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galaxy.jobs package

Support for running a tool in Galaxy via an internal job management system

class galaxy.jobs.JobDestination(**kwds)[source]

Bases: galaxy.util.bunch.Bunch

Provides details about where a job runs

__init__(**kwds)[source]

Initialize self. See help(type(self)) for accurate signature.

class galaxy.jobs.JobToolConfiguration(**kwds)[source]

Bases: galaxy.util.bunch.Bunch

Provides details on what handler and destination a tool should use

A JobToolConfiguration will have the required attribute ‘id’ and optional attributes ‘handler’, ‘destination’, and ‘params’

__init__(**kwds)[source]

Initialize self. See help(type(self)) for accurate signature.

get_resource_group()[source]
galaxy.jobs.config_exception(e, file)[source]
galaxy.jobs.job_config_xml_to_dict(config, root)[source]
class galaxy.jobs.JobConfiguration(app: galaxy.structured_app.MinimalManagerApp)[source]

Bases: galaxy.web_stack.handlers.ConfiguresHandlers

A parser and interface to advanced job management features.

These features are configured in the job configuration, by default, job_conf.xml

DEFAULT_BASE_HANDLER_POOLS: Tuple[str, …] = ('job-handlers',)
DEFAULT_NWORKERS = 4
DEFAULT_HANDLER_READY_WINDOW_SIZE = 100
JOB_RESOURCE_CONDITIONAL_XML = '<conditional name="__job_resource">\n        <param name="__job_resource__select" type="select" label="Job Resource Parameters">\n            <option value="no">Use default job resource parameters</option>\n            <option value="yes">Specify job resource parameters</option>\n        </param>\n        <when value="no"/>\n        <when value="yes"/>\n    </conditional>'
__init__(app: galaxy.structured_app.MinimalManagerApp)[source]

Parse the job configuration XML.

runner_plugins: List[dict]
handlers: dict
handler_runner_plugins: Dict[str, str]
destinations: Dict[str, tuple]
tools: Dict[str, list]
tool_classes: Dict[str, list]
resource_groups: Dict[str, list]
resource_parameters: Dict[str, Any]
get_tool_resource_xml(tool_id, tool_type)[source]

Given a tool id, return XML elements describing parameters to insert into job resources.

Tool id

A tool ID (a string)

Tool type

A tool type (a string)

Returns

List of parameter elements.

static get_params(config, parent)[source]
static get_envs(parent)[source]

Parses any child <env> tags in to a dictionary suitable for persistence.

Parameters

parent (lxml.etree._Element) – Parent element in which to find child <env> tags.

Returns

dict

static get_resubmits(parent)[source]

Parses any child <resubmit> tags in to a dictionary suitable for persistence.

Parameters

parent (lxml.etree._Element) – Parent element in which to find child <resubmit> tags.

Returns

dict

property default_job_tool_configuration

The default JobToolConfiguration, used if a tool does not have an explicit defintion in the configuration. It consists of a reference to the default handler and default destination.

Returns

JobToolConfiguration – a representation of a <tool> element that uses the default handler and destination

get_job_tool_configurations(ids, tool_classes)[source]

Get all configured JobToolConfigurations for a tool ID, or, if given a list of IDs, the JobToolConfigurations for the first id in ids matching a tool definition.

Note

You should not mix tool shed tool IDs, versionless tool shed IDs, and tool config tool IDs that refer to the same tool.

Parameters

ids (list or str.) – Tool ID or IDs to fetch the JobToolConfiguration of.

Returns

list – JobToolConfiguration Bunches representing <tool> elements matching the specified ID(s).

Example tool ID strings include:

  • Full tool shed id: toolshed.example.org/repos/nate/filter_tool_repo/filter_tool/1.0.0

  • Tool shed id less version: toolshed.example.org/repos/nate/filter_tool_repo/filter_tool

  • Tool config tool id: filter_tool

get_destination(id_or_tag)[source]

Given a destination ID or tag, return the JobDestination matching the provided ID or tag

Parameters

id_or_tag (str) – A destination ID or tag.

Returns

JobDestination – A valid destination

Destinations are deepcopied as they are expected to be passed in to job runners, which will modify them for persisting params set at runtime.

get_destinations(id_or_tag)[source]

Given a destination ID or tag, return all JobDestinations matching the provided ID or tag

Parameters

id_or_tag (str) – A destination ID or tag.

Returns

list or tuple of JobDestinations

Destinations are not deepcopied, so they should not be passed to anything which might modify them.

get_job_runner_plugins(handler_id)[source]

Load all configured job runner plugins

Returns

list of job runner plugins

is_id(collection)[source]

Given a collection of handlers or destinations, indicate whether the collection represents a tag or a real ID

Parameters

collection (tuple or list) – A representation of a destination or handler

Returns

bool

is_tag(collection)[source]

Given a collection of handlers or destinations, indicate whether the collection represents a tag or a real ID

Parameters

collection (tuple or list) – A representation of a destination or handler

Returns

bool

convert_legacy_destinations(job_runners)[source]

Converts legacy (from a URL) destinations to contain the appropriate runner params defined in the URL.

Parameters

job_runners (list of job runner plugins) – All loaded job runner plugins.

class galaxy.jobs.HasResourceParameters[source]

Bases: object

get_resource_parameters(job=None)[source]
class galaxy.jobs.JobWrapper(job, queue, use_persisted_destination=False)[source]

Bases: galaxy.jobs.HasResourceParameters

Wraps a ‘model.Job’ with convenience methods for running processes and state management.

__init__(job, queue, use_persisted_destination=False)[source]

Initialize self. See help(type(self)) for accurate signature.

property external_output_metadata
property dataset_path_rewriter
property outputs_directory

Default location of outputs_to_working_directory.

property created_with_galaxy_version
property dependency_shell_commands

Shell fragment to inject dependencies.

property cleanup_job

Remove the job after it is complete, should return “always”, “onsuccess”, or “never”.

property requires_containerization
property use_metadata_binary
can_split()[source]
get_job_runner_url()[source]
get_parallelism()[source]
property shell
disable_commands_in_new_shell()[source]

Provide an extension point to disable this isolation, Pulsar builds its own job script so this is not needed for remote jobs.

property strict_shell
property commands_in_new_shell
property galaxy_lib_dir
property galaxy_virtual_env
get_job_runner()
property job_destination

Return the JobDestination that this job will use to run. This will either be a configured destination, a randomly selected destination if the configured destination was a tag, or a dynamically generated destination from the dynamic runner.

Calling this method for the first time causes the dynamic runner to do its calculation, if any.

Returns

JobDestination

get_job()[source]
get_id_tag()[source]
get_param_dict(_job=None)[source]

Restore the dictionary of parameters from the database.

property validate_outputs
get_version_string_path()[source]
get_version_string_path_legacy()[source]
prepare(compute_environment=None)[source]

Prepare the job to run by creating the working directory and the config files.

property guest_ports
property working_directory
working_directory_exists()[source]
property tool_working_directory
clear_working_directory()[source]
default_compute_environment(job=None)[source]
fail(message, exception=False, tool_stdout='', tool_stderr='', exit_code=None, job_stdout=None, job_stderr=None)[source]

Indicate job failure by setting state and message on all output datasets.

pause(job=None, message=None)[source]
is_ready_for_resubmission(job=None)[source]
mark_as_resubmitted(info=None)[source]
change_state(state, info=False, flush=True, job=None)[source]
get_state()[source]
set_runner(runner_url, external_id)[source]
set_job_destination(job_destination, external_id=None, flush=True, job=None)[source]

Persist job destination params in the database for recovery.

self.job_destination is not used because a runner may choose to rewrite parts of the destination (e.g. the params).

set_external_id(external_id, job=None, flush=True)[source]
property home_target
property tmp_target
get_destination_configuration(key, default=None)[source]

Get a destination parameter that can be defaulted back in app.config if it needs to be applied globally.

enqueue()[source]
finish(tool_stdout, tool_stderr, tool_exit_code=None, job_stdout=None, job_stderr=None, check_output_detected_state=None, remote_metadata_directory=None, job_metrics_directory=None)[source]

Called to indicate that the associated command has been run. Updates the output datasets based on stderr and stdout from the command, and the contents of the output files.

discover_outputs(job, inp_data, out_data, out_collections, final_job_state)[source]
check_tool_output(tool_stdout, tool_stderr, tool_exit_code, job, job_stdout=None, job_stderr=None)[source]
cleanup(delete_files=True)[source]
get_output_sizes()[source]
check_limits(runtime=None)[source]
has_limits()[source]
get_command_line()[source]
get_session_id()[source]
get_env_setup_clause()[source]
get_input_dataset_fnames(ds)[source]
get_input_fnames()[source]
get_input_paths(job=None)[source]
get_input_path(dataset)[source]
get_output_basenames()[source]
get_output_fnames()[source]
get_output_path(dataset)[source]
get_mutable_output_fnames()[source]
get_output_hdas_and_fnames()[source]
compute_outputs()[source]
get_output_file_id(file)[source]
property object_store
property tmp_dir_creation_statement
home_directory()[source]
tmp_directory()[source]
get_tool_provided_job_metadata()[source]
get_dataset_finish_context(job_context, output_dataset_assoc)[source]
invalidate_external_metadata()[source]
setup_external_metadata(exec_dir=None, tmp_dir=None, dataset_files_path=None, config_root=None, config_file=None, datatypes_config=None, resolve_metadata_dependencies=False, set_extension=True, **kwds)[source]
check_for_entry_points(check_already_configured=True)[source]
container_monitor_command(container, **kwds)[source]
property user
change_ownership_for_run()[source]
reclaim_ownership()[source]
property user_system_pwent
property galaxy_system_pwent
get_output_destination(output_path)[source]

Destination for outputs marked as from_work_dir. This is the normal case, just copy these files directly to the ultimate destination.

property requires_setting_metadata
set_container(container)[source]
class galaxy.jobs.TaskWrapper(task, queue)[source]

Bases: galaxy.jobs.JobWrapper

Extension of JobWrapper intended for running tasks. Should be refactored into a generalized executable unit wrapper parent, then jobs and tasks.

__init__(task, queue)[source]

Initialize self. See help(type(self)) for accurate signature.

property dataset_path_rewriter
can_split()[source]
get_job()[source]
get_task()[source]
get_id_tag()[source]
prepare(compute_environment=None)[source]

Prepare the job to run by creating the working directory and the config files.

fail(message, exception=False)[source]

Indicate job failure by setting state and message on all output datasets.

change_state(state, info=False, flush=True, job=None)[source]
get_state()[source]
get_exit_code()[source]
set_runner(runner_url, external_id)[source]
finish(stdout, stderr, tool_exit_code=None, **kwds)[source]

Called to indicate that the associated command has been run. Updates the output datasets based on stderr and stdout from the command, and the contents of the output files.

cleanup(delete_files=True)[source]
get_command_line()[source]
get_session_id()[source]
get_output_file_id(file)[source]
get_tool_provided_job_metadata()[source]
get_dataset_finish_context(job_context, dataset)[source]
setup_external_metadata(exec_dir=None, tmp_dir=None, dataset_files_path=None, config_root=None, config_file=None, datatypes_config=None, set_extension=True, **kwds)[source]
get_output_destination(output_path)[source]

Destination for outputs marked as from_work_dir. These must be copied with the same basenme as the path for the ultimate output destination. This is required in the task case so they can be merged.

class galaxy.jobs.ComputeEnvironment[source]

Bases: object

Definition of the job as it will be run on the (potentially) remote compute server.

abstract output_names()[source]

Output unqualified filenames defined by job.

abstract input_path_rewrite(dataset)[source]

Input path for specified dataset.

abstract output_path_rewrite(dataset)[source]

Output path for specified dataset.

abstract input_extra_files_rewrite(dataset)[source]

Input extra files path rewrite for specified dataset.

abstract output_extra_files_rewrite(dataset)[source]

Output extra files path rewrite for specified dataset.

abstract input_metadata_rewrite(dataset, metadata_value)[source]

Input metadata path rewrite for specified dataset.

abstract unstructured_path_rewrite(path)[source]

Rewrite loc file paths, etc..

abstract working_directory()[source]

Job working directory (potentially remote)

abstract config_directory()[source]

Directory containing config files (potentially remote)

abstract sep()[source]

os.path.sep for the platform this job will execute in.

abstract new_file_path()[source]

Absolute path to dump new files for this job on compute server.

abstract tool_directory()[source]

Absolute path to tool files for this job on compute server.

abstract version_path()[source]

Location of the version file for the underlying tool.

abstract home_directory()[source]

Home directory of target job - none if HOME should not be set.

abstract tmp_directory()[source]

Temp directory of target job - none if HOME should not be set.

abstract galaxy_url()[source]

URL to access Galaxy API from for this compute environment.

class galaxy.jobs.SimpleComputeEnvironment[source]

Bases: object

config_directory()[source]
sep()[source]
class galaxy.jobs.SharedComputeEnvironment(job_wrapper, job)[source]

Bases: galaxy.jobs.SimpleComputeEnvironment

Default ComputeEnviornment for job and task wrapper to pass to ToolEvaluator - valid when Galaxy and compute share all the relevant file systems.

__init__(job_wrapper, job)[source]

Initialize self. See help(type(self)) for accurate signature.

output_names()[source]
output_paths()[source]
input_path_rewrite(dataset)[source]
output_path_rewrite(dataset)[source]
input_extra_files_rewrite(dataset)[source]
output_extra_files_rewrite(dataset)[source]
input_metadata_rewrite(dataset, metadata_value)[source]
unstructured_path_rewrite(path)[source]
working_directory()[source]
env_config_directory()[source]

Working directory (possibly as environment variable evaluation).

new_file_path()[source]
version_path()[source]
tool_directory()[source]
home_directory()[source]
tmp_directory()[source]
galaxy_url()[source]
class galaxy.jobs.NoopQueue[source]

Bases: object

Implements the JobQueue / JobStopQueue interface but does nothing

put(*args, **kwargs)[source]
put_stop(*args)[source]
shutdown()[source]

Submodules

galaxy.jobs.command_factory module

galaxy.jobs.command_factory.build_command(runner, job_wrapper, container=None, modify_command_for_container=True, include_metadata=False, include_work_dir_outputs=True, create_tool_working_directory=True, remote_command_params=None, remote_job_directory=None, stdout_file=None, stderr_file=None)[source]

Compose the sequence of commands necessary to execute a job. This will currently include:

  • environment settings corresponding to any requirement tags

  • preparing input files

  • command line taken from job wrapper

  • commands to set metadata (if include_metadata is True)

galaxy.jobs.dynamic_tool_destination module

galaxy.jobs.dynamic_tool_destination.priority_list: Set[str] = {}

Instantiated to a list of all valid destinations in the job configuration file if run directly to validate configs. Otherwise, remains None. We often check to see if app is None, because if it is then we’ll try using the destination_list instead. -

galaxy.jobs.dynamic_tool_destination.destination_list: Set[str] = {}

The largest the edit distance can be for a word to be considered A correction for another word.

galaxy.jobs.dynamic_tool_destination.max_edit_dist = 2

List of valid categories that can be expected in the configuration.

exception galaxy.jobs.dynamic_tool_destination.MalformedYMLException[source]

Bases: Exception

exception galaxy.jobs.dynamic_tool_destination.ScannerError[source]

Bases: Exception

galaxy.jobs.dynamic_tool_destination.get_keys_from_dict(dl, keys_list)[source]

This function builds a list using the keys from nest dictionaries

class galaxy.jobs.dynamic_tool_destination.RuleValidator[source]

Bases: object

This class is the primary facility for validating configs. It’s always called in map_tool_to_destination and it’s called for validating config directly through DynamicToolDestination.py

classmethod validate_rule(rule_type: str, app, return_bool: bool = False, *args, **kwargs)[source]

This function is responsible for passing each rule to its relevant function.

Parameters

  • rule_type – the current rule’s type

  • return_bool – True when we are only interested in the result of the validation, and not the validated rule itself.

Return type

bool, dict (depending on return_bool)

Returns

validated rule or result of validation (depending on return_bool)

galaxy.jobs.dynamic_tool_destination.parse_yaml(path: str = '/config/tool_destinations.yml', job_conf_path: str = '/config/job_conf.xml', app=None, test: bool = False, return_bool: bool = False)[source]

Get a yaml file from path and send it to validate_config for validation.

Parameters

  • path – the path to the tool destinations config file

  • job_conf_path – the path to the job config file

  • test – indicates whether to run in test mode or production mode

  • return_bool (bool) – True when we are only interested in the result of the validation, and not the validated rule itself.

Return type

bool, dict (depending on return_bool)

Returns

validated rule or result of validation (depending on return_bool)

galaxy.jobs.dynamic_tool_destination.validate_destination(app, destination: str, err_message: str, err_message_contents, return_bool: bool = True)[source]

Validate received destination id.

Parameters

  • app – Current app

  • destination – string containing the destination id that is being validated

  • err_message – Error message to be formatted with the contents of err_message_contents upon the event of invalid destination

  • err_message_contents (tuple) – A tuple of strings to be placed in err_message

  • return_bool – Whether or not the calling function has been told to return a boolean value or not. Determines whether or not to print ‘Ignoring…’ after error messages.

Return type

bool

Returns

True if the destination is valid and False otherwise.

galaxy.jobs.dynamic_tool_destination.validate_config(obj: dict, app=None, return_bool: bool = False)[source]

Validate received config.

Parameters

  • obj – the entire contents of the config

  • return_bool – True when we are only interested in the result of the validation, and not the validated rule itself.

Return type

bool, dict (depending on return_bool)

Returns

validated rule or result of validation (depending on return_bool)

galaxy.jobs.dynamic_tool_destination.bytes_to_str(size, unit='YB')[source]

Uses the bi convention: 1024 B = 1 KB since this method primarily has inputs of bytes for RAM

@type size: int @param size: the size in int (bytes) to be converted to str

@rtype: str @return return_str: the resulting string

galaxy.jobs.dynamic_tool_destination.str_to_bytes(size)[source]

Uses the bi convention: 1024 B = 1 KB since this method primarily has inputs of bytes for RAM

@type size: str @param size: the size in str to be converted to int (bytes)

@rtype: int @return curr_size: the resulting size converted from str

galaxy.jobs.dynamic_tool_destination.importer(test)[source]

Uses Mock galaxy for testing or real galaxy for production

@type test: bool @param test: True when being run from a test

galaxy.jobs.dynamic_tool_destination.map_tool_to_destination(job, app, tool, user_email, test=False, path=None, job_conf_path=None)[source]

Dynamically allocate resources

@param job: galaxy job @param app: current app @param tool: current tool

@type test: bool @param test: True when running in test mode

@type path: str @param path: path to tool_destinations.yml

@type job_conf_path: str @param job_conf_path: path to job_conf.xml

galaxy.jobs.dynamic_tool_destination.get_destination_list_from_job_config(job_config_location) → set[source]

returns A list of all destination IDs declared in the job configuration

Parameters

job_config_location (str) – The location of the job config file relative to the galaxy root directory. If NoneType, defaults to galaxy/config/job_conf.xml, galaxy/config/job_conf.xml.sample_advanced, or galaxy/config/job_conf.xml.sample_basic (first one that exists)

Returns

A list of all of the destination IDs declared in the job configuration file.

galaxy.jobs.dynamic_tool_destination.get_edit_distance(source, target)[source]

returns the edit distance (levenshtein distance) between two strings. code from: en.wikibooks.org/wiki/Algorithm_Implementation/Strings/Levenshtein_distance

@type str1: str @param str1: The first string

@type str2: str @param str2: The second string

@rtype: int @return: The edit distance between str1 and str2

galaxy.jobs.dynamic_tool_destination.get_typo_correction(typo_str, word_set, max_dist)[source]

returns the string in a set that closest matches the input string, as long as the edit distance between them is equal to or smaller than a value, or the words are the same when case is not considered. If there are no appropriate matches, nothing is returned instead.

Parameters

  • typo_str (str) – The string to be compared

  • word_set (set of str) – The set of strings to compare to

  • max_dist (int) – the largest allowed edit distance between the word and the result. If nothing is within this range, nothing is returned

Return type

str or NoneType

Returns

The closest matching string, or None, if no strings being compared to are within max_dist edit distance.

galaxy.jobs.dynamic_tool_destination.verbose = True

list of all valid priorities, inferred from the global default_desinations section of the config

galaxy.jobs.handler module

Galaxy job handler, prepares, runs, tracks, and finishes Galaxy jobs

class galaxy.jobs.handler.JobHandlerI[source]

Bases: object

start()[source]
shutdown()[source]
class galaxy.jobs.handler.JobHandler(app)[source]

Bases: galaxy.jobs.handler.JobHandlerI

Handle the preparation, running, tracking, and finishing of jobs

__init__(app)[source]

Initialize self. See help(type(self)) for accurate signature.

start()[source]
shutdown()[source]
class galaxy.jobs.handler.ItemGrabber(app, grab_type='Job', handler_assignment_method=None, max_grab=None, self_handler_tags=None, handler_tags=None)[source]

Bases: object

__init__(app, grab_type='Job', handler_assignment_method=None, max_grab=None, self_handler_tags=None, handler_tags=None)[source]

Initialize self. See help(type(self)) for accurate signature.

setup_query()[source]
static get_grabbable_handler_assignment_method(handler_assignment_methods)[source]
grab_unhandled_items()[source]

Attempts to assign unassigned jobs or invocaions to itself using DB serialization methods, if enabled. This simply sets Job.handler or WorkflowInvocation.handler to the current server name, which causes the job to be picked up by the appropriate handler.

class galaxy.jobs.handler.JobHandlerQueue(app, dispatcher)[source]

Bases: galaxy.util.monitors.Monitors

Job Handler’s Internal Queue, this is what actually implements waiting for jobs to be runnable and dispatching to a JobRunner.

STOP_SIGNAL = <object object>
__init__(app, dispatcher)[source]

Initializes the Job Handler Queue, creates (unstarted) monitoring thread

start()[source]

Starts the JobHandler’s thread after checking for any unhandled jobs.

job_wrapper(job, use_persisted_destination=False)[source]
job_pair_for_id(id)[source]
get_user_job_count(user_id)[source]
get_user_job_count_per_destination(user_id)[source]
increase_running_job_count(user_id, destination_id)[source]
get_total_job_count_per_destination()[source]
put(job_id, tool_id)[source]

Add a job to the queue (by job identifier)

shutdown()[source]

Attempts to gracefully shut down the worker thread

class galaxy.jobs.handler.JobHandlerStopQueue(app, dispatcher)[source]

Bases: galaxy.util.monitors.Monitors

A queue for jobs which need to be terminated prematurely.

STOP_SIGNAL = <object object>
__init__(app, dispatcher)[source]

Initialize self. See help(type(self)) for accurate signature.

start()[source]
monitor()[source]

Continually iterate the waiting jobs, stop any that are found.

monitor_step()[source]

Called repeatedly by monitor to stop jobs.

put(job_id, error_msg=None)[source]
shutdown()[source]

Attempts to gracefully shut down the worker thread

class galaxy.jobs.handler.DefaultJobDispatcher(app)[source]

Bases: object

__init__(app)[source]

Initialize self. See help(type(self)) for accurate signature.

start()[source]
url_to_destination(url)[source]

This is used by the runner mapper (a.k.a. dynamic runner) and recovery methods to have runners convert URLs to destinations.

New-style runner plugin IDs must match the URL’s scheme for this to work.

put(job_wrapper)[source]
stop(job, job_wrapper)[source]

Stop the given job. The input variable job may be either a Job or a Task.

recover(job, job_wrapper)[source]
shutdown()[source]

galaxy.jobs.manager module

Top-level Galaxy job manager, moves jobs to handler(s)

class galaxy.jobs.manager.JobManager(app: galaxy.structured_app.MinimalManagerApp)[source]

Bases: object

Highest level interface to job management.

__init__(app: galaxy.structured_app.MinimalManagerApp)[source]

Initialize self. See help(type(self)) for accurate signature.

job_handler: galaxy.jobs.handler.JobHandlerI
start()[source]
enqueue(job, tool=None, flush=True)[source]

Queue a job for execution.

Due to the nature of some handler assignment methods which are wholly DB-based, the enqueue method will flush the job. Callers who create the job typically should not flush the job before handing it off to enqueue(). If a job handler cannot be assigned, py:class:ToolExecutionError is raised.

Parameters
Raises

ToolExecutionError – if a handler was unable to be assigned.

Returns

str or None – Handler ID, tag, or pool assigned to the job.

stop(job, message=None)[source]

Stop a job that is currently executing.

This can be safely called on jobs that have already terminated.

Parameters

  • job (Instance of galaxy.model.Job.) – Job to stop.

