toil.batchSystems.singleMachine¶

Attributes¶

`EXIT_STATUS_UNAVAILABLE_VALUE`
`SYS_MAX_SIZE`
`logger`

Exceptions¶

InsufficientSystemResources

Common base class for all non-exit exceptions.

Classes¶

`BatchSystemSupport`	Partial implementation of AbstractBatchSystem, support methods.
`ResourcePool`	Represents an integral amount of a resource (such as memory bytes).
`ResourceSet`	Represents a collection of distinct resources (such as accelerators).
`UpdatedBatchJobInfo`
`OptionSetter`	Protocol for the setOption function we get to let us set up CLI options for
`ExternalBatchIdMessage`	Produced when using a batch system, links toil assigned batch ID to
`Config`	Class to represent configuration operations for a toil workflow run.
`Toil`	A context manager that represents a Toil workflow.
`AcceleratorRequirement`	Requirement for one or more computational accelerators, like a GPU or FPGA.
`JobDescription`	Stores all the information that the Toil Leader ever needs to know about a Job.
`Requirer`	Base class implementing the storage and presentation of requirements.
`SingleMachineBatchSystem`	The interface for running jobs on a single machine, runs all the jobs you
`Info`	Record for a running job.

Functions¶

`make_open_interval_action`(min[, max])	Returns an argparse action class to check if the input is within the given half-open interval.
`accelerator_satisfies`(candidate, requirement[, ignore])	Test if candidate partially satisfies the given requirement.
`get_individual_local_accelerators`()	Determine all the local accelerators available. Report each with count 1,
`get_restrictive_environment_for_local_accelerators`(...)	Get environment variables which can be applied to a process to restrict it
`cpu_count`()	Get the rounded-up integer number of whole CPUs available.

Module Contents¶

toil.batchSystems.singleMachine.EXIT_STATUS_UNAVAILABLE_VALUE = 255¶

class toil.batchSystems.singleMachine.BatchSystemSupport(config, maxCores, maxMemory, maxDisk)[source]¶

Bases: AbstractBatchSystem

Partial implementation of AbstractBatchSystem, support methods.

Parameters:

config (toil.common.Config)
maxCores (float)
maxMemory (int)
maxDisk (int)

check_resource_request(requirer)[source]¶

Check resource request is not greater than that available or allowed.

Parameters:

requirer (toil.job.Requirer) – Object whose requirements are being checked
job_name (str) – Name of the job being checked, for generating a useful error report.
detail (str) – Batch-system-specific message to include in the error.

Raises:

InsufficientSystemResources – raised when a resource is requested in an amount greater than allowed

Return type:

None

setEnv(name, value=None)[source]¶

Set an environment variable for the worker process before it is launched. The worker process will typically inherit the environment of the machine it is running on but this method makes it possible to override specific variables in that inherited environment before the worker is launched. Note that this mechanism is different to the one used by the worker internally to set up the environment of a job. A call to this method affects all jobs issued after this method returns. Note to implementors: This means that you would typically need to copy the variables before enqueuing a job.

If no value is provided it will be looked up from the current environment.

Parameters:

name (str) – the environment variable to be set on the worker.
value (Optional[str]) – if given, the environment variable given by name will be set to this value. If None, the variable’s current value will be used as the value on the worker

Raises:

RuntimeError – if value is None and the name cannot be found in the environment

Return type:

None

set_message_bus(message_bus)[source]¶

Give the batch system an opportunity to connect directly to the message bus, so that it can send informational messages about the jobs it is running to other Toil components.

Parameters:: message_bus (toil.bus.MessageBus)
Return type:: None

get_batch_logs_dir()[source]¶

Get the directory where the backing batch system should save its logs.

Only really makes sense if the backing batch system actually saves logs to a filesystem; Kubernetes for example does not. Ought to be a directory shared between the leader and the workers, if the backing batch system writes logs onto the worker’s view of the filesystem, like many HPC schedulers do.

Return type:: str

format_std_out_err_path(toil_job_id, cluster_job_id, std)[source]¶

Format path for batch system standard output/error and other files generated by the batch system itself.

Files will be written to the batch logs directory (–batchLogsDir, defaulting to the Toil work directory) with names containing both the Toil and batch system job IDs, for ease of debugging job failures.

Param:

int toil_job_id : The unique id that Toil gives a job.

Param:

cluster_job_id : What the cluster, for example, GridEngine, uses as its internal job id.

Param:

string std : The provenance of the stream (for example: ‘err’ for ‘stderr’ or ‘out’ for ‘stdout’)

Return type:

string : Formatted filename; however if self.config.noStdOutErr is true, returns ‘/dev/null’ or equivalent.

Parameters:

toil_job_id (int)
cluster_job_id (str)
std (str)

format_std_out_err_glob(toil_job_id)[source]¶

Get a glob string that will match all file paths generated by format_std_out_err_path for a job.

Parameters:: toil_job_id (int)
Return type:: str

static workerCleanup(info)[source]¶

Cleans up the worker node on batch system shutdown.

Also see supportsWorkerCleanup().

Parameters:: info (WorkerCleanupInfo) – A named tuple consisting of all the relevant information for cleaning up the worker.
Return type:: None

exception toil.batchSystems.singleMachine.InsufficientSystemResources(requirer, resource, available=None, batch_system=None, source=None, details=[])[source]¶

Bases: Exception

Common base class for all non-exit exceptions.

Parameters:

requirer (toil.job.Requirer)
resource (str)
available (Optional[toil.job.ParsedRequirement])
batch_system (Optional[str])
source (Optional[str])
details (List[str])

__str__()[source]¶

Explain the exception.

Return type:: str

class toil.batchSystems.singleMachine.ResourcePool(initial_value, resource_type, timeout=5)[source]¶

Represents an integral amount of a resource (such as memory bytes). Amounts can be acquired immediately or with a timeout, and released. Provides a context manager to do something with an amount of resource acquired.

Parameters:

initial_value (int)
resource_type (str)
timeout (float)

acquireNow(amount)[source]¶

Reserve the given amount of the given resource. Returns True if successful and False if this is not possible immediately.

Parameters:: amount (int)
Return type:: bool

acquire(amount)[source]¶

Reserve the given amount of the given resource. Raises AcquisitionTimeoutException if this is not possible in under self.timeout time.

Parameters:: amount (int)
Return type:: None

release(amount)[source]¶

Parameters:: amount (int)
Return type:: None

__str__()[source]¶

Return str(self).

Return type:: str

__repr__()[source]¶

Return repr(self).

Return type:: str

acquisitionOf(amount)[source]¶

Parameters:: amount (int)
Return type:: Iterator[None]

class toil.batchSystems.singleMachine.ResourceSet(initial_value, resource_type, timeout=5)[source]¶

Represents a collection of distinct resources (such as accelerators). Subsets can be acquired immediately or with a timeout, and released. Provides a context manager to do something with a set of of resources acquired.

Parameters:

initial_value (Set[int])
resource_type (str)
timeout (float)

acquireNow(subset)[source]¶

Reserve the given amount of the given resource. Returns True if successful and False if this is not possible immediately.

Parameters:: subset (Set[int])
Return type:: bool

acquire(subset)[source]¶

Reserve the given amount of the given resource. Raises AcquisitionTimeoutException if this is not possible in under self.timeout time.

Parameters:: subset (Set[int])
Return type:: None

release(subset)[source]¶

Parameters:: subset (Set[int])
Return type:: None

get_free_snapshot()[source]¶

Get a snapshot of what items are free right now. May be stale as soon as you get it, but you will need some kind of hint to try and do an acquire.

Return type:: Set[int]

__str__()[source]¶

Return str(self).

Return type:: str

__repr__()[source]¶

Return repr(self).

Return type:: str

acquisitionOf(subset)[source]¶

Parameters:: subset (Set[int])
Return type:: Iterator[None]

class toil.batchSystems.singleMachine.UpdatedBatchJobInfo[source]¶

Bases: NamedTuple

jobID: int¶

exitStatus: int¶

The exit status (integer value) of the job. 0 implies successful.

EXIT_STATUS_UNAVAILABLE_VALUE is used when the exit status is not available (e.g. job is lost, or otherwise died but actual exit code was not reported).

exitReason: BatchJobExitReason | None¶

wallTime: float | int | None¶

class toil.batchSystems.singleMachine.OptionSetter[source]¶

Bases: Protocol

Protocol for the setOption function we get to let us set up CLI options for each batch system.

Actual functionality is defined in the Config class.

OptionType¶

__call__(option_name, parsing_function=None, check_function=None, default=None, env=None, old_names=None)[source]¶

Parameters:

option_name (str)
parsing_function (Optional[Callable[[Any], OptionType]])
check_function (Optional[Callable[[OptionType], Union[None, bool]]])
default (Optional[OptionType])
env (Optional[List[str]])
old_names (Optional[List[str]])

Return type:

bool

class toil.batchSystems.singleMachine.ExternalBatchIdMessage[source]¶

Bases: NamedTuple

Produced when using a batch system, links toil assigned batch ID to Batch system ID (Whatever’s returned by local implementation, PID, batch ID, etc)

toil_batch_id: int¶

external_batch_id: str¶

batch_system: str¶

class toil.batchSystems.singleMachine.Config[source]¶

Class to represent configuration operations for a toil workflow run.

logFile: str | None¶

logRotating: bool¶

cleanWorkDir: str¶

max_jobs: int¶

max_local_jobs: int¶

manualMemArgs: bool¶

run_local_jobs_on_workers: bool¶

coalesceStatusCalls: bool¶

mesos_endpoint: str | None¶

mesos_framework_id: str | None¶

mesos_role: str | None¶

mesos_name: str¶

kubernetes_host_path: str | None¶

kubernetes_owner: str | None¶

kubernetes_service_account: str | None¶

kubernetes_pod_timeout: float¶

kubernetes_privileged: bool¶

tes_endpoint: str¶

tes_user: str¶

tes_password: str¶

tes_bearer_token: str¶

aws_batch_region: str | None¶

aws_batch_queue: str | None¶

aws_batch_job_role_arn: str | None¶

scale: float¶

batchSystem: str¶

batch_logs_dir: str | None¶: The backing scheduler will be instructed, if possible, to save logs to this directory, where the leader can read them.

statePollingWait: int¶

state_polling_timeout: int¶

disableAutoDeployment: bool¶

workflowID: str | None¶: 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¶

colored_logs: bool¶

workDir: str | None¶

coordination_dir: str | None¶

noStdOutErr: bool¶

stats: bool¶

clean: str | None¶

clusterStats: str¶

restart: bool¶

caching: bool | None¶

symlinkImports: bool¶

moveOutputs: bool¶

provisioner: str | None¶

nodeTypes: List[Tuple[Set[str], float | None]]¶

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¶

maxPreemptibleServiceJobs: int¶

maxServiceJobs: int¶

deadlockWait: float | int¶

deadlockCheckInterval: float | int¶

defaultMemory: int¶

defaultCores: float | int¶

defaultDisk: int¶

defaultPreemptible: bool¶

defaultAccelerators: List[toil.job.AcceleratorRequirement]¶

maxCores: int¶

maxMemory: int¶

maxDisk: int¶

retryCount: int¶

enableUnlimitedPreemptibleRetries: bool¶

doubleMem: bool¶

maxJobDuration: int¶

rescueJobsFrequency: int¶

job_store_timeout: float¶

maxLogFileSize: int¶

writeLogs: str¶

writeLogsGzip: str¶

writeLogsFromAllJobs: bool¶

write_messages: str | None¶

realTimeLogging: bool¶

environment: Dict[str, str]¶

disableChaining: bool¶

disableJobStoreChecksumVerification: bool¶

sseKey: str | None¶

servicePollingInterval: int¶

useAsync: bool¶

forceDockerAppliance: bool¶

statusWait: int¶

disableProgress: bool¶

readGlobalFileMutableByDefault: bool¶

debugWorker: bool¶

disableWorkerOutputCapture: bool¶

badWorker: float¶

badWorkerFailInterval: float¶

kill_polling_interval: int¶

cwl: bool¶

set_from_default_config()[source]¶

Return type:: None

prepare_start()[source]¶

After options are set, prepare for initial start of workflow.

Return type:: None

prepare_restart()[source]¶

Before restart options are set, prepare for a restart of a workflow. Set up any execution-specific parameters and clear out any stale ones.

Return type:: None

setOptions(options)[source]¶

Creates a config object from the options object.

Parameters:: options (argparse.Namespace)
Return type:: None

check_configuration_consistency()[source]¶

Old checks that cannot be fit into an action class for argparse

Return type:: None

__eq__(other)[source]¶

Return self==value.

Parameters:: other (object)
Return type:: bool

__hash__()[source]¶

Return hash(self).

Return type:: int

class toil.batchSystems.singleMachine.Toil(options)[source]¶

Bases: ContextManager[Toil]

A context manager that represents a Toil workflow.

Specifically the batch system, job store, and its configuration.

Parameters:: options (argparse.Namespace)

config: Config¶

__enter__()[source]¶

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.

Return type:: Toil

__exit__(exc_type, exc_val, exc_tb)[source]¶

Clean up after a workflow invocation.

Depending on the configuration, delete the job store.

Parameters:

exc_type (Optional[Type[BaseException]])
exc_val (Optional[BaseException])
exc_tb (Optional[types.TracebackType])

Return type:

Literal[False]

start(rootJob)[source]¶

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.

Parameters:: rootJob (toil.job.Job) – The root job of the workflow
Returns:: The root job’s return value
Return type:: Any

restart()[source]¶

Restarts a workflow that has been interrupted.

Returns:: The root job’s return value
Return type:: Any

classmethod getJobStore(locator)[source]¶

Create an instance of the concrete job store implementation that matches the given locator.

Parameters:: locator (str) – The location of the job store to be represent by the instance
Returns:: an instance of a concrete subclass of AbstractJobStore
Return type:: toil.jobStores.abstractJobStore.AbstractJobStore

static parseLocator(locator)[source]¶

Parameters:: locator (str)
Return type:: Tuple[str, str]

static buildLocator(name, rest)[source]¶

Parameters:

name (str)
rest (str)

Return type:

str

classmethod resumeJobStore(locator)[source]¶

Parameters:: locator (str)
Return type:: toil.jobStores.abstractJobStore.AbstractJobStore

static createBatchSystem(config)[source]¶

Create an instance of the batch system specified in the given config.

Parameters:: config (Config) – the current configuration
Returns:: an instance of a concrete subclass of AbstractBatchSystem
Return type:: toil.batchSystems.abstractBatchSystem.AbstractBatchSystem

importFile(srcUrl: str, sharedFileName: str, symlink: bool = True) → None[source]¶
importFile(srcUrl: str, sharedFileName: None = None, symlink: bool = True) → toil.fileStores.FileID

import_file(src_uri: str, shared_file_name: str, symlink: bool = True, check_existence: bool = True) → None[source]¶

import_file(src_uri: str, shared_file_name: None = None, symlink: bool = True, check_existence: bool = True) → toil.fileStores.FileID

Import the file at the given URL into the job store.

By default, returns None if the file does not exist.

Parameters:: check_existence – If true, raise FileNotFoundError if the file does not exist. If false, return None when the file does not exist.

See toil.jobStores.abstractJobStore.AbstractJobStore.importFile() for a full description

exportFile(jobStoreFileID, dstUrl)[source]¶

Parameters:

jobStoreFileID (toil.fileStores.FileID)
dstUrl (str)

Return type:

None

export_file(file_id, dst_uri)[source]¶

Export file to destination pointed at by the destination URL.

See toil.jobStores.abstractJobStore.AbstractJobStore.exportFile() for a full description

Parameters:

file_id (toil.fileStores.FileID)
dst_uri (str)

Return type:

None

static normalize_uri(uri, check_existence=False)[source]¶

Given a URI, if it has no scheme, prepend “file:”.

Parameters:

check_existence (bool) – If set, raise FileNotFoundError if a URI points to a local file that does not exist.
uri (str)

Return type:

str

static getToilWorkDir(configWorkDir=None)[source]¶

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.

Parameters:: configWorkDir (Optional[str]) – Value passed to the program using the –workDir flag
Returns:: Path to the Toil work directory, constant across all machines
Return type:: str

classmethod get_toil_coordination_dir(config_work_dir, config_coordination_dir)[source]¶

Return a path to a writable directory, which will be in memory if convenient. Ought to be used for file locking and coordination.

Parameters:

config_work_dir (Optional[str]) – Value passed to the program using the –workDir flag
config_coordination_dir (Optional[str]) – Value passed to the program using the –coordinationDir flag
workflow_id – Used if a tmpdir_prefix exists to create full directory paths unique per workflow

Returns:

Path to the Toil coordination directory. Ought to be on a POSIX filesystem that allows directories containing open files to be deleted.

Return type:

str

static get_workflow_path_component(workflow_id)[source]¶

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.

Parameters:: workflow_id (str) – The ID of the current Toil workflow.
Return type:: str

classmethod getLocalWorkflowDir(workflowID, configWorkDir=None)[source]¶

Return the directory where worker directories and the cache will be located for this workflow on this machine.

Parameters:

configWorkDir (Optional[str]) – Value passed to the program using the –workDir flag
workflowID (str)

Returns:

Path to the local workflow directory on this machine

Return type:

str

classmethod get_local_workflow_coordination_dir(workflow_id, config_work_dir, config_coordination_dir)[source]¶

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.

Parameters:

workflow_id (str) – Unique ID of the current workflow.
config_work_dir (Optional[str]) – Value used for the work directory in the current Toil Config.
config_coordination_dir (Optional[str]) – Value used for the coordination directory in the current Toil Config.

Returns:

Path to the local workflow coordination directory on this machine.

Return type:

str

toil.batchSystems.singleMachine.SYS_MAX_SIZE = 9223372036854775807¶

toil.batchSystems.singleMachine.make_open_interval_action(min, max=None)[source]¶

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)

Parameters:

min (Union[int, float]) – float/int
max (Optional[Union[int, float]]) – optional float/int

Returns:

argparse action class

Return type:

Type[argparse.Action]

class toil.batchSystems.singleMachine.AcceleratorRequirement[source]¶

Bases: TypedDict

Requirement for one or more computational accelerators, like a GPU or FPGA.

count: int¶: How many of the accelerator are needed to run the job.

kind: str¶: What kind of accelerator is required. Can be “gpu”. Other kinds defined in the future might be “fpga”, etc.

model: typing_extensions.NotRequired[str]¶: What model of accelerator is needed. The exact set of values available depends on what the backing scheduler calls its accelerators; strings like “nvidia-tesla-k80” might be expected to work. If a specific model of accelerator is not required, this should be absent.

brand: typing_extensions.NotRequired[str]¶: What brand or manufacturer of accelerator is required. The exact set of values available depends on what the backing scheduler calls the brands of its accleerators; strings like “nvidia” or “amd” might be expected to work. If a specific brand of accelerator is not required (for example, because the job can use multiple brands of accelerator that support a given API) this should be absent.

api: typing_extensions.NotRequired[str]¶: What API is to be used to communicate with the accelerator. This can be “cuda”. Other APIs supported in the future might be “rocm”, “opencl”, “metal”, etc. If the job does not need a particular API to talk to the accelerator, this should be absent.

class toil.batchSystems.singleMachine.JobDescription(requirements, jobName, unitName='', displayName='', local=None)[source]¶

Bases: Requirer

Stores all the information that the Toil Leader ever needs to know about a Job.

This includes:

Resource requirements.
Which jobs are children or follow-ons or predecessors of this job.
A reference to the Job object in the job store.

Can be obtained from an actual (i.e. executable) Job object, and can be used to obtain the Job object from the JobStore.

Never contains other Jobs or JobDescriptions: all reference is by ID.

Subclassed into variants for checkpoint jobs and service jobs that have their specific parameters.

Parameters:

requirements (Mapping[str, Union[int, str, bool]])
jobName (str)
unitName (Optional[str])
displayName (Optional[str])
local (Optional[bool])

get_names()[source]¶

Get the names and ID of this job as a named tuple.

Return type:: toil.bus.Names

get_chain()[source]¶

Get all the jobs that executed in this job’s chain, in order.

For each job, produces a named tuple with its various names and its original job store ID. The jobs in the chain are in execution order.

If the job hasn’t run yet or it didn’t chain, produces a one-item list.

Return type:: List[toil.bus.Names]

serviceHostIDsInBatches()[source]¶

Find all batches of service host job IDs that can be started at the same time.

(in the order they need to start in)

Return type:: Iterator[List[str]]

successorsAndServiceHosts()[source]¶

Get an iterator over all child, follow-on, and service job IDs.

Return type:: Iterator[str]

allSuccessors()[source]¶

Get an iterator over all child, follow-on, and chained, inherited successor job IDs.

Follow-ons will come before children.

Return type:: Iterator[str]

successors_by_phase()[source]¶

Get an iterator over all child/follow-on/chained inherited successor job IDs, along with their phase numbere on the stack.

Phases ececute higher numbers to lower numbers.

Return type:: Iterator[Tuple[int, str]]

property services¶
Get a collection of the IDs of service host jobs for this job, in arbitrary order.: Will be empty if the job has no unfinished services.

has_body()[source]¶

Returns True if we have a job body associated, and False otherwise.

Return type:: bool

attach_body(file_store_id, user_script)[source]¶

Attach a job body to this JobDescription.

Takes the file store ID that the body is stored at, and the required user script module.

The file store ID can also be “firstJob” for the root job, stored as a shared file instead.

Parameters:

file_store_id (str)
user_script (toil.resource.ModuleDescriptor)

Return type:

None

detach_body()[source]¶

Drop the body reference from a JobDescription.

Return type:: None

get_body()[source]¶

Get the information needed to load the job body.

Returns:: a file store ID (or magic shared file name “firstJob”) and a user script module.
Return type:: Tuple[str, toil.resource.ModuleDescriptor]

Fails if no body is attached; check has_body() first.

nextSuccessors()[source]¶

Return the collection of job IDs for the successors of this job that are ready to run.

If those jobs have multiple predecessor relationships, they may still be blocked on other jobs.

Returns None when at the final phase (all successors done), and an empty collection if there are more phases but they can’t be entered yet (e.g. because we are waiting for the job itself to run).

Return type:: Optional[Set[str]]

filterSuccessors(predicate)[source]¶

Keep only successor jobs for which the given predicate function approves.

The predicate function is called with the job’s ID.

Treats all other successors as complete and forgets them.

Parameters:: predicate (Callable[[str], bool])
Return type:: None

filterServiceHosts(predicate)[source]¶

Keep only services for which the given predicate approves.

The predicate function is called with the service host job’s ID.

Treats all other services as complete and forgets them.

Parameters:: predicate (Callable[[str], bool])
Return type:: None

clear_nonexistent_dependents(job_store)[source]¶

Remove all references to child, follow-on, and associated service jobs that do not exist.

That is to say, all those that have been completed and removed.

Parameters:: job_store (toil.jobStores.abstractJobStore.AbstractJobStore)
Return type:: None

clear_dependents()[source]¶

Remove all references to successor and service jobs.

Return type:: None

is_subtree_done()[source]¶

Check if the subtree is done.

Returns:: True if the job appears to be done, and all related child, follow-on, and service jobs appear to be finished and removed.
Return type:: bool

replace(other)[source]¶

Take on the ID of another JobDescription, retaining our own state and type.

When updated in the JobStore, we will save over the other JobDescription.

Useful for chaining jobs: the chained-to job can replace the parent job.

Merges cleanup state and successors other than this job from the job being replaced into this one.

Parameters:: other (JobDescription) – Job description to replace.
Return type:: None

assert_is_not_newer_than(other)[source]¶

Make sure this JobDescription is not newer than a prospective new version of the JobDescription.

Parameters:: other (JobDescription)
Return type:: None

is_updated_by(other)[source]¶

Return True if the passed JobDescription is a distinct, newer version of this one.

Parameters:: other (JobDescription)
Return type:: bool

addChild(childID)[source]¶

Make the job with the given ID a child of the described job.

Parameters:: childID (str)
Return type:: None

addFollowOn(followOnID)[source]¶

Make the job with the given ID a follow-on of the described job.

Parameters:: followOnID (str)
Return type:: None

addServiceHostJob(serviceID, parentServiceID=None)[source]¶

Make the ServiceHostJob with the given ID a service of the described job.

If a parent ServiceHostJob ID is given, that parent service will be started first, and must have already been added.

hasChild(childID)[source]¶

Return True if the job with the given ID is a child of the described job.

Parameters:: childID (str)
Return type:: bool

hasFollowOn(followOnID)[source]¶

Test if the job with the given ID is a follow-on of the described job.

Parameters:: followOnID (str)
Return type:: bool

hasServiceHostJob(serviceID)[source]¶

Test if the ServiceHostJob is a service of the described job.

Return type:: bool

renameReferences(renames)[source]¶

Apply the given dict of ID renames to all references to jobs.

Does not modify our own ID or those of finished predecessors. IDs not present in the renames dict are left as-is.

Parameters:: renames (Dict[TemporaryID, str]) – Rename operations to apply.
Return type:: None

addPredecessor()[source]¶

Notify the JobDescription that a predecessor has been added to its Job.

Return type:: None

onRegistration(jobStore)[source]¶

Perform setup work that requires the JobStore.

Called by the Job saving logic when this JobDescription meets the JobStore and has its ID assigned.

Overridden to perform setup work (like hooking up flag files for service jobs) that requires the JobStore.

Parameters:: jobStore (toil.jobStores.abstractJobStore.AbstractJobStore) – The job store we are being placed into
Return type:: None

setupJobAfterFailure(exit_status=None, exit_reason=None)[source]¶

Configure job after a failure.

Reduce the remainingTryCount if greater than zero and set the memory to be at least as big as the default memory (in case of exhaustion of memory, which is common).

Requires a configuration to have been assigned (see toil.job.Requirer.assignConfig()).

Parameters:

exit_status (Optional[int]) – The exit code from the job.
exit_reason (Optional[toil.batchSystems.abstractBatchSystem.BatchJobExitReason]) – The reason the job stopped, if available from the batch system.

Return type:

None

getLogFileHandle(jobStore)[source]¶

Create a context manager that yields a file handle to the log file.

Assumes logJobStoreFileID is set.

property remainingTryCount¶
Get the number of tries remaining.: The try count set on the JobDescription, or the default based on the retry count from the config if none is set.

clearRemainingTryCount()[source]¶

Clear remainingTryCount and set it back to its default value.

Returns:: True if a modification to the JobDescription was made, and False otherwise.
Return type:: bool

__str__()[source]¶

Produce a useful logging string identifying this job.

Return type:: str

__repr__()[source]¶: Return repr(self).

reserve_versions(count)[source]¶

Reserve a job version number for later, for journaling asynchronously.

Parameters:: count (int)
Return type:: None

pre_update_hook()[source]¶

Run before pickling and saving a created or updated version of this job.

Called by the job store.

Return type:: None

class toil.batchSystems.singleMachine.Requirer(requirements)[source]¶

Base class implementing the storage and presentation of requirements.

Has cores, memory, disk, and preemptability as properties.

Parameters:: requirements (Mapping[str, ParseableRequirement])

assignConfig(config)[source]¶

Assign the given config object to be used to provide default values.

Must be called exactly once on a loaded JobDescription before any requirements are queried.

Parameters:: config (toil.common.Config) – Config object to query
Return type:: None

__getstate__()[source]¶

Return the dict to use as the instance’s __dict__ when pickling.

Return type:: Dict[str, Any]

__copy__()[source]¶

Return a semantically-shallow copy of the object, for copy.copy().

Return type:: Requirer

__deepcopy__(memo)[source]¶

Return a semantically-deep copy of the object, for copy.deepcopy().

Parameters:: memo (Any)
Return type:: Requirer

property requirements: RequirementsDict¶

Get dict containing all non-None, non-defaulted requirements.

Return type:: RequirementsDict

property disk: int¶

Get the maximum number of bytes of disk required.

Return type:: int

property memory: int¶

Get the maximum number of bytes of memory required.

Return type:: int

property cores: int | float¶

Get the number of CPU cores required.

Return type:: Union[int, float]

property preemptible: bool¶

Whether a preemptible node is permitted, or a nonpreemptible one is required.

Return type:: bool

preemptable(val)[source]¶

Parameters:: val (ParseableFlag)
Return type:: None

property accelerators: List[AcceleratorRequirement]¶

Any accelerators, such as GPUs, that are needed.

Return type:: List[AcceleratorRequirement]

scale(requirement, factor)[source]¶

Return a copy of this object with the given requirement scaled up or down.

Only works on requirements where that makes sense.

Parameters:

requirement (str)
factor (float)

Return type:

Requirer

requirements_string()[source]¶

Get a nice human-readable string of our requirements.

Return type:: str

toil.batchSystems.singleMachine.accelerator_satisfies(candidate, requirement, ignore=[])[source]¶

Test if candidate partially satisfies the given requirement.

Returns:

True if the given candidate at least partially satisfies the given requirement (i.e. check all fields other than count).

Parameters:

candidate (AcceleratorRequirement)
requirement (AcceleratorRequirement)
ignore (List[str])

Return type:

bool

toil.batchSystems.singleMachine.get_individual_local_accelerators()[source]¶

Determine all the local accelerators available. Report each with count 1, in the order of the number that can be used to assign them.

TODO: How will numbers work with multiple types of accelerator? We need an accelerator assignment API.

Return type:: List[toil.job.AcceleratorRequirement]

toil.batchSystems.singleMachine.get_restrictive_environment_for_local_accelerators(accelerator_numbers)[source]¶

Get environment variables which can be applied to a process to restrict it to using only the given accelerator numbers.

The numbers are in the space of accelerators returned by get_individual_local_accelerators().

Parameters:: accelerator_numbers (Union[Set[int], List[int]])
Return type:: Dict[str, str]

toil.batchSystems.singleMachine.cpu_count()[source]¶

Get the rounded-up integer number of whole CPUs available.

Counts hyperthreads as CPUs.

Uses the system’s actual CPU count, or the current v1 cgroup’s quota per period, if the quota is set.

Ignores the cgroup’s cpu shares value, because it’s extremely difficult to interpret. See https://github.com/kubernetes/kubernetes/issues/81021.

Caches result for efficiency.

Returns:: Integer count of available CPUs, minimum 1.
Return type:: int

toil.batchSystems.singleMachine.logger¶

class toil.batchSystems.singleMachine.SingleMachineBatchSystem(config, maxCores, maxMemory, maxDisk, max_jobs=None)[source]¶

Bases: toil.batchSystems.abstractBatchSystem.BatchSystemSupport

The interface for running jobs on a single machine, runs all the jobs you give it as they come in, but in parallel.

Uses a single “daddy” thread to manage a fleet of child processes.

Communication with the daddy thread happens via two queues: one queue of jobs waiting to be run (the input queue), and one queue of jobs that are finished/stopped and need to be returned by getUpdatedBatchJob (the output queue).

When the batch system is shut down, the daddy thread is stopped.

If running in debug-worker mode, jobs are run immediately as they are sent to the batch system, in the sending thread, and the daddy thread is not run. But the queues are still used.

Parameters:

config (toil.common.Config)
maxCores (float)
maxMemory (int)
maxDisk (int)
max_jobs (Optional[int])

classmethod supportsAutoDeployment()[source]¶

Whether this batch system supports auto-deployment of the user script itself.

If it does, the setUserScript() can be invoked to set the resource object representing the user script.

Note to implementors: If your implementation returns True here, it should also override

classmethod supportsWorkerCleanup()[source]¶

Whether this batch system supports worker cleanup.

Indicates whether this batch system invokes BatchSystemSupport.workerCleanup() after the last job for a particular workflow invocation finishes. Note that the term worker refers to an entire node, not just a worker process. A worker process may run more than one job sequentially, and more than one concurrent worker process may exist on a worker node, for the same workflow. The batch system is said to shut down after the last worker process terminates.

numCores¶

minCores = 0.1¶: The minimal fractional CPU. Tasks with a smaller core requirement will be rounded up to this value.

physicalMemory¶

daddy()[source]¶

Be the “daddy” thread.

Our job is to look at jobs from the input queue.

If a job fits in the available resources, we allocate resources for it and kick off a child process.

We also check on our children.

When a child finishes, we reap it, release its resources, and put its information in the output queue.

getSchedulingStatusMessage()[source]¶

Get a log message fragment for the user about anything that might be going wrong in the batch system, if available.

If no useful message is available, return None.

This can be used to report what resource is the limiting factor when scheduling jobs, for example. If the leader thinks the workflow is stuck, the message can be displayed to the user to help them diagnose why it might be stuck.

Returns:: User-directed message about scheduling state.

check_resource_request(requirer)[source]¶

Check resource request is not greater than that available or allowed.

Parameters:

requirer (toil.job.Requirer) – Object whose requirements are being checked
job_name (str) – Name of the job being checked, for generating a useful error report.
detail (str) – Batch-system-specific message to include in the error.

Raises:

InsufficientSystemResources – raised when a resource is requested in an amount greater than allowed

Return type:

None

issueBatchJob(command, job_desc, job_environment=None)[source]¶

Adds the command and resources to a queue to be run.

Parameters:

command (str)
job_desc (toil.job.JobDescription)
job_environment (Optional[Dict[str, str]])

Return type:

int

killBatchJobs(jobIDs)[source]¶

Kills jobs by ID.

Parameters:: jobIDs (List[int])
Return type:: None

getIssuedBatchJobIDs()[source]¶

Just returns all the jobs that have been run, but not yet returned as updated.

Return type:: List[int]

getRunningBatchJobIDs()[source]¶

Gets a map of jobs as job ID numbers that are currently running (not just waiting) and how long they have been running, in seconds.

Returns:: dictionary with currently running job ID number keys and how many seconds they have been running as the value
Return type:: Dict[int, float]

shutdown()[source]¶

Terminate cleanly and join daddy thread.

Return type:: None

getUpdatedBatchJob(maxWait)[source]¶

Returns a tuple of a no-longer-running job, the return value of its process, and its runtime, or None.

Parameters:: maxWait (int)
Return type:: Optional[toil.batchSystems.abstractBatchSystem.UpdatedBatchJobInfo]

classmethod add_options(parser)[source]¶

If this batch system provides any command line options, add them to the given parser.

Parameters:: parser (Union[argparse.ArgumentParser, argparse._ArgumentGroup])
Return type:: None

classmethod setOptions(setOption)[source]¶

Process command line or configuration options relevant to this batch system.

Parameters:: setOption (toil.batchSystems.options.OptionSetter) – A function with signature setOption(option_name, parsing_function=None, check_function=None, default=None, env=None) returning nothing, used to update run configuration as a side effect.

class toil.batchSystems.singleMachine.Info(startTime, popen, resources, killIntended)[source]¶

Record for a running job.

Stores the start time of the job, the Popen object representing its child (or None), the tuple of (coreFractions, memory, disk) it is using (or None), and whether the job is supposed to be being killed.

toil.batchSystems.singleMachine¶

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