if self.prefix is not None:
r = not import_from(self.prefix)
elif prefix is not None:
r = not import_from(prefix)
else:
r = (not import_from('vistrails.packages.') and
not import_from('userpackages.'))
except Exception, e:
raise self.LoadFailed(self, e, traceback.format_exc())
if r:
raise self.InitializationFailed(self, errors)
self.set_properties()
self.do_load_configuration()
record_usage(loaded_package='%s %s' % (self.identifier, self.version))
def initialize(self):
if not self._loaded:
raise VistrailsInternalError("Called initialize() on non-loaded "
"Package %s" % self.codepath)
self.check_requirements()
try:
name = self.prefix + self.codepath + '.init'
try:
__import__(name, globals(), locals(), [])
except ImportError, e:
# FIXME !!! Want to differentiate between .init not
# existing and an error with an import in the .init
def execute(self, pipeline, **kwargs):
"""execute(pipeline, **kwargs):
kwargs:
controller = fetch('controller', None)
locator = fetch('locator', None)
current_version = fetch('current_version', None)
view = fetch('view', DummyView())
aliases = fetch('aliases', None)
params = fetch('params', None)
extra_info = fetch('extra_info', None)
logger = fetch('logger', DummyLogController)
reason = fetch('reason', None)
actions = fetch('actions', None)
done_summon_hooks = fetch('done_summon_hooks', [])
module_executed_hook = fetch('module_executed_hook', [])
job_monitor = fetch('job_monitor', None)
Executes a pipeline using caching. Caching works by reusing
pipelines directly. This means that there exists one global
pipeline whose parts get executed over and over again.
This function returns a triple of dictionaries (objs, errs, execs).
objs is a mapping from local ids (the ids in the pipeline) to
objects **in the persistent pipeline**. Notice, these are not
the objects inside the passed pipeline, but the objects they
were mapped to in the persistent pipeline.
errs is a dictionary from local ids to error messages of modules
that might have returns errors.
execs is a dictionary from local ids to boolean values indicating
whether they were executed or not.
If modules have no error associated with but were not executed, it
means they were cached."""
# Setup named arguments. We don't use named parameters so
# that positional parameter calls fail earlier
new_kwargs = {}
def fetch(name, default):
new_kwargs[name] = r = kwargs.pop(name, default)
return r
controller = fetch('controller', None)
locator = fetch('locator', None)
current_version = fetch('current_version', None)
view = fetch('view', DummyView())
vistrail_variables = fetch('vistrail_variables', None)
aliases = fetch('aliases', None)
params = fetch('params', None)
extra_info = fetch('extra_info', None)
logger = fetch('logger', DummyLogController)
sinks = fetch('sinks', None)
reason = fetch('reason', None)
actions = fetch('actions', None)
done_summon_hooks = fetch('done_summon_hooks', [])
module_executed_hook = fetch('module_executed_hook', [])
stop_on_error = fetch('stop_on_error', True)
parent_exec = fetch('parent_exec', None)
job_monitor = fetch('job_monitor', None)
if len(kwargs) > 0:
raise VistrailsInternalError('Wrong parameters passed '
'to execute: %s' % kwargs)
self.clean_non_cacheable_modules()
record_usage(execute=True)
# if controller is not None:
# vistrail = controller.vistrail
# (pipeline, module_remap) = \
# core.db.io.expand_workflow(vistrail, pipeline)
# new_kwargs['module_remap'] = module_remap
# else:
# vistrail = None
if controller is not None:
vistrail = controller.vistrail
else:
vistrail = None
time_start = time.time()
logger = logger.start_workflow_execution(parent_exec, vistrail,
pipeline, current_version)
new_kwargs['logger'] = logger
self.annotate_workflow_execution(logger, reason, aliases, params)
res = self.setup_pipeline(pipeline, **new_kwargs)
modules_added = res[2]
conns_added = res[3]
to_delete = res[4]
errors = res[5]
if len(errors) == 0:
res = self.execute_pipeline(pipeline, *(res[:2]), **new_kwargs)
else:
res = (to_delete, res[0], errors, {}, {}, {}, [])
for (i, error) in errors.iteritems():
view.set_module_error(i, error.msg, error.errorTrace)
self.finalize_pipeline(pipeline, *(res[:-1]), **new_kwargs)
time_end = time.time()
result = InstanceObject(objects=res[1],
errors=res[2],
executed=res[3],
suspended=res[4],
parameter_changes=res[6],
modules_added=modules_added,
conns_added=conns_added)
logger.finish_workflow_execution(result.errors,
suspended=result.suspended)
record_usage(time=time_end - time_start,
modules=len(res[1]),
errors=len(res[2]),
executed=len(res[3]),
suspended=len(res[4]))
return result
def execute(self, pipeline, **kwargs):
"""execute(pipeline, **kwargs):
kwargs:
controller = fetch('controller', None)
locator = fetch('locator', None)
current_version = fetch('current_version', None)
view = fetch('view', DummyView())
aliases = fetch('aliases', None)
params = fetch('params', None)
extra_info = fetch('extra_info', None)
logger = fetch('logger', DummyLogController)
reason = fetch('reason', None)
actions = fetch('actions', None)
done_summon_hooks = fetch('done_summon_hooks', [])
module_executed_hook = fetch('module_executed_hook', [])
job_monitor = fetch('job_monitor', None)
Executes a pipeline using caching. Caching works by reusing
pipelines directly. This means that there exists one global
pipeline whose parts get executed over and over again.
This function returns a triple of dictionaries (objs, errs, execs).
objs is a mapping from local ids (the ids in the pipeline) to
objects **in the persistent pipeline**. Notice, these are not
the objects inside the passed pipeline, but the objects they
were mapped to in the persistent pipeline.
errs is a dictionary from local ids to error messages of modules
that might have returns errors.
execs is a dictionary from local ids to boolean values indicating
whether they were executed or not.
If modules have no error associated with but were not executed, it
means they were cached."""
# Setup named arguments. We don't use named parameters so
# that positional parameter calls fail earlier
new_kwargs = {}
def fetch(name, default):
new_kwargs[name] = r = kwargs.pop(name, default)
return r
controller = fetch('controller', None)
locator = fetch('locator', None)
current_version = fetch('current_version', None)
view = fetch('view', DummyView())
vistrail_variables = fetch('vistrail_variables', None)
aliases = fetch('aliases', None)
params = fetch('params', None)
extra_info = fetch('extra_info', None)
logger = fetch('logger', DummyLogController)
sinks = fetch('sinks', None)
reason = fetch('reason', None)
actions = fetch('actions', None)
done_summon_hooks = fetch('done_summon_hooks', [])
module_executed_hook = fetch('module_executed_hook', [])
stop_on_error = fetch('stop_on_error', True)
parent_exec = fetch('parent_exec', None)
job_monitor = fetch('job_monitor', None)
if len(kwargs) > 0:
raise VistrailsInternalError('Wrong parameters passed '
'to execute: %s' % kwargs)
self.clean_non_cacheable_modules()
record_usage(execute=True)
# if controller is not None:
# vistrail = controller.vistrail
# (pipeline, module_remap) = \
# core.db.io.expand_workflow(vistrail, pipeline)
# new_kwargs['module_remap'] = module_remap
# else:
# vistrail = None
if controller is not None:
vistrail = controller.vistrail
else:
vistrail = None
time_start = time.time()
logger = logger.start_workflow_execution(
parent_exec,
vistrail, pipeline, current_version)
new_kwargs['logger'] = logger
self.annotate_workflow_execution(logger, reason, aliases, params)
res = self.setup_pipeline(pipeline, **new_kwargs)
modules_added = res[2]
conns_added = res[3]
to_delete = res[4]
errors = res[5]
if len(errors) == 0:
res = self.execute_pipeline(pipeline, *(res[:2]), **new_kwargs)
else:
res = (to_delete, res[0], errors, {}, {}, {}, [])
for (i, error) in errors.iteritems():
view.set_module_error(i, error.msg, error.errorTrace)
self.finalize_pipeline(pipeline, *(res[:-1]), **new_kwargs)
time_end = time.time()
result = InstanceObject(objects=res[1],
errors=res[2],
executed=res[3],
suspended=res[4],
parameter_changes=res[6],
modules_added=modules_added,
conns_added=conns_added)
logger.finish_workflow_execution(result.errors, suspended=result.suspended)
record_usage(time=time_end - time_start, modules=len(res[1]),
errors=len(res[2]), executed=len(res[3]),
suspended=len(res[4]))
return result
me.module.logging.end_update(me.module, me)
logging_obj.signalError(me.module, me)
abort = abort or me.abort
except ModuleError, me:
me.module.logging.end_update(me.module, me, me.errorTrace)
logging_obj.signalError(me.module, me)
abort = me.abort
except ModuleBreakpoint, mb:
mb.module.logging.end_update(mb.module)
logging_obj.signalError(mb.module, mb)
abort = True
if stop_on_error or abort:
break
if Generator.generators:
record_usage(generators=len(Generator.generators))
# execute all generators until inputs are exhausted
# this makes sure branching and multiple sinks are executed correctly
if not logging_obj.errors and not logging_obj.suspended and \
Generator.generators:
result = True
abort = False
while result is not None:
try:
for m in Generator.generators:
result = m.generator.next()
continue
except AbortExecution:
break
except ModuleErrors, mes:
for me in mes.module_errors:
me.module.logging.end_update(me.module, me)
logging_obj.signalError(me.module, me)
abort = abort or me.abort
except ModuleError, me:
me.module.logging.end_update(me.module, me, me.errorTrace)
logging_obj.signalError(me.module, me)
abort = me.abort
except ModuleBreakpoint, mb:
mb.module.logging.end_update(mb.module)
logging_obj.signalError(mb.module, mb)
abort = True
if stop_on_error or abort:
break
if Generator.generators:
record_usage(generators=len(Generator.generators))
# execute all generators until inputs are exhausted
# this makes sure branching and multiple sinks are executed correctly
if not logging_obj.errors and not logging_obj.suspended and \
Generator.generators:
result = True
abort = False
while result is not None:
try:
for m in Generator.generators:
result = m.generator.next()
continue
except AbortExecution:
break
except ModuleErrors, mes:
for me in mes.module_errors:
