dpdispatcher package

class dpdispatcher.DistributedShell(*args, **kwargs)[source]

Bases: Machine

Methods

`do_submit`(job)	Submit th job to yarn using distributed shell.
`kill`(job)	Kill the job.
`resources_arginfo`()	Generate the resources arginfo.
`resources_subfields`()	Generate the resources subfields.

arginfo
bind_context
check_finish_tag
check_if_recover
check_status
default_resources
deserialize
gen_command_env_cuda_devices
gen_script
gen_script_command
gen_script_custom_flags_lines
gen_script_end
gen_script_env
gen_script_header
gen_script_wait
load_from_dict
load_from_json
serialize
sub_script_cmd
sub_script_head

check_finish_tag(job)[source]

check_status(job)[source]

do_submit(job)[source]

Submit th job to yarn using distributed shell.

Parameters:

jobJob class instance: job to be submitted

Returns:

job_id: string: submit process id

gen_script_end(job)[source]

gen_script_env(job)[source]

gen_script_header(job)[source]

dpdispatcher.DpCloudServer: alias of Bohrium

dpdispatcher.DpCloudServerContext: alias of BohriumContext

class dpdispatcher.Fugaku(*args, **kwargs)[source]

Bases: Machine

Methods

`do_submit`(job)	Submit a single job, assuming that no job is running there.
`kill`(job)	Kill the job.
`resources_arginfo`()	Generate the resources arginfo.
`resources_subfields`()	Generate the resources subfields.

arginfo
bind_context
check_finish_tag
check_if_recover
check_status
default_resources
deserialize
gen_command_env_cuda_devices
gen_script
gen_script_command
gen_script_custom_flags_lines
gen_script_end
gen_script_env
gen_script_header
gen_script_wait
load_from_dict
load_from_json
serialize
sub_script_cmd
sub_script_head

check_finish_tag(job)[source]

check_status(job)[source]

default_resources(resources)[source]

do_submit(job)[source]: Submit a single job, assuming that no job is running there.

gen_script(job)[source]

gen_script_header(job)[source]

class dpdispatcher.HDFSContext(*args, **kwargs)[source]

Bases: BaseContext

Methods

`check_file_exists`(fname)	Check whether the given file exists, often used in checking whether the belonging job has finished.
`download`(submission[, check_exists, ...])	Download backward files from HDFS root dir.
`machine_arginfo`()	Generate the machine arginfo.
`machine_subfields`()	Generate the machine subfields.
`upload`(submission[, dereference])	Upload forward files and forward command files to HDFS root dir.

bind_submission
check_finish
clean
get_job_root
load_from_dict
read_file
write_file

bind_submission(submission)[source]

check_file_exists(fname)[source]

Check whether the given file exists, often used in checking whether the belonging job has finished.

Parameters:

fnamestring: file name to be checked

Returns:

status: boolean

clean()[source]

download(submission, check_exists=False, mark_failure=True, back_error=False)[source]

Download backward files from HDFS root dir.

Parameters:

submissionSubmission class instance: represents a collection of tasks, such as backward file names
check_existsbool: whether to check if the file exists
mark_failurebool: whether to mark the task as failed if the file does not exist
back_errorbool: whether to download error files

Returns:

none

get_job_root()[source]

classmethod load_from_dict(context_dict)[source]

read_file(fname)[source]

upload(submission, dereference=True)[source]

Upload forward files and forward command files to HDFS root dir.

Parameters:

submissionSubmission class instance: represents a collection of tasks, such as forward file names
dereferencebool: whether to dereference symbolic links

Returns:

none

write_file(fname, write_str)[source]

class dpdispatcher.Job(job_task_list, *, resources, machine=None)[source]

Bases: object

Job is generated by Submission automatically. A job ususally has many tasks and it may request computing resources from job scheduler systems. Each Job can generate a script file to be submitted to the job scheduler system or executed locally.

Parameters:

job_task_listlist of Task: the tasks belonging to the job
resourcesResources: the machine resources. Passed from Submission when it constructs jobs.
machinemachine: machine object to execute the job. Passed from Submission when it constructs jobs.

Methods

`deserialize`(job_dict[, machine])	Convert the job_dict to a Submission class object.
`get_job_state`()	Get the jobs.
`serialize`([if_static])	Convert the Task class instance to a dictionary.

get_hash
handle_unexpected_job_state
job_to_json
register_job_id
submit_job

classmethod deserialize(job_dict, machine=None)[source]

Convert the job_dict to a Submission class object.

Parameters:

job_dictdict: the dictionary which contains the job information
machineMachine: the machine object to execute the job

Returns:

submissionJob: the Job class instance converted from the job_dict

get_hash()[source]

get_job_state()[source]

Get the jobs. Usually, this method will query the database of slurm or pbs job scheduler system and get the results.

Notes

this method will not submit or resubmit the jobs if the job is unsubmitted.

handle_unexpected_job_state()[source]

job_to_json()[source]

register_job_id(job_id)[source]

serialize(if_static=False)[source]

Convert the Task class instance to a dictionary.

Parameters:

if_staticbool: whether dump the job runtime infomation (job_id, job_state, fail_count, job_uuid etc.) to the dictionary.

Returns:

task_dictdict: the dictionary converted from the Task class instance

submit_job()[source]

class dpdispatcher.LSF(*args, **kwargs)[source]

Bases: Machine

LSF batch.

Methods

`default_resources`(resources)
`kill`(job)	Kill the job.
`resources_arginfo`()	Generate the resources arginfo.
`resources_subfields`()	Generate the resources subfields.

arginfo
bind_context
check_finish_tag
check_if_recover
check_status
deserialize
do_submit
gen_command_env_cuda_devices
gen_script
gen_script_command
gen_script_custom_flags_lines
gen_script_end
gen_script_env
gen_script_header
gen_script_wait
load_from_dict
load_from_json
serialize
sub_script_cmd
sub_script_head

check_finish_tag(job)[source]

check_status(**kwargs)

default_resources(resources)[source]

do_submit(**kwargs): Submit a single job, assuming that no job is running there.

gen_script(job)[source]

gen_script_header(job)[source]

kill(job)[source]

Kill the job.

Parameters:

jobJob: job

classmethod resources_subfields() → List[Argument][source]

Generate the resources subfields.

Returns:

list[Argument]: resources subfields

sub_script_cmd(res)[source]

sub_script_head(res)[source]

class dpdispatcher.LazyLocalContext(*args, **kwargs)[source]

Bases: BaseContext

Run jobs in the local server and local directory.

Parameters:

local_rootstr: The local directory to store the jobs.
remote_rootstr, optional: The argument takes no effect.
remote_profiledict, optional: The remote profile. The default is {}.
*args: The arguments.
**kwargs: The keyword arguments.

Methods

`machine_arginfo`()	Generate the machine arginfo.
`machine_subfields`()	Generate the machine subfields.

bind_submission
block_call
block_checkcall
call
check_file_exists
check_finish
clean
download
get_job_root
get_return
load_from_dict
read_file
upload
write_file

bind_submission(submission)[source]

block_call(cmd)[source]

block_checkcall(cmd)[source]

call(cmd)[source]

check_file_exists(fname)[source]

check_finish(proc)[source]

clean()[source]

download(jobs, check_exists=False, mark_failure=True, back_error=False)[source]

get_job_root()[source]

get_return(proc)[source]

classmethod load_from_dict(context_dict)[source]

read_file(fname)[source]

upload(jobs, dereference=True)[source]

write_file(fname, write_str)[source]

dpdispatcher.Lebesgue: alias of Bohrium

dpdispatcher.LebesgueContext: alias of BohriumContext

class dpdispatcher.LocalContext(*args, **kwargs)[source]

Bases: BaseContext

Run jobs in the local server and remote directory.

Parameters:

local_rootstr: The local directory to store the jobs.
remote_rootstr: The remote directory to store the jobs.
remote_profiledict, optional: The remote profile. The default is {}.
*args: The arguments.
**kwargs: The keyword arguments.

Methods

`machine_arginfo`()	Generate the machine arginfo.
`machine_subfields`()	Generate the machine subfields.

bind_submission
block_call
block_checkcall
call
check_file_exists
check_finish
clean
download
get_job_root
get_return
load_from_dict
read_file
upload
write_file

bind_submission(submission)[source]

block_call(cmd)[source]

block_checkcall(cmd)[source]

call(cmd)[source]

check_file_exists(fname)[source]

check_finish(proc)[source]

clean()[source]

download(submission, check_exists=False, mark_failure=True, back_error=False)[source]

get_job_root()[source]

get_return(proc)[source]

classmethod load_from_dict(context_dict)[source]

read_file(fname)[source]

upload(submission)[source]

write_file(fname, write_str)[source]

class dpdispatcher.Machine(*args, **kwargs)[source]

Bases: object

A machine is used to handle the connection with remote machines.

Parameters:

contextSubClass derived from BaseContext: The context is used to mainatin the connection with remote machine.

Methods

`do_submit`(job)	Submit a single job, assuming that no job is running there.
`kill`(job)	Kill the job.
`resources_arginfo`()	Generate the resources arginfo.
`resources_subfields`()	Generate the resources subfields.

arginfo
bind_context
check_finish_tag
check_if_recover
check_status
default_resources
deserialize
gen_command_env_cuda_devices
gen_script
gen_script_command
gen_script_custom_flags_lines
gen_script_end
gen_script_env
gen_script_header
gen_script_wait
load_from_dict
load_from_json
serialize
sub_script_cmd
sub_script_head

alias: Tuple[str, ...] = ()

classmethod arginfo()[source]

bind_context(context)[source]

abstract check_finish_tag(**kwargs)[source]

check_if_recover(submission)[source]

abstract check_status(job)[source]

default_resources(res)[source]

classmethod deserialize(machine_dict)[source]

abstract do_submit(job)[source]: Submit a single job, assuming that no job is running there.

gen_command_env_cuda_devices(resources)[source]

gen_script(job)[source]

gen_script_command(job)[source]

gen_script_custom_flags_lines(job)[source]

gen_script_end(job)[source]

gen_script_env(job)[source]

abstract gen_script_header(job)[source]

gen_script_wait(resources)[source]

kill(job)[source]

Kill the job.

If not implemented, pass and let the user manually kill it.

Parameters:

jobJob: job

classmethod load_from_dict(machine_dict)[source]

classmethod load_from_json(json_path)[source]

options = {'Bohrium', 'DistributedShell', 'Fugaku', 'LSF', 'OpenAPI', 'PBS', 'Shell', 'Slurm', 'SlurmJobArray', 'Torque'}

classmethod resources_arginfo() → Argument[source]

Generate the resources arginfo.

Returns:

Argument: resources arginfo

classmethod resources_subfields() → List[Argument][source]

Generate the resources subfields.

Returns:

list[Argument]: resources subfields

serialize(if_empty_remote_profile=False)[source]

sub_script_cmd(res)[source]

sub_script_head(res)[source]

subclasses_dict = {'Bohrium': <class 'dpdispatcher.dp_cloud_server.Bohrium'>, 'DistributedShell': <class 'dpdispatcher.distributed_shell.DistributedShell'>, 'DpCloudServer': <class 'dpdispatcher.dp_cloud_server.Bohrium'>, 'Fugaku': <class 'dpdispatcher.fugaku.Fugaku'>, 'LSF': <class 'dpdispatcher.lsf.LSF'>, 'Lebesgue': <class 'dpdispatcher.dp_cloud_server.Bohrium'>, 'OpenAPI': <class 'dpdispatcher.openapi.OpenAPI'>, 'PBS': <class 'dpdispatcher.pbs.PBS'>, 'Shell': <class 'dpdispatcher.shell.Shell'>, 'Slurm': <class 'dpdispatcher.slurm.Slurm'>, 'SlurmJobArray': <class 'dpdispatcher.slurm.SlurmJobArray'>, 'Torque': <class 'dpdispatcher.pbs.Torque'>, 'bohrium': <class 'dpdispatcher.dp_cloud_server.Bohrium'>, 'distributedshell': <class 'dpdispatcher.distributed_shell.DistributedShell'>, 'dpcloudserver': <class 'dpdispatcher.dp_cloud_server.Bohrium'>, 'fugaku': <class 'dpdispatcher.fugaku.Fugaku'>, 'lebesgue': <class 'dpdispatcher.dp_cloud_server.Bohrium'>, 'lsf': <class 'dpdispatcher.lsf.LSF'>, 'openapi': <class 'dpdispatcher.openapi.OpenAPI'>, 'pbs': <class 'dpdispatcher.pbs.PBS'>, 'shell': <class 'dpdispatcher.shell.Shell'>, 'slurm': <class 'dpdispatcher.slurm.Slurm'>, 'slurmjobarray': <class 'dpdispatcher.slurm.SlurmJobArray'>, 'torque': <class 'dpdispatcher.pbs.Torque'>}

class dpdispatcher.OpenAPI(*args, **kwargs)[source]

Bases: Machine

Methods

`do_submit`(job)	Submit a single job, assuming that no job is running there.
`kill`(job)	Kill the job.
`resources_arginfo`()	Generate the resources arginfo.
`resources_subfields`()	Generate the resources subfields.

arginfo
bind_context
check_finish_tag
check_if_recover
check_status
default_resources
deserialize
gen_command_env_cuda_devices
gen_local_script
gen_script
gen_script_command
gen_script_custom_flags_lines
gen_script_end
gen_script_env
gen_script_header
gen_script_wait
load_from_dict
load_from_json
map_dp_job_state
serialize
sub_script_cmd
sub_script_head

check_finish_tag(job)[source]

check_if_recover(submission)[source]

check_status(job)[source]

do_submit(job)[source]: Submit a single job, assuming that no job is running there.

gen_local_script(job)[source]

gen_script(job)[source]

gen_script_header(job)[source]

static map_dp_job_state(status)[source]

class dpdispatcher.OpenAPIContext(*args, **kwargs)[source]

Bases: BaseContext

Methods

`machine_arginfo`()	Generate the machine arginfo.
`machine_subfields`()	Generate the machine subfields.

bind_submission
check_file_exists
check_finish
check_home_file_exits
clean
download
load_from_dict
read_file
read_home_file
upload
upload_job
write_file
write_home_file
write_local_file

bind_submission(submission)[source]

check_file_exists(fname)[source]

check_home_file_exits(fname)[source]

clean()[source]

download(submission)[source]

classmethod load_from_dict(context_dict)[source]

read_file(fname)[source]

read_home_file(fname)[source]

upload(submission)[source]

upload_job(job, common_files=None)[source]

write_file(fname, write_str)[source]

write_home_file(fname, write_str)[source]

write_local_file(fname, write_str)[source]

class dpdispatcher.PBS(*args, **kwargs)[source]

Bases: Machine

Methods

`do_submit`(job)	Submit a single job, assuming that no job is running there.
`kill`(job)	Kill the job.
`resources_arginfo`()	Generate the resources arginfo.
`resources_subfields`()	Generate the resources subfields.

arginfo
bind_context
check_finish_tag
check_if_recover
check_status
default_resources
deserialize
gen_command_env_cuda_devices
gen_script
gen_script_command
gen_script_custom_flags_lines
gen_script_end
gen_script_env
gen_script_header
gen_script_wait
load_from_dict
load_from_json
serialize
sub_script_cmd
sub_script_head

check_finish_tag(job)[source]

check_status(job)[source]

default_resources(resources)[source]

do_submit(job)[source]: Submit a single job, assuming that no job is running there.

gen_script(job)[source]

gen_script_header(job)[source]

kill(job)[source]

Kill the job.

Parameters:

jobJob: job

class dpdispatcher.Resources(number_node, cpu_per_node, gpu_per_node, queue_name, group_size, *, custom_flags=[], strategy={'if_cuda_multi_devices': False, 'ratio_unfinished': 0.0}, para_deg=1, module_unload_list=[], module_purge=False, module_list=[], source_list=[], envs={}, prepend_script=[], append_script=[], wait_time=0, **kwargs)[source]

Bases: object

Resources is used to describe the machine resources we need to do calculations.

Parameters:

number_nodeint

The number of node need for each job.

cpu_per_nodeint

cpu numbers of each node.

gpu_per_nodeint

gpu numbers of each node.

queue_namestr

The queue name of batch job scheduler system.

group_sizeint

The number of tasks in a job.

custom_flagslist of Str

The extra lines pass to job submitting script header

strategydict

strategies we use to generation job submitting scripts. if_cuda_multi_devices : bool

If there are multiple nvidia GPUS on the node, and we want to assign the tasks to different GPUS. If true, dpdispatcher will manually export environment variable CUDA_VISIBLE_DEVICES to different task. Usually, this option will be used with Task.task_need_resources variable simultaneously.

ratio_unfinishedfloat: The ratio of task that can be unfinished.

para_degint

Decide how many tasks will be run in parallel. Usually run with strategy[‘if_cuda_multi_devices’]

source_listlist of Path

The env file to be sourced before the command execution.

wait_timeint

The waitting time in second after a single task submitted. Default: 0.

Methods

arginfo
deserialize
load_from_dict
load_from_json
serialize

static arginfo(detail_kwargs=True)[source]

classmethod deserialize(resources_dict)[source]

classmethod load_from_dict(resources_dict)[source]

classmethod load_from_json(json_file)[source]

serialize()[source]

class dpdispatcher.SSHContext(*args, **kwargs)[source]

Bases: BaseContext

Attributes:

sftp
ssh

Methods

`block_checkcall`(cmd[, asynchronously, ...])	Run command with arguments.
`machine_arginfo`()	Generate the machine arginfo.
`machine_subfields`()	Generate the machine subfields.

bind_submission
block_call
call
check_file_exists
check_finish
clean
close
download
get_job_root
get_return
load_from_dict
read_file
upload
write_file

bind_submission(submission)[source]

block_call(cmd)[source]

block_checkcall(cmd, asynchronously=False, stderr_whitelist=None)[source]

Run command with arguments. Wait for command to complete. If the return code was zero then return, otherwise raise RuntimeError.

Parameters:

cmdstr: The command to run.
asynchronouslybool, optional, default=False: Run command asynchronously. If True, nohup will be used to run the command.
stderr_whitelistlist of str, optional, default=None: If not None, the stderr will be checked against the whitelist. If the stderr contains any of the strings in the whitelist, the command will be considered successful.

call(cmd)[source]

check_file_exists(fname)[source]

check_finish(cmd_pipes)[source]

clean()[source]

close()[source]

download(submission, check_exists=False, mark_failure=True, back_error=False)[source]

get_job_root()[source]

get_return(cmd_pipes)[source]

classmethod load_from_dict(context_dict)[source]

classmethod machine_subfields() → List[Argument][source]

Generate the machine subfields.

Returns:

list[Argument]: machine subfields

read_file(fname)[source]

property sftp

property ssh

upload(submission, dereference=True)[source]

write_file(fname, write_str)[source]

class dpdispatcher.Shell(*args, **kwargs)[source]

Bases: Machine

Methods

`do_submit`(job)	Submit a single job, assuming that no job is running there.
`kill`(job)	Kill the job.
`resources_arginfo`()	Generate the resources arginfo.
`resources_subfields`()	Generate the resources subfields.

arginfo
bind_context
check_finish_tag
check_if_recover
check_status
default_resources
deserialize
gen_command_env_cuda_devices
gen_script
gen_script_command
gen_script_custom_flags_lines
gen_script_end
gen_script_env
gen_script_header
gen_script_wait
load_from_dict
load_from_json
serialize
sub_script_cmd
sub_script_head

check_finish_tag(job)[source]

check_status(job)[source]

default_resources(resources)[source]

do_submit(job)[source]: Submit a single job, assuming that no job is running there.

gen_script(job)[source]

gen_script_header(job)[source]

kill(job)[source]

Kill the job.

Parameters:

jobJob: job

class dpdispatcher.Slurm(*args, **kwargs)[source]

Bases: Machine

Methods

`kill`(job)	Kill the job.
`resources_arginfo`()	Generate the resources arginfo.
`resources_subfields`()	Generate the resources subfields.

arginfo
bind_context
check_finish_tag
check_if_recover
check_status
default_resources
deserialize
do_submit
gen_command_env_cuda_devices
gen_script
gen_script_command
gen_script_custom_flags_lines
gen_script_end
gen_script_env
gen_script_header
gen_script_wait
load_from_dict
load_from_json
serialize
sub_script_cmd
sub_script_head

check_finish_tag(job)[source]

check_status(**kwargs)

default_resources(resources)[source]

do_submit(**kwargs): Submit a single job, assuming that no job is running there.

gen_script(job)[source]

gen_script_header(job)[source]

kill(job)[source]

Kill the job.

Parameters:

jobJob: job

classmethod resources_subfields() → List[Argument][source]

Generate the resources subfields.

Returns:

list[Argument]: resources subfields

class dpdispatcher.Submission(work_base, machine=None, resources=None, forward_common_files=[], backward_common_files=[], *, task_list=[])[source]

Bases: object

A submission represents a collection of tasks. These tasks usually locate at a common directory. And these Tasks may share common files to be uploaded and downloaded.

Parameters:

work_basePath: the base directory of the local tasks. It is usually the dir name of project .
machineMachine: machine class object (for example, PBS, Slurm, Shell) to execute the jobs. The machine can still be bound after the instantiation with the bind_submission method.
resourcesResources: the machine resources (cpu or gpu) used to generate the slurm/pbs script
forward_common_fileslist: the common files to be uploaded to other computers before the jobs begin
backward_common_fileslist: the common files to be downloaded from other computers after the jobs finish
task_listlist of Task: a list of tasks to be run.

Methods

`async_run_submission`(**kwargs)	Async interface of run_submission.
`bind_machine`(machine)	Bind this submission to a machine.
`check_all_finished`()	Check whether all the jobs in the submission.
`check_ratio_unfinished`(ratio_unfinished)	Calculate the ratio of unfinished tasks in the submission.
`deserialize`(submission_dict[, machine])	Convert the submission_dict to a Submission class object.
`generate_jobs`()	After tasks register to the self.belonging_tasks, This method generate the jobs and add these jobs to self.belonging_jobs.
`handle_unexpected_submission_state`()	Handle unexpected job state of the submission.
`run_submission`(*[, dry_run, exit_on_submit, ...])	Main method to execute the submission.
`serialize`([if_static])	Convert the Submission class instance to a dictionary.
`update_submission_state`()	Check whether all the jobs in the submission.

clean_jobs
download_jobs
get_hash
register_task
register_task_list
remove_unfinished_tasks
submission_from_json
submission_to_json
try_download_result
try_recover_from_json
upload_jobs

async async_run_submission(**kwargs)[source]

Async interface of run_submission.

Examples

>>> import asyncio
>>> from dpdispacher import Machine, Resource, Submission
>>> async def run_jobs():
...     backgroud_task = set()
...     # task1
...     task1 = Task(...)
...     submission1 = Submission(..., task_list=[task1])
...     background_task = asyncio.create_task(
...         submission1.async_run_submission(check_interval=2, clean=False)
...     )
...     # task2
...     task2 = Task(...)
...     submission2 = Submission(..., task_list=[task1])
...     background_task = asyncio.create_task(
...         submission2.async_run_submission(check_interval=2, clean=False)
...     )
...     background_tasks.add(background_task)
...     result = await asyncio.gather(*background_tasks)
...     return result
>>> run_jobs()

May raise Error if pass clean=True explicitly when submit to pbs or slurm.

bind_machine(machine)[source]

Bind this submission to a machine. update the machine’s context remote_root and local_root.

Parameters:

machineMachine: the machine to bind with

check_all_finished()[source]

Check whether all the jobs in the submission.

Notes

This method will not handle unexpected job state in the submission.

check_ratio_unfinished(ratio_unfinished: float) → bool[source]

Calculate the ratio of unfinished tasks in the submission.

Parameters:

ratio_unfinishedfloat: the ratio of unfinished tasks in the submission

Returns:

bool: whether the ratio of unfinished tasks in the submission is larger than ratio_unfinished

clean_jobs()[source]

classmethod deserialize(submission_dict, machine=None)[source]

Convert the submission_dict to a Submission class object.

Parameters:

submission_dictdict: path-like, the base directory of the local tasks
machineMachine: Machine class Object to execute the jobs

Returns:

submissionSubmission: the Submission class instance converted from the submission_dict

download_jobs()[source]

generate_jobs()[source]: After tasks register to the self.belonging_tasks, This method generate the jobs and add these jobs to self.belonging_jobs. The jobs are generated by the tasks randomly, and there are self.resources.group_size tasks in a task. Why we randomly shuffle the tasks is under the consideration of load balance. The random seed is a constant (to be concrete, 42). And this insures that the jobs are equal when we re-run the program.

get_hash()[source]

handle_unexpected_submission_state()[source]: Handle unexpected job state of the submission. If the job state is unsubmitted, submit the job. If the job state is terminated (killed unexpectly), resubmit the job. If the job state is unknown, raise an error.

register_task(task)[source]

register_task_list(task_list)[source]

remove_unfinished_tasks()[source]

run_submission(*, dry_run=False, exit_on_submit=False, clean=True, check_interval=30)[source]: Main method to execute the submission. First, check whether old Submission exists on the remote machine, and try to recover from it. Second, upload the local files to the remote machine where the tasks to be executed. Third, run the submission defined previously. Forth, wait until the tasks in the submission finished and download the result file to local directory. If dry_run is True, submission will be uploaded but not be executed and exit. If exit_on_submit is True, submission will exit.

serialize(if_static=False)[source]

Convert the Submission class instance to a dictionary.

Parameters:

if_staticbool: whether dump the job runtime infomation (like job_id, job_state, fail_count) to the dictionary.

Returns:

submission_dictdict: the dictionary converted from the Submission class instance

classmethod submission_from_json(json_file_name='submission.json')[source]

submission_to_json()[source]

try_download_result()[source]

try_recover_from_json()[source]

update_submission_state()[source]

Check whether all the jobs in the submission.

Notes

this method will not handle unexpected (like resubmit terminated) job state in the submission.

upload_jobs()[source]

class dpdispatcher.Task(command, task_work_path, forward_files=[], backward_files=[], outlog='log', errlog='err')[source]

Bases: object

A task is a sequential command to be executed, as well as the files it depends on to transmit forward and backward.

Parameters:

commandStr: the command to be executed.
task_work_pathPath: the directory of each file where the files are dependent on.
forward_fileslist of Path: the files to be transmitted to remote machine before the command execute.
backward_fileslist of Path: the files to be transmitted from remote machine after the comand finished.
outlogStr: the filename to which command redirect stdout
errlogStr: the filename to which command redirect stderr

Methods

`deserialize`(task_dict)	Convert the task_dict to a Task class object.
`get_task_state`(context)	Get the task state by checking the tag file.

arginfo
get_hash
load_from_dict
load_from_json
serialize

static arginfo()[source]

classmethod deserialize(task_dict)[source]

Convert the task_dict to a Task class object.

Parameters:

task_dictdict: the dictionary which contains the task information

Returns:

taskTask: the Task class instance converted from the task_dict

get_hash()[source]

get_task_state(context)[source]

Get the task state by checking the tag file.

Parameters:

contextContext: the context of the task

classmethod load_from_dict(task_dict: dict) → Task[source]

classmethod load_from_json(json_file)[source]

serialize()[source]

class dpdispatcher.Torque(*args, **kwargs)[source]

Bases: PBS

Methods

`do_submit`(job)	Submit a single job, assuming that no job is running there.
`kill`(job)	Kill the job.
`resources_arginfo`()	Generate the resources arginfo.
`resources_subfields`()	Generate the resources subfields.

arginfo
bind_context
check_finish_tag
check_if_recover
check_status
default_resources
deserialize
gen_command_env_cuda_devices
gen_script
gen_script_command
gen_script_custom_flags_lines
gen_script_end
gen_script_env
gen_script_header
gen_script_wait
load_from_dict
load_from_json
serialize
sub_script_cmd
sub_script_head

check_status(job)[source]

gen_script_header(job)[source]

dpdispatcher.info()[source]: Show basic information about dpdispatcher, its location and version.

Subpackages

dpdispatcher.dpcloudserver package

Submodules

dpdispatcher.JobStatus module

class dpdispatcher.JobStatus.JobStatus(value)[source]

Bases: IntEnum

An enumeration.

completing = 6

finished = 5

running = 3

terminated = 4

unknown = 100

unsubmitted = 1

waiting = 2

dpdispatcher.arginfo module

dpdispatcher.base_context module

class dpdispatcher.base_context.BaseContext(*args, **kwargs)[source]

Bases: object

Methods

`machine_arginfo`()	Generate the machine arginfo.
`machine_subfields`()	Generate the machine subfields.

bind_submission
check_finish
clean
download
load_from_dict
read_file
upload
write_file

alias: Tuple[str, ...] = ()

bind_submission(submission)[source]

check_finish(proc)[source]

abstract clean()[source]

abstract download(submission, check_exists=False, mark_failure=True, back_error=False)[source]

classmethod load_from_dict(context_dict)[source]

classmethod machine_arginfo() → Argument[source]

Generate the machine arginfo.

Returns:

Argument: machine arginfo

classmethod machine_subfields() → List[Argument][source]

Generate the machine subfields.

Returns:

list[Argument]: machine subfields

options = {'BohriumContext', 'HDFSContext', 'LazyLocalContext', 'LocalContext', 'OpenAPIContext', 'SSHContext'}

abstract read_file(fname)[source]

subclasses_dict = {'Bohrium': <class 'dpdispatcher.dp_cloud_server_context.BohriumContext'>, 'BohriumContext': <class 'dpdispatcher.dp_cloud_server_context.BohriumContext'>, 'DpCloudServer': <class 'dpdispatcher.dp_cloud_server_context.BohriumContext'>, 'DpCloudServerContext': <class 'dpdispatcher.dp_cloud_server_context.BohriumContext'>, 'HDFS': <class 'dpdispatcher.hdfs_context.HDFSContext'>, 'HDFSContext': <class 'dpdispatcher.hdfs_context.HDFSContext'>, 'LazyLocal': <class 'dpdispatcher.lazy_local_context.LazyLocalContext'>, 'LazyLocalContext': <class 'dpdispatcher.lazy_local_context.LazyLocalContext'>, 'Lebesgue': <class 'dpdispatcher.dp_cloud_server_context.BohriumContext'>, 'LebesgueContext': <class 'dpdispatcher.dp_cloud_server_context.BohriumContext'>, 'Local': <class 'dpdispatcher.local_context.LocalContext'>, 'LocalContext': <class 'dpdispatcher.local_context.LocalContext'>, 'OpenAPI': <class 'dpdispatcher.openapi_context.OpenAPIContext'>, 'OpenAPIContext': <class 'dpdispatcher.openapi_context.OpenAPIContext'>, 'SSH': <class 'dpdispatcher.ssh_context.SSHContext'>, 'SSHContext': <class 'dpdispatcher.ssh_context.SSHContext'>, 'bohrium': <class 'dpdispatcher.dp_cloud_server_context.BohriumContext'>, 'bohriumcontext': <class 'dpdispatcher.dp_cloud_server_context.BohriumContext'>, 'dpcloudserver': <class 'dpdispatcher.dp_cloud_server_context.BohriumContext'>, 'dpcloudservercontext': <class 'dpdispatcher.dp_cloud_server_context.BohriumContext'>, 'hdfs': <class 'dpdispatcher.hdfs_context.HDFSContext'>, 'hdfscontext': <class 'dpdispatcher.hdfs_context.HDFSContext'>, 'lazylocal': <class 'dpdispatcher.lazy_local_context.LazyLocalContext'>, 'lazylocalcontext': <class 'dpdispatcher.lazy_local_context.LazyLocalContext'>, 'lebesgue': <class 'dpdispatcher.dp_cloud_server_context.BohriumContext'>, 'lebesguecontext': <class 'dpdispatcher.dp_cloud_server_context.BohriumContext'>, 'local': <class 'dpdispatcher.local_context.LocalContext'>, 'localcontext': <class 'dpdispatcher.local_context.LocalContext'>, 'openapi': <class 'dpdispatcher.openapi_context.OpenAPIContext'>, 'openapicontext': <class 'dpdispatcher.openapi_context.OpenAPIContext'>, 'ssh': <class 'dpdispatcher.ssh_context.SSHContext'>, 'sshcontext': <class 'dpdispatcher.ssh_context.SSHContext'>}

abstract upload(submission)[source]

abstract write_file(fname, write_str)[source]

dpdispatcher.distributed_shell module

class dpdispatcher.distributed_shell.DistributedShell(*args, **kwargs)[source]

Bases: Machine

Methods

`do_submit`(job)	Submit th job to yarn using distributed shell.
`kill`(job)	Kill the job.
`resources_arginfo`()	Generate the resources arginfo.
`resources_subfields`()	Generate the resources subfields.

arginfo
bind_context
check_finish_tag
check_if_recover
check_status
default_resources
deserialize
gen_command_env_cuda_devices
gen_script
gen_script_command
gen_script_custom_flags_lines
gen_script_end
gen_script_env
gen_script_header
gen_script_wait
load_from_dict
load_from_json
serialize
sub_script_cmd
sub_script_head

check_finish_tag(job)[source]

check_status(job)[source]

do_submit(job)[source]

Submit th job to yarn using distributed shell.

Parameters:

jobJob class instance: job to be submitted

Returns:

job_id: string: submit process id

gen_script_end(job)[source]

gen_script_env(job)[source]

gen_script_header(job)[source]

dpdispatcher.dp_cloud_server module

class dpdispatcher.dp_cloud_server.Bohrium(*args, **kwargs)[source]

Bases: Machine

Methods

`do_submit`(job)	Submit a single job, assuming that no job is running there.
`kill`(job)	Kill the job.
`resources_arginfo`()	Generate the resources arginfo.
`resources_subfields`()	Generate the resources subfields.

arginfo
bind_context
check_finish_tag
check_if_recover
check_status
default_resources
deserialize
gen_command_env_cuda_devices
gen_local_script
gen_script
gen_script_command
gen_script_custom_flags_lines
gen_script_end
gen_script_env
gen_script_header
gen_script_wait
load_from_dict
load_from_json
map_dp_job_state
serialize
sub_script_cmd
sub_script_head

alias: Tuple[str, ...] = ('Lebesgue', 'DpCloudServer')

check_finish_tag(job)[source]

check_if_recover(submission)[source]

check_status(job)[source]

do_submit(job)[source]: Submit a single job, assuming that no job is running there.

gen_local_script(job)[source]

gen_script(job)[source]

gen_script_header(job)[source]

static map_dp_job_state(status)[source]

dpdispatcher.dp_cloud_server.DpCloudServer: alias of Bohrium

dpdispatcher.dp_cloud_server.Lebesgue: alias of Bohrium

dpdispatcher.dp_cloud_server_context module

class dpdispatcher.dp_cloud_server_context.BohriumContext(*args, **kwargs)[source]

Bases: BaseContext

Methods

`machine_arginfo`()	Generate the machine arginfo.
`machine_subfields`()	Generate the machine subfields.

bind_submission
check_file_exists
check_finish
check_home_file_exits
clean
download
load_from_dict
read_file
read_home_file
upload
upload_job
write_file
write_home_file
write_local_file

alias: Tuple[str, ...] = ('DpCloudServerContext', 'LebesgueContext')

bind_submission(submission)[source]

check_file_exists(fname)[source]

check_home_file_exits(fname)[source]

clean()[source]

download(submission)[source]

classmethod load_from_dict(context_dict)[source]

classmethod machine_subfields() → List[Argument][source]

Generate the machine subfields.

Returns:

list[Argument]: machine subfields

read_file(fname)[source]

read_home_file(fname)[source]

upload(submission)[source]

upload_job(job, common_files=None)[source]

write_file(fname, write_str)[source]

write_home_file(fname, write_str)[source]

write_local_file(fname, write_str)[source]

dpdispatcher.dp_cloud_server_context.DpCloudServerContext: alias of BohriumContext

dpdispatcher.dp_cloud_server_context.LebesgueContext: alias of BohriumContext

dpdispatcher.dpdisp module

dpdispatcher.dpdisp.main()[source]

dpdispatcher.fugaku module

class dpdispatcher.fugaku.Fugaku(*args, **kwargs)[source]

Bases: Machine

Methods

`do_submit`(job)	Submit a single job, assuming that no job is running there.
`kill`(job)	Kill the job.
`resources_arginfo`()	Generate the resources arginfo.
`resources_subfields`()	Generate the resources subfields.

arginfo
bind_context
check_finish_tag
check_if_recover
check_status
default_resources
deserialize
gen_command_env_cuda_devices
gen_script
gen_script_command
gen_script_custom_flags_lines
gen_script_end
gen_script_env
gen_script_header
gen_script_wait
load_from_dict
load_from_json
serialize
sub_script_cmd
sub_script_head

check_finish_tag(job)[source]

check_status(job)[source]

default_resources(resources)[source]

do_submit(job)[source]: Submit a single job, assuming that no job is running there.

gen_script(job)[source]

gen_script_header(job)[source]

dpdispatcher.hdfs_cli module

class dpdispatcher.hdfs_cli.HDFS[source]

Bases: object

Fundamental class for HDFS basic manipulation.

Methods

`copy_from_local`(local_path, to_uri)	Returns: True on success Raises: on unexpected error.
`exists`(uri)	Check existence of hdfs uri Returns: True on exists Raises: RuntimeError.
`mkdir`(uri)	Make new hdfs directory Returns: True on success Raises: RuntimeError.
`remove`(uri)	Check existence of hdfs uri Returns: True on exists Raises: RuntimeError.

copy_to_local
move
read_hdfs_file

static copy_from_local(local_path, to_uri)[source]: Returns: True on success Raises: on unexpected error.

static copy_to_local(from_uri, local_path)[source]

static exists(uri)[source]: Check existence of hdfs uri Returns: True on exists Raises: RuntimeError.

static mkdir(uri)[source]: Make new hdfs directory Returns: True on success Raises: RuntimeError.

static move(from_uri, to_uri)[source]

static read_hdfs_file(uri)[source]

static remove(uri)[source]: Check existence of hdfs uri Returns: True on exists Raises: RuntimeError.

dpdispatcher.hdfs_context module

class dpdispatcher.hdfs_context.HDFSContext(*args, **kwargs)[source]

Bases: BaseContext

Methods

`check_file_exists`(fname)	Check whether the given file exists, often used in checking whether the belonging job has finished.
`download`(submission[, check_exists, ...])	Download backward files from HDFS root dir.
`machine_arginfo`()	Generate the machine arginfo.
`machine_subfields`()	Generate the machine subfields.
`upload`(submission[, dereference])	Upload forward files and forward command files to HDFS root dir.

bind_submission
check_finish
clean
get_job_root
load_from_dict
read_file
write_file

bind_submission(submission)[source]

check_file_exists(fname)[source]

Check whether the given file exists, often used in checking whether the belonging job has finished.

Parameters:

fnamestring: file name to be checked

Returns:

status: boolean

clean()[source]

download(submission, check_exists=False, mark_failure=True, back_error=False)[source]

Download backward files from HDFS root dir.

Parameters:

submissionSubmission class instance: represents a collection of tasks, such as backward file names
check_existsbool: whether to check if the file exists
mark_failurebool: whether to mark the task as failed if the file does not exist
back_errorbool: whether to download error files

Returns:

none

get_job_root()[source]

classmethod load_from_dict(context_dict)[source]

read_file(fname)[source]

upload(submission, dereference=True)[source]

Upload forward files and forward command files to HDFS root dir.

Parameters:

submissionSubmission class instance: represents a collection of tasks, such as forward file names
dereferencebool: whether to dereference symbolic links

Returns:

none

write_file(fname, write_str)[source]

dpdispatcher.lazy_local_context module

class dpdispatcher.lazy_local_context.LazyLocalContext(*args, **kwargs)[source]

Bases: BaseContext

Run jobs in the local server and local directory.

Parameters:

local_rootstr: The local directory to store the jobs.
remote_rootstr, optional: The argument takes no effect.
remote_profiledict, optional: The remote profile. The default is {}.
*args: The arguments.
**kwargs: The keyword arguments.

Methods

`machine_arginfo`()	Generate the machine arginfo.
`machine_subfields`()	Generate the machine subfields.

bind_submission
block_call
block_checkcall
call
check_file_exists
check_finish
clean
download
get_job_root
get_return
load_from_dict
read_file
upload
write_file

bind_submission(submission)[source]

block_call(cmd)[source]

block_checkcall(cmd)[source]

call(cmd)[source]

check_file_exists(fname)[source]

check_finish(proc)[source]

clean()[source]

download(jobs, check_exists=False, mark_failure=True, back_error=False)[source]

get_job_root()[source]

get_return(proc)[source]

classmethod load_from_dict(context_dict)[source]

read_file(fname)[source]

upload(jobs, dereference=True)[source]

write_file(fname, write_str)[source]

class dpdispatcher.lazy_local_context.SPRetObj(ret)[source]

Bases: object

Methods

read
readlines

read()[source]

readlines()[source]

dpdispatcher.local_context module

class dpdispatcher.local_context.LocalContext(*args, **kwargs)[source]

Bases: BaseContext

Run jobs in the local server and remote directory.

Parameters:

local_rootstr: The local directory to store the jobs.
remote_rootstr: The remote directory to store the jobs.
remote_profiledict, optional: The remote profile. The default is {}.
*args: The arguments.
**kwargs: The keyword arguments.

Methods

`machine_arginfo`()	Generate the machine arginfo.
`machine_subfields`()	Generate the machine subfields.

bind_submission
block_call
block_checkcall
call
check_file_exists
check_finish
clean
download
get_job_root
get_return
load_from_dict
read_file
upload
write_file

bind_submission(submission)[source]

block_call(cmd)[source]

block_checkcall(cmd)[source]

call(cmd)[source]

check_file_exists(fname)[source]

check_finish(proc)[source]

clean()[source]

download(submission, check_exists=False, mark_failure=True, back_error=False)[source]

get_job_root()[source]

get_return(proc)[source]

classmethod load_from_dict(context_dict)[source]

read_file(fname)[source]

upload(submission)[source]

write_file(fname, write_str)[source]

class dpdispatcher.local_context.SPRetObj(ret)[source]

Bases: object

Methods

read
readlines

read()[source]

readlines()[source]

dpdispatcher.lsf module

class dpdispatcher.lsf.LSF(*args, **kwargs)[source]

Bases: Machine

LSF batch.

Methods

`default_resources`(resources)
`kill`(job)	Kill the job.
`resources_arginfo`()	Generate the resources arginfo.
`resources_subfields`()	Generate the resources subfields.

arginfo
bind_context
check_finish_tag
check_if_recover
check_status
deserialize
do_submit
gen_command_env_cuda_devices
gen_script
gen_script_command
gen_script_custom_flags_lines
gen_script_end
gen_script_env
gen_script_header
gen_script_wait
load_from_dict
load_from_json
serialize
sub_script_cmd
sub_script_head

check_finish_tag(job)[source]

check_status(**kwargs)

default_resources(resources)[source]

do_submit(**kwargs): Submit a single job, assuming that no job is running there.

gen_script(job)[source]

gen_script_header(job)[source]

kill(job)[source]

Kill the job.

Parameters:

jobJob: job

classmethod resources_subfields() → List[Argument][source]

Generate the resources subfields.

Returns:

list[Argument]: resources subfields

sub_script_cmd(res)[source]

sub_script_head(res)[source]

dpdispatcher.machine module

class dpdispatcher.machine.Machine(*args, **kwargs)[source]

Bases: object

A machine is used to handle the connection with remote machines.

Parameters:

contextSubClass derived from BaseContext: The context is used to mainatin the connection with remote machine.

Methods

`do_submit`(job)	Submit a single job, assuming that no job is running there.
`kill`(job)	Kill the job.
`resources_arginfo`()	Generate the resources arginfo.
`resources_subfields`()	Generate the resources subfields.

arginfo
bind_context
check_finish_tag
check_if_recover
check_status
default_resources
deserialize
gen_command_env_cuda_devices
gen_script
gen_script_command
gen_script_custom_flags_lines
gen_script_end
gen_script_env
gen_script_header
gen_script_wait
load_from_dict
load_from_json
serialize
sub_script_cmd
sub_script_head

alias: Tuple[str, ...] = ()

classmethod arginfo()[source]

bind_context(context)[source]

abstract check_finish_tag(**kwargs)[source]

check_if_recover(submission)[source]

abstract check_status(job)[source]

default_resources(res)[source]

classmethod deserialize(machine_dict)[source]

abstract do_submit(job)[source]: Submit a single job, assuming that no job is running there.

gen_command_env_cuda_devices(resources)[source]

gen_script(job)[source]

gen_script_command(job)[source]

gen_script_custom_flags_lines(job)[source]

gen_script_end(job)[source]

gen_script_env(job)[source]

abstract gen_script_header(job)[source]

gen_script_wait(resources)[source]

kill(job)[source]

Kill the job.

If not implemented, pass and let the user manually kill it.

Parameters:

jobJob: job

classmethod load_from_dict(machine_dict)[source]

classmethod load_from_json(json_path)[source]

options = {'Bohrium', 'DistributedShell', 'Fugaku', 'LSF', 'OpenAPI', 'PBS', 'Shell', 'Slurm', 'SlurmJobArray', 'Torque'}

classmethod resources_arginfo() → Argument[source]

Generate the resources arginfo.

Returns:

Argument: resources arginfo

classmethod resources_subfields() → List[Argument][source]

Generate the resources subfields.

Returns:

list[Argument]: resources subfields

serialize(if_empty_remote_profile=False)[source]

sub_script_cmd(res)[source]

sub_script_head(res)[source]

subclasses_dict = {'Bohrium': <class 'dpdispatcher.dp_cloud_server.Bohrium'>, 'DistributedShell': <class 'dpdispatcher.distributed_shell.DistributedShell'>, 'DpCloudServer': <class 'dpdispatcher.dp_cloud_server.Bohrium'>, 'Fugaku': <class 'dpdispatcher.fugaku.Fugaku'>, 'LSF': <class 'dpdispatcher.lsf.LSF'>, 'Lebesgue': <class 'dpdispatcher.dp_cloud_server.Bohrium'>, 'OpenAPI': <class 'dpdispatcher.openapi.OpenAPI'>, 'PBS': <class 'dpdispatcher.pbs.PBS'>, 'Shell': <class 'dpdispatcher.shell.Shell'>, 'Slurm': <class 'dpdispatcher.slurm.Slurm'>, 'SlurmJobArray': <class 'dpdispatcher.slurm.SlurmJobArray'>, 'Torque': <class 'dpdispatcher.pbs.Torque'>, 'bohrium': <class 'dpdispatcher.dp_cloud_server.Bohrium'>, 'distributedshell': <class 'dpdispatcher.distributed_shell.DistributedShell'>, 'dpcloudserver': <class 'dpdispatcher.dp_cloud_server.Bohrium'>, 'fugaku': <class 'dpdispatcher.fugaku.Fugaku'>, 'lebesgue': <class 'dpdispatcher.dp_cloud_server.Bohrium'>, 'lsf': <class 'dpdispatcher.lsf.LSF'>, 'openapi': <class 'dpdispatcher.openapi.OpenAPI'>, 'pbs': <class 'dpdispatcher.pbs.PBS'>, 'shell': <class 'dpdispatcher.shell.Shell'>, 'slurm': <class 'dpdispatcher.slurm.Slurm'>, 'slurmjobarray': <class 'dpdispatcher.slurm.SlurmJobArray'>, 'torque': <class 'dpdispatcher.pbs.Torque'>}

dpdispatcher.openapi module

class dpdispatcher.openapi.OpenAPI(*args, **kwargs)[source]

Bases: Machine

Methods

`do_submit`(job)	Submit a single job, assuming that no job is running there.
`kill`(job)	Kill the job.
`resources_arginfo`()	Generate the resources arginfo.
`resources_subfields`()	Generate the resources subfields.

arginfo
bind_context
check_finish_tag
check_if_recover
check_status
default_resources
deserialize
gen_command_env_cuda_devices
gen_local_script
gen_script
gen_script_command
gen_script_custom_flags_lines
gen_script_end
gen_script_env
gen_script_header
gen_script_wait
load_from_dict
load_from_json
map_dp_job_state
serialize
sub_script_cmd
sub_script_head

check_finish_tag(job)[source]

check_if_recover(submission)[source]

check_status(job)[source]

do_submit(job)[source]: Submit a single job, assuming that no job is running there.

gen_local_script(job)[source]

gen_script(job)[source]

gen_script_header(job)[source]

static map_dp_job_state(status)[source]

dpdispatcher.openapi_context module

class dpdispatcher.openapi_context.OpenAPIContext(*args, **kwargs)[source]

Bases: BaseContext

Methods

`machine_arginfo`()	Generate the machine arginfo.
`machine_subfields`()	Generate the machine subfields.

bind_submission
check_file_exists
check_finish
check_home_file_exits
clean
download
load_from_dict
read_file
read_home_file
upload
upload_job
write_file
write_home_file
write_local_file

bind_submission(submission)[source]

check_file_exists(fname)[source]

check_home_file_exits(fname)[source]

clean()[source]

download(submission)[source]

classmethod load_from_dict(context_dict)[source]

read_file(fname)[source]

read_home_file(fname)[source]

upload(submission)[source]

upload_job(job, common_files=None)[source]

write_file(fname, write_str)[source]

write_home_file(fname, write_str)[source]

write_local_file(fname, write_str)[source]

dpdispatcher.pbs module

class dpdispatcher.pbs.PBS(*args, **kwargs)[source]

Bases: Machine

Methods

`do_submit`(job)	Submit a single job, assuming that no job is running there.
`kill`(job)	Kill the job.
`resources_arginfo`()	Generate the resources arginfo.
`resources_subfields`()	Generate the resources subfields.

arginfo
bind_context
check_finish_tag
check_if_recover
check_status
default_resources
deserialize
gen_command_env_cuda_devices
gen_script
gen_script_command
gen_script_custom_flags_lines
gen_script_end
gen_script_env
gen_script_header
gen_script_wait
load_from_dict
load_from_json
serialize
sub_script_cmd
sub_script_head

check_finish_tag(job)[source]

check_status(job)[source]

default_resources(resources)[source]

do_submit(job)[source]: Submit a single job, assuming that no job is running there.

gen_script(job)[source]

gen_script_header(job)[source]

kill(job)[source]

Kill the job.

Parameters:

jobJob: job

class dpdispatcher.pbs.Torque(*args, **kwargs)[source]

Bases: PBS

Methods

`do_submit`(job)	Submit a single job, assuming that no job is running there.
`kill`(job)	Kill the job.
`resources_arginfo`()	Generate the resources arginfo.
`resources_subfields`()	Generate the resources subfields.

arginfo
bind_context
check_finish_tag
check_if_recover
check_status
default_resources
deserialize
gen_command_env_cuda_devices
gen_script
gen_script_command
gen_script_custom_flags_lines
gen_script_end
gen_script_env
gen_script_header
gen_script_wait
load_from_dict
load_from_json
serialize
sub_script_cmd
sub_script_head

check_status(job)[source]

gen_script_header(job)[source]

dpdispatcher.shell module

class dpdispatcher.shell.Shell(*args, **kwargs)[source]

Bases: Machine

Methods

`do_submit`(job)	Submit a single job, assuming that no job is running there.
`kill`(job)	Kill the job.
`resources_arginfo`()	Generate the resources arginfo.
`resources_subfields`()	Generate the resources subfields.

arginfo
bind_context
check_finish_tag
check_if_recover
check_status
default_resources
deserialize
gen_command_env_cuda_devices
gen_script
gen_script_command
gen_script_custom_flags_lines
gen_script_end
gen_script_env
gen_script_header
gen_script_wait
load_from_dict
load_from_json
serialize
sub_script_cmd
sub_script_head

check_finish_tag(job)[source]

check_status(job)[source]

default_resources(resources)[source]

do_submit(job)[source]: Submit a single job, assuming that no job is running there.

gen_script(job)[source]

gen_script_header(job)[source]

kill(job)[source]

Kill the job.

