def _submit_graph(self, pyfiles, dependencies, nodes):
jobs = []
soma_deps = []
for idx, fname in enumerate(pyfiles):
name = os.path.splitext(os.path.split(fname)[1])[0]
jobs.append(Job(command=[sys.executable, fname], name=name))
for key, values in list(dependencies.items()):
for val in values:
soma_deps.append((jobs[val], jobs[key]))
wf = Workflow(jobs, soma_deps)
logger.info('serializing workflow')
Helper.serialize('workflow', wf)
controller = WorkflowController()
logger.info('submitting workflow')
wf_id = controller.submit_workflow(wf)
Helper.wait_workflow(wf_id, controller)
def _submit_graph(self, pyfiles, dependencies, nodes):
jobs = []
soma_deps = []
for idx, fname in enumerate(pyfiles):
name = os.path.splitext(os.path.split(fname)[1])[0]
jobs.append(Job(command=[sys.executable, fname], name=name))
for key, values in list(dependencies.items()):
for val in values:
soma_deps.append((jobs[val], jobs[key]))
wf = Workflow(jobs, soma_deps)
logger.info('serializing workflow')
Helper.serialize('workflow', wf)
controller = WorkflowController()
logger.info('submitting workflow')
wf_id = controller.submit_workflow(wf)
Helper.wait_workflow(wf_id, controller)
def run(self, **Xy):
'''Run soma-workflow without gui
Example
-------
>>> from sklearn import datasets
>>> from epac.map_reduce.engine import SomaWorkflowEngine
>>> from epac.tests.wfexamples2test import WFExample2
>>> ## Build dataset
>>> ## =============
>>> X, y = datasets.make_classification(n_samples=10,
... n_features=20,
... n_informative=5,
... random_state=1)
>>> Xy = {'X':X, 'y':y}
>>> ## Build epac tree
>>> ## ===============
>>> tree_root_node = WFExample2().get_workflow()
>>> ## Build SomaWorkflowEngine and run function for each node
>>> ## =======================================================
>>> sfw_engine = SomaWorkflowEngine(tree_root=tree_root_node,
... function_name="trasform",
... num_processes=3)
>>> tree_root_node = sfw_engine.run(**Xy)
>>> ## Run reduce process
>>> ## ==================
>>> tree_root_node.reduce()
ResultSet(
[{'key': SelectKBest/SVC(C=1), 'y/test/score_recall_mean/pval': [ 0.], 'y/test/score_recall/pval': [ 0. 0.], 'y/test/score_accuray': 0.8, 'y/test/score_f1/pval': [ 0. 0.], 'y/test/score_precision/pval': [ 0. 0.], 'y/test/score_precision': [ 0.8 0.8], 'y/test/score_recall': [ 0.8 0.8], 'y/test/score_f1': [ 0.8 0.8], 'y/test/score_recall_mean': 0.8, 'y/test/score_accuray/pval': [ 0.]},
{'key': SelectKBest/SVC(C=3), 'y/test/score_recall_mean/pval': [ 0.], 'y/test/score_recall/pval': [ 0. 0.], 'y/test/score_accuray': 0.8, 'y/test/score_f1/pval': [ 0. 0.], 'y/test/score_precision/pval': [ 0. 0.], 'y/test/score_precision': [ 0.8 0.8], 'y/test/score_recall': [ 0.8 0.8], 'y/test/score_f1': [ 0.8 0.8], 'y/test/score_recall_mean': 0.8, 'y/test/score_accuray/pval': [ 0.]}])
'''
try:
from soma.workflow.client import Job, Workflow
from soma.workflow.client import Helper, FileTransfer
from soma.workflow.client import WorkflowController
except ImportError:
errmsg = "No soma-workflow is found. "\
"Please verify your soma-worklow"\
"on your computer (e.g. PYTHONPATH) \n"
sys.stderr.write(errmsg)
sys.stdout.write(errmsg)
raise NoSomaWFError
tmp_work_dir_path = tempfile.mkdtemp()
cur_work_dir = os.getcwd()
os.chdir(tmp_work_dir_path)
ft_working_directory = FileTransfer(is_input=True,
client_path=tmp_work_dir_path,
name="working directory")
## Save the database and tree to working directory
## ===============================================
np.savez(os.path.join(tmp_work_dir_path,
SomaWorkflowEngine.dataset_relative_path), **Xy)
store = StoreFs(dirpath=os.path.join(
tmp_work_dir_path,
SomaWorkflowEngine.tree_root_relative_path))
self.tree_root.save_tree(store=store)
## Subtree job allocation on disk
## ==============================
node_input = NodesInput(self.tree_root.get_key())
split_node_input = SplitNodesInput(self.tree_root,
num_processes=self.num_processes)
nodesinput_list = split_node_input.split(node_input)
keysfile_list = self._save_job_list(tmp_work_dir_path,
nodesinput_list)
## Build soma-workflow
## ===================
jobs = [Job(command=[u"epac_mapper",
u'--datasets', '"%s"' %
(SomaWorkflowEngine.dataset_relative_path),
u'--keysfile', '"%s"' %
(nodesfile)],
referenced_input_files=[ft_working_directory],
referenced_output_files=[ft_working_directory],
name="epac_job_key=%s" % (nodesfile),
working_directory=ft_working_directory)
for nodesfile in keysfile_list]
soma_workflow = Workflow(jobs=jobs)
if not self.resource_id or self.resource_id == "":
self.resource_id = socket.gethostname()
controller = WorkflowController(self.resource_id,
