobStore(locator) jobStore.resume() return jobStore
[docs] @staticmethod def createBatchSystem(config: Config) -> "AbstractBatchSystem": """ Create an instance of the batch system specified in the given config. :param config: the current configuration :return: an instance of a concrete subclass of AbstractBatchSystem """ kwargs = dict( config=config, maxCores=config.maxCores, maxMemory=config.maxMemory, maxDisk=config.maxDisk, ) from toil.batchSystems.registry import (get_batch_system, get_batch_systems) try: batch_system = get_batch_system(config.batchSystem) except KeyError: raise RuntimeError( f"Unrecognized batch system: {config.batchSystem} " f'(choose from: {", ".join(get_batch_systems())})' ) if config.caching and not batch_system.supportsWorkerCleanup(): raise RuntimeError( f"{config.batchSystem} currently does not support shared caching, because it " "does not support cleaning up a worker after the last job finishes. Set " "--caching=false" ) logger.debug( "Using the %s" % re.sub("([a-z])([A-Z])", r"\g<1> \g<2>", batch_system.__name__).lower() ) return batch_system(**kwargs)
def _setupAutoDeployment( self, userScript: Optional["ModuleDescriptor"] = None ) -> None: """ Determine the user script, save it to the job store and inject a reference to the saved copy into the batch system. Do it such that the batch system can auto-deploy the resource on the worker nodes. :param userScript: the module descriptor referencing the user script. If None, it will be looked up in the job store. """ if userScript is not None: # This branch is hit when a workflow is being started if userScript.belongsToToil: logger.debug( "User script %s belongs to Toil. No need to auto-deploy it.", userScript, ) userScript = None else: if ( self._batchSystem.supportsAutoDeployment() and not self.config.disableAutoDeployment ): # Note that by saving the ModuleDescriptor, and not the Resource we allow for # redeploying a potentially modified user script on workflow restarts. with self._jobStore.write_shared_file_stream("userScript") as f: pickle.dump(userScript, f, protocol=pickle.HIGHEST_PROTOCOL) else: from toil.batchSystems.singleMachine import \ SingleMachineBatchSystem if not isinstance(self._batchSystem, SingleMachineBatchSystem): logger.warning( "Batch system does not support auto-deployment. The user script " "%s will have to be present at the same location on every worker.", userScript, ) userScript = None else: # This branch is hit on restarts if ( self._batchSystem.supportsAutoDeployment() and not self.config.disableAutoDeployment ): # We could deploy a user script from toil.jobStores.abstractJobStore import NoSuchFileException try: with self._jobStore.read_shared_file_stream("userScript") as f: userScript = safeUnpickleFromStream(f) except NoSuchFileException: logger.debug( "User script neither set explicitly nor present in the job store." ) userScript = None if userScript is None: logger.debug("No user script to auto-deploy.") else: logger.debug("Saving user script %s as a resource", userScript) userScriptResource = userScript.saveAsResourceTo(self._jobStore) logger.debug( "Injecting user script %s into batch system.", userScriptResource ) self._batchSystem.setUserScript(userScriptResource) # Importing a file with a shared file name returns None, but without one it # returns a file ID. Explain this to MyPy. @overload def importFile( self, srcUrl: str, sharedFileName: str, symlink: bool = True ) -> None: ... @overload def importFile( self, srcUrl: str, sharedFileName: None = None, symlink: bool = True ) -> FileID: ...
[docs] @deprecated(new_function_name="import_file") def importFile( self, srcUrl: str, sharedFileName: Optional[str] = None, symlink: bool = True ) -> Optional[FileID]: return self.import_file(srcUrl, sharedFileName, symlink)
@overload def import_file( self, src_uri: str, shared_file_name: str, symlink: bool = True, check_existence: bool = True, ) -> None: ... @overload def import_file( self, src_uri: str, shared_file_name: None = None, symlink: bool = True, check_existence: bool = True, ) -> FileID: ...
[docs] def import_file( self, src_uri: str, shared_file_name: Optional[str] = None, symlink: bool = True, check_existence: bool = True, ) -> Optional[FileID]: """ Import the file at the given URL into the job store. By default, returns None if the file does not exist. :param check_existence: If true, raise FileNotFoundError if the file does not exist. If false, return None when the file does not exist. See :func:`toil.jobStores.abstractJobStore.AbstractJobStore.importFile` for a full description """ self._assertContextManagerUsed() full_uri = self.normalize_uri(src_uri, check_existence=check_existence) try: imported = self._jobStore.import_file( full_uri, shared_file_name=shared_file_name, symlink=symlink ) except FileNotFoundError: # TODO: I thought we refactored the different job store import # methods to not raise and instead return None, but that looks to # not currently be the case. if check_existence: raise else: # So translate the raise-based API if needed. # TODO: If check_existence is false but a shared file name is # specified, we have no way to report the lack of file # existence, since we also return None on success! return None if imported is None and shared_file_name is None and check_existence: # We need to protect the caller from missing files. # We think a file was missing, and we got None becasuse of it. # We didn't get None instead because of usign a shared file name. raise FileNotFoundError(f"Could not find file {src_uri}") return imported
[docs] @deprecated(new_function_name="export_file") def exportFile(self, jobStoreFileID: FileID, dstUrl: str) -> None: return self.export_file(jobStoreFileID, dstUrl)
[docs] def export_file(self, file_id: FileID, dst_uri: str) -> None: """ Export file to destination pointed at by the destination URL. See :func:`toil.jobStores.abstractJobStore.AbstractJobStore.exportFile` for a full description """ self._assertContextManagerUsed() dst_uri = self.normalize_uri(dst_uri) self._jobStore.export_file(file_id, dst_uri)
[docs] @staticmethod def normalize_uri(uri: str, check_existence: bool = False) -> str: """ Given a URI, if it has no scheme, prepend "file:". :param check_existence: If set, raise FileNotFoundError if a URI points to a local file that does not exist. """ if urlparse(uri).scheme == 'file': uri = unquote(urlparse(uri).path) # this should strip off the local file scheme; it will be added back # account for the scheme-less case, which should be coerced to a local absolute path if urlparse(uri).scheme == "": abs_path = os.path.abspath(uri) if not os.path.exists(abs_path) and check_existence: raise FileNotFoundError( f'Could not find local file "{abs_path}" when importing "{uri}".\n' f'Make sure paths are relative to "{os.getcwd()}" or use absolute paths.\n' f'If this is not a local file, please include the scheme (s3:/, gs:/, ftp://, etc.).') return f'file://{quote(abs_path)}' return uri
def _setBatchSystemEnvVars(self) -> None: """Set the environment variables required by the job store and those passed on command line.""" for envDict in (self._jobStore.get_env(), self.config.environment): for k, v in envDict.items(): self._batchSystem.setEnv(k, v) def _serialiseEnv(self) -> None: """Put the environment in a globally accessible pickle file.""" # Dump out the environment of this process in the environment pickle file. with self._jobStore.write_shared_file_stream( "environment.pickle" ) as fileHandle: pickle.dump(dict(os.environ), fileHandle, pickle.HIGHEST_PROTOCOL) logger.debug("Written the environment for the jobs to the environment file") def _cacheAllJobs(self) -> None: """Download all jobs in the current job store into self.jobCache.""" logger.debug("Caching all jobs in job store") self._jobCache = { jobDesc.jobStoreID: jobDesc for jobDesc in } logger.debug(f"{len(self._jobCache)} jobs downloaded.") def _cacheJob(self, job: "JobDescription") -> None: """ Add given job to current job cache. :param job: job to be added to current job cache """ self._jobCache[job.jobStoreID] = job
[docs] @staticmethod def getToilWorkDir(configWorkDir: Optional[str] = None) -> str: """ Return a path to a writable directory under which per-workflow directories exist. This directory is always required to exist on a machine, even if the Toil worker has not run yet. If your workers and leader have different temp directories, you may need to set TOIL_WORKDIR. :param configWorkDir: Value passed to the program using the --workDir flag :return: Path to the Toil work directory, constant across all machines """ workDir = ( os.getenv("TOIL_WORKDIR_OVERRIDE") or configWorkDir or os.getenv("TOIL_WORKDIR") or tempfile.gettempdir() ) if not os.path.exists(workDir): raise RuntimeError( f"The directory specified by --workDir or TOIL_WORKDIR ({workDir}) does not exist." ) return workDir
[docs] @classmethod def get_toil_coordination_dir( cls, config_work_dir: Optional[str], config_coordination_dir: Optional[str] ) -> str: """ Return a path to a writable directory, which will be in memory if convenient. Ought to be used for file locking and coordination. :param config_work_dir: Value passed to the program using the --workDir flag :param config_coordination_dir: Value passed to the program using the --coordinationDir flag :return: Path to the Toil coordination directory. Ought to be on a POSIX filesystem that allows directories containing open files to be deleted. """ if "XDG_RUNTIME_DIR" in os.environ and not os.path.exists( os.environ["XDG_RUNTIME_DIR"] ): # Slurm has been observed providing this variable but not keeping # the directory live as long as we run for. logger.warning( "XDG_RUNTIME_DIR is set to nonexistent directory %s; your environment may be out of spec!", os.environ["XDG_RUNTIME_DIR"], ) # Go get a coordination directory, using a lot of short-circuiting of # or and the fact that and returns its second argument when it # succeeds. coordination_dir: Optional[str] = ( # First try an override env var os.getenv("TOIL_COORDINATION_DIR_OVERRIDE") or # Then the value from the config config_coordination_dir or # Then a normal env var # TODO: why/how would this propagate when not using single machine? os.getenv("TOIL_COORDINATION_DIR") or # Then try a `toil` subdirectory of the XDG runtime directory # (often /var/run/users/<UID>). But only if we are actually in a # session that has the env var set. Otherwise it might belong to a # different set of sessions and get cleaned up out from under us # when that session ends. # We don't think Slurm XDG sessions are trustworthy, depending on # the cluster's PAM configuration, so don't use them. ( "XDG_RUNTIME_DIR" in os.environ and "SLURM_JOBID" not in os.environ and try_path(os.path.join(os.environ["XDG_RUNTIME_DIR"], "toil")) ) or # Try under /run/lock. It might be a temp dir style sticky directory. try_path("/run/lock") or # Finally, fall back on the work dir and hope it's a legit filesystem. cls.getToilWorkDir(config_work_dir) ) if coordination_dir is None: raise RuntimeError( "Could not determine a coordination directory by any method!" ) return coordination_dir
@staticmethod def _get_workflow_path_component(workflow_id: str) -> str: """ Get a safe filesystem path component for a workflow. Will be consistent for all processes on a given machine, and different for all processes on different machines. :param workflow_id: The ID of the current Toil workflow. """ return str(uuid.uuid5(uuid.UUID(getNodeID()), workflow_id)).replace("-", "")
[docs] @classmethod def getLocalWorkflowDir( cls, workflowID: str, configWorkDir: Optional[str] = None ) -> str: """ Return the directory where worker directories and the cache will be located for this workflow on this machine. :param configWorkDir: Value passed to the program using the --workDir flag :return: Path to the local workflow directory on this machine """ # Get the global Toil work directory. This ensures that it exists. base = cls.getToilWorkDir(configWorkDir=configWorkDir) # Create a directory unique to each host in case workDir is on a shared FS. # This prevents workers on different nodes from erasing each other's directories. workflowDir: str = os.path.join( base, cls._get_workflow_path_component(workflowID) ) try: # Directory creation is atomic os.mkdir(workflowDir) except OSError as err: if err.errno != 17: # The directory exists if a previous worker set it up. raise else: logger.debug( "Created the workflow directory for this machine at %s" % workflowDir ) return workflowDir
[docs] @classmethod def get_local_workflow_coordination_dir( cls, workflow_id: str, config_work_dir: Optional[str], config_coordination_dir: Optional[str], ) -> str: """ Return the directory where coordination files should be located for this workflow on this machine. These include internal Toil databases and lock files for the machine. If an in-memory filesystem is available, it is used. Otherwise, the local workflow directory, which may be on a shared network filesystem, is used. :param workflow_id: Unique ID of the current workflow. :param config_work_dir: Value used for the work directory in the current Toil Config. :param config_coordination_dir: Value used for the coordination directory in the current Toil Config. :return: Path to the local workflow coordination directory on this machine. """ # Start with the base coordination or work dir base = cls.get_toil_coordination_dir(config_work_dir, config_coordination_dir) # Make a per-workflow and node subdirectory subdir = os.path.join(base, cls._get_workflow_path_component(workflow_id)) # Make it exist os.makedirs(subdir, exist_ok=True) # TODO: May interfere with workflow directory creation logging if it's the same directory. # Return it return subdir
def _runMainLoop(self, rootJob: "JobDescription") -> Any: """ Run the main loop with the given job. :param rootJob: The root job for the workflow. """ logProcessContext(self.config) with RealtimeLogger( self._batchSystem, level=self.options.logLevel if self.options.realTimeLogging else None, ): # FIXME: common should not import from leader from toil.leader import Leader return Leader( config=self.config, batchSystem=self._batchSystem, provisioner=self._provisioner, jobStore=self._jobStore, rootJob=rootJob, jobCache=self._jobCache, ).run() def _shutdownBatchSystem(self) -> None: """Shuts down current batch system if it has been created.""" startTime = time.time() logger.debug("Shutting down batch system ...") self._batchSystem.shutdown() logger.debug( "... finished shutting down the batch system in %s seconds." % (time.time() - startTime) ) def _assertContextManagerUsed(self) -> None: if not self._inContextManager: raise ToilContextManagerException()
[docs] class ToilRestartException(Exception): def __init__(self, message: str) -> None: super().__init__(message)
[docs] class ToilContextManagerException(Exception): def __init__(self) -> None: super().__init__( 'This method cannot be called outside the "with Toil(...)" context manager.' )
[docs] class ToilMetrics: def __init__( self, bus: MessageBus, provisioner: Optional["AbstractProvisioner"] = None ) -> None: clusterName = "none" region = "us-west-2" if provisioner is not None: clusterName = str(provisioner.clusterName) if provisioner._zone is not None: if == "aws": # Remove AZ name region = zone_to_region(provisioner._zone) else: region = provisioner._zone registry = lookupEnvVar( name="docker registry", envName="TOIL_DOCKER_REGISTRY", defaultValue=dockerRegistry, ) self.mtailImage = f"{registry}/toil-mtail:{dockerTag}" self.grafanaImage = f"{registry}/toil-grafana:{dockerTag}" self.prometheusImage = f"{registry}/toil-prometheus:{dockerTag}" self.startDashboard(clusterName=clusterName, zone=region) # Always restart the mtail container, because metrics should start from scratch # for each workflow try: subprocess.check_call(["docker", "rm", "-f", "toil_mtail"]) except subprocess.CalledProcessError: pass try: self.mtailProc: Optional[subprocess.Popen[bytes]] = subprocess.Popen( [ "docker", "run", "--rm", "--interactive", "--net=host", "--name", "toil_mtail", "-p", "3903:3903", self.mtailImage, ], stdin=subprocess.PIPE, stdout=subprocess.PIPE, ) except subprocess.CalledProcessError: logger.warning("Couldn't start toil metrics server.") self.mtailProc = None except KeyboardInterrupt: self.mtailProc.terminate() # type: ignore[union-attr] # On single machine, launch a node exporter instance to monitor CPU/RAM usage. # On AWS this is handled by the EC2 init script self.nodeExporterProc: Optional[subprocess.Popen[bytes]] = None if not provisioner: try: self.nodeExporterProc = subprocess.Popen( [ "docker", "run", "--rm", "--net=host", "-p", "9100:9100", "-v", "/proc:/host/proc", "-v", "/sys:/host/sys", "-v", "/:/rootfs", "", "-collector.procfs", "/host/proc", "-collector.sysfs", "/host/sys", "-collector.filesystem.ignored-mount-points", "^/(sys|proc|dev|host|etc)($|/)", ] ) except subprocess.CalledProcessError: logger.warning( "Couldn't start node exporter, won't get RAM and CPU usage for dashboard." ) except KeyboardInterrupt: if self.nodeExporterProc is not None: self.nodeExporterProc.terminate() # When messages come in on the message bus, call our methods. # TODO: Just annotate the methods with some kind of @listener and get # their argument types and magically register them? # TODO: There's no way to tell MyPy we have a dict from types to # functions that take them. TARGETS = { ClusterSizeMessage: self.logClusterSize, ClusterDesiredSizeMessage: self.logClusterDesiredSize, QueueSizeMessage: self.logQueueSize, JobMissingMessage: self.logMissingJob, JobIssuedMessage: self.logIssuedJob, JobFailedMessage: self.logFailedJob, JobCompletedMessage: self.logCompletedJob, } # The only way to make this inteligible to MyPy is to wrap the dict in # a function that can cast. MessageType = TypeVar("MessageType") def get_listener( message_type: Type[MessageType], ) -> Callable[[MessageType], None]: return cast(Callable[[MessageType], None], TARGETS[message_type]) # Then set up the listeners. self._listeners = [ bus.subscribe(message_type, get_listener(message_type)) for message_type in TARGETS.keys() ] @staticmethod def _containerRunning(containerName: str) -> bool: try: result = ( subprocess.check_output( ["docker", "inspect", "-f", "'{{.State.Running}}'", containerName] ).decode("utf-8") == "true" ) except subprocess.CalledProcessError: result = False return result
[docs] def startDashboard(self, clusterName: str, zone: str) -> None: try: if not self._containerRunning("toil_prometheus"): try: subprocess.check_call(["docker", "rm", "-f", "toil_prometheus"]) except subprocess.CalledProcessError: pass subprocess.check_call( [ "docker", "run", "--name", "toil_prometheus", "--net=host", "-d", "-p", "9090:9090", self.prometheusImage, clusterName, zone, ] ) if not self._containerRunning("toil_grafana"): try: subprocess.check_call(["docker", "rm", "-f", "toil_grafana"]) except subprocess.CalledProcessError: pass subprocess.check_call( [ "docker", "run", "--name", "toil_grafana", "-d", "-p=3000:3000", self.grafanaImage, ] ) except subprocess.CalledProcessError: logger.warning("Could not start prometheus/grafana dashboard.") return try: self.add_prometheus_data_source() except requests.exceptions.ConnectionError: logger.debug( "Could not add data source to Grafana dashboard - no metrics will be displayed." )
[docs] @retry(errors=[requests.exceptions.ConnectionError]) def add_prometheus_data_source(self) -> None: "http://localhost:3000/api/datasources", auth=("admin", "admin"), data='{"name":"DS_PROMETHEUS","type":"prometheus", "url":"http://localhost:9090", "access":"direct"}', headers={"content-type": "application/json", "access": "direct"}, )
[docs] def log(self, message: str) -> None: if self.mtailProc: self.mtailProc.stdin.write((message + "\n").encode("utf-8")) # type: ignore[union-attr] self.mtailProc.stdin.flush() # type: ignore[union-attr]
# Note: The mtail configuration (dashboard/mtail/toil.mtail) depends on these messages # remaining intact
[docs] def logClusterSize(self, m: ClusterSizeMessage) -> None: self.log("current_size '%s' %i" % (m.instance_type, m.current_size))
[docs] def logClusterDesiredSize(self, m: ClusterDesiredSizeMessage) -> None: self.log("desired_size '%s' %i" % (m.instance_type, m.desired_size))
[docs] def logQueueSize(self, m: QueueSizeMessage) -> None: self.log("queue_size %i" % m.queue_size)
[docs] def logMissingJob(self, m: JobMissingMessage) -> None: self.log("missing_job")
[docs] def logIssuedJob(self, m: JobIssuedMessage) -> None: self.log("issued_job %s" % m.job_type)
[docs] def logFailedJob(self, m: JobFailedMessage) -> None: self.log("failed_job %s" % m.job_type)
[docs] def logCompletedJob(self, m: JobCompletedMessage) -> None: self.log("completed_job %s" % m.job_type)
[docs] def shutdown(self) -> None: if self.mtailProc is not None: logger.debug("Stopping mtail") self.mtailProc.kill() logger.debug("Stopped mtail") if self.nodeExporterProc is not None: logger.debug("Stopping node exporter") self.nodeExporterProc.kill() logger.debug("Stopped node exporter") self._listeners = []