Parameters:

jobJob: job

dpdispatcher.slurm module

class dpdispatcher.slurm.Slurm(*args, **kwargs)[source]

Bases: Machine

Methods

`kill`(job)	Kill the job.
`resources_arginfo`()	Generate the resources arginfo.
`resources_subfields`()	Generate the resources subfields.

arginfo
bind_context
check_finish_tag
check_if_recover
check_status
default_resources
deserialize
do_submit
gen_command_env_cuda_devices
gen_script
gen_script_command
gen_script_custom_flags_lines
gen_script_end
gen_script_env
gen_script_header
gen_script_wait
load_from_dict
load_from_json
serialize
sub_script_cmd
sub_script_head

check_finish_tag(job)[source]

check_status(**kwargs)

default_resources(resources)[source]

do_submit(**kwargs): Submit a single job, assuming that no job is running there.

gen_script(job)[source]

gen_script_header(job)[source]

kill(job)[source]

Kill the job.

Parameters:

jobJob: job

classmethod resources_subfields() → List[Argument][source]

Generate the resources subfields.

Returns:

list[Argument]: resources subfields

class dpdispatcher.slurm.SlurmJobArray(*args, **kwargs)[source]

Bases: Slurm

Slurm with job array enabled for multiple tasks in a job.

Methods

`kill`(job)	Kill the job.
`resources_arginfo`()	Generate the resources arginfo.
`resources_subfields`()	Generate the resources subfields.

arginfo
bind_context
check_finish_tag
check_if_recover
check_status
default_resources
deserialize
do_submit
gen_command_env_cuda_devices
gen_script
gen_script_command
gen_script_custom_flags_lines
gen_script_end
gen_script_env
gen_script_header
gen_script_wait
load_from_dict
load_from_json
serialize
sub_script_cmd
sub_script_head

check_finish_tag(job)[source]

check_status(**kwargs)

gen_script_command(job)[source]

gen_script_end(job)[source]

gen_script_header(job)[source]

classmethod resources_subfields() → List[Argument][source]

Generate the resources subfields.

Returns:

list[Argument]: resources subfields

dpdispatcher.ssh_context module

class dpdispatcher.ssh_context.SSHContext(*args, **kwargs)[source]

Bases: BaseContext

Attributes:

sftp
ssh

Methods

`block_checkcall`(cmd[, asynchronously, ...])	Run command with arguments.
`machine_arginfo`()	Generate the machine arginfo.
`machine_subfields`()	Generate the machine subfields.

bind_submission
block_call
call
check_file_exists
check_finish
clean
close
download
get_job_root
get_return
load_from_dict
read_file
upload
write_file

bind_submission(submission)[source]

block_call(cmd)[source]

block_checkcall(cmd, asynchronously=False, stderr_whitelist=None)[source]

Run command with arguments. Wait for command to complete. If the return code was zero then return, otherwise raise RuntimeError.

Parameters:

cmdstr: The command to run.
asynchronouslybool, optional, default=False: Run command asynchronously. If True, nohup will be used to run the command.
stderr_whitelistlist of str, optional, default=None: If not None, the stderr will be checked against the whitelist. If the stderr contains any of the strings in the whitelist, the command will be considered successful.

call(cmd)[source]

check_file_exists(fname)[source]

check_finish(cmd_pipes)[source]

clean()[source]

close()[source]

download(submission, check_exists=False, mark_failure=True, back_error=False)[source]

get_job_root()[source]

get_return(cmd_pipes)[source]

classmethod load_from_dict(context_dict)[source]

classmethod machine_subfields() → List[Argument][source]

Generate the machine subfields.

Returns:

list[Argument]: machine subfields

read_file(fname)[source]

property sftp

property ssh

upload(submission, dereference=True)[source]

write_file(fname, write_str)[source]

class dpdispatcher.ssh_context.SSHSession(hostname, username, password=None, port=22, key_filename=None, passphrase=None, timeout=10, totp_secret=None, tar_compress=True, look_for_keys=True)[source]

Bases: object

Attributes:

remote
rsync_available
sftp: Returns sftp.

Methods

inter_handler(title, instructions, prompt_list)

inter_handler: the callback for paramiko.transport.auth_interactive.

arginfo
close
ensure_alive
exec_command
get
get_ssh_client
put

static arginfo()[source]

close()[source]

ensure_alive(max_check=10, sleep_time=10)[source]

exec_command(**kwargs)

get(from_f, to_f)[source]

get_ssh_client()[source]

inter_handler(title, instructions, prompt_list)[source]

inter_handler: the callback for paramiko.transport.auth_interactive.

The prototype for this function is defined by Paramiko, so all of the arguments need to be there, even though we don’t use ‘title’ or ‘instructions’.

The function is expected to return a tuple of data containing the responses to the provided prompts. Experimental results suggests that there will be one call of this function per prompt, but the mechanism allows for multiple prompts to be sent at once, so it’s best to assume that that can happen.

Since tuples can’t really be built on the fly, the responses are collected in a list which is then converted to a tuple when it’s time to return a value.

Experiments suggest that the username prompt never happens. This makes sense, but the Username prompt is included here just in case.

put(from_f, to_f)[source]

property remote: str

property rsync_available: bool

property sftp: Returns sftp. Open a new one if not existing.

dpdispatcher.submission module

class dpdispatcher.submission.Job(job_task_list, *, resources, machine=None)[source]

Bases: object

Job is generated by Submission automatically. A job ususally has many tasks and it may request computing resources from job scheduler systems. Each Job can generate a script file to be submitted to the job scheduler system or executed locally.

Parameters:

job_task_listlist of Task: the tasks belonging to the job
resourcesResources: the machine resources. Passed from Submission when it constructs jobs.
machinemachine: machine object to execute the job. Passed from Submission when it constructs jobs.

Methods

`deserialize`(job_dict[, machine])	Convert the job_dict to a Submission class object.
`get_job_state`()	Get the jobs.
`serialize`([if_static])	Convert the Task class instance to a dictionary.

get_hash
handle_unexpected_job_state
job_to_json
register_job_id
submit_job

classmethod deserialize(job_dict, machine=None)[source]

Convert the job_dict to a Submission class object.

Parameters:

job_dictdict: the dictionary which contains the job information
machineMachine: the machine object to execute the job

Returns:

submissionJob: the Job class instance converted from the job_dict

get_hash()[source]

get_job_state()[source]

Get the jobs. Usually, this method will query the database of slurm or pbs job scheduler system and get the results.

Notes

this method will not submit or resubmit the jobs if the job is unsubmitted.

handle_unexpected_job_state()[source]

job_to_json()[source]

register_job_id(job_id)[source]

serialize(if_static=False)[source]

Convert the Task class instance to a dictionary.

Parameters:

if_staticbool: whether dump the job runtime infomation (job_id, job_state, fail_count, job_uuid etc.) to the dictionary.

Returns:

task_dictdict: the dictionary converted from the Task class instance

submit_job()[source]

class dpdispatcher.submission.Resources(number_node, cpu_per_node, gpu_per_node, queue_name, group_size, *, custom_flags=[], strategy={'if_cuda_multi_devices': False, 'ratio_unfinished': 0.0}, para_deg=1, module_unload_list=[], module_purge=False, module_list=[], source_list=[], envs={}, prepend_script=[], append_script=[], wait_time=0, **kwargs)[source]

Bases: object

Resources is used to describe the machine resources we need to do calculations.

Parameters:

number_nodeint

The number of node need for each job.

cpu_per_nodeint

cpu numbers of each node.

gpu_per_nodeint

gpu numbers of each node.

queue_namestr

The queue name of batch job scheduler system.

group_sizeint

The number of tasks in a job.

custom_flagslist of Str

The extra lines pass to job submitting script header

strategydict

strategies we use to generation job submitting scripts. if_cuda_multi_devices : bool

If there are multiple nvidia GPUS on the node, and we want to assign the tasks to different GPUS. If true, dpdispatcher will manually export environment variable CUDA_VISIBLE_DEVICES to different task. Usually, this option will be used with Task.task_need_resources variable simultaneously.

ratio_unfinishedfloat: The ratio of task that can be unfinished.

para_degint

Decide how many tasks will be run in parallel. Usually run with strategy[‘if_cuda_multi_devices’]

source_listlist of Path

The env file to be sourced before the command execution.

wait_timeint

The waitting time in second after a single task submitted. Default: 0.

Methods

arginfo
deserialize
load_from_dict
load_from_json
serialize

static arginfo(detail_kwargs=True)[source]

classmethod deserialize(resources_dict)[source]

classmethod load_from_dict(resources_dict)[source]

classmethod load_from_json(json_file)[source]

serialize()[source]

class dpdispatcher.submission.Submission(work_base, machine=None, resources=None, forward_common_files=[], backward_common_files=[], *, task_list=[])[source]

Bases: object

A submission represents a collection of tasks. These tasks usually locate at a common directory. And these Tasks may share common files to be uploaded and downloaded.

