def __init__(self,
galaxy_url=None,
galaxy_api_key=None,
max_retries=None,
retry_delay=None,
polling_interval=None,
output_folder='.',
stream=_sys.stderr,
descriptions=True,
verbosity=1,
elapsed_times=True):
self.galaxy_api_key = galaxy_api_key
# create Galaxy instance
self._galaxy_instance = _common.get_galaxy_instance(
galaxy_url,
galaxy_api_key,
max_retries=max_retries,
retry_delay=retry_delