示例#1
0
    def createTask(self):
        """create a task with some defaults"""
        from Ganga.GPI import tasks, CoreTask, CoreTransform, Executable, GenericSplitter
        t = CoreTask()

        trf = CoreTransform()
        trf.application = Executable()
        trf.unit_splitter = GenericSplitter()
        trf.unit_splitter.attribute = "application.args"
        trf.unit_splitter.values = ['arg 1', 'arg 2', 'arg 3']

        t.appendTransform(trf)
        t.float = 20

        return t
示例#2
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    def createTask(self):
        """create a task with some defaults"""
        from Ganga.GPI import tasks, CoreTask, CoreTransform, Executable, GenericSplitter
        t = CoreTask()

        trf = CoreTransform()
        trf.application = Executable()
        trf.unit_splitter = GenericSplitter()
        trf.unit_splitter.attribute = "application.args"
        trf.unit_splitter.values = ['arg 1', 'arg 2', 'arg 3']

        t.appendTransform(trf)
        t.float = 20

        return t
示例#3
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    def test_k_Tasks(self):
        from Ganga.GPI import CoreTask, CoreTransform, Executable, Local, GenericSplitter, LocalFile, GangaDataset, \
            GangaDatasetSplitter, TaskChainInput, File, tasks

        # -- TASKS EXAMPLE START
        # First create the overall Task
        t = CoreTask()

        # Now create the Transform ( -> Job template)
        trf = CoreTransform()
        trf.application = Executable()
        trf.backend = Local()

        # Set the unit splitter (unique to CoreTransform - you may have better ways of creating units in your own
        # plugins). This will create a unit based on the splitting of any given splitter
        # If you put in your own splitter here, use the trf.fields_to_copy string list to tell Tasks which fields of
        # a Job to preserve from the split. Here, Tasks already knows about GenericSplitter and knows that we want to
        # change the 'application' object for each Unit/Master Job
        trf.unit_splitter = GenericSplitter()
        trf.unit_splitter.attribute = "application.args"
        trf.unit_splitter.values = ['arg 1', 'arg 2', 'arg 3']

        # Append the transform
        t.appendTransform(trf)

        # set the maximum number of active jobs to have running (allows for throttling)
        t.float = 100

        # run the Task
        t.run()
        # -- TASKS EXAMPLE STOP

        # -- TASKS OVERVIEW START
        tasks
        tasks(0).overview()
        # -- TASKS OVERVIEW STOP

        t = CoreTask()
        trf = CoreTransform()
        trf.application = Executable()
        trf.backend = Local()
        trf.unit_splitter = GenericSplitter()
        trf.unit_splitter.attribute = "application.args"
        trf.unit_splitter.values = ['arg 1', 'arg 2', 'arg 3']
        t.appendTransform(trf)
        t.float = 100

        # -- TASKS OPTIONS START
        # note - done at the transform level rather than task level as different backends may not need it
        trf.max_active_threads = 10  # optional - specifies the max number of submissions to queue up
        trf.submit_with_threads = True
        # -- TASKS OPTIONS STOP

        # -- TASKS JOBCHAIN START
        # Create a test script
        open('my_script3.sh', 'w').write("""#!/bin/bash
        echo $PATH
        ls -ltr
        more __GangaInputData.txt__
        echo "MY TEST FILE" > output_file.txt
        sleep 120
        """)

        # Create the parent task
        t = CoreTask()

        # Create the first transform
        trf1 = CoreTransform()
        trf1.application = Executable()
        trf1.application.exe = File('my_script3.sh')
        trf1.outputfiles = [LocalFile("*.txt")]
        d = GangaDataset()
        d.files = [LocalFile("*.txt")]
        d.treat_as_inputfiles = True
        trf1.addInputData(d)
        trf1.files_per_unit = 1
        trf1.submit_with_threads = True

        trf1.splitter = GangaDatasetSplitter()
        trf1.splitter.files_per_subjob = 2

        trf1.backend = Local()
        t.appendTransform(trf1)