[docs] def parseSetEnv(l: List[str]) -> Dict[str, Optional[str]]: """ Parse a list of strings of the form "NAME=VALUE" or just "NAME" into a dictionary. Strings of the latter from will result in dictionary entries whose value is None. >>> parseSetEnv([]) {} >>> parseSetEnv(['a']) {'a': None} >>> parseSetEnv(['a=']) {'a': ''} >>> parseSetEnv(['a=b']) {'a': 'b'} >>> parseSetEnv(['a=a', 'a=b']) {'a': 'b'} >>> parseSetEnv(['a=b', 'c=d']) {'a': 'b', 'c': 'd'} >>> parseSetEnv(['a=b=c']) {'a': 'b=c'} >>> parseSetEnv(['']) Traceback (most recent call last): ... ValueError: Empty name >>> parseSetEnv(['=1']) Traceback (most recent call last): ... ValueError: Empty name """ d = {} v: Optional[str] = None for i in l: try: k, v = i.split("=", 1) except ValueError: k, v = i, None if not k: raise ValueError("Empty name") d[k] = v return d
[docs] def iC(minValue: int, maxValue: Optional[int] = None) -> Callable[[int], bool]: """Returns a function that checks if a given int is in the given half-open interval.""" if not isinstance(minValue, int): raise RuntimeError( f"minValue must be of type 'int', was type: {type(minValue)}: {minValue!r}." ) if maxValue is None: return lambda x: minValue <= x if not isinstance(maxValue, int): raise RuntimeError( f"maxValue must be of type 'int' (or None), was type: {type(maxValue)}: {maxValue!r}." ) return lambda x: minValue <= x < maxValue
[docs] def fC(minValue: float, maxValue: Optional[float] = None) -> Callable[[float], bool]: """Returns a function that checks if a given float is in the given half-open interval.""" if not isinstance(minValue, float): raise RuntimeError( f"minValue must be of type 'float', was type: {type(minValue)}: {minValue!r}." ) if maxValue is None: return lambda x: minValue <= x if not isinstance(maxValue, float): raise RuntimeError( f"maxValue must be of type 'float' (or None), was type: {type(maxValue)}: {maxValue!r}." ) return lambda x: minValue <= x < maxValue
[docs] def parse_accelerator_list(specs: Optional[str]) -> List["AcceleratorRequirement"]: """ Parse a string description of one or more accelerator requirements. """ if specs is None or len(specs) == 0: # Not specified, so the default default is to not need any. return [] # Otherwise parse each requirement. from toil.job import parse_accelerator return [parse_accelerator(r) for r in specs.split(",")]
[docs] def cacheDirName(workflowID: str) -> str: """ :return: Name of the cache directory. """ return f"cache-{workflowID}"
[docs] def getDirSizeRecursively(dirPath: str) -> int: """ This method will return the cumulative number of bytes occupied by the files on disk in the directory and its subdirectories. If the method is unable to access a file or directory (due to insufficient permissions, or due to the file or directory having been removed while this function was attempting to traverse it), the error will be handled internally, and a (possibly 0) lower bound on the size of the directory will be returned. The environment variable 'BLOCKSIZE'='512' is set instead of the much cleaner --block-size=1 because Apple can't handle it. :param str dirPath: A valid path to a directory or file. :return: Total size, in bytes, of the file or directory at dirPath. """ # du is often faster than using os.lstat(), sometimes significantly so. # The call: 'du -s /some/path' should give the number of 512-byte blocks # allocated with the environment variable: BLOCKSIZE='512' set, and we # multiply this by 512 to return the filesize in bytes. try: return ( int( subprocess.check_output( ["du", "-s", dirPath], env=dict(os.environ, BLOCKSIZE="512") ) .decode("utf-8") .split()[0] ) * 512 ) except subprocess.CalledProcessError: # Something was inaccessible or went away return 0
[docs] def getFileSystemSize(dirPath: str) -> Tuple[int, int]: """ Return the free space, and total size of the file system hosting `dirPath`. :param dirPath: A valid path to a directory. :return: free space and total size of file system """ if not os.path.exists(dirPath): raise RuntimeError(f"Could not find dir size for non-existent path: {dirPath}") diskStats = os.statvfs(dirPath) freeSpace = diskStats.f_frsize * diskStats.f_bavail diskSize = diskStats.f_frsize * diskStats.f_blocks return freeSpace, diskSize
[docs] def safeUnpickleFromStream(stream: IO[Any]) -> Any: string = return pickle.loads(string)