Parameters:

work_basePath: the base directory of the local tasks. It is usually the dir name of project .
machineMachine: machine class object (for example, PBS, Slurm, Shell) to execute the jobs. The machine can still be bound after the instantiation with the bind_submission method.
resourcesResources: the machine resources (cpu or gpu) used to generate the slurm/pbs script
forward_common_fileslist: the common files to be uploaded to other computers before the jobs begin
backward_common_fileslist: the common files to be downloaded from other computers after the jobs finish
task_listlist of Task: a list of tasks to be run.

Methods

`async_run_submission`(**kwargs)	Async interface of run_submission.
`bind_machine`(machine)	Bind this submission to a machine.
`check_all_finished`()	Check whether all the jobs in the submission.
`check_ratio_unfinished`(ratio_unfinished)	Calculate the ratio of unfinished tasks in the submission.
`deserialize`(submission_dict[, machine])	Convert the submission_dict to a Submission class object.
`generate_jobs`()	After tasks register to the self.belonging_tasks, This method generate the jobs and add these jobs to self.belonging_jobs.
`handle_unexpected_submission_state`()	Handle unexpected job state of the submission.
`run_submission`(*[, dry_run, exit_on_submit, ...])	Main method to execute the submission.
`serialize`([if_static])	Convert the Submission class instance to a dictionary.
`update_submission_state`()	Check whether all the jobs in the submission.

clean_jobs
download_jobs
get_hash
register_task
register_task_list
remove_unfinished_tasks
submission_from_json
submission_to_json
try_download_result
try_recover_from_json
upload_jobs

async async_run_submission(**kwargs)[source]

Async interface of run_submission.

Examples

>>> import asyncio
>>> from dpdispacher import Machine, Resource, Submission
>>> async def run_jobs():
...     backgroud_task = set()
...     # task1
...     task1 = Task(...)
...     submission1 = Submission(..., task_list=[task1])
...     background_task = asyncio.create_task(
...         submission1.async_run_submission(check_interval=2, clean=False)
...     )
...     # task2
...     task2 = Task(...)
...     submission2 = Submission(..., task_list=[task1])
...     background_task = asyncio.create_task(
...         submission2.async_run_submission(check_interval=2, clean=False)
...     )
...     background_tasks.add(background_task)
...     result = await asyncio.gather(*background_tasks)
...     return result
>>> run_jobs()

May raise Error if pass clean=True explicitly when submit to pbs or slurm.

bind_machine(machine)[source]

Bind this submission to a machine. update the machine’s context remote_root and local_root.

Parameters:

machineMachine: the machine to bind with

check_all_finished()[source]

Check whether all the jobs in the submission.

Notes

This method will not handle unexpected job state in the submission.

check_ratio_unfinished(ratio_unfinished: float) → bool[source]

Calculate the ratio of unfinished tasks in the submission.

Parameters:

ratio_unfinishedfloat: the ratio of unfinished tasks in the submission

Returns:

bool: whether the ratio of unfinished tasks in the submission is larger than ratio_unfinished

clean_jobs()[source]

classmethod deserialize(submission_dict, machine=None)[source]

Convert the submission_dict to a Submission class object.

Parameters:

submission_dictdict: path-like, the base directory of the local tasks
machineMachine: Machine class Object to execute the jobs

Returns:

submissionSubmission: the Submission class instance converted from the submission_dict

download_jobs()[source]

generate_jobs()[source]: After tasks register to the self.belonging_tasks, This method generate the jobs and add these jobs to self.belonging_jobs. The jobs are generated by the tasks randomly, and there are self.resources.group_size tasks in a task. Why we randomly shuffle the tasks is under the consideration of load balance. The random seed is a constant (to be concrete, 42). And this insures that the jobs are equal when we re-run the program.

get_hash()[source]

handle_unexpected_submission_state()[source]: Handle unexpected job state of the submission. If the job state is unsubmitted, submit the job. If the job state is terminated (killed unexpectly), resubmit the job. If the job state is unknown, raise an error.

register_task(task)[source]

register_task_list(task_list)[source]

remove_unfinished_tasks()[source]

run_submission(*, dry_run=False, exit_on_submit=False, clean=True, check_interval=30)[source]: Main method to execute the submission. First, check whether old Submission exists on the remote machine, and try to recover from it. Second, upload the local files to the remote machine where the tasks to be executed. Third, run the submission defined previously. Forth, wait until the tasks in the submission finished and download the result file to local directory. If dry_run is True, submission will be uploaded but not be executed and exit. If exit_on_submit is True, submission will exit.

serialize(if_static=False)[source]

Convert the Submission class instance to a dictionary.

Parameters:

if_staticbool: whether dump the job runtime infomation (like job_id, job_state, fail_count) to the dictionary.

Returns:

submission_dictdict: the dictionary converted from the Submission class instance

classmethod submission_from_json(json_file_name='submission.json')[source]

submission_to_json()[source]

try_download_result()[source]

try_recover_from_json()[source]

update_submission_state()[source]

Check whether all the jobs in the submission.

Notes

this method will not handle unexpected (like resubmit terminated) job state in the submission.

upload_jobs()[source]

class dpdispatcher.submission.Task(command, task_work_path, forward_files=[], backward_files=[], outlog='log', errlog='err')[source]

Bases: object

A task is a sequential command to be executed, as well as the files it depends on to transmit forward and backward.

Parameters:

commandStr: the command to be executed.
task_work_pathPath: the directory of each file where the files are dependent on.
forward_fileslist of Path: the files to be transmitted to remote machine before the command execute.
backward_fileslist of Path: the files to be transmitted from remote machine after the comand finished.
outlogStr: the filename to which command redirect stdout
errlogStr: the filename to which command redirect stderr

Methods

`deserialize`(task_dict)	Convert the task_dict to a Task class object.
`get_task_state`(context)	Get the task state by checking the tag file.

arginfo
get_hash
load_from_dict
load_from_json
serialize

static arginfo()[source]

classmethod deserialize(task_dict)[source]

Convert the task_dict to a Task class object.

Parameters:

task_dictdict: the dictionary which contains the task information

Returns:

taskTask: the Task class instance converted from the task_dict

get_hash()[source]

get_task_state(context)[source]

Get the task state by checking the tag file.

Parameters:

contextContext: the context of the task

classmethod load_from_dict(task_dict: dict) → Task[source]

classmethod load_from_json(json_file)[source]

serialize()[source]

dpdispatcher.utils module

exception dpdispatcher.utils.RetrySignal[source]

Bases: Exception

Exception to give a signal to retry the function.

dpdispatcher.utils.generate_totp(secret: str, period: int = 30, token_length: int = 6) → str[source]

Generate time-based one time password (TOTP) from the secret.

Some HPCs use TOTP for two-factor authentication for safety.

Parameters:

secretstr: The encoded secret provided by the HPC. It’s usually extracted from a 2D code and base32 encoded.
periodint, default=30: Time period where the code is valid in seconds.
token_lengthint, default=6: The token length.

Returns:

token: str: The generated token.

References

https://github.com/lepture/otpauth/blob/49914d83d36dbcd33c9e26f65002b21ce09a6303/otpauth.py#L143-L160

dpdispatcher.utils.get_sha256(filename)[source]

Get sha256 of a file.

Parameters:

filenamestr: The filename.

Returns:

sha256: str: The sha256.

dpdispatcher.utils.hotp(key: str, period: int, token_length: int = 6, digest='sha1')[source]

dpdispatcher.utils.retry(max_retry: int = 3, sleep: ~typing.Union[int, float] = 60, catch_exception: ~typing.Type[BaseException] = <class 'dpdispatcher.utils.RetrySignal'>) → Callable[source]

Retry the function until it succeeds or fails for certain times.

Parameters:

max_retryint, default=3: The maximum retry times. If None, it will retry forever.
sleepint or float, default=60: The sleep time in seconds.
catch_exceptionException, default=Exception: The exception to catch.

Returns:

decorator: Callable: The decorator.

Examples

>>> @retry(max_retry=3, sleep=60, catch_exception=RetrySignal)
... def func():
...     raise RetrySignal("Failed")

dpdispatcher.utils.rsync(from_file: str, to_file: str, port: int = 22, key_filename: Optional[str] = None, timeout: Union[int, float] = 10)[source]

Call rsync to transfer files.

Parameters:

from_filestr: SRC
to_filestr: DEST
portint, default=22: port for ssh
key_filenamestr, optional: identity file name
timeoutint, default=10: timeout for ssh

Raises:

RuntimeError: when return code is not 0

dpdispatcher.utils.run_cmd_with_all_output(cmd, shell=True)[source]