"""
API operations on a jobs.
.. seealso:: :class:`galaxy.model.Jobs`
"""
from sqlalchemy import or_, and_
from sqlalchemy.orm import aliased
import json
from galaxy.web import _future_expose_api as expose_api
from galaxy.web.base.controller import BaseAPIController
from galaxy.web.base.controller import UsesLibraryMixinItems
from galaxy import exceptions
from galaxy import util
from galaxy import model
from galaxy import managers
import logging
log = logging.getLogger( __name__ )
[docs]class JobController( BaseAPIController, UsesLibraryMixinItems ):
def __init__( self, app ):
super( JobController, self ).__init__( app )
self.hda_manager = managers.hdas.HDAManager( app )
@expose_api
[docs] def index( self, trans, **kwd ):
"""
index( trans, state=None, tool_id=None, history_id=None, date_range_min=None, date_range_max=None, user_details=False )
* GET /api/jobs:
return jobs for current user
!! if user is admin and user_details is True, then
return jobs for all galaxy users based on filtering - this is an extended service
:type state: string or list
:param state: limit listing of jobs to those that match one of the included states. If none, all are returned.
Valid Galaxy job states include:
'new', 'upload', 'waiting', 'queued', 'running', 'ok', 'error', 'paused', 'deleted', 'deleted_new'
:type tool_id: string or list
:param tool_id: limit listing of jobs to those that match one of the included tool_ids. If none, all are returned.
:type user_details: boolean
:param user_details: if true, and requestor is an admin, will return external job id and user email.
:type date_range_min: string '2014-01-01'
:param date_range_min: limit the listing of jobs to those updated on or after requested date
:type date_range_max: string '2014-12-31'
:param date_range_max: limit the listing of jobs to those updated on or before requested date
:type history_id: string
:param history_id: limit listing of jobs to those that match the history_id. If none, all are returned.
:rtype: list
:returns: list of dictionaries containing summary job information
"""
state = kwd.get( 'state', None )
is_admin = trans.user_is_admin()
user_details = kwd.get('user_details', False)
if is_admin:
query = trans.sa_session.query( trans.app.model.Job )
else:
query = trans.sa_session.query( trans.app.model.Job ).filter(trans.app.model.Job.user == trans.user)
def build_and_apply_filters( query, objects, filter_func ):
if objects is not None:
if isinstance( objects, basestring ):
query = query.filter( filter_func( objects ) )
elif isinstance( objects, list ):
t = []
for obj in objects:
t.append( filter_func( obj ) )
query = query.filter( or_( *t ) )
return query
query = build_and_apply_filters( query, state, lambda s: trans.app.model.Job.state == s )
query = build_and_apply_filters( query, kwd.get( 'tool_id', None ), lambda t: trans.app.model.Job.tool_id == t )
query = build_and_apply_filters( query, kwd.get( 'tool_id_like', None ), lambda t: trans.app.model.Job.tool_id.like(t) )
query = build_and_apply_filters( query, kwd.get( 'date_range_min', None ), lambda dmin: trans.app.model.Job.table.c.update_time >= dmin )
query = build_and_apply_filters( query, kwd.get( 'date_range_max', None ), lambda dmax: trans.app.model.Job.table.c.update_time <= dmax )
history_id = kwd.get( 'history_id', None )
if history_id is not None:
try:
decoded_history_id = self.decode_id(history_id)
query = query.filter( trans.app.model.Job.history_id == decoded_history_id )
except:
raise exceptions.ObjectAttributeInvalidException()
out = []
if kwd.get( 'order_by' ) == 'create_time':
order_by = trans.app.model.Job.create_time.desc()
else:
order_by = trans.app.model.Job.update_time.desc()
for job in query.order_by( order_by ).all():
job_dict = job.to_dict( 'collection', system_details=is_admin )
j = self.encode_all_ids( trans, job_dict, True )
if user_details:
j['user_email'] = job.user.email
out.append(j)
return out
@expose_api
[docs] def show( self, trans, id, **kwd ):
"""
show( trans, id )
* GET /api/jobs/{job_id}:
return jobs for current user
:type id: string
:param id: Specific job id
:type full: boolean
:param full: whether to return extra information
:rtype: dictionary
:returns: dictionary containing full description of job data
"""
job = self.__get_job( trans, id )
is_admin = trans.user_is_admin()
job_dict = self.encode_all_ids( trans, job.to_dict( 'element', system_details=is_admin ), True )
full_output = util.asbool( kwd.get( 'full', 'false' ) )
if full_output:
job_dict.update( dict( stderr=job.stderr, stdout=job.stdout ) )
if is_admin:
job_dict['user_email'] = job.user.email
def metric_to_dict(metric):
metric_name = metric.metric_name
metric_value = metric.metric_value
metric_plugin = metric.plugin
title, value = trans.app.job_metrics.format(metric_plugin, metric_name, metric_value)
return dict(
title=title,
value=value,
plugin=metric_plugin,
name=metric_name,
raw_value=str(metric_value),
)
job_dict['job_metrics'] = [metric_to_dict(metric) for metric in job.metrics]