  • message (str) – Message (if any) to be set on the job and output dataset(s) to explain the reason for stopping.

shutdown()[source]
class galaxy.jobs.manager.NoopManager(*args, **kwargs)[source]

Bases: object

Implements the JobManager interface but does nothing

__init__(*args, **kwargs)[source]

Initialize self. See help(type(self)) for accurate signature.

enqueue(*args, **kwargs)[source]
stop(*args, **kwargs)[source]
class galaxy.jobs.manager.NoopHandler(*args, **kwargs)[source]

Bases: galaxy.jobs.handler.JobHandlerI

Implements the JobHandler interface but does nothing

__init__(*args, **kwargs)[source]

Initialize self. See help(type(self)) for accurate signature.

start()[source]
shutdown(*args)[source]

galaxy.jobs.mapper module

exception galaxy.jobs.mapper.JobMappingConfigurationException[source]

Bases: Exception

exception galaxy.jobs.mapper.JobMappingException(failure_message)[source]

Bases: Exception

__init__(failure_message)[source]

Initialize self. See help(type(self)) for accurate signature.

exception galaxy.jobs.mapper.JobNotReadyException(job_state=None, message=None)[source]

Bases: Exception

__init__(job_state=None, message=None)[source]

Initialize self. See help(type(self)) for accurate signature.

class galaxy.jobs.mapper.JobRunnerMapper(job_wrapper, url_to_destination, job_config)[source]

Bases: object

This class is responsible to managing the mapping of jobs (in the form of job_wrappers) to job runner url strings.

__init__(job_wrapper, url_to_destination, job_config)[source]

Initialize self. See help(type(self)) for accurate signature.

get_job_destination(params)[source]

cached_job_destination is a public property that is sometimes externally set to short-circuit the mapper, such as during resubmits. get_job_destination will respect that and not run the mapper if so.

cache_job_destination(raw_job_destination)[source]

Force update of cached_job_destination to mapper determined job destination, overwriting any externally set cached_job_destination

galaxy.jobs.rule_helper module

class galaxy.jobs.rule_helper.RuleHelper(app)[source]

Bases: object

Utility to allow job rules to interface cleanly with the rest of Galaxy and shield them from low-level details of models, metrics, etc….

Currently focus is on figuring out job statistics for a given user, but could interface with other stuff as well.

__init__(app)[source]

Initialize self. See help(type(self)) for accurate signature.

supports_container(job_or_tool, container_type)[source]

Job rules can pass this function a job, job_wrapper, or tool and determine if the underlying tool believes it can be run with a specific container type.

Parameters

  • job_or_tool –

  • container_type – either “docker” or “singularity” currently

Returns

true if the tool supports the specified container type.

supports_docker(job_or_tool)[source]

Returns true if the tool or job supports running on a singularity container.

Parameters

job_or_tool – the job or tool to test for.

Returns

true if the tool/job can run in docker.

supports_singularity(job_or_tool)[source]

Returns true if the tool or job supports running on a singularity container.

Parameters

job_or_tool – the job or tool to test for.

Returns

true if the tool/job can run in singularity.

job_count(**kwds)[source]
sum_job_runtime(**kwds)[source]
metric_query(select, metric_name, plugin, numeric=True)[source]
query(select_expression)[source]
should_burst(destination_ids, num_jobs, job_states=None)[source]

Check if the specified destinations destination_ids have at least num_jobs assigned to it - send in job_state as queued to limit this check to number of jobs queued.

See stock_rules for an simple example of using this function - but to get the most out of it - it should probably be used with custom job rules that can respond to the bursting by allocating resources, launching cloud nodes, etc….

choose_one(lst, hash_value=None)[source]

Choose a random value from supplied list. If hash_value is passed in then every request with that same hash_value would produce the same choice from the supplied list.

job_hash(job, hash_by=None)[source]

Produce a reproducible hash for the given job on various criteria - for instance if hash_by is “workflow_invocation,history” - all jobs within the same workflow invocation will receive the same hash - for jobs outside of workflows all jobs within the same history will receive the same hash, other jobs will be hashed on job’s id randomly.

Primarily intended for use with choose_one above - to consistent route or schedule related jobs.

galaxy.jobs.stock_rules module

Stock job ‘dynamic’ rules for use in job_conf.xml - these may cover some simple use cases but will just proxy into functions in rule_helper so similar functionality - but more tailored and composable can be utilized in custom rules.

galaxy.jobs.stock_rules.choose_one(rule_helper, job, destination_ids, hash_by='job')[source]
galaxy.jobs.stock_rules.burst(rule_helper, job, from_destination_ids, to_destination_id, num_jobs, job_states=None)[source]
galaxy.jobs.stock_rules.docker_dispatch(rule_helper, tool, docker_destination_id, default_destination_id)[source]

galaxy.jobs.transfer_manager module