def _handle_post_job_actions( self, step, job, replacement_dict ):
# Create new PJA associations with the created job, to be run on completion.
# PJA Parameter Replacement (only applies to immediate actions-- rename specifically, for now)
# Pass along replacement dict with the execution of the PJA so we don't have to modify the object.
for pja in step.post_job_actions:
if pja.action_type in ActionBox.immediate_actions:
ActionBox.execute( self.trans.app, self.trans.sa_session, pja, job, replacement_dict )
else:
job.add_post_job_action( pja )
def _handle_post_job_actions(self, step, job, replacement_dict):
# Create new PJA associations with the created job, to be run on completion.
# PJA Parameter Replacement (only applies to immediate actions-- rename specifically, for now)
# Pass along replacement dict with the execution of the PJA so we don't have to modify the object.
for pja in step.post_job_actions:
if pja.action_type in ActionBox.immediate_actions:
ActionBox.execute(self.trans.app, self.trans.sa_session, pja,
job, replacement_dict)
else:
job.add_post_job_action(pja)
def _remap_job_on_rerun(self, trans, galaxy_session, rerun_remap_job_id, current_job, out_data):
"""
Re-connect dependent datasets for a job that is being rerun (because it failed initially).
If a job fails, the user has the option to try the job again with changed parameters.
To be able to resume jobs that depend on this jobs output datasets we change the dependent's job
input datasets to be those of the job that is being rerun.
"""
try:
old_job = trans.sa_session.query(trans.app.model.Job).get(rerun_remap_job_id)
assert old_job is not None, '(%s/%s): Old job id is invalid' % (rerun_remap_job_id, current_job.id)
assert old_job.tool_id == current_job.tool_id, '(%s/%s): Old tool id (%s) does not match rerun tool id (%s)' % (old_job.id, current_job.id, old_job.tool_id, current_job.tool_id)
if trans.user is not None:
assert old_job.user_id == trans.user.id, '(%s/%s): Old user id (%s) does not match rerun user id (%s)' % (old_job.id, current_job.id, old_job.user_id, trans.user.id)
elif trans.user is None and type(galaxy_session) == trans.model.GalaxySession:
assert old_job.session_id == galaxy_session.id, '(%s/%s): Old session id (%s) does not match rerun session id (%s)' % (old_job.id, current_job.id, old_job.session_id, galaxy_session.id)
else:
raise Exception('(%s/%s): Remapping via the API is not (yet) supported' % (old_job.id, current_job.id))
# Duplicate PJAs before remap.
for pjaa in old_job.post_job_actions:
current_job.add_post_job_action(pjaa.post_job_action)
if old_job.workflow_invocation_step:
replacement_dict = {}
for parameter in old_job.workflow_invocation_step.workflow_invocation.input_parameters:
if parameter.type == WorkflowRequestInputParameter.types.REPLACEMENT_PARAMETERS:
replacement_dict[parameter.name] = parameter.value
for pja in old_job.workflow_invocation_step.workflow_step.post_job_actions:
# execute immediate actions here, with workflow context.
if pja.action_type in ActionBox.immediate_actions:
ActionBox.execute(trans.app, trans.sa_session, pja, current_job, replacement_dict)
for p in old_job.parameters:
if p.name.endswith('|__identifier__'):
current_job.parameters.append(p.copy())
remapped_hdas = self.__remap_data_inputs(old_job=old_job, current_job=current_job)
for jtod in old_job.output_datasets:
for (job_to_remap, jtid) in [(jtid.job, jtid) for jtid in jtod.dataset.dependent_jobs]:
if (trans.user is not None and job_to_remap.user_id == trans.user.id) or (
trans.user is None and job_to_remap.session_id == galaxy_session.id):
self.__remap_parameters(job_to_remap, jtid, jtod, out_data)
trans.sa_session.add(job_to_remap)
trans.sa_session.add(jtid)
jtod.dataset.visible = False
trans.sa_session.add(jtod)
for jtodc in old_job.output_dataset_collection_instances:
hdca = jtodc.dataset_collection_instance
hdca.collection.replace_failed_elements(remapped_hdas)
if hdca.implicit_collection_jobs:
for job in hdca.implicit_collection_jobs.jobs:
if job.job_id == old_job.id:
job.job_id = current_job.id
except Exception:
log.exception('Cannot remap rerun dependencies.')
def _handle_post_job_actions( self, step, job, replacement_dict ):
# Create new PJA associations with the created job, to be run on completion.
# PJA Parameter Replacement (only applies to immediate actions-- rename specifically, for now)
# Pass along replacement dict with the execution of the PJA so we don't have to modify the object.
# Combine workflow and runtime post job actions into the effective post
# job actions for this execution.
effective_post_job_actions = step.post_job_actions[:]
for key, value in self.runtime_post_job_actions.iteritems():
effective_post_job_actions.append( self.__to_pja( key, value, None ) )
for pja in effective_post_job_actions:
if pja.action_type in ActionBox.immediate_actions:
ActionBox.execute( self.trans.app, self.trans.sa_session, pja, job, replacement_dict )
else:
job.add_post_job_action( pja )
def update_state( self, incoming ):
# Build a callback that handles setting an input to be required at
# runtime. We still process all other parameters the user might have
# set. We also need to make sure all datasets have a dummy value
# for dependencies to see
self.post_job_actions = ActionBox.handle_incoming(incoming)
make_runtime_key = incoming.get( 'make_runtime', None )
make_buildtime_key = incoming.get( 'make_buildtime', None )
def item_callback( trans, key, input, value, error, old_value, context ):
# Dummy value for Data parameters
if isinstance( input, DataToolParameter ) or isinstance( input, DataCollectionToolParameter ):
return DummyDataset(), None
# Deal with build/runtime (does not apply to Data parameters)
if key == make_buildtime_key:
return input.get_initial_value( trans, context ), None
elif isinstance( old_value, RuntimeValue ):
return old_value, None
elif key == make_runtime_key:
return RuntimeValue(), None
elif isinstance(value, basestring) and re.search("\$\{.+?\}", str(value)):
# Workflow Parameter Replacement, so suppress error from going to the workflow level.
return value, None
else:
return value, error
# Update state using incoming values
errors = self.tool.update_state( self.trans, self.tool.inputs, self.state.inputs, incoming, item_callback=item_callback )
self.errors = errors or None
def render_body(context, **pageargs):
context.caller_stack._push_frame()
try:
__M_locals = __M_dict_builtin(pageargs=pageargs)
isinstance = context.get('isinstance', UNDEFINED)
basestring = context.get('basestring', UNDEFINED)
errors = context.get('errors', UNDEFINED)
tuple = context.get('tuple', UNDEFINED)
int = context.get('int', UNDEFINED)
h = context.get('h', UNDEFINED)
history_id = context.get('history_id', UNDEFINED)
workflow = context.get('workflow', UNDEFINED)
def do_inputs(inputs,
values,
errors,
prefix,
step,
other_values=None,
already_used=None):
return render_do_inputs(context.locals_(__M_locals), inputs,
values, errors, prefix, step, other_values,
already_used)
len = context.get('len', UNDEFINED)
step_version_changes = context.get('step_version_changes', UNDEFINED)
dict = context.get('dict', UNDEFINED)
t = context.get('t', UNDEFINED)
enumerate = context.get('enumerate', UNDEFINED)
has_upgrade_messages = context.get('has_upgrade_messages', UNDEFINED)
steps = context.get('steps', UNDEFINED)
trans = context.get('trans', UNDEFINED)
__M_writer = context.writer()
# SOURCE LINE 1
__M_writer(u'\n\n')
# SOURCE LINE 243
__M_writer(u'\n\n')
# SOURCE LINE 298
__M_writer(u'\n\n')
# SOURCE LINE 300
from galaxy.tools.parameters import DataToolParameter, RuntimeValue
from galaxy.tools.parameters import DataCollectionToolParameter
from galaxy.jobs.actions.post import ActionBox
import re
import colorsys
import random
used_accumulator = []
wf_parms = {}
for step in steps:
for v in [
ActionBox.get_short_str(pja)
for pja in step.post_job_actions
] + step.state.inputs.values():
if isinstance(v, basestring):
for rematch in re.findall('\$\{.+?\}', v):
if rematch[2:-1] not in wf_parms:
wf_parms[rematch[2:-1]] = ""
if wf_parms:
hue_offset = 1.0 / len(wf_parms)
hue = 0.0
for k in wf_parms.iterkeys():
wf_parms[k] = "#%X%X%X" % tuple(
[int(x * 255) for x in colorsys.hsv_to_rgb(hue, .1, .9)])
hue += hue_offset
__M_locals_builtin_stored = __M_locals_builtin()
__M_locals.update(
__M_dict_builtin([
(__M_key, __M_locals_builtin_stored[__M_key]) for __M_key in [
'hue', 'hue_offset', 'wf_parms', 'ActionBox',
'DataToolParameter', 'rematch', 'used_accumulator', 'k',
'random', 'pja', 're', 'step', 'RuntimeValue', 'colorsys',
'v', 'DataCollectionToolParameter', 'x'
] if __M_key in __M_locals_builtin_stored
]))
# SOURCE LINE 323
__M_writer(u'\n\n')
# SOURCE LINE 365
__M_writer(u'\n\n')
# SOURCE LINE 470
__M_writer(
u'\n\n<div id=\'ec_button_container\'>\n <span class="action-button" id="show_all_tool_body">Expand All</span>\n <span class="action-button" id="hide_all_tool_body">Collapse</span>\n</div>\n\n<h2>Running workflow "'
)
# SOURCE LINE 477
__M_writer(unicode(h.to_unicode(workflow.name)))
__M_writer(u'"</h2>\n\n')
# SOURCE LINE 479
if has_upgrade_messages:
# SOURCE LINE 480
__M_writer(
u'<div class="warningmessage">\n Problems were encountered when loading this workflow, likely due to tool\n version changes. Missing parameter values have been replaced with default.\n Please review the parameter values below.\n</div>\n'
)
pass
# SOURCE LINE 486
__M_writer(u'\n')
# SOURCE LINE 487
if step_version_changes:
# SOURCE LINE 488
__M_writer(
u' <div class="infomessage">\n The following tools are beinge executed with a different version from\n what was available when this workflow was last saved because the\n previous version is no longer available for use on this galaxy\n instance.\n To upgrade your workflow and dismiss this message simply edit the\n workflow and re-save it to update the stored tool version.\n <ul>\n'
)
# SOURCE LINE 496
for vc in step_version_changes:
# SOURCE LINE 497
__M_writer(u' <li>')
__M_writer(unicode(vc))
__M_writer(u'</li>\n')
pass
# SOURCE LINE 499
__M_writer(u' </ul>\n </div>\n')
pass
# SOURCE LINE 502
__M_writer(u'\n')
# SOURCE LINE 503
if workflow.annotation:
# SOURCE LINE 504
__M_writer(u' <div class="workflow-annotation">')
__M_writer(unicode(workflow.annotation))
__M_writer(u'</div>\n <hr/>\n')
pass
# SOURCE LINE 507
__M_writer(u'\n<form id="tool_form" name="tool_form" method="POST">\n')
# SOURCE LINE 510
__M_writer(u'\n')
# SOURCE LINE 511
if wf_parms:
# SOURCE LINE 512
__M_writer(
u'<div class="metadataForm">\n <div class="metadataFormTitle">Workflow Parameters</div>\n <div class="metadataFormBody">\n'
)
# SOURCE LINE 515
for parm in wf_parms:
# SOURCE LINE 516
__M_writer(
u" <div class='form-row'><label style='width:100px;'>"
)
__M_writer(unicode(parm))
__M_writer(u'<input style="border:2px solid ')
__M_writer(unicode(wf_parms[parm]))
__M_writer(
u';border-left-width:8px;" type="text" class=\'wf_parm_input ptag_'
)
__M_writer(unicode(parm))
__M_writer(u'\' name="wf_parm|')
__M_writer(unicode(parm))
__M_writer(u'" value=""/></label></div>\n')
pass
# SOURCE LINE 518
__M_writer(
u' </div>\n</div>\n <script type="text/javascript">\n // Set the change hooks for workflow parameters.\n $(document).ready(function () {\n $(\'.wf_parm_input\').bind(\'change keypress keyup\', function(event){\n // DBTODO This is probably not reliable. Ensure we have the right class.\n var new_text = $(this).val();\n if (new_text === \'\'){\n var tag_id = $(this).attr("class").split(\' \')[1].substring(5);\n // Set text properly.\n $(\'.wfpspan.wf_parm__\'+tag_id).text(tag_id);\n }else{\n var tag_id = $(this).attr("class").split(\' \')[1].substring(5);\n // Set text properly.\n $(\'.wfpspan.wf_parm__\'+tag_id).text(new_text);\n // Now set the hidden input to the generated text.\n $(\'.wfpspan.wf_parm__\'+tag_id).not(\'.pja_wfp\').each(function(){\n var new_text = $(this).parent().text();\n $(this).parent().siblings().children().val(new_text);\n });\n }\n });\n });\n </script>\n'
)
pass
# SOURCE LINE 544
for i, step in enumerate(steps):
# SOURCE LINE 545
__M_writer(
u' <!-- Only way module would be missing is if tool is missing, but\n that would cause missing_tools.mako to render instead of this\n template. -->\n '
)
# SOURCE LINE 548
module = step.module
__M_locals_builtin_stored = __M_locals_builtin()
__M_locals.update(
__M_dict_builtin([(__M_key, __M_locals_builtin_stored[__M_key])
for __M_key in ['module']
if __M_key in __M_locals_builtin_stored]))
__M_writer(u'\n <input type="hidden" name="')
# SOURCE LINE 549
__M_writer(unicode(step.id))
__M_writer(u'|tool_state" value="')
__M_writer(unicode(module.encode_runtime_state(t, step.state)))
__M_writer(u'">\n')
# SOURCE LINE 550
if step.type == 'tool' or step.type is None:
# SOURCE LINE 551
__M_writer(u' ')
tool = trans.app.toolbox.get_tool(step.tool_id)
__M_locals_builtin_stored = __M_locals_builtin()
__M_locals.update(
__M_dict_builtin([
(__M_key, __M_locals_builtin_stored[__M_key])
for __M_key in ['tool']
if __M_key in __M_locals_builtin_stored
]))
# SOURCE LINE 553
__M_writer(
u'\n <div class="toolForm">\n <div class="toolFormTitle">\n <span class=\'title_ul_text\'>Step '
)
# SOURCE LINE 556
__M_writer(unicode(int(step.order_index) + 1))
__M_writer(u': ')
__M_writer(unicode(tool.name))
__M_writer(u'</span>\n')
# SOURCE LINE 557
if tool.version:
# SOURCE LINE 558
__M_writer(u' (version ')
__M_writer(unicode(tool.version))
__M_writer(u')\n')
pass
# SOURCE LINE 560
if step.annotations:
# SOURCE LINE 561
__M_writer(
u' <div class="step-annotation">')
__M_writer(
unicode(h.to_unicode(step.annotations[0].annotation)))
__M_writer(u'</div>\n')
pass
# SOURCE LINE 563
__M_writer(
u' </div>\n <div class="toolFormBody">\n '
)
# SOURCE LINE 565
__M_writer(
unicode(
do_inputs(tool.inputs, step.state.inputs,
errors.get(step.id, dict()), "", step, None,
used_accumulator)))
__M_writer(u'\n')
# SOURCE LINE 566
if step.post_job_actions:
# SOURCE LINE 567
__M_writer(
u" <hr/>\n <div class='form-row'>\n"
)
# SOURCE LINE 569
if len(step.post_job_actions) > 1:
# SOURCE LINE 570
__M_writer(
u' <label>Actions:</label>\n'
)
# SOURCE LINE 571
else:
# SOURCE LINE 572
__M_writer(
u' <label>Action:</label>\n'
)
pass
# SOURCE LINE 574
__M_writer(u' ')
pja_ss_all = []
for pja_ss in [
ActionBox.get_short_str(pja)
for pja in step.post_job_actions
]:
for rematch in re.findall('\$\{.+?\}', pja_ss):
pja_ss = pja_ss.replace(
rematch,
'<span style="background-color:%s" class="wfpspan wf_parm__%s pja_wfp">%s</span>'
% (wf_parms[rematch[2:-1]], rematch[2:-1],
rematch[2:-1]))
pja_ss_all.append(pja_ss)
__M_locals_builtin_stored = __M_locals_builtin()
__M_locals.update(
__M_dict_builtin([
(__M_key, __M_locals_builtin_stored[__M_key])
for __M_key in
['rematch', 'pja_ss_all', 'pja', 'pja_ss']
if __M_key in __M_locals_builtin_stored
]))
# SOURCE LINE 580
__M_writer(u'\n ')
# SOURCE LINE 581
__M_writer(unicode('<br/>'.join(pja_ss_all)))
__M_writer(u'\n </div>\n')
pass
# SOURCE LINE 584
__M_writer(u' </div>\n </div>\n')
# SOURCE LINE 586
else:
# SOURCE LINE 587
__M_writer(
u' <div class="toolForm">\n <div class="toolFormTitle">\n <span class=\'title_ul_text\'>Step '
)
# SOURCE LINE 589
__M_writer(unicode(int(step.order_index) + 1))
__M_writer(u': ')
__M_writer(unicode(module.name))
__M_writer(u'</span>\n')
# SOURCE LINE 590
if step.annotations:
# SOURCE LINE 591
__M_writer(
u' <div class="step-annotation">')
__M_writer(unicode(step.annotations[0].annotation))
__M_writer(u'</div>\n')
pass
# SOURCE LINE 593
__M_writer(
u' </div>\n <div class="toolFormBody">\n '
)
# SOURCE LINE 595
# Filter possible inputs to data types that are valid for subsequent steps
type_filter = []
for oc in step.output_connections:
for ic in oc.input_step.module.get_data_inputs():
if 'extensions' in ic and ic['name'] == oc.input_name:
type_filter += ic['extensions']
if not type_filter:
type_filter = ['data']
__M_locals_builtin_stored = __M_locals_builtin()
__M_locals.update(
__M_dict_builtin([
(__M_key, __M_locals_builtin_stored[__M_key])
for __M_key in ['ic', 'oc', 'type_filter']
if __M_key in __M_locals_builtin_stored
]))
# SOURCE LINE 604
__M_writer(u'\n ')
# SOURCE LINE 605
__M_writer(
unicode(
do_inputs(module.get_runtime_inputs(type_filter),
step.state.inputs,
errors.get(step.id, dict()), "", step, None,
used_accumulator)))
__M_writer(u'\n </div>\n </div>\n')
pass
pass
# SOURCE LINE 610
if history_id is None:
# SOURCE LINE 611
__M_writer(
u' <p id=\'new_history_p\'>\n <input type="checkbox" name=\'new_history\' value="true" id=\'new_history_cbx\'/><label for=\'new_history_cbx\'>Send results to a new history </label>\n <span id="new_history_input">named: <input type=\'text\' name=\'new_history_name\' value=\''
)
# SOURCE LINE 613
__M_writer(
filters.html_escape(unicode(h.to_unicode(workflow.name))))
__M_writer(u"'/></span>\n </p>\n")
pass
# SOURCE LINE 616
__M_writer(
u'<input type="submit" class="btn btn-primary" name="run_workflow" value="Run workflow" />\n</form>\n'
)
return ''
finally:
context.caller_stack._pop_frame()
def render_body(context, **pageargs):
context.caller_stack._push_frame()
try:
__M_locals = __M_dict_builtin(pageargs=pageargs)
basestring = context.get('basestring', UNDEFINED)
errors = context.get('errors', UNDEFINED)
tuple = context.get('tuple', UNDEFINED)
int = context.get('int', UNDEFINED)
h = context.get('h', UNDEFINED)
app = context.get('app', UNDEFINED)
workflow = context.get('workflow', UNDEFINED)
def do_inputs(inputs, values, errors, prefix, step, other_values=None):
return render_do_inputs(context.locals_(__M_locals), inputs,
values, errors, prefix, step, other_values)
len = context.get('len', UNDEFINED)
dict = context.get('dict', UNDEFINED)
t = context.get('t', UNDEFINED)
enumerate = context.get('enumerate', UNDEFINED)
has_upgrade_messages = context.get('has_upgrade_messages', UNDEFINED)
steps = context.get('steps', UNDEFINED)
isinstance = context.get('isinstance', UNDEFINED)
__M_writer = context.writer()
# SOURCE LINE 1
__M_writer(u'\n\n')
# SOURCE LINE 13
__M_writer(u'\n\n')
# SOURCE LINE 32
__M_writer(u'\n\n')
# SOURCE LINE 34
from galaxy.tools.parameters import DataToolParameter, RuntimeValue
from galaxy.jobs.actions.post import ActionBox
import re
import colorsys
import random
wf_parms = {}
for step in steps:
for v in step.state.inputs.itervalues():
if isinstance(v, basestring):
for rematch in re.findall('\$\{.+?\}', v):
if rematch[2:-1] not in wf_parms:
wf_parms[rematch[2:-1]] = ""
if wf_parms:
hue_offset = 1.0 / len(wf_parms)
hue = 0.0
for k in wf_parms.iterkeys():
wf_parms[k] = "#%X%X%X" % tuple(
[int(x * 255) for x in colorsys.hsv_to_rgb(hue, .1, .9)])
hue += hue_offset
__M_locals.update(
__M_dict_builtin([
(__M_key, __M_locals_builtin()[__M_key]) for __M_key in [
'hue', 'hue_offset', 'wf_parms', 'ActionBox',
'DataToolParameter', 'rematch', 'k', 'random', 're',
'step', 'RuntimeValue', 'colorsys', 'v', 'x'
] if __M_key in __M_locals_builtin()
]))
# SOURCE LINE 54
__M_writer(u'\n\n')
# SOURCE LINE 91
__M_writer(u'\n\n')
# SOURCE LINE 163
__M_writer(u'\n\n<h2>Running workflow "')
# SOURCE LINE 165
__M_writer(unicode(h.to_unicode(workflow.name)))
__M_writer(u'"</h2>\n\n')
# SOURCE LINE 167
if has_upgrade_messages:
# SOURCE LINE 168
__M_writer(
u'<div class="warningmessage">\n Problems were encountered when loading this workflow, likely due to tool\n version changes. Missing parameter values have been replaced with default.\n Please review the parameter values below.\n</div>\n'
)
# SOURCE LINE 174
__M_writer(u'\n')
# SOURCE LINE 175
if workflow.annotation:
# SOURCE LINE 176
__M_writer(u' <div class="workflow-annotation">Annotation: ')
__M_writer(unicode(workflow.annotation))
__M_writer(u'</div>\n <hr/>\n')
# SOURCE LINE 179
__M_writer(u'\n<form id="tool_form" name="tool_form" method="POST">\n')
# SOURCE LINE 182
__M_writer(u'\n\n')
# SOURCE LINE 184
if wf_parms:
# SOURCE LINE 185
__M_writer(
u'<div class="metadataForm">\n <div class="metadataFormTitle">Workflow Parameters</div>\n <div class="metadataFormBody">\n'
)
# SOURCE LINE 188
for parm in wf_parms:
# SOURCE LINE 189
__M_writer(
u" <div class='form-row'><label style='width:100px;'>"
)
__M_writer(unicode(parm))
__M_writer(u'<input style="border:2px solid ')
__M_writer(unicode(wf_parms[parm]))
__M_writer(
u';border-left-width:8px;" type="text" class=\'wf_parm_input ptag_'
)
__M_writer(unicode(parm))
__M_writer(u'\' name="wf_parm|')
__M_writer(unicode(parm))
__M_writer(u'" value=""/></label></div>\n')
# SOURCE LINE 191
__M_writer(
u' </div>\n</div>\n <script type="text/javascript">\n // Set the change hooks for workflow parameters.\n $(document).ready(function () {\n $(\'.wf_parm_input\').bind(\'change keypress keyup\', function(event){\n // DBTODO This is probably not reliable. Ensure we have the right class.\n var new_text = $(this).val();\n if (new_text === \'\'){\n var tag_id = $(this).attr("class").split(\' \')[1].substring(5);\n // Set text properly.\n $(\'.wfpspan.wf_parm__\'+tag_id).text(tag_id);\n }else{\n var tag_id = $(this).attr("class").split(\' \')[1].substring(5);\n // Set text properly.\n $(\'.wfpspan.wf_parm__\'+tag_id).text(new_text);\n // Now set the hidden input to the generated text.\n $(\'.wfpspan.wf_parm__\'+tag_id).not(\'.pja_wfp\').each(function(){\n // var new_text = $(this).parent().text();\n $(this).parent().siblings().children().val(new_text);\n });\n }\n });\n });\n </script>\n'
)
# SOURCE LINE 217
__M_writer(u'\n')
# SOURCE LINE 218
for i, step in enumerate(steps):
# SOURCE LINE 219
if step.type == 'tool' or step.type is None:
# SOURCE LINE 220
__M_writer(u' ')
tool = app.toolbox.tools_by_id[step.tool_id]
__M_locals.update(
__M_dict_builtin([(__M_key, __M_locals_builtin()[__M_key])
for __M_key in ['tool']
if __M_key in __M_locals_builtin()]))
__M_writer(u'\n <input type="hidden" name="')
# SOURCE LINE 221
__M_writer(unicode(step.id))
__M_writer(u'|tool_state" value="')
__M_writer(unicode(step.state.encode(tool, app)))
__M_writer(
u'">\n <div class="toolForm">\n <div class="toolFormTitle">\n Step '
)
# SOURCE LINE 224
__M_writer(unicode(int(step.order_index) + 1))
__M_writer(u': ')
__M_writer(unicode(tool.name))
__M_writer(u'\n')
# SOURCE LINE 225
if step.annotations:
# SOURCE LINE 226
__M_writer(
u' <div class="step-annotation">Annotation: '
)
__M_writer(
unicode(h.to_unicode(step.annotations[0].annotation)))
__M_writer(u'</div>\n')
# SOURCE LINE 228
__M_writer(
u' </div>\n <div class="toolFormBody">\n '
)
# SOURCE LINE 230
__M_writer(
unicode(
do_inputs(tool.inputs, step.state.inputs,
errors.get(step.id, dict()), "", step)))
__M_writer(u'\n')
# SOURCE LINE 231
if step.post_job_actions:
# SOURCE LINE 232
__M_writer(
u" <hr/>\n <div class='form-row'>\n"
)
# SOURCE LINE 234
if len(step.post_job_actions) > 1:
# SOURCE LINE 235
__M_writer(
u' <label>Actions:</label>\n')
# SOURCE LINE 236
else:
# SOURCE LINE 237
__M_writer(
u' <label>Action:</label>\n')
# SOURCE LINE 239
pja_ss_all = []
for pja_ss in [
ActionBox.get_short_str(pja)
for pja in step.post_job_actions
]:
for rematch in re.findall('\$\{.+?\}', pja_ss):
pja_ss = pja_ss.replace(
rematch,
'<span style="background-color:%s" class="wfpspan wf_parm__%s pja_wfp">%s</span>'
% (wf_parms[rematch[2:-1]], rematch[2:-1],
rematch[2:-1]))
pja_ss_all.append(pja_ss)
__M_locals.update(
__M_dict_builtin([
(__M_key, __M_locals_builtin()[__M_key])
for __M_key in
['rematch', 'pja_ss_all', 'pja', 'pja_ss']
if __M_key in __M_locals_builtin()
]))
# SOURCE LINE 245
__M_writer(u'\n ')
# SOURCE LINE 246
__M_writer(unicode('<br/>'.join(pja_ss_all)))
__M_writer(u'\n </div>\n')
# SOURCE LINE 249
__M_writer(u' </div>\n </div>\n')
# SOURCE LINE 251
else:
# SOURCE LINE 252
__M_writer(u' ')
module = step.module
__M_locals.update(
__M_dict_builtin([(__M_key, __M_locals_builtin()[__M_key])
for __M_key in ['module']
if __M_key in __M_locals_builtin()]))
__M_writer(u'\n <input type="hidden" name="')
# SOURCE LINE 253
__M_writer(unicode(step.id))
__M_writer(u'|tool_state" value="')
__M_writer(unicode(module.encode_runtime_state(t, step.state)))
__M_writer(
u'">\n <div class="toolForm">\n <div class="toolFormTitle">\n Step '
)
# SOURCE LINE 256
__M_writer(unicode(int(step.order_index) + 1))
__M_writer(u': ')
__M_writer(unicode(module.name))
__M_writer(u'\n')
# SOURCE LINE 257
if step.annotations:
# SOURCE LINE 258
__M_writer(
u' <div class="step-annotation">Annotation: '
)
__M_writer(unicode(step.annotations[0].annotation))
__M_writer(u'</div>\n')
# SOURCE LINE 260
__M_writer(
u' </div>\n <div class="toolFormBody">\n '
)
# SOURCE LINE 262
__M_writer(
unicode(
do_inputs(module.get_runtime_inputs(),
step.state.inputs,
errors.get(step.id, dict()), "", step)))
__M_writer(u'\n </div>\n </div>\n')
# SOURCE LINE 267
__M_writer(
u'<input type="submit" name="run_workflow" value="Run workflow" />\n</form>'
)
return ''
finally:
context.caller_stack._pop_frame()
def get_post_job_actions( self, incoming=None):
if incoming is None:
return self.post_job_actions
else:
return ActionBox.handle_incoming(incoming)
def _execute_workflow(self, sample):
for key, value in sample.workflow['mappings'].items():
if 'hda' not in value and 'ldda' in value:
# If HDA is already here, it's an external input, we're not copying anything.
ldda = self.sa_session.query(
self.app.model.LibraryDatasetDatasetAssociation).get(
value['ldda'])
if ldda.dataset.state in [
'new', 'upload', 'queued', 'running', 'empty',
'discarded'
]:
log.error(
"Cannot import dataset '%s' to user history since its state is '%s'. "
% (ldda.name, ldda.dataset.state))
elif ldda.dataset.state in ['ok', 'error']:
hda = ldda.to_history_dataset_association(
target_history=sample.history, add_to_history=True)
sample.workflow['mappings'][key]['hda'] = hda.id
self.sa_session.add(sample)
self.sa_session.flush()
workflow_dict = sample.workflow
import copy
new_wf_dict = copy.deepcopy(workflow_dict)
for key in workflow_dict['mappings']:
if not isinstance(key, int):
new_wf_dict['mappings'][int(
key)] = workflow_dict['mappings'][key]
workflow_dict = new_wf_dict
fk_trans = FakeTrans(self.app,
history=sample.history,
user=sample.request.user)
workflow = self.sa_session.query(self.app.model.Workflow).get(
workflow_dict['id'])
if not workflow:
log.error("Workflow mapping failure.")
return
if len(workflow.steps) == 0:
log.error(
"Workflow cannot be run because it does not have any steps")
return
if workflow.has_cycles:
log.error("Workflow cannot be run because it contains cycles")
return
if workflow.has_errors:
log.error(
"Workflow cannot be run because of validation errors in some steps"
)
return
# Build the state for each step
errors = {}
# Build a fake dictionary prior to execution.
# Prepare each step
for step in workflow.steps:
step.upgrade_messages = {}
# Contruct modules
if step.type == 'tool' or step.type is None:
# Restore the tool state for the step
step.module = module_factory.from_workflow_step(fk_trans, step)
# Fix any missing parameters
step.upgrade_messages = step.module.check_and_update_state()
# Any connected input needs to have value DummyDataset (these
# are not persisted so we need to do it every time)
step.module.add_dummy_datasets(
connections=step.input_connections)
# Store state with the step
step.state = step.module.state
# Error dict
if step.tool_errors:
errors[step.id] = step.tool_errors
else:
# Non-tool specific stuff?
step.module = module_factory.from_workflow_step(fk_trans, step)
step.state = step.module.get_runtime_state()
# Connections by input name
step.input_connections_by_name = dict(
(conn.input_name, conn) for conn in step.input_connections)
for step in workflow.steps:
step.upgrade_messages = {}
# Connections by input name
step.input_connections_by_name = \
dict((conn.input_name, conn) for conn in step.input_connections)
# Extract just the arguments for this step by prefix
step_errors = None
if step.type == 'tool' or step.type is None:
module = module_factory.from_workflow_step(fk_trans, step)
# Fix any missing parameters
step.upgrade_messages = module.check_and_update_state()
# Any connected input needs to have value DummyDataset (these
# are not persisted so we need to do it every time)
module.add_dummy_datasets(connections=step.input_connections)
# Get the tool
tool = module.tool
# Get the state
step.state = state = module.state
if step_errors:
errors[step.id] = state.inputs["__errors__"] = step_errors
# Run each step, connecting outputs to inputs
workflow_invocation = self.app.model.WorkflowInvocation()
workflow_invocation.workflow = workflow
outputs = odict()
for i, step in enumerate(workflow.steps):
job = None
if step.type == 'tool' or step.type is None:
tool = self.app.toolbox.get_tool(step.tool_id)
def callback(input, prefixed_name, **kwargs):
if isinstance(input, DataToolParameter):
if prefixed_name in step.input_connections_by_name:
conn = step.input_connections_by_name[
prefixed_name]
return outputs[conn.output_step.id][
conn.output_name]
visit_input_values(tool.inputs, step.state.inputs, callback)
job, out_data = tool.execute(fk_trans,
step.state.inputs,
history=sample.history)
outputs[step.id] = out_data
for pja in step.post_job_actions:
if pja.action_type in ActionBox.immediate_actions:
ActionBox.execute(self.app,
self.sa_session,
pja,
job,
replacement_dict=None)
else:
job.add_post_job_action(pja)
else:
job, out_data = step.module.execute(fk_trans, step.state)
outputs[step.id] = out_data
if step.id in workflow_dict['mappings']:
data = self.sa_session.query(
self.app.model.HistoryDatasetAssociation).get(
workflow_dict['mappings'][str(step.id)]['hda'])
outputs[step.id]['output'] = data
workflow_invocation_step = self.app.model.WorkflowInvocationStep()
workflow_invocation_step.workflow_invocation = workflow_invocation
workflow_invocation_step.workflow_step = step
workflow_invocation_step.job = job
self.sa_session.add(workflow_invocation)
self.sa_session.flush()
def _execute_workflow(self, sample):
for key, value in sample.workflow['mappings'].items():
if 'hda' not in value and 'ldda' in value:
# If HDA is already here, it's an external input, we're not copying anything.
ldda = self.sa_session.query(self.app.model.LibraryDatasetDatasetAssociation).get(value['ldda'])
if ldda.dataset.state in ['new', 'upload', 'queued', 'running', 'empty', 'discarded']:
log.error("Cannot import dataset '%s' to user history since its state is '%s'. " % (ldda.name, ldda.dataset.state))
elif ldda.dataset.state in ['ok', 'error']:
hda = ldda.to_history_dataset_association(target_history=sample.history, add_to_history=True)
sample.workflow['mappings'][key]['hda'] = hda.id
self.sa_session.add(sample)
self.sa_session.flush()
workflow_dict = sample.workflow
import copy
new_wf_dict = copy.deepcopy(workflow_dict)
for key in workflow_dict['mappings']:
if not isinstance(key, int):
new_wf_dict['mappings'][int(key)] = workflow_dict['mappings'][key]
workflow_dict = new_wf_dict
fk_trans = FakeTrans(self.app, history=sample.history, user=sample.request.user)
workflow = self.sa_session.query(self.app.model.Workflow).get(workflow_dict['id'])
if not workflow:
log.error("Workflow mapping failure.")
return
if len(workflow.steps) == 0:
log.error("Workflow cannot be run because it does not have any steps")
return
if workflow.has_cycles:
log.error("Workflow cannot be run because it contains cycles")
return
if workflow.has_errors:
log.error("Workflow cannot be run because of validation errors in some steps")
return
# Build the state for each step
errors = {}
# Build a fake dictionary prior to execution.
# Prepare each step
for step in workflow.steps:
step.upgrade_messages = {}
# Contruct modules
if step.type == 'tool' or step.type is None:
# Restore the tool state for the step
step.module = module_factory.from_workflow_step(fk_trans, step)
# Fix any missing parameters
step.upgrade_messages = step.module.check_and_update_state()
# Any connected input needs to have value DummyDataset (these
# are not persisted so we need to do it every time)
step.module.add_dummy_datasets(connections=step.input_connections)
# Store state with the step
step.state = step.module.state
# Error dict
if step.tool_errors:
errors[step.id] = step.tool_errors
else:
# Non-tool specific stuff?
step.module = module_factory.from_workflow_step(fk_trans, step)
step.state = step.module.get_runtime_state()
# Connections by input name
step.input_connections_by_name = dict((conn.input_name, conn) for conn in step.input_connections)
for step in workflow.steps:
step.upgrade_messages = {}
# Connections by input name
step.input_connections_by_name = \
dict((conn.input_name, conn) for conn in step.input_connections)
# Extract just the arguments for this step by prefix
step_errors = None
if step.type == 'tool' or step.type is None:
module = module_factory.from_workflow_step(fk_trans, step)
# Fix any missing parameters
step.upgrade_messages = module.check_and_update_state()
# Any connected input needs to have value DummyDataset (these
# are not persisted so we need to do it every time)
module.add_dummy_datasets(connections=step.input_connections)
# Get the tool
tool = module.tool
# Get the state
step.state = state = module.state
if step_errors:
errors[step.id] = state.inputs["__errors__"] = step_errors
# Run each step, connecting outputs to inputs
workflow_invocation = self.app.model.WorkflowInvocation()
workflow_invocation.workflow = workflow
outputs = odict()
for i, step in enumerate(workflow.steps):
job = None
if step.type == 'tool' or step.type is None:
tool = self.app.toolbox.get_tool(step.tool_id)
def callback(input, prefixed_name, **kwargs):
if isinstance(input, DataToolParameter):
if prefixed_name in step.input_connections_by_name:
conn = step.input_connections_by_name[prefixed_name]
return outputs[conn.output_step.id][conn.output_name]
visit_input_values(tool.inputs, step.state.inputs, callback)
job, out_data = tool.execute(fk_trans, step.state.inputs, history=sample.history)
outputs[step.id] = out_data
for pja in step.post_job_actions:
if pja.action_type in ActionBox.immediate_actions:
ActionBox.execute(self.app, self.sa_session, pja, job, replacement_dict=None)
else:
job.add_post_job_action(pja)
else:
job, out_data = step.module.execute(fk_trans, step.state)
outputs[step.id] = out_data
if step.id in workflow_dict['mappings']:
data = self.sa_session.query(self.app.model.HistoryDatasetAssociation).get(workflow_dict['mappings'][str(step.id)]['hda'])
outputs[step.id]['output'] = data
workflow_invocation_step = self.app.model.WorkflowInvocationStep()
workflow_invocation_step.workflow_invocation = workflow_invocation
workflow_invocation_step.workflow_step = step
workflow_invocation_step.job = job
self.sa_session.add(workflow_invocation)
self.sa_session.flush()
def create(self, trans, payload, **kwd):
"""
POST /api/workflows
We're not creating workflows from the api. Just execute for now.
However, we will import them if installed_repository_file is specified
"""
# ------------------------------------------------------------------------------- #
### RPARK: dictionary containing which workflows to change and edit ###
param_map = {}
if payload.has_key("parameters"):
param_map = payload["parameters"]
# ------------------------------------------------------------------------------- #
if "workflow_id" not in payload:
# create new
if "installed_repository_file" in payload:
workflow_controller = trans.webapp.controllers["workflow"]
result = workflow_controller.import_workflow(trans=trans, cntrller="api", **payload)
return result
trans.response.status = 403
return "Either workflow_id or installed_repository_file must be specified"
if "installed_repository_file" in payload:
trans.response.status = 403
return "installed_repository_file may not be specified with workflow_id"
stored_workflow = trans.sa_session.query(self.app.model.StoredWorkflow).get(
trans.security.decode_id(payload["workflow_id"])
)
if stored_workflow.user != trans.user and not trans.user_is_admin():
if (
trans.sa_session.query(trans.app.model.StoredWorkflowUserShareAssociation)
.filter_by(user=trans.user, stored_workflow=stored_workflow)
.count()
== 0
):
trans.response.status = 400
return "Workflow is not owned by or shared with current user"
workflow = stored_workflow.latest_workflow
if payload["history"].startswith("hist_id="):
# Passing an existing history to use.
history = trans.sa_session.query(self.app.model.History).get(
trans.security.decode_id(payload["history"][8:])
)
if history.user != trans.user and not trans.user_is_admin():
trans.response.status = 400
return "Invalid History specified."
else:
history = self.app.model.History(name=payload["history"], user=trans.user)
trans.sa_session.add(history)
trans.sa_session.flush()
ds_map = payload["ds_map"]
add_to_history = "no_add_to_history" not in payload
for k in ds_map:
try:
if ds_map[k]["src"] == "ldda":
ldda = trans.sa_session.query(self.app.model.LibraryDatasetDatasetAssociation).get(
trans.security.decode_id(ds_map[k]["id"])
)
assert trans.user_is_admin() or trans.app.security_agent.can_access_dataset(
trans.get_current_user_roles(), ldda.dataset
)
hda = ldda.to_history_dataset_association(history, add_to_history=add_to_history)
elif ds_map[k]["src"] == "ld":
ldda = (
trans.sa_session.query(self.app.model.LibraryDataset)
.get(trans.security.decode_id(ds_map[k]["id"]))
.library_dataset_dataset_association
)
assert trans.user_is_admin() or trans.app.security_agent.can_access_dataset(
trans.get_current_user_roles(), ldda.dataset
)
hda = ldda.to_history_dataset_association(history, add_to_history=add_to_history)
elif ds_map[k]["src"] == "hda":
# Get dataset handle, add to dict and history if necessary
hda = trans.sa_session.query(self.app.model.HistoryDatasetAssociation).get(
trans.security.decode_id(ds_map[k]["id"])
)
assert trans.user_is_admin() or trans.app.security_agent.can_access_dataset(
trans.get_current_user_roles(), hda.dataset
)
else:
trans.response.status = 400
return "Unknown dataset source '%s' specified." % ds_map[k]["src"]
if add_to_history and hda.history != history:
hda = hda.copy()
history.add_dataset(hda)
ds_map[k]["hda"] = hda
except AssertionError:
trans.response.status = 400
return "Invalid Dataset '%s' Specified" % ds_map[k]["id"]
if not workflow:
trans.response.status = 400
return "Workflow not found."
if len(workflow.steps) == 0:
trans.response.status = 400
return "Workflow cannot be run because it does not have any steps"
if workflow.has_cycles:
trans.response.status = 400
return "Workflow cannot be run because it contains cycles"
if workflow.has_errors:
trans.response.status = 400
return "Workflow cannot be run because of validation errors in some steps"
# Build the state for each step
rval = {}
for step in workflow.steps:
step_errors = None
if step.type == "tool" or step.type is None:
step.module = module_factory.from_workflow_step(trans, step)
# Check for missing parameters
step.upgrade_messages = step.module.check_and_update_state()
# Any connected input needs to have value DummyDataset (these
# are not persisted so we need to do it every time)
step.module.add_dummy_datasets(connections=step.input_connections)
step.state = step.module.state
####################################################
####################################################
# RPARK: IF TOOL_NAME IN PARAMETER MAP #
if step.tool_id in param_map:
change_param = param_map[step.tool_id]["param"]
change_value = param_map[step.tool_id]["value"]
step.state.inputs[change_param] = change_value
####################################################
####################################################
if step.tool_errors:
trans.response.status = 400
return "Workflow cannot be run because of validation errors in some steps: %s" % step_errors
if step.upgrade_messages:
trans.response.status = 400
return "Workflow cannot be run because of step upgrade messages: %s" % step.upgrade_messages
else:
# This is an input step. Make sure we have an available input.
if step.type == "data_input" and str(step.id) not in ds_map:
trans.response.status = 400
return "Workflow cannot be run because an expected input step '%s' has no input dataset." % step.id
step.module = module_factory.from_workflow_step(trans, step)
step.state = step.module.get_runtime_state()
step.input_connections_by_name = dict((conn.input_name, conn) for conn in step.input_connections)
# Run each step, connecting outputs to inputs
workflow_invocation = self.app.model.WorkflowInvocation()
workflow_invocation.workflow = workflow
outputs = util.odict.odict()
rval["history"] = trans.security.encode_id(history.id)
rval["outputs"] = []
for i, step in enumerate(workflow.steps):
job = None
if step.type == "tool" or step.type is None:
tool = self.app.toolbox.get_tool(step.tool_id)
def callback(input, value, prefixed_name, prefixed_label):
if isinstance(input, DataToolParameter):
if prefixed_name in step.input_connections_by_name:
conn = step.input_connections_by_name[prefixed_name]
return outputs[conn.output_step.id][conn.output_name]
visit_input_values(tool.inputs, step.state.inputs, callback)
job, out_data = tool.execute(trans, step.state.inputs, history=history)
outputs[step.id] = out_data
for pja in step.post_job_actions:
if pja.action_type in ActionBox.immediate_actions:
ActionBox.execute(self.app, trans.sa_session, pja, job, replacement_dict=None)
else:
job.add_post_job_action(pja)
for v in out_data.itervalues():
rval["outputs"].append(trans.security.encode_id(v.id))
else:
# This is an input step. Use the dataset inputs from ds_map.
job, out_data = step.module.execute(trans, step.state)
outputs[step.id] = out_data
outputs[step.id]["output"] = ds_map[str(step.id)]["hda"]
workflow_invocation_step = self.app.model.WorkflowInvocationStep()
workflow_invocation_step.workflow_invocation = workflow_invocation
workflow_invocation_step.workflow_step = step
workflow_invocation_step.job = job
trans.sa_session.add(workflow_invocation)
trans.sa_session.flush()
return rval
def render_javascripts(context):
context.caller_stack._push_frame()
try:
_import_ns = {}
_mako_get_namespace(context, '__anon_0x7f5a30573590')._populate(
_import_ns, [u'render_individual_tagging_element'])
h = _import_ns.get('h', context.get('h', UNDEFINED))
trans = _import_ns.get('trans', context.get('trans', UNDEFINED))
stored = _import_ns.get('stored', context.get('stored', UNDEFINED))
parent = _import_ns.get('parent', context.get('parent', UNDEFINED))
__M_writer = context.writer()
# SOURCE LINE 10
__M_writer(u'\n\n ')
# SOURCE LINE 12
__M_writer(unicode(parent.javascripts()))
__M_writer(
u'\n\n <!--[if lt IE 9]>\n <script type=\'text/javascript\' src="'
)
# SOURCE LINE 15
__M_writer(unicode(h.url_for('/static/scripts/libs/IE/excanvas.js')))
__M_writer(u'"></script>\n <![endif]-->\n\n ')
# SOURCE LINE 18
__M_writer(
unicode(
h.js("libs/jquery/jquery.event.drag",
"libs/jquery/jquery.event.drop",
"libs/jquery/jquery.event.hover",
"libs/jquery/jquery.form", "libs/jquery/jstorage",
"galaxy.workflow_editor.canvas",
"libs/jquery/jquery.autocomplete",
"galaxy.autocom_tagging", "galaxy.workflows")))
# SOURCE LINE 26
__M_writer(
u'\n\n <!--[if lt IE 7]>\n <script type=\'text/javascript\'>\n window.lt_ie_7 = true;\n </script>\n <![endif]-->\n\n <script type=\'text/javascript\'>\n // Globals\n workflow = null;\n canvas_manager = null;\n active_ajax_call = false;\n\n var workflow_id = "'
)
# SOURCE LINE 40
__M_writer(unicode(trans.security.encode_id(stored.id)))
__M_writer(
u'";\n\n // URLs used by galaxy.workflows.js\n var tool_search_url = "'
)
# SOURCE LINE 43
__M_writer(unicode(h.url_for(controller='root', action='tool_search')))
__M_writer(u'",\n get_datatypes_url = "')
# SOURCE LINE 44
__M_writer(
unicode(h.url_for(controller='workflow', action='get_datatypes')))
__M_writer(u'",\n load_workflow_url = "')
# SOURCE LINE 45
__M_writer(
unicode(h.url_for(controller='workflow', action='load_workflow')))
__M_writer(u'",\n run_workflow_url = "')
# SOURCE LINE 46
__M_writer(
unicode(
h.url_for(controller='root',
action='index',
workflow_id=trans.security.encode_id(stored.id))))
__M_writer(u'",\n rename_async_url = "')
# SOURCE LINE 47
__M_writer(
unicode(
h.url_for(controller='workflow',
action='rename_async',
id=trans.security.encode_id(stored.id))))
__M_writer(u'",\n annotate_async_url = "')
# SOURCE LINE 48
__M_writer(
unicode(
h.url_for(controller='workflow',
action='annotate_async',
id=trans.security.encode_id(stored.id))))
__M_writer(u'",\n get_new_module_info_url = "')
# SOURCE LINE 49
__M_writer(
unicode(
h.url_for(controller='workflow',
action='get_new_module_info')))
__M_writer(u'",\n workflow_index_url = "')
# SOURCE LINE 50
__M_writer(unicode(h.url_for(controller='workflow', action='index')))
__M_writer(u'",\n save_workflow_url = "')
# SOURCE LINE 51
__M_writer(
unicode(h.url_for(controller='workflow', action='save_workflow')))
__M_writer(u'";\n\n ')
# SOURCE LINE 53
from galaxy.jobs.actions.post import ActionBox
# SOURCE LINE 55
__M_writer(
u'\n // Post-job action vars.\n var pja_list = "')
# SOURCE LINE 57
__M_writer(unicode(ActionBox.get_add_list()))
__M_writer(
u'",\n get_pja_form = function(pja, node) {\n var p_str = \'\';\n // FIXME: this writes JS code; this logic should be codified in galaxy.workflows.js\n '
)
# SOURCE LINE 61
__M_writer(unicode(ActionBox.get_forms(trans)))
__M_writer(
u'\n return p_str;\n };\n\n // NOTE: code to initialize and edit workflows is in galaxy.workflows.js\n </script>\n'
)
return ''
finally:
context.caller_stack._pop_frame()
class JobWrapper( object ):
"""
Wraps a 'model.Job' with convenience methods for running processes and
state management.
"""
def __init__( self, job, queue ):
self.job_id = job.id
self.session_id = job.session_id
self.user_id = job.user_id
self.tool = queue.app.toolbox.tools_by_id.get( job.tool_id, None )
self.queue = queue
self.app = queue.app
self.sa_session = self.app.model.context
self.extra_filenames = []
self.command_line = None
# Tool versioning variables
self.version_string_cmd = None
self.version_string = ""
self.galaxy_lib_dir = None
# With job outputs in the working directory, we need the working
# directory to be set before prepare is run, or else premature deletion
# and job recovery fail.
# Create the working dir if necessary
try:
self.app.object_store.create(job, base_dir='job_work', dir_only=True, extra_dir=str(self.job_id))
self.working_directory = self.app.object_store.get_filename(job, base_dir='job_work', dir_only=True, extra_dir=str(self.job_id))
log.debug('(%s) Working directory for job is: %s' % (self.job_id, self.working_directory))
except ObjectInvalid:
raise Exception('Unable to create job working directory, job failure')
self.output_paths = None
self.output_hdas_and_paths = None
self.tool_provided_job_metadata = None
# Wrapper holding the info required to restore and clean up from files used for setting metadata externally
self.external_output_metadata = metadata.JobExternalOutputMetadataWrapper( job )
self.params = None
if job.params:
self.params = from_json_string( job.params )
self.__user_system_pwent = None
self.__galaxy_system_pwent = None
def get_job_runner( self ):
return self.tool.get_job_runner( self.params )
def get_job( self ):
return self.sa_session.query( model.Job ).get( self.job_id )
def get_id_tag(self):
# For compatability with drmaa, which uses job_id right now, and TaskWrapper
return str(self.job_id)
def get_param_dict( self ):
"""
Restore the dictionary of parameters from the database.
"""
job = self.get_job()
param_dict = dict( [ ( p.name, p.value ) for p in job.parameters ] )
param_dict = self.tool.params_from_strings( param_dict, self.app )
return param_dict
def get_version_string_path( self ):
return os.path.abspath(os.path.join(self.app.config.new_file_path, "GALAXY_VERSION_STRING_%s" % self.job_id))
def prepare( self ):
"""
Prepare the job to run by creating the working directory and the
config files.
"""
self.sa_session.expunge_all() #this prevents the metadata reverting that has been seen in conjunction with the PBS job runner
if not os.path.exists( self.working_directory ):
os.mkdir( self.working_directory )
# Restore parameters from the database
job = self.get_job()
if job.user is None and job.galaxy_session is None:
raise Exception( 'Job %s has no user and no session.' % job.id )
incoming = dict( [ ( p.name, p.value ) for p in job.parameters ] )
incoming = self.tool.params_from_strings( incoming, self.app )
# Do any validation that could not be done at job creation
self.tool.handle_unvalidated_param_values( incoming, self.app )
# Restore input / output data lists
inp_data = dict( [ ( da.name, da.dataset ) for da in job.input_datasets ] )
out_data = dict( [ ( da.name, da.dataset ) for da in job.output_datasets ] )
inp_data.update( [ ( da.name, da.dataset ) for da in job.input_library_datasets ] )
out_data.update( [ ( da.name, da.dataset ) for da in job.output_library_datasets ] )
# Set up output dataset association for export history jobs. Because job
# uses a Dataset rather than an HDA or LDA, it's necessary to set up a
# fake dataset association that provides the needed attributes for
# preparing a job.
class FakeDatasetAssociation ( object ):
def __init__( self, dataset=None ):
self.dataset = dataset
self.file_name = dataset.file_name
self.metadata = dict()
self.children = []
special = self.sa_session.query( model.JobExportHistoryArchive ).filter_by( job=job ).first()
if not special:
special = self.sa_session.query( model.GenomeIndexToolData ).filter_by( job=job ).first()
if special:
out_data[ "output_file" ] = FakeDatasetAssociation( dataset=special.dataset )
# These can be passed on the command line if wanted as $userId $userEmail
if job.history and job.history.user: # check for anonymous user!
userId = '%d' % job.history.user.id
userEmail = str(job.history.user.email)
else:
userId = 'Anonymous'
userEmail = 'Anonymous'
incoming['__user_id__'] = incoming['userId'] = userId
incoming['__user_email__'] = incoming['userEmail'] = userEmail
# Build params, done before hook so hook can use
param_dict = self.tool.build_param_dict( incoming, inp_data, out_data, self.get_output_fnames(), self.working_directory )
# Certain tools require tasks to be completed prior to job execution
# ( this used to be performed in the "exec_before_job" hook, but hooks are deprecated ).
self.tool.exec_before_job( self.queue.app, inp_data, out_data, param_dict )
# Run the before queue ("exec_before_job") hook
self.tool.call_hook( 'exec_before_job', self.queue.app, inp_data=inp_data,
out_data=out_data, tool=self.tool, param_dict=incoming)
self.sa_session.flush()
# Build any required config files
config_filenames = self.tool.build_config_files( param_dict, self.working_directory )
# FIXME: Build the param file (might return None, DEPRECATED)
param_filename = self.tool.build_param_file( param_dict, self.working_directory )
# Build the job's command line
self.command_line = self.tool.build_command_line( param_dict )
# FIXME: for now, tools get Galaxy's lib dir in their path
if self.command_line and self.command_line.startswith( 'python' ):
self.galaxy_lib_dir = os.path.abspath( "lib" ) # cwd = galaxy root
# Shell fragment to inject dependencies
if self.app.config.use_tool_dependencies:
self.dependency_shell_commands = self.tool.build_dependency_shell_commands()
else:
self.dependency_shell_commands = None
# We need command_line persisted to the db in order for Galaxy to re-queue the job
# if the server was stopped and restarted before the job finished
job.command_line = self.command_line
self.sa_session.add( job )
self.sa_session.flush()
# Return list of all extra files
extra_filenames = config_filenames
if param_filename is not None:
extra_filenames.append( param_filename )
self.param_dict = param_dict
self.extra_filenames = extra_filenames
self.version_string_cmd = self.tool.version_string_cmd
return extra_filenames
def fail( self, message, exception=False ):
"""
Indicate job failure by setting state and message on all output
datasets.
"""
job = self.get_job()
self.sa_session.refresh( job )
# if the job was deleted, don't fail it
if not job.state == job.states.DELETED:
# Check if the failure is due to an exception
if exception:
# Save the traceback immediately in case we generate another
# below
job.traceback = traceback.format_exc()
# Get the exception and let the tool attempt to generate
# a better message
etype, evalue, tb = sys.exc_info()
m = self.tool.handle_job_failure_exception( evalue )
if m:
message = m
if self.app.config.outputs_to_working_directory:
for dataset_path in self.get_output_fnames():
try:
shutil.move( dataset_path.false_path, dataset_path.real_path )
log.debug( "fail(): Moved %s to %s" % ( dataset_path.false_path, dataset_path.real_path ) )
except ( IOError, OSError ), e:
log.error( "fail(): Missing output file in working directory: %s" % e )
for dataset_assoc in job.output_datasets + job.output_library_datasets:
dataset = dataset_assoc.dataset
self.sa_session.refresh( dataset )
dataset.state = dataset.states.ERROR
dataset.blurb = 'tool error'
dataset.info = message
dataset.set_size()
dataset.dataset.set_total_size()
if dataset.ext == 'auto':
dataset.extension = 'data'
# Update (non-library) job output datasets through the object store
if dataset not in job.output_library_datasets:
self.app.object_store.update_from_file(dataset.dataset, create=True)
self.sa_session.add( dataset )
self.sa_session.flush()
job.state = job.states.ERROR
job.command_line = self.command_line
job.info = message
self.sa_session.add( job )
self.sa_session.flush()
#Perform email action even on failure.
for pja in [pjaa.post_job_action for pjaa in job.post_job_actions if pjaa.post_job_action.action_type == "EmailAction"]:
ActionBox.execute(self.app, self.sa_session, pja, job)
# If the job was deleted, call tool specific fail actions (used for e.g. external metadata) and clean up
if self.tool:
self.tool.job_failed( self, message, exception )
if self.app.config.cleanup_job == 'always' or (self.app.config.cleanup_job == 'onsuccess' and job.state == job.states.DELETED):
self.cleanup()
def render_javascripts(context):
context.caller_stack._push_frame()
try:
_import_ns = {}
_mako_get_namespace(context, '__anon_0x7f5a30573590')._populate(_import_ns, [u'render_individual_tagging_element'])
h = _import_ns.get('h', context.get('h', UNDEFINED))
trans = _import_ns.get('trans', context.get('trans', UNDEFINED))
stored = _import_ns.get('stored', context.get('stored', UNDEFINED))
parent = _import_ns.get('parent', context.get('parent', UNDEFINED))
__M_writer = context.writer()
# SOURCE LINE 10
__M_writer(u'\n\n ')
# SOURCE LINE 12
__M_writer(unicode(parent.javascripts()))
__M_writer(u'\n\n <!--[if lt IE 9]>\n <script type=\'text/javascript\' src="')
# SOURCE LINE 15
__M_writer(unicode(h.url_for('/static/scripts/libs/IE/excanvas.js')))
__M_writer(u'"></script>\n <![endif]-->\n\n ')
# SOURCE LINE 18
__M_writer(unicode(h.js( "libs/jquery/jquery.event.drag",
"libs/jquery/jquery.event.drop",
"libs/jquery/jquery.event.hover",
"libs/jquery/jquery.form",
"libs/jquery/jstorage",
"galaxy.workflow_editor.canvas",
"libs/jquery/jquery.autocomplete",
"galaxy.autocom_tagging",
"galaxy.workflows" )))
# SOURCE LINE 26
__M_writer(u'\n\n <!--[if lt IE 7]>\n <script type=\'text/javascript\'>\n window.lt_ie_7 = true;\n </script>\n <![endif]-->\n\n <script type=\'text/javascript\'>\n // Globals\n workflow = null;\n canvas_manager = null;\n active_ajax_call = false;\n\n var workflow_id = "')
# SOURCE LINE 40
__M_writer(unicode(trans.security.encode_id( stored.id ) ))
__M_writer(u'";\n\n // URLs used by galaxy.workflows.js\n var tool_search_url = "')
# SOURCE LINE 43
__M_writer(unicode(h.url_for( controller='root', action='tool_search' )))
__M_writer(u'",\n get_datatypes_url = "')
# SOURCE LINE 44
__M_writer(unicode(h.url_for( controller='workflow', action='get_datatypes' )))
__M_writer(u'",\n load_workflow_url = "')
# SOURCE LINE 45
__M_writer(unicode(h.url_for( controller='workflow', action='load_workflow' )))
__M_writer(u'",\n run_workflow_url = "')
# SOURCE LINE 46
__M_writer(unicode(h.url_for( controller='root', action='index', workflow_id=trans.security.encode_id(stored.id))))
__M_writer(u'",\n rename_async_url = "')
# SOURCE LINE 47
__M_writer(unicode(h.url_for( controller='workflow', action='rename_async', id=trans.security.encode_id(stored.id) )))
__M_writer(u'",\n annotate_async_url = "')
# SOURCE LINE 48
__M_writer(unicode(h.url_for( controller='workflow', action='annotate_async', id=trans.security.encode_id(stored.id) )))
__M_writer(u'",\n get_new_module_info_url = "')
# SOURCE LINE 49
__M_writer(unicode(h.url_for(controller='workflow', action='get_new_module_info' )))
__M_writer(u'",\n workflow_index_url = "')
# SOURCE LINE 50
__M_writer(unicode(h.url_for( controller='workflow', action='index' )))
__M_writer(u'",\n save_workflow_url = "')
# SOURCE LINE 51
__M_writer(unicode(h.url_for(controller='workflow', action='save_workflow' )))
__M_writer(u'";\n\n ')
# SOURCE LINE 53
from galaxy.jobs.actions.post import ActionBox
# SOURCE LINE 55
__M_writer(u'\n // Post-job action vars.\n var pja_list = "')
# SOURCE LINE 57
__M_writer(unicode(ActionBox.get_add_list()))
__M_writer(u'",\n get_pja_form = function(pja, node) {\n var p_str = \'\';\n // FIXME: this writes JS code; this logic should be codified in galaxy.workflows.js\n ')
# SOURCE LINE 61
__M_writer(unicode(ActionBox.get_forms(trans)))
__M_writer(u'\n return p_str;\n };\n\n // NOTE: code to initialize and edit workflows is in galaxy.workflows.js\n </script>\n')
return ''
finally:
context.caller_stack._pop_frame()
def get_post_job_actions( self, incoming ):
return ActionBox.handle_incoming( incoming )
def finish( self, stdout, stderr ):
"""
Called to indicate that the associated command has been run. Updates
the output datasets based on stderr and stdout from the command, and
the contents of the output files.
"""
# default post job setup
self.sa_session.expunge_all()
job = self.get_job()
try:
self.reclaim_ownership()
except:
self.fail( job.info )
log.exception( '(%s) Failed to change ownership of %s, failing' % ( job.id, self.working_directory ) )
# if the job was deleted, don't finish it
if job.state == job.states.DELETED or job.state == job.states.ERROR:
#ERROR at this point means the job was deleted by an administrator.
return self.fail( job.info )
if stderr:
job.state = job.states.ERROR
else:
job.state = job.states.OK
if self.version_string_cmd:
version_filename = self.get_version_string_path()
if os.path.exists(version_filename):
self.version_string = open(version_filename).read()
os.unlink(version_filename)
if self.app.config.outputs_to_working_directory and not self.__link_file_check():
for dataset_path in self.get_output_fnames():
try:
shutil.move( dataset_path.false_path, dataset_path.real_path )
log.debug( "finish(): Moved %s to %s" % ( dataset_path.false_path, dataset_path.real_path ) )
except ( IOError, OSError ):
# this can happen if Galaxy is restarted during the job's
# finish method - the false_path file has already moved,
# and when the job is recovered, it won't be found.
if os.path.exists( dataset_path.real_path ) and os.stat( dataset_path.real_path ).st_size > 0:
log.warning( "finish(): %s not found, but %s is not empty, so it will be used instead" % ( dataset_path.false_path, dataset_path.real_path ) )
else:
return self.fail( "Job %s's output dataset(s) could not be read" % job.id )
job_context = ExpressionContext( dict( stdout = stdout, stderr = stderr ) )
job_tool = self.app.toolbox.tools_by_id.get( job.tool_id, None )
def in_directory( file, directory ):
# Make both absolute.
directory = os.path.abspath( directory )
file = os.path.abspath( file )
#Return true, if the common prefix of both is equal to directory
#e.g. /a/b/c/d.rst and directory is /a/b, the common prefix is /a/b
return os.path.commonprefix( [ file, directory ] ) == directory
for dataset_assoc in job.output_datasets + job.output_library_datasets:
context = self.get_dataset_finish_context( job_context, dataset_assoc.dataset.dataset )
#should this also be checking library associations? - can a library item be added from a history before the job has ended? - lets not allow this to occur
for dataset in dataset_assoc.dataset.dataset.history_associations + dataset_assoc.dataset.dataset.library_associations: #need to update all associated output hdas, i.e. history was shared with job running
#
# If HDA is to be copied from the working directory, do it now so that other attributes are correctly set.
#
if isinstance( dataset, model.HistoryDatasetAssociation ):
joda = self.sa_session.query( model.JobToOutputDatasetAssociation ).filter_by( job=job, dataset=dataset ).first()
if joda and job_tool:
hda_tool_output = job_tool.outputs.get( joda.name, None )
if hda_tool_output and hda_tool_output.from_work_dir:
# Copy from working dir to HDA.
source_file = os.path.join( os.path.abspath( self.working_directory ), hda_tool_output.from_work_dir )
if in_directory( source_file, self.working_directory ):
try:
shutil.move( source_file, dataset.file_name )
log.debug( "finish(): Moved %s to %s as directed by from_work_dir" % ( source_file, dataset.file_name ) )
except ( IOError, OSError ):
log.debug( "finish(): Could not move %s to %s as directed by from_work_dir" % ( source_file, dataset.file_name ) )
else:
# Security violation.
log.exception( "from_work_dir specified a location not in the working directory: %s, %s" % ( source_file, self.working_directory ) )
dataset.blurb = 'done'
dataset.peek = 'no peek'
dataset.info = ( dataset.info or '' ) + context['stdout'] + context['stderr']
dataset.tool_version = self.version_string
dataset.set_size()
# Update (non-library) job output datasets through the object store
if dataset not in job.output_library_datasets:
self.app.object_store.update_from_file(dataset.dataset, create=True)
if context['stderr']:
dataset.blurb = "error"
elif dataset.has_data():
# If the tool was expected to set the extension, attempt to retrieve it
if dataset.ext == 'auto':
dataset.extension = context.get( 'ext', 'data' )
dataset.init_meta( copy_from=dataset )
#if a dataset was copied, it won't appear in our dictionary:
#either use the metadata from originating output dataset, or call set_meta on the copies
#it would be quicker to just copy the metadata from the originating output dataset,
#but somewhat trickier (need to recurse up the copied_from tree), for now we'll call set_meta()
if not self.app.config.set_metadata_externally or \
( not self.external_output_metadata.external_metadata_set_successfully( dataset, self.sa_session ) \
and self.app.config.retry_metadata_internally ):
dataset.set_meta( overwrite = False )
elif not self.external_output_metadata.external_metadata_set_successfully( dataset, self.sa_session ) and not context['stderr']:
dataset._state = model.Dataset.states.FAILED_METADATA
else:
#load metadata from file
#we need to no longer allow metadata to be edited while the job is still running,
#since if it is edited, the metadata changed on the running output will no longer match
#the metadata that was stored to disk for use via the external process,
#and the changes made by the user will be lost, without warning or notice
dataset.metadata.from_JSON_dict( self.external_output_metadata.get_output_filenames_by_dataset( dataset, self.sa_session ).filename_out )
try:
assert context.get( 'line_count', None ) is not None
if ( not dataset.datatype.composite_type and dataset.dataset.is_multi_byte() ) or self.tool.is_multi_byte:
dataset.set_peek( line_count=context['line_count'], is_multi_byte=True )
else:
dataset.set_peek( line_count=context['line_count'] )
except:
if ( not dataset.datatype.composite_type and dataset.dataset.is_multi_byte() ) or self.tool.is_multi_byte:
dataset.set_peek( is_multi_byte=True )
else:
dataset.set_peek()
try:
# set the name if provided by the tool
dataset.name = context['name']
except:
pass
else:
dataset.blurb = "empty"
if dataset.ext == 'auto':
dataset.extension = 'txt'
self.sa_session.add( dataset )
if context['stderr']:
dataset_assoc.dataset.dataset.state = model.Dataset.states.ERROR
else:
dataset_assoc.dataset.dataset.state = model.Dataset.states.OK
# If any of the rest of the finish method below raises an
# exception, the fail method will run and set the datasets to
# ERROR. The user will never see that the datasets are in error if
# they were flushed as OK here, since upon doing so, the history
# panel stops checking for updates. So allow the
# self.sa_session.flush() at the bottom of this method set
# the state instead.
for pja in job.post_job_actions:
ActionBox.execute(self.app, self.sa_session, pja.post_job_action, job)
# Flush all the dataset and job changes above. Dataset state changes
# will now be seen by the user.
self.sa_session.flush()
# Save stdout and stderr
if len( stdout ) > 32768:
log.error( "stdout for job %d is greater than 32K, only first part will be logged to database" % job.id )
job.stdout = stdout[:32768]
if len( stderr ) > 32768:
log.error( "stderr for job %d is greater than 32K, only first part will be logged to database" % job.id )
job.stderr = stderr[:32768]
# custom post process setup
inp_data = dict( [ ( da.name, da.dataset ) for da in job.input_datasets ] )
out_data = dict( [ ( da.name, da.dataset ) for da in job.output_datasets ] )
inp_data.update( [ ( da.name, da.dataset ) for da in job.input_library_datasets ] )
out_data.update( [ ( da.name, da.dataset ) for da in job.output_library_datasets ] )
param_dict = dict( [ ( p.name, p.value ) for p in job.parameters ] ) # why not re-use self.param_dict here? ##dunno...probably should, this causes tools.parameters.basic.UnvalidatedValue to be used in following methods instead of validated and transformed values during i.e. running workflows
param_dict = self.tool.params_from_strings( param_dict, self.app )
# Check for and move associated_files
self.tool.collect_associated_files(out_data, self.working_directory)
gitd = self.sa_session.query( model.GenomeIndexToolData ).filter_by( job=job ).first()
if gitd:
self.tool.collect_associated_files({'' : gitd}, self.working_directory)
# Create generated output children and primary datasets and add to param_dict
collected_datasets = {'children':self.tool.collect_child_datasets(out_data, self.working_directory),'primary':self.tool.collect_primary_datasets(out_data, self.working_directory)}
param_dict.update({'__collected_datasets__':collected_datasets})