        # Create the second transform
        trf2 = CoreTransform()
        trf2.application = Executable()
        trf1.application.exe = File('my_script3.sh')
        trf2.submit_with_threads = True

        d = TaskChainInput()
        d.input_trf_id = trf1.getID()
        trf2.addInputData(d)

        trf2.splitter = GangaDatasetSplitter()
        trf2.splitter.files_per_subjob = 2

        trf2.backend = Local()
        t.appendTransform(trf2)

        # Set the Task running
        t.float = 1
        t.run()
示例#4
0
    def test_k_Tasks(self):
        from Ganga.GPI import CoreTask, CoreTransform, Executable, Local, GenericSplitter, LocalFile, GangaDataset, \
            GangaDatasetSplitter, TaskChainInput, File, tasks

        # -- TASKS EXAMPLE START
        # First create the overall Task
        t = CoreTask()

        # Now create the Transform ( -> Job template)
        trf = CoreTransform()
        trf.application = Executable()
        trf.backend = Local()

        # Set the unit splitter (unique to CoreTransform - you may have better ways of creating units in your own
        # plugins). This will create a unit based on the splitting of any given splitter
        # If you put in your own splitter here, use the trf.fields_to_copy string list to tell Tasks which fields of
        # a Job to preserve from the split. Here, Tasks already knows about GenericSplitter and knows that we want to
        # change the 'application' object for each Unit/Master Job
        trf.unit_splitter = GenericSplitter()
        trf.unit_splitter.attribute = "application.args"
        trf.unit_splitter.values = ['arg 1', 'arg 2', 'arg 3']

        # Append the transform
        t.appendTransform(trf)

        # set the maximum number of active jobs to have running (allows for throttling)
        t.float = 100

        # run the Task
        t.run()
        # -- TASKS EXAMPLE STOP

        # -- TASKS OVERVIEW START
        tasks
        tasks(0).overview()
        # -- TASKS OVERVIEW STOP

        t = CoreTask()
        trf = CoreTransform()
        trf.application = Executable()
        trf.backend = Local()
        trf.unit_splitter = GenericSplitter()
        trf.unit_splitter.attribute = "application.args"
        trf.unit_splitter.values = ['arg 1', 'arg 2', 'arg 3']
        t.appendTransform(trf)
        t.float = 100

        # -- TASKS OPTIONS START
        # note - done at the transform level rather than task level as different backends may not need it
        trf.max_active_threads = 10  # optional - specifies the max number of submissions to queue up
        trf.submit_with_threads = True
        # -- TASKS OPTIONS STOP

        # -- TASKS JOBCHAIN START
        # Create a test script
        open('my_script3.sh', 'w').write("""#!/bin/bash
        echo $PATH
        ls -ltr
        more __GangaInputData.txt__
        echo "MY TEST FILE" > output_file.txt
        sleep 120
        """)

        # Create the parent task
        t = CoreTask()

        # Create the first transform
        trf1 = CoreTransform()
        trf1.application = Executable()
        trf1.application.exe = File('my_script3.sh')
        trf1.outputfiles = [LocalFile("*.txt")]
        d = GangaDataset()
        d.files = [LocalFile("*.txt")]
        d.treat_as_inputfiles = True
        trf1.addInputData(d)
        trf1.files_per_unit = 1
        trf1.submit_with_threads = True

        trf1.splitter = GangaDatasetSplitter()
        trf1.splitter.files_per_subjob = 2

        trf1.backend = Local()
        t.appendTransform(trf1)

        # Create the second transform
        trf2 = CoreTransform()
        trf2.application = Executable()
        trf1.application.exe = File('my_script3.sh')
        trf2.submit_with_threads = True

        d = TaskChainInput()
        d.input_trf_id = trf1.getID()
        trf2.addInputData(d)

        trf2.splitter = GangaDatasetSplitter()
        trf2.splitter.files_per_subjob = 2

        trf2.backend = Local()
        t.appendTransform(trf2)

        # Set the Task running
        t.float = 1
        t.run()