parser.add_argument('nbTasks',
metavar='NB_TASK',
type=int,
help='Number of task by group.')
parser.add_argument('nbCmds',
metavar='NB_CMD',
type=int,
help='Number of commands by task')
parser.add_argument('server',
metavar='SERVER',
type=str,
help='Name of the server on which to submit job')
parser.add_argument('--sleep', type=int, default=5, help='Sleep duration in s')
args = parser.parse_args()
# Create graph
runner = "puliclient.contrib.generic.GenericRunner"
name = "Job_Test"
tags = {"prod": "mikros_test", "comment": "JOB TEST", "nbFrames": 1}
puliGraph = Graph(name, poolName='mik', tags=tags, maxRN=5)
print "NB_GROUP = " + str(args.nbGroups)
print "NB_TASK = " + str(args.nbTasks)
print "NB_CMD = " + str(args.nbCmds)
print "SERVER = " + args.server
createFolderNodes(puliGraph, args.nbGroups, args.nbTasks, args.nbCmds,
args.sleep)
puliGraph.submit(args.server, 8004)
if __name__ == "__main__":
#
# Submission script
#
tags = {
"prod": "prod_name",
"shot": "shot_code",
# Add any valuable info relative to the job here: type, step, version, iteration...
}
# First we create a graph
# Added to the graph is a dict of tags that will be used to clarify the job process
graph = Graph('simple job', tags=tags)
# To define a Task, we need 3 arguments :
# - its name
# - a runner is a python class that defines the workflow execution for a given job type.
# Here, we will use MyRunner which has been declared previously
# - an arguments dict
name = "wait 10s"
runner = "example.MyRunner"
arguments = {"wait": 10}
# Then add a new task to the graph
graph.addNewTask(name, runner=runner, arguments=arguments)
# Finally submit the graph to the server
graph.submit("pulitest", 8004)
def compile(job):
g = Graph(job.name, job, username())
from pprint import pprint
pprint(g.toRepresentation())
if __name__ == '__main__':
# In this example we will create 2 tasks to execute custom callables
# Internally we will use a predefined runner: CallableRunner
# The function or class method we are asking to execute must be accessible to the render nodes.
tags = {
"prod": "prod_name",
"shot": "shot_code",
# Add any valuable info relative to the job here: type, step, version, iteration...
}
# First we create a graph
# Added to the graph is a dict of tags that will be used to clarify the job process
graph = Graph('job with callable', tags=tags)
# First task
name = "callable function"
graph.addNewCallable(
myFunction,
"callable function",
user_args=("param1", "param2"),
user_kwargs={"wait": 10},
)
# Second task
name = "callable method"
graph.addNewCallable(
def submit(job, poolName=None, maxRN=-1):
g = Graph(job.name, job, username(), poolName, maxRN)
print g.submit(gethost(), getport())