# Certain tools require tasks to be completed after job execution
# ( this used to be performed in the "exec_after_process" hook, but hooks are deprecated ).
self.tool.exec_after_process( self.queue.app, inp_data, out_data, param_dict, job = job )
# Call 'exec_after_process' hook
self.tool.call_hook( 'exec_after_process', self.queue.app, inp_data=inp_data,
out_data=out_data, param_dict=param_dict,
tool=self.tool, stdout=stdout, stderr=stderr )
job.command_line = self.command_line
bytes = 0
# Once datasets are collected, set the total dataset size (includes extra files)
for dataset_assoc in job.output_datasets:
dataset_assoc.dataset.dataset.set_total_size()
bytes += dataset_assoc.dataset.dataset.get_total_size()
if job.user:
job.user.total_disk_usage += bytes
# fix permissions
for path in [ dp.real_path for dp in self.get_output_fnames() ]:
util.umask_fix_perms( path, self.app.config.umask, 0666, self.app.config.gid )
self.sa_session.flush()
log.debug( 'job %d ended' % self.job_id )
if self.app.config.cleanup_job == 'always' or ( not stderr and self.app.config.cleanup_job == 'onsuccess' ):
self.cleanup()
def render_body(context,**pageargs):
context.caller_stack._push_frame()
try:
__M_locals = __M_dict_builtin(pageargs=pageargs)
basestring = context.get('basestring', UNDEFINED)
errors = context.get('errors', UNDEFINED)
tuple = context.get('tuple', UNDEFINED)
int = context.get('int', UNDEFINED)
h = context.get('h', UNDEFINED)
app = context.get('app', UNDEFINED)
workflow = context.get('workflow', UNDEFINED)
def do_inputs(inputs,values,errors,prefix,step,other_values=None):
return render_do_inputs(context.locals_(__M_locals),inputs,values,errors,prefix,step,other_values)
len = context.get('len', UNDEFINED)
dict = context.get('dict', UNDEFINED)
t = context.get('t', UNDEFINED)
enumerate = context.get('enumerate', UNDEFINED)
has_upgrade_messages = context.get('has_upgrade_messages', UNDEFINED)
steps = context.get('steps', UNDEFINED)
isinstance = context.get('isinstance', UNDEFINED)
__M_writer = context.writer()
# SOURCE LINE 1
__M_writer(u'\n\n')
# SOURCE LINE 13
__M_writer(u'\n\n')
# SOURCE LINE 32
__M_writer(u'\n\n')
# SOURCE LINE 34
from galaxy.tools.parameters import DataToolParameter, RuntimeValue
from galaxy.jobs.actions.post import ActionBox
import re
import colorsys
import random
wf_parms = {}
for step in steps:
for v in step.state.inputs.itervalues():
if isinstance(v, basestring):
for rematch in re.findall('\$\{.+?\}', v):
if rematch[2:-1] not in wf_parms:
wf_parms[rematch[2:-1]] = ""
if wf_parms:
hue_offset = 1.0 / len(wf_parms)
hue = 0.0
for k in wf_parms.iterkeys():
wf_parms[k] = "#%X%X%X" % tuple([int(x * 255) for x in colorsys.hsv_to_rgb(hue, .1, .9)])
hue += hue_offset
__M_locals.update(__M_dict_builtin([(__M_key, __M_locals_builtin()[__M_key]) for __M_key in ['hue','hue_offset','wf_parms','ActionBox','DataToolParameter','rematch','k','random','re','step','RuntimeValue','colorsys','v','x'] if __M_key in __M_locals_builtin()]))
# SOURCE LINE 54
__M_writer(u'\n\n')
# SOURCE LINE 91
__M_writer(u'\n\n')
# SOURCE LINE 163
__M_writer(u'\n\n<h2>Running workflow "')
# SOURCE LINE 165
__M_writer(unicode(h.to_unicode( workflow.name )))
__M_writer(u'"</h2>\n\n')
# SOURCE LINE 167
if has_upgrade_messages:
# SOURCE LINE 168
__M_writer(u'<div class="warningmessage">\n Problems were encountered when loading this workflow, likely due to tool\n version changes. Missing parameter values have been replaced with default.\n Please review the parameter values below.\n</div>\n')
# SOURCE LINE 174
__M_writer(u'\n')
# SOURCE LINE 175
if workflow.annotation:
# SOURCE LINE 176
__M_writer(u' <div class="workflow-annotation">Annotation: ')
__M_writer(unicode(workflow.annotation))
__M_writer(u'</div>\n <hr/>\n')
# SOURCE LINE 179
__M_writer(u'\n<form id="tool_form" name="tool_form" method="POST">\n')
# SOURCE LINE 182
__M_writer(u'\n\n')
# SOURCE LINE 184
if wf_parms:
# SOURCE LINE 185
__M_writer(u'<div class="metadataForm">\n <div class="metadataFormTitle">Workflow Parameters</div>\n <div class="metadataFormBody">\n')
# SOURCE LINE 188
for parm in wf_parms:
# SOURCE LINE 189
__M_writer(u" <div class='form-row'><label style='width:100px;'>")
__M_writer(unicode(parm))
__M_writer(u'<input style="border:2px solid ')
__M_writer(unicode(wf_parms[parm]))
__M_writer(u';border-left-width:8px;" type="text" class=\'wf_parm_input ptag_')
__M_writer(unicode(parm))
__M_writer(u'\' name="wf_parm|')
__M_writer(unicode(parm))
__M_writer(u'" value=""/></label></div>\n')
# SOURCE LINE 191
__M_writer(u' </div>\n</div>\n <script type="text/javascript">\n // Set the change hooks for workflow parameters.\n $(document).ready(function () {\n $(\'.wf_parm_input\').bind(\'change keypress keyup\', function(event){\n // DBTODO This is probably not reliable. Ensure we have the right class.\n var new_text = $(this).val();\n if (new_text === \'\'){\n var tag_id = $(this).attr("class").split(\' \')[1].substring(5);\n // Set text properly.\n $(\'.wfpspan.wf_parm__\'+tag_id).text(tag_id);\n }else{\n var tag_id = $(this).attr("class").split(\' \')[1].substring(5);\n // Set text properly.\n $(\'.wfpspan.wf_parm__\'+tag_id).text(new_text);\n // Now set the hidden input to the generated text.\n $(\'.wfpspan.wf_parm__\'+tag_id).not(\'.pja_wfp\').each(function(){\n // var new_text = $(this).parent().text();\n $(this).parent().siblings().children().val(new_text);\n });\n }\n });\n });\n </script>\n')
# SOURCE LINE 217
__M_writer(u'\n')
# SOURCE LINE 218
for i, step in enumerate( steps ):
# SOURCE LINE 219
if step.type == 'tool' or step.type is None:
# SOURCE LINE 220
__M_writer(u' ')
tool = app.toolbox.tools_by_id[step.tool_id]
__M_locals.update(__M_dict_builtin([(__M_key, __M_locals_builtin()[__M_key]) for __M_key in ['tool'] if __M_key in __M_locals_builtin()]))
__M_writer(u'\n <input type="hidden" name="')
# SOURCE LINE 221
__M_writer(unicode(step.id))
__M_writer(u'|tool_state" value="')
__M_writer(unicode(step.state.encode( tool, app )))
__M_writer(u'">\n <div class="toolForm">\n <div class="toolFormTitle">\n Step ')
# SOURCE LINE 224
__M_writer(unicode(int(step.order_index)+1))
__M_writer(u': ')
__M_writer(unicode(tool.name))
__M_writer(u'\n')
# SOURCE LINE 225
if step.annotations:
# SOURCE LINE 226
__M_writer(u' <div class="step-annotation">Annotation: ')
__M_writer(unicode(h.to_unicode( step.annotations[0].annotation )))
__M_writer(u'</div>\n')
# SOURCE LINE 228
__M_writer(u' </div>\n <div class="toolFormBody">\n ')
# SOURCE LINE 230
__M_writer(unicode(do_inputs( tool.inputs, step.state.inputs, errors.get( step.id, dict() ), "", step )))
__M_writer(u'\n')
# SOURCE LINE 231
if step.post_job_actions:
# SOURCE LINE 232
__M_writer(u" <hr/>\n <div class='form-row'>\n")
# SOURCE LINE 234
if len(step.post_job_actions) > 1:
# SOURCE LINE 235
__M_writer(u' <label>Actions:</label>\n')
# SOURCE LINE 236
else:
# SOURCE LINE 237
__M_writer(u' <label>Action:</label>\n')
# SOURCE LINE 239
pja_ss_all = []
for pja_ss in [ActionBox.get_short_str(pja) for pja in step.post_job_actions]:
for rematch in re.findall('\$\{.+?\}', pja_ss):
pja_ss = pja_ss.replace(rematch, '<span style="background-color:%s" class="wfpspan wf_parm__%s pja_wfp">%s</span>' % (wf_parms[rematch[2:-1]], rematch[2:-1], rematch[2:-1]))
pja_ss_all.append(pja_ss)
__M_locals.update(__M_dict_builtin([(__M_key, __M_locals_builtin()[__M_key]) for __M_key in ['rematch','pja_ss_all','pja','pja_ss'] if __M_key in __M_locals_builtin()]))
# SOURCE LINE 245
__M_writer(u'\n ')
# SOURCE LINE 246
__M_writer(unicode('<br/>'.join(pja_ss_all)))
__M_writer(u'\n </div>\n')
# SOURCE LINE 249
__M_writer(u' </div>\n </div>\n')
# SOURCE LINE 251
else:
# SOURCE LINE 252
__M_writer(u' ')
module = step.module
__M_locals.update(__M_dict_builtin([(__M_key, __M_locals_builtin()[__M_key]) for __M_key in ['module'] if __M_key in __M_locals_builtin()]))
__M_writer(u'\n <input type="hidden" name="')
# SOURCE LINE 253
__M_writer(unicode(step.id))
__M_writer(u'|tool_state" value="')
__M_writer(unicode(module.encode_runtime_state( t, step.state )))
__M_writer(u'">\n <div class="toolForm">\n <div class="toolFormTitle">\n Step ')
# SOURCE LINE 256
__M_writer(unicode(int(step.order_index)+1))
__M_writer(u': ')
__M_writer(unicode(module.name))
__M_writer(u'\n')
# SOURCE LINE 257
if step.annotations:
# SOURCE LINE 258
__M_writer(u' <div class="step-annotation">Annotation: ')
__M_writer(unicode(step.annotations[0].annotation))
__M_writer(u'</div>\n')
# SOURCE LINE 260
__M_writer(u' </div>\n <div class="toolFormBody">\n ')
# SOURCE LINE 262
__M_writer(unicode(do_inputs( module.get_runtime_inputs(), step.state.inputs, errors.get( step.id, dict() ), "", step )))
__M_writer(u'\n </div>\n </div>\n')
# SOURCE LINE 267
__M_writer(u'<input type="submit" name="run_workflow" value="Run workflow" />\n</form>')
return ''
finally:
context.caller_stack._pop_frame()
def render_body(context,**pageargs):
context.caller_stack._push_frame()
try:
__M_locals = __M_dict_builtin(pageargs=pageargs)
isinstance = context.get('isinstance', UNDEFINED)
basestring = context.get('basestring', UNDEFINED)
errors = context.get('errors', UNDEFINED)
tuple = context.get('tuple', UNDEFINED)
int = context.get('int', UNDEFINED)
h = context.get('h', UNDEFINED)
history_id = context.get('history_id', UNDEFINED)
workflow = context.get('workflow', UNDEFINED)
def do_inputs(inputs,values,errors,prefix,step,other_values=None,already_used=None):
return render_do_inputs(context.locals_(__M_locals),inputs,values,errors,prefix,step,other_values,already_used)
len = context.get('len', UNDEFINED)
step_version_changes = context.get('step_version_changes', UNDEFINED)
dict = context.get('dict', UNDEFINED)
t = context.get('t', UNDEFINED)
enumerate = context.get('enumerate', UNDEFINED)
has_upgrade_messages = context.get('has_upgrade_messages', UNDEFINED)
steps = context.get('steps', UNDEFINED)
trans = context.get('trans', UNDEFINED)
__M_writer = context.writer()
# SOURCE LINE 1
__M_writer(u'\n\n')
# SOURCE LINE 243
__M_writer(u'\n\n')
# SOURCE LINE 298
__M_writer(u'\n\n')
# SOURCE LINE 300
from galaxy.tools.parameters import DataToolParameter, RuntimeValue
from galaxy.tools.parameters import DataCollectionToolParameter
from galaxy.jobs.actions.post import ActionBox
import re
import colorsys
import random
used_accumulator = []
wf_parms = {}
for step in steps:
for v in [ActionBox.get_short_str(pja) for pja in step.post_job_actions] + step.state.inputs.values():
if isinstance(v, basestring):
for rematch in re.findall('\$\{.+?\}', v):
if rematch[2:-1] not in wf_parms:
wf_parms[rematch[2:-1]] = ""
if wf_parms:
hue_offset = 1.0 / len(wf_parms)
hue = 0.0
for k in wf_parms.iterkeys():
wf_parms[k] = "#%X%X%X" % tuple([int(x * 255) for x in colorsys.hsv_to_rgb(hue, .1, .9)])
hue += hue_offset
__M_locals_builtin_stored = __M_locals_builtin()
__M_locals.update(__M_dict_builtin([(__M_key, __M_locals_builtin_stored[__M_key]) for __M_key in ['hue','hue_offset','wf_parms','ActionBox','DataToolParameter','rematch','used_accumulator','k','random','pja','re','step','RuntimeValue','colorsys','v','DataCollectionToolParameter','x'] if __M_key in __M_locals_builtin_stored]))
# SOURCE LINE 323
__M_writer(u'\n\n')
# SOURCE LINE 365
__M_writer(u'\n\n')
# SOURCE LINE 470
__M_writer(u'\n\n<div id=\'ec_button_container\'>\n <span class="action-button" id="show_all_tool_body">Expand All</span>\n <span class="action-button" id="hide_all_tool_body">Collapse</span>\n</div>\n\n<h2>Running workflow "')
# SOURCE LINE 477
__M_writer(unicode(h.to_unicode( workflow.name )))
__M_writer(u'"</h2>\n\n')
# SOURCE LINE 479
if has_upgrade_messages:
# SOURCE LINE 480
__M_writer(u'<div class="warningmessage">\n Problems were encountered when loading this workflow, likely due to tool\n version changes. Missing parameter values have been replaced with default.\n Please review the parameter values below.\n</div>\n')
pass
# SOURCE LINE 486
__M_writer(u'\n')
# SOURCE LINE 487
if step_version_changes:
# SOURCE LINE 488
__M_writer(u' <div class="infomessage">\n The following tools are beinge executed with a different version from\n what was available when this workflow was last saved because the\n previous version is no longer available for use on this galaxy\n instance.\n To upgrade your workflow and dismiss this message simply edit the\n workflow and re-save it to update the stored tool version.\n <ul>\n')
# SOURCE LINE 496
for vc in step_version_changes:
# SOURCE LINE 497
__M_writer(u' <li>')
__M_writer(unicode(vc))
__M_writer(u'</li>\n')
pass
# SOURCE LINE 499
__M_writer(u' </ul>\n </div>\n')
pass
# SOURCE LINE 502
__M_writer(u'\n')
# SOURCE LINE 503
if workflow.annotation:
# SOURCE LINE 504
__M_writer(u' <div class="workflow-annotation">')
__M_writer(unicode(workflow.annotation))
__M_writer(u'</div>\n <hr/>\n')
pass
# SOURCE LINE 507
__M_writer(u'\n<form id="tool_form" name="tool_form" method="POST">\n')
# SOURCE LINE 510
__M_writer(u'\n')
# SOURCE LINE 511
if wf_parms:
# SOURCE LINE 512
__M_writer(u'<div class="metadataForm">\n <div class="metadataFormTitle">Workflow Parameters</div>\n <div class="metadataFormBody">\n')
# SOURCE LINE 515
for parm in wf_parms:
# SOURCE LINE 516
__M_writer(u" <div class='form-row'><label style='width:100px;'>")
__M_writer(unicode(parm))
__M_writer(u'<input style="border:2px solid ')
__M_writer(unicode(wf_parms[parm]))
__M_writer(u';border-left-width:8px;" type="text" class=\'wf_parm_input ptag_')
__M_writer(unicode(parm))
__M_writer(u'\' name="wf_parm|')
__M_writer(unicode(parm))
__M_writer(u'" value=""/></label></div>\n')
pass
# SOURCE LINE 518
__M_writer(u' </div>\n</div>\n <script type="text/javascript">\n // Set the change hooks for workflow parameters.\n $(document).ready(function () {\n $(\'.wf_parm_input\').bind(\'change keypress keyup\', function(event){\n // DBTODO This is probably not reliable. Ensure we have the right class.\n var new_text = $(this).val();\n if (new_text === \'\'){\n var tag_id = $(this).attr("class").split(\' \')[1].substring(5);\n // Set text properly.\n $(\'.wfpspan.wf_parm__\'+tag_id).text(tag_id);\n }else{\n var tag_id = $(this).attr("class").split(\' \')[1].substring(5);\n // Set text properly.\n $(\'.wfpspan.wf_parm__\'+tag_id).text(new_text);\n // Now set the hidden input to the generated text.\n $(\'.wfpspan.wf_parm__\'+tag_id).not(\'.pja_wfp\').each(function(){\n var new_text = $(this).parent().text();\n $(this).parent().siblings().children().val(new_text);\n });\n }\n });\n });\n </script>\n')
pass
# SOURCE LINE 544
for i, step in enumerate( steps ):
# SOURCE LINE 545
__M_writer(u' <!-- Only way module would be missing is if tool is missing, but\n that would cause missing_tools.mako to render instead of this\n template. -->\n ')
# SOURCE LINE 548
module = step.module
__M_locals_builtin_stored = __M_locals_builtin()
__M_locals.update(__M_dict_builtin([(__M_key, __M_locals_builtin_stored[__M_key]) for __M_key in ['module'] if __M_key in __M_locals_builtin_stored]))
__M_writer(u'\n <input type="hidden" name="')
# SOURCE LINE 549
__M_writer(unicode(step.id))
__M_writer(u'|tool_state" value="')
__M_writer(unicode(module.encode_runtime_state( t, step.state )))
__M_writer(u'">\n')
# SOURCE LINE 550
if step.type == 'tool' or step.type is None:
# SOURCE LINE 551
__M_writer(u' ')
tool = trans.app.toolbox.get_tool( step.tool_id )
__M_locals_builtin_stored = __M_locals_builtin()
__M_locals.update(__M_dict_builtin([(__M_key, __M_locals_builtin_stored[__M_key]) for __M_key in ['tool'] if __M_key in __M_locals_builtin_stored]))
# SOURCE LINE 553
__M_writer(u'\n <div class="toolForm">\n <div class="toolFormTitle">\n <span class=\'title_ul_text\'>Step ')
# SOURCE LINE 556
__M_writer(unicode(int(step.order_index)+1))
__M_writer(u': ')
__M_writer(unicode(tool.name))
__M_writer(u'</span>\n')
# SOURCE LINE 557
if tool.version:
# SOURCE LINE 558
__M_writer(u' (version ')
__M_writer(unicode(tool.version))
__M_writer(u')\n')
pass
# SOURCE LINE 560
if step.annotations:
# SOURCE LINE 561
__M_writer(u' <div class="step-annotation">')
__M_writer(unicode(h.to_unicode( step.annotations[0].annotation )))
__M_writer(u'</div>\n')
pass
# SOURCE LINE 563
__M_writer(u' </div>\n <div class="toolFormBody">\n ')
# SOURCE LINE 565
__M_writer(unicode(do_inputs( tool.inputs, step.state.inputs, errors.get( step.id, dict() ), "", step, None, used_accumulator )))
__M_writer(u'\n')
# SOURCE LINE 566
if step.post_job_actions:
# SOURCE LINE 567
__M_writer(u" <hr/>\n <div class='form-row'>\n")
# SOURCE LINE 569
if len(step.post_job_actions) > 1:
# SOURCE LINE 570
__M_writer(u' <label>Actions:</label>\n')
# SOURCE LINE 571
else:
# SOURCE LINE 572
__M_writer(u' <label>Action:</label>\n')
pass
# SOURCE LINE 574
__M_writer(u' ')
pja_ss_all = []
for pja_ss in [ActionBox.get_short_str(pja) for pja in step.post_job_actions]:
for rematch in re.findall('\$\{.+?\}', pja_ss):
pja_ss = pja_ss.replace(rematch, '<span style="background-color:%s" class="wfpspan wf_parm__%s pja_wfp">%s</span>' % (wf_parms[rematch[2:-1]], rematch[2:-1], rematch[2:-1]))
pja_ss_all.append(pja_ss)
__M_locals_builtin_stored = __M_locals_builtin()
__M_locals.update(__M_dict_builtin([(__M_key, __M_locals_builtin_stored[__M_key]) for __M_key in ['rematch','pja_ss_all','pja','pja_ss'] if __M_key in __M_locals_builtin_stored]))
# SOURCE LINE 580
__M_writer(u'\n ')
# SOURCE LINE 581
__M_writer(unicode('<br/>'.join(pja_ss_all)))
__M_writer(u'\n </div>\n')
pass
# SOURCE LINE 584
__M_writer(u' </div>\n </div>\n')
# SOURCE LINE 586
else:
# SOURCE LINE 587
__M_writer(u' <div class="toolForm">\n <div class="toolFormTitle">\n <span class=\'title_ul_text\'>Step ')
# SOURCE LINE 589
__M_writer(unicode(int(step.order_index)+1))
__M_writer(u': ')
__M_writer(unicode(module.name))
__M_writer(u'</span>\n')
# SOURCE LINE 590
if step.annotations:
# SOURCE LINE 591
__M_writer(u' <div class="step-annotation">')
__M_writer(unicode(step.annotations[0].annotation))
__M_writer(u'</div>\n')
pass
# SOURCE LINE 593
__M_writer(u' </div>\n <div class="toolFormBody">\n ')
# SOURCE LINE 595
# Filter possible inputs to data types that are valid for subsequent steps
type_filter = []
for oc in step.output_connections:
for ic in oc.input_step.module.get_data_inputs():
if 'extensions' in ic and ic['name'] == oc.input_name:
type_filter += ic['extensions']
if not type_filter:
type_filter = ['data']
__M_locals_builtin_stored = __M_locals_builtin()
__M_locals.update(__M_dict_builtin([(__M_key, __M_locals_builtin_stored[__M_key]) for __M_key in ['ic','oc','type_filter'] if __M_key in __M_locals_builtin_stored]))
# SOURCE LINE 604
__M_writer(u'\n ')
# SOURCE LINE 605
__M_writer(unicode(do_inputs( module.get_runtime_inputs(type_filter), step.state.inputs, errors.get( step.id, dict() ), "", step, None, used_accumulator )))
__M_writer(u'\n </div>\n </div>\n')
pass
pass
# SOURCE LINE 610
if history_id is None:
# SOURCE LINE 611
__M_writer(u' <p id=\'new_history_p\'>\n <input type="checkbox" name=\'new_history\' value="true" id=\'new_history_cbx\'/><label for=\'new_history_cbx\'>Send results to a new history </label>\n <span id="new_history_input">named: <input type=\'text\' name=\'new_history_name\' value=\'')
# SOURCE LINE 613
__M_writer(filters.html_escape(unicode( h.to_unicode( workflow.name ) )))
__M_writer(u"'/></span>\n </p>\n")
pass
# SOURCE LINE 616
__M_writer(u'<input type="submit" class="btn btn-primary" name="run_workflow" value="Run workflow" />\n</form>\n')
return ''
finally:
context.caller_stack._pop_frame()
def get_post_job_actions(self, incoming):
return ActionBox.handle_incoming(incoming)
def _workflow_to_dict_run(self, trans, stored):
"""
Builds workflow dictionary used by run workflow form
"""
workflow = stored.latest_workflow
if len(workflow.steps) == 0:
raise exceptions.MessageException('Workflow cannot be run because it does not have any steps.')
if attach_ordered_steps(workflow, workflow.steps):
raise exceptions.MessageException('Workflow cannot be run because it contains cycles.')
trans.workflow_building_mode = workflow_building_modes.USE_HISTORY
module_injector = WorkflowModuleInjector(trans)
has_upgrade_messages = False
step_version_changes = []
missing_tools = []
errors = {}
for step in workflow.steps:
try:
module_injector.inject(step, steps=workflow.steps, exact_tools=False)
except exceptions.ToolMissingException:
if step.tool_id not in missing_tools:
missing_tools.append(step.tool_id)
continue
if step.upgrade_messages:
has_upgrade_messages = True
if step.type == 'tool' or step.type is None:
if step.module.version_changes:
step_version_changes.extend(step.module.version_changes)
step_errors = step.module.get_errors()
if step_errors:
errors[step.id] = step_errors
if missing_tools:
workflow.annotation = self.get_item_annotation_str(trans.sa_session, trans.user, workflow)
raise exceptions.MessageException('Following tools missing: %s' % missing_tools)
workflow.annotation = self.get_item_annotation_str(trans.sa_session, trans.user, workflow)
step_order_indices = {}
for step in workflow.steps:
step_order_indices[step.id] = step.order_index
step_models = []
for i, step in enumerate(workflow.steps):
step_model = None
if step.type == 'tool':
incoming = {}
tool = trans.app.toolbox.get_tool(step.tool_id, tool_version=step.tool_version)
params_to_incoming(incoming, tool.inputs, step.state.inputs, trans.app)
step_model = tool.to_json(trans, incoming, workflow_building_mode=workflow_building_modes.USE_HISTORY)
step_model['post_job_actions'] = [{
'short_str' : ActionBox.get_short_str(pja),
'action_type' : pja.action_type,
'output_name' : pja.output_name,
'action_arguments' : pja.action_arguments
} for pja in step.post_job_actions]
else:
inputs = step.module.get_runtime_inputs(connections=step.output_connections)
step_model = {
'inputs' : [input.to_dict(trans) for input in inputs.values()]
}
step_model['step_type'] = step.type
step_model['step_label'] = step.label
step_model['step_name'] = step.module.get_name()
step_model['step_version'] = step.module.get_version()
step_model['step_index'] = step.order_index
step_model['output_connections'] = [{
'input_step_index' : step_order_indices.get(oc.input_step_id),
'output_step_index' : step_order_indices.get(oc.output_step_id),
'input_name' : oc.input_name,
'output_name' : oc.output_name
} for oc in step.output_connections]
if step.annotations:
step_model['annotation'] = step.annotations[0].annotation
if step.upgrade_messages:
step_model['messages'] = step.upgrade_messages
step_models.append(step_model)
return {
'id': trans.app.security.encode_id(stored.id),
'history_id': trans.app.security.encode_id(trans.history.id) if trans.history else None,
'name': stored.name,
'steps': step_models,
'step_version_changes': step_version_changes,
'has_upgrade_messages': has_upgrade_messages,
'workflow_resource_parameters': self._workflow_resource_parameters(trans, stored, workflow),
}
def create(self, trans, payload, **kwd):
"""
POST /api/workflows
We're not creating workflows from the api. Just execute for now.
However, we will import them if installed_repository_file is specified
"""
# ------------------------------------------------------------------------------- #
### RPARK: dictionary containing which workflows to change and edit ###
param_map = {}
if (payload.has_key('parameters')):
param_map = payload['parameters']
# ------------------------------------------------------------------------------- #
if 'workflow_id' not in payload:
# create new
if 'installed_repository_file' in payload:
workflow_controller = trans.webapp.controllers['workflow']
result = workflow_controller.import_workflow(trans=trans,
cntrller='api',
**payload)
return result
trans.response.status = 403
return "Either workflow_id or installed_repository_file must be specified"
if 'installed_repository_file' in payload:
trans.response.status = 403
return "installed_repository_file may not be specified with workflow_id"
stored_workflow = trans.sa_session.query(
self.app.model.StoredWorkflow).get(
trans.security.decode_id(payload['workflow_id']))
if stored_workflow.user != trans.user and not trans.user_is_admin():
if trans.sa_session.query(
trans.app.model.StoredWorkflowUserShareAssociation
).filter_by(user=trans.user,
stored_workflow=stored_workflow).count() == 0:
trans.response.status = 400
return ("Workflow is not owned by or shared with current user")
workflow = stored_workflow.latest_workflow
if payload['history'].startswith('hist_id='):
#Passing an existing history to use.
history = trans.sa_session.query(self.app.model.History).get(
trans.security.decode_id(payload['history'][8:]))
if history.user != trans.user and not trans.user_is_admin():
trans.response.status = 400
return "Invalid History specified."
else:
history = self.app.model.History(name=payload['history'],
user=trans.user)
trans.sa_session.add(history)
trans.sa_session.flush()
ds_map = payload['ds_map']
add_to_history = 'no_add_to_history' not in payload
for k in ds_map:
try:
if ds_map[k]['src'] == 'ldda':
ldda = trans.sa_session.query(
self.app.model.LibraryDatasetDatasetAssociation).get(
trans.security.decode_id(ds_map[k]['id']))
assert trans.user_is_admin(
) or trans.app.security_agent.can_access_dataset(
trans.get_current_user_roles(), ldda.dataset)
hda = ldda.to_history_dataset_association(
history, add_to_history=add_to_history)
elif ds_map[k]['src'] == 'ld':
ldda = trans.sa_session.query(
self.app.model.LibraryDataset).get(
trans.security.decode_id(
ds_map[k]
['id'])).library_dataset_dataset_association
assert trans.user_is_admin(
) or trans.app.security_agent.can_access_dataset(
trans.get_current_user_roles(), ldda.dataset)
hda = ldda.to_history_dataset_association(
history, add_to_history=add_to_history)
elif ds_map[k]['src'] == 'hda':
# Get dataset handle, add to dict and history if necessary
hda = trans.sa_session.query(
self.app.model.HistoryDatasetAssociation).get(
trans.security.decode_id(ds_map[k]['id']))
assert trans.user_is_admin(
) or trans.app.security_agent.can_access_dataset(
trans.get_current_user_roles(), hda.dataset)
else:
trans.response.status = 400
return "Unknown dataset source '%s' specified." % ds_map[
k]['src']
if add_to_history and hda.history != history:
hda = hda.copy()
history.add_dataset(hda)
ds_map[k]['hda'] = hda
except AssertionError:
trans.response.status = 400
return "Invalid Dataset '%s' Specified" % ds_map[k]['id']
if not workflow:
trans.response.status = 400
return "Workflow not found."
if len(workflow.steps) == 0:
trans.response.status = 400
return "Workflow cannot be run because it does not have any steps"
if workflow.has_cycles:
trans.response.status = 400
return "Workflow cannot be run because it contains cycles"
if workflow.has_errors:
trans.response.status = 400
return "Workflow cannot be run because of validation errors in some steps"
# Build the state for each step
rval = {}
for step in workflow.steps:
step_errors = None
if step.type == 'tool' or step.type is None:
step.module = module_factory.from_workflow_step(trans, step)
# Check for missing parameters
step.upgrade_messages = step.module.check_and_update_state()
# Any connected input needs to have value DummyDataset (these
# are not persisted so we need to do it every time)
step.module.add_dummy_datasets(
connections=step.input_connections)
step.state = step.module.state
####################################################
####################################################
# RPARK: IF TOOL_NAME IN PARAMETER MAP #
if step.tool_id in param_map:
change_param = param_map[step.tool_id]['param']
change_value = param_map[step.tool_id]['value']
step.state.inputs[change_param] = change_value
####################################################
####################################################
if step.tool_errors:
trans.response.status = 400
return "Workflow cannot be run because of validation errors in some steps: %s" % step_errors
if step.upgrade_messages:
trans.response.status = 400
return "Workflow cannot be run because of step upgrade messages: %s" % step.upgrade_messages
else:
# This is an input step. Make sure we have an available input.
if step.type == 'data_input' and str(step.id) not in ds_map:
trans.response.status = 400
return "Workflow cannot be run because an expected input step '%s' has no input dataset." % step.id
step.module = module_factory.from_workflow_step(trans, step)
step.state = step.module.get_runtime_state()
step.input_connections_by_name = dict(
(conn.input_name, conn) for conn in step.input_connections)
# Run each step, connecting outputs to inputs
workflow_invocation = self.app.model.WorkflowInvocation()
workflow_invocation.workflow = workflow
outputs = util.odict.odict()
rval['history'] = trans.security.encode_id(history.id)
rval['outputs'] = []
for i, step in enumerate(workflow.steps):
job = None
if step.type == 'tool' or step.type is None:
tool = self.app.toolbox.get_tool(step.tool_id)
def callback(input, value, prefixed_name, prefixed_label):
if isinstance(input, DataToolParameter):
if prefixed_name in step.input_connections_by_name:
conn = step.input_connections_by_name[
prefixed_name]
return outputs[conn.output_step.id][
conn.output_name]
visit_input_values(tool.inputs, step.state.inputs, callback)
job, out_data = tool.execute(trans,
step.state.inputs,
history=history)
outputs[step.id] = out_data
for pja in step.post_job_actions:
if pja.action_type in ActionBox.immediate_actions:
ActionBox.execute(self.app,
trans.sa_session,
pja,
job,
replacement_dict=None)
else:
job.add_post_job_action(pja)
for v in out_data.itervalues():
rval['outputs'].append(trans.security.encode_id(v.id))
else:
#This is an input step. Use the dataset inputs from ds_map.
job, out_data = step.module.execute(trans, step.state)
outputs[step.id] = out_data
outputs[step.id]['output'] = ds_map[str(step.id)]['hda']
workflow_invocation_step = self.app.model.WorkflowInvocationStep()
workflow_invocation_step.workflow_invocation = workflow_invocation
workflow_invocation_step.workflow_step = step
workflow_invocation_step.job = job
trans.sa_session.add(workflow_invocation)
trans.sa_session.flush()
return rval
def _workflow_to_dict_run(self, trans, stored):
"""
Builds workflow dictionary used by run workflow form
"""
workflow = stored.latest_workflow
if len(workflow.steps) == 0:
raise exceptions.MessageException(
'Workflow cannot be run because it does not have any steps.')
if attach_ordered_steps(workflow, workflow.steps):
raise exceptions.MessageException(
'Workflow cannot be run because it contains cycles.')
trans.workflow_building_mode = workflow_building_modes.USE_HISTORY
module_injector = WorkflowModuleInjector(trans)
has_upgrade_messages = False
step_version_changes = []
missing_tools = []
errors = {}
for step in workflow.steps:
try:
module_injector.inject(step,
steps=workflow.steps,
exact_tools=False)
except exceptions.ToolMissingException:
if step.tool_id not in missing_tools:
missing_tools.append(step.tool_id)
continue
if step.upgrade_messages:
has_upgrade_messages = True
if step.type == 'tool' or step.type is None:
if step.module.version_changes:
step_version_changes.extend(step.module.version_changes)
step_errors = step.module.get_errors()
if step_errors:
errors[step.id] = step_errors
if missing_tools:
workflow.annotation = self.get_item_annotation_str(
trans.sa_session, trans.user, workflow)
raise exceptions.MessageException('Following tools missing: %s' %
', '.join(missing_tools))
workflow.annotation = self.get_item_annotation_str(
trans.sa_session, trans.user, workflow)
step_order_indices = {}
for step in workflow.steps:
step_order_indices[step.id] = step.order_index
step_models = []
for i, step in enumerate(workflow.steps):
step_model = None
if step.type == 'tool':
incoming = {}
tool = trans.app.toolbox.get_tool(
step.tool_id, tool_version=step.tool_version)
params_to_incoming(incoming, tool.inputs, step.state.inputs,
trans.app)
step_model = tool.to_json(
trans,
incoming,
workflow_building_mode=workflow_building_modes.USE_HISTORY)
step_model['post_job_actions'] = [{
'short_str':
ActionBox.get_short_str(pja),
'action_type':
pja.action_type,
'output_name':
pja.output_name,
'action_arguments':
pja.action_arguments
} for pja in step.post_job_actions]
else:
inputs = step.module.get_runtime_inputs(
connections=step.output_connections)
step_model = {
'inputs':
[input.to_dict(trans) for input in inputs.values()]
}
step_model['step_type'] = step.type
step_model['step_label'] = step.label
step_model['step_name'] = step.module.get_name()
step_model['step_version'] = step.module.get_version()
step_model['step_index'] = step.order_index
step_model['output_connections'] = [{
'input_step_index':
step_order_indices.get(oc.input_step_id),
'output_step_index':
step_order_indices.get(oc.output_step_id),
'input_name':
oc.input_name,
'output_name':
oc.output_name
} for oc in step.output_connections]
if step.annotations:
step_model['annotation'] = step.annotations[0].annotation
if step.upgrade_messages:
step_model['messages'] = step.upgrade_messages
step_models.append(step_model)
return {
'id':
trans.app.security.encode_id(stored.id),
'history_id':
trans.app.security.encode_id(trans.history.id)
if trans.history else None,
'name':
stored.name,
'steps':
step_models,
'step_version_changes':
step_version_changes,
'has_upgrade_messages':
has_upgrade_messages,
'workflow_resource_parameters':
self._workflow_resource_parameters(trans, stored, workflow),
}
def create(self, trans, payload, **kwd):
"""
POST /api/workflows
We're not creating workflows from the api. Just execute for now.
However, we will import them if installed_repository_file is specified
"""
# Pull parameters out of payload.
workflow_id = payload['workflow_id']
param_map = payload.get('parameters', {})
ds_map = payload['ds_map']
add_to_history = 'no_add_to_history' not in payload
history_param = payload['history']
# Get/create workflow.
if not workflow_id:
# create new
if 'installed_repository_file' in payload:
workflow_controller = trans.webapp.controllers[ 'workflow' ]
result = workflow_controller.import_workflow( trans=trans,
cntrller='api',
**payload)
return result
trans.response.status = 403
return "Either workflow_id or installed_repository_file must be specified"
if 'installed_repository_file' in payload:
trans.response.status = 403
return "installed_repository_file may not be specified with workflow_id"
# Get workflow + accessibility check.
stored_workflow = trans.sa_session.query(self.app.model.StoredWorkflow).get(
trans.security.decode_id(workflow_id))
if stored_workflow.user != trans.user and not trans.user_is_admin():
if trans.sa_session.query(trans.app.model.StoredWorkflowUserShareAssociation).filter_by(user=trans.user, stored_workflow=stored_workflow).count() == 0:
trans.response.status = 400
return("Workflow is not owned by or shared with current user")
workflow = stored_workflow.latest_workflow
# Get target history.
if history_param.startswith('hist_id='):
#Passing an existing history to use.
history = trans.sa_session.query(self.app.model.History).get(
trans.security.decode_id(history_param[8:]))
if history.user != trans.user and not trans.user_is_admin():
trans.response.status = 400
return "Invalid History specified."
else:
# Send workflow outputs to new history.
history = self.app.model.History(name=history_param, user=trans.user)
trans.sa_session.add(history)
trans.sa_session.flush()
# Set workflow inputs.
for k in ds_map:
try:
if ds_map[k]['src'] == 'ldda':
ldda = trans.sa_session.query(self.app.model.LibraryDatasetDatasetAssociation).get(
trans.security.decode_id(ds_map[k]['id']))
assert trans.user_is_admin() or trans.app.security_agent.can_access_dataset( trans.get_current_user_roles(), ldda.dataset )
hda = ldda.to_history_dataset_association(history, add_to_history=add_to_history)
elif ds_map[k]['src'] == 'ld':
ldda = trans.sa_session.query(self.app.model.LibraryDataset).get(
trans.security.decode_id(ds_map[k]['id'])).library_dataset_dataset_association
assert trans.user_is_admin() or trans.app.security_agent.can_access_dataset( trans.get_current_user_roles(), ldda.dataset )
hda = ldda.to_history_dataset_association(history, add_to_history=add_to_history)
elif ds_map[k]['src'] == 'hda':
# Get dataset handle, add to dict and history if necessary
hda = trans.sa_session.query(self.app.model.HistoryDatasetAssociation).get(
trans.security.decode_id(ds_map[k]['id']))
assert trans.user_is_admin() or trans.app.security_agent.can_access_dataset( trans.get_current_user_roles(), hda.dataset )
else:
trans.response.status = 400
return "Unknown dataset source '%s' specified." % ds_map[k]['src']
if add_to_history and hda.history != history:
hda = hda.copy()
history.add_dataset(hda)
ds_map[k]['hda'] = hda
except AssertionError:
trans.response.status = 400
return "Invalid Dataset '%s' Specified" % ds_map[k]['id']
# Sanity checks.
if not workflow:
trans.response.status = 400
return "Workflow not found."
if len( workflow.steps ) == 0:
trans.response.status = 400
return "Workflow cannot be run because it does not have any steps"
if workflow.has_cycles:
trans.response.status = 400
return "Workflow cannot be run because it contains cycles"
if workflow.has_errors:
trans.response.status = 400
return "Workflow cannot be run because of validation errors in some steps"
# Build the state for each step
rval = {}
for step in workflow.steps:
step_errors = None
if step.type == 'tool' or step.type is None:
step.module = module_factory.from_workflow_step( trans, step )
# Check for missing parameters
step.upgrade_messages = step.module.check_and_update_state()
# Any connected input needs to have value DummyDataset (these
# are not persisted so we need to do it every time)
step.module.add_dummy_datasets( connections=step.input_connections )
step.state = step.module.state
_update_step_parameters(step, param_map)
if step.tool_errors:
trans.response.status = 400
return "Workflow cannot be run because of validation errors in some steps: %s" % step_errors
if step.upgrade_messages:
trans.response.status = 400
return "Workflow cannot be run because of step upgrade messages: %s" % step.upgrade_messages
else:
# This is an input step. Make sure we have an available input.
if step.type == 'data_input' and str(step.id) not in ds_map:
trans.response.status = 400
return "Workflow cannot be run because an expected input step '%s' has no input dataset." % step.id
step.module = module_factory.from_workflow_step( trans, step )
step.state = step.module.get_runtime_state()
step.input_connections_by_name = dict( ( conn.input_name, conn ) for conn in step.input_connections )
# Run each step, connecting outputs to inputs
workflow_invocation = self.app.model.WorkflowInvocation()
workflow_invocation.workflow = workflow
outputs = util.odict.odict()
rval['history'] = trans.security.encode_id(history.id)
rval['outputs'] = []
for step in workflow.steps:
job = None
if step.type == 'tool' or step.type is None:
tool = self.app.toolbox.get_tool( step.tool_id )
def callback( input, value, prefixed_name, prefixed_label ):
if isinstance( input, DataToolParameter ):
if prefixed_name in step.input_connections_by_name:
conn = step.input_connections_by_name[ prefixed_name ]
return outputs[ conn.output_step.id ][ conn.output_name ]
visit_input_values( tool.inputs, step.state.inputs, callback )
job, out_data = tool.execute( trans, step.state.inputs, history=history)
outputs[ step.id ] = out_data
# Do post-job actions.
replacement_params = payload.get('replacement_params', {})
for pja in step.post_job_actions:
if pja.action_type in ActionBox.immediate_actions:
ActionBox.execute(trans.app, trans.sa_session, pja, job, replacement_dict=replacement_params)
else:
job.add_post_job_action(pja)
for v in out_data.itervalues():
rval['outputs'].append(trans.security.encode_id(v.id))
else:
#This is an input step. Use the dataset inputs from ds_map.
job, out_data = step.module.execute( trans, step.state)
outputs[step.id] = out_data
outputs[step.id]['output'] = ds_map[str(step.id)]['hda']
workflow_invocation_step = self.app.model.WorkflowInvocationStep()
workflow_invocation_step.workflow_invocation = workflow_invocation
workflow_invocation_step.workflow_step = step
workflow_invocation_step.job = job
trans.sa_session.add( workflow_invocation )
trans.sa_session.flush()
return rval