return job_dict
@expose_api
@expose_api
[docs] def outputs( self, trans, id, **kwd ):
"""
show( trans, id )
* GET /api/jobs/{job_id}/outputs
returns output datasets created by job
:type id: string
:param id: Encoded job id
:rtype: dictionary
:returns: dictionary containing output dataset associations
"""
job = self.__get_job( trans, id )
return self.__dictify_associations( trans, job.output_datasets, job.output_library_datasets )
def __dictify_associations( self, trans, *association_lists ):
rval = []
for association_list in association_lists:
rval.extend( map( lambda a: self.__dictify_association( trans, a ), association_list ) )
return rval
def __dictify_association( self, trans, job_dataset_association ):
dataset_dict = None
dataset = job_dataset_association.dataset
if dataset:
if isinstance( dataset, model.HistoryDatasetAssociation ):
dataset_dict = dict( src="hda", id=trans.security.encode_id( dataset.id ) )
else:
dataset_dict = dict( src="ldda", id=trans.security.encode_id( dataset.id ) )
return dict( name=job_dataset_association.name, dataset=dataset_dict )
def __get_job( self, trans, id ):
try:
decoded_job_id = self.decode_id( id )
except Exception:
raise exceptions.MalformedId()
query = trans.sa_session.query( trans.app.model.Job )
if trans.user_is_admin():
query = query.filter(
trans.app.model.Job.id == decoded_job_id
)
else:
query = query.filter(
trans.app.model.Job.user == trans.user,
trans.app.model.Job.id == decoded_job_id
)
job = query.first()
if job is None:
raise exceptions.ObjectNotFound()
return job
@expose_api
[docs] def create( self, trans, payload, **kwd ):
""" See the create method in tools.py in order to submit a job. """
raise NotImplementedError( 'Please POST to /api/tools instead.' )
@expose_api
[docs] def search( self, trans, payload, **kwd ):
"""
search( trans, payload )
* POST /api/jobs/search:
return jobs for current user
:type payload: dict
:param payload: Dictionary containing description of requested job. This is in the same format as
a request to POST /apt/tools would take to initiate a job
:rtype: list
:returns: list of dictionaries containing summary job information of the jobs that match the requested job run
This method is designed to scan the list of previously run jobs and find records of jobs that had
the exact some input parameters and datasets. This can be used to minimize the amount of repeated work, and simply
recycle the old results.
"""
tool_id = None
if 'tool_id' in payload:
tool_id = payload.get( 'tool_id' )
if tool_id is None:
raise exceptions.ObjectAttributeMissingException( "No tool id" )
tool = trans.app.toolbox.get_tool( tool_id )
if tool is None:
raise exceptions.ObjectNotFound( "Requested tool not found" )
if 'inputs' not in payload:
raise exceptions.ObjectAttributeMissingException( "No inputs defined" )
inputs = payload[ 'inputs' ]
input_data = {}
input_param = {}
for k, v in inputs.items():
if isinstance( v, dict ):
if 'id' in v:
if 'src' not in v or v[ 'src' ] == 'hda':
hda_id = self.decode_id( v['id'] )
dataset = self.hda_manager.get_accessible( hda_id, trans.user )
else:
dataset = self.get_library_dataset_dataset_association( trans, v['id'] )
if dataset is None:
raise exceptions.ObjectNotFound( "Dataset %s not found" % ( v[ 'id' ] ) )
input_data[k] = dataset.dataset_id
else:
input_param[k] = json.dumps( str(v) )
query = trans.sa_session.query( trans.app.model.Job ).filter(
trans.app.model.Job.tool_id == tool_id,
trans.app.model.Job.user == trans.user
)
if 'state' not in payload:
query = query.filter(
or_(
trans.app.model.Job.state == 'running',
trans.app.model.Job.state == 'queued',
trans.app.model.Job.state == 'waiting',
trans.app.model.Job.state == 'running',
trans.app.model.Job.state == 'ok',
)
)
else:
if isinstance( payload[ 'state' ], basestring ):
query = query.filter( trans.app.model.Job.state == payload[ 'state' ] )
elif isinstance( payload[ 'state' ], list ):
o = []
for s in payload[ 'state' ]:
o.append( trans.app.model.Job.state == s )
query = query.filter(
or_( *o )
)
for k, v in input_param.items():
a = aliased( trans.app.model.JobParameter )
query = query.filter( and_(
trans.app.model.Job.id == a.job_id,
a.name == k,
a.value == v
) )
for k, v in input_data.items():
# Here we are attempting to link the inputs to the underlying
# dataset (not the dataset association).
# This way, if the calculation was done using a copied HDA
# (copied from the library or another history), the search will
# still find the job
a = aliased( trans.app.model.JobToInputDatasetAssociation )
b = aliased( trans.app.model.HistoryDatasetAssociation )
query = query.filter( and_(
trans.app.model.Job.id == a.job_id,
a.dataset_id == b.id,
b.deleted == False,
b.dataset_id == v
) )
out = []
for job in query.all():
# check to make sure none of the output files have been deleted
if all( list( a.dataset.deleted == False for a in job.output_datasets ) ):
out.append( self.encode_all_ids( trans, job.to_dict( 'element' ), True ) )
return out