self.login,
self.pw)
## run soma-workflow
## =================
wf_id = controller.submit_workflow(workflow=soma_workflow,
name="epac workflow")
Helper.transfer_input_files(wf_id, controller)
Helper.wait_workflow(wf_id, controller)
Helper.transfer_output_files(wf_id, controller)
if self.remove_finished_wf:
controller.delete_workflow(wf_id)
## read result tree
## ================
self.tree_root = store.load()
os.chdir(cur_work_dir)
if os.path.isdir(tmp_work_dir_path) and self.remove_local_tree:
shutil.rmtree(tmp_work_dir_path)
return self.tree_root
def run(self, **Xy):
'''Run soma-workflow without gui
Example
-------
>>> from sklearn import datasets
>>> from epac.map_reduce.engine import SomaWorkflowEngine
>>> from epac.tests.wfexamples2test import WFExample2
>>> ## Build dataset
>>> ## =============
>>> X, y = datasets.make_classification(n_samples=10,
... n_features=20,
... n_informative=5,
... random_state=1)
>>> Xy = {'X':X, 'y':y}
>>> ## Build epac tree
>>> ## ===============
>>> tree_root_node = WFExample2().get_workflow()
>>> ## Build SomaWorkflowEngine and run function for each node
>>> ## =======================================================
>>> sfw_engine = SomaWorkflowEngine(tree_root=tree_root_node,
... function_name="trasform",
... num_processes=3)
>>> tree_root_node = sfw_engine.run(**Xy)
>>> ## Run reduce process
>>> ## ==================
>>> tree_root_node.reduce()
ResultSet(
[{'key': SelectKBest/SVC(C=1), 'y/test/score_recall_mean/pval': [ 0.], 'y/test/score_recall/pval': [ 0. 0.], 'y/test/score_accuray': 0.8, 'y/test/score_f1/pval': [ 0. 0.], 'y/test/score_precision/pval': [ 0. 0.], 'y/test/score_precision': [ 0.8 0.8], 'y/test/score_recall': [ 0.8 0.8], 'y/test/score_f1': [ 0.8 0.8], 'y/test/score_recall_mean': 0.8, 'y/test/score_accuray/pval': [ 0.]},
{'key': SelectKBest/SVC(C=3), 'y/test/score_recall_mean/pval': [ 0.], 'y/test/score_recall/pval': [ 0. 0.], 'y/test/score_accuray': 0.8, 'y/test/score_f1/pval': [ 0. 0.], 'y/test/score_precision/pval': [ 0. 0.], 'y/test/score_precision': [ 0.8 0.8], 'y/test/score_recall': [ 0.8 0.8], 'y/test/score_f1': [ 0.8 0.8], 'y/test/score_recall_mean': 0.8, 'y/test/score_accuray/pval': [ 0.]}])
'''
try:
from soma.workflow.client import Job, Workflow
from soma.workflow.client import Helper, FileTransfer
from soma.workflow.client import WorkflowController
except ImportError:
errmsg = "No soma-workflow is found. "\
"Please verify your soma-worklow"\
"on your computer (e.g. PYTHONPATH) \n"
sys.stderr.write(errmsg)
sys.stdout.write(errmsg)
raise NoSomaWFError
tmp_work_dir_path = tempfile.mkdtemp()
cur_work_dir = os.getcwd()
os.chdir(tmp_work_dir_path)
ft_working_directory = FileTransfer(is_input=True,
client_path=tmp_work_dir_path,
name="working directory")
## Save the database and tree to working directory
## ===============================================
np.savez(
os.path.join(tmp_work_dir_path,
SomaWorkflowEngine.dataset_relative_path), **Xy)
store = StoreFs(dirpath=os.path.join(
tmp_work_dir_path, SomaWorkflowEngine.tree_root_relative_path))
self.tree_root.save_tree(store=store)
## Subtree job allocation on disk
## ==============================
node_input = NodesInput(self.tree_root.get_key())
split_node_input = SplitNodesInput(self.tree_root,
num_processes=self.num_processes)
nodesinput_list = split_node_input.split(node_input)
keysfile_list = self._save_job_list(tmp_work_dir_path, nodesinput_list)
## Build soma-workflow
## ===================
jobs = [
Job(command=[
u"epac_mapper", u'--datasets',
'"%s"' % (SomaWorkflowEngine.dataset_relative_path),
u'--keysfile',
'"%s"' % (nodesfile)
],
referenced_input_files=[ft_working_directory],
referenced_output_files=[ft_working_directory],
name="epac_job_key=%s" % (nodesfile),
working_directory=ft_working_directory)
for nodesfile in keysfile_list
]
soma_workflow = Workflow(jobs=jobs)
if not self.resource_id or self.resource_id == "":
self.resource_id = socket.gethostname()
controller = WorkflowController(self.resource_id, self.login, self.pw)
## run soma-workflow
## =================
wf_id = controller.submit_workflow(workflow=soma_workflow,
name="epac workflow")
Helper.transfer_input_files(wf_id, controller)
Helper.wait_workflow(wf_id, controller)
Helper.transfer_output_files(wf_id, controller)
controller.delete_workflow(wf_id)
## read result tree
## ================
self.tree_root = store.load()
os.chdir(cur_work_dir)
if os.path.isdir(tmp_work_dir_path):
shutil.rmtree(tmp_work_dir_path)
return self.tree_root
from soma.workflow.client import Job, Workflow, WorkflowController, SharedResourcePath, FileTransfer
# SharedResourcePath creation for the input file.
# The input file is read direclty in the data directory located on the
# the computing resource side.
myfile = SharedResourcePath(relative_path="myfile",
namespace="MyApp",
uuid="my_example_dir")
# FileTransfer creation for the output file.
# That way the output file will not be written in the data directory
# located on the computing resource file system.
copy_of_myfile = FileTransfer(is_input=False,
client_path="/tmp/soma_workflow_examples/copy_of_myfile",
name="copy of my file")
# Job and Workflow creation
copy_job = Job(command=["cp", myfile, copy_of_myfile],
name="copy",
referenced_input_files=[],
referenced_output_files=[copy_of_myfile])
workflow = Workflow(jobs=[copy_job],
dependencies=[])
# workflow submission
controller = WorkflowController("DSV_cluster", login, password)
controller.submit_workflow(workflow=workflow,
name="shared resource path example")
from soma.workflow.client import Helper
# FileTransfer creation for input files
myfile = FileTransfer(is_input=True,
client_path="/tmp/soma_workflow_examples/myfile",
name="myfile")
# FileTransfer creation for output files
copy_of_myfile = FileTransfer(is_input=False,
client_path="/tmp/soma_workflow_examples/copy_of_myfile",
name="copy of my file")
# Job and Workflow
copy_job = Job(command=["cp", myfile, copy_of_myfile],
name="copy",
referenced_input_files=[myfile],
referenced_output_files=[copy_of_myfile])
workflow = Workflow(jobs=[copy_job],
dependencies=[])
# submit the workflow
controller = WorkflowController("jinpeng-Latitude-E6530", "jinpeng")
wf_id = controller.submit_workflow(workflow=workflow,
name="simple transfer")
Helper.transfer_input_files(wf_id, controller)
Helper.wait_workflow(wf_id, controller)
Helper.transfer_output_files(wf_id, controller)
controller.delete_workflow(wf_id)
f.write("Content of my file2 \n")
f.close()
# Creation of the FileTransfer object to transfer the working directory
my_working_directory = FileTransfer(is_input=True,
client_path="/tmp/my_working_directory",
name="working directory")
# Jobs and Workflow
job1 = Job(command=["cp", "myfile1" , "copy_of_myfile1"],
name="job1",
referenced_input_files=[my_working_directory],
referenced_output_files=[my_working_directory],
working_directory=my_working_directory)
job2 = Job(command=["cp", "myfile2" , "copy_of_myfile2"],
name="job2",
referenced_input_files=[my_working_directory],
referenced_output_files=[my_working_directory],
working_directory=my_working_directory)
workflow = Workflow(jobs=[job1, job2],
dependencies=[])
# Submit the workflow
print "password? "
password = getpass.getpass()
controller = WorkflowController("DSV_cluster", login, password)
controller.submit_workflow(workflow=workflow,
name="working directory transfer example")
from soma.workflow.client import Job, Workflow, WorkflowController
job_1 = Job(command=["sleep", "60"], name="job 1")
job_2 = Job(command=["sleep", "60"], name="job 2")
job_3 = Job(command=["sleep", "60"], name="job 3")
job_4 = Job(command=["sleep", "60"], name="job 4")
jobs = [job_1, job_2, job_3, job_4]
dependencies = [(job_1, job_2),
(job_1, job_3),
(job_2, job_4),
(job_3, job_4)]
workflow = Workflow(jobs=jobs,
dependencies=dependencies)
controller = WorkflowController("DSV_cluster", login, password)
controller.submit_workflow(workflow=workflow,
name="simple example")
group_elements = []
first_job = Job(command=["sleep", "10"], name="first job")
last_job = Job(command=["sleep", "10"], name="last job")
jobs.append(first_job)
jobs.append(last_job)
for i in range(0, 30):
job = Job(command=["sleep", "60"], name="job " + repr(i))
jobs.append(job)
dependencies.append((first_job, job))
dependencies.append((job, last_job))
group_elements.append(job)
thirty_jobs_group = Group(elements=group_elements,
name="my 30 jobs")
workflow = Workflow(jobs=jobs,
dependencies= dependencies,
root_group=[first_job, thirty_jobs_group, last_job])
controller = WorkflowController("DSV_cluster", login, password)
controller.submit_workflow(workflow=workflow,
name="Simple workflow with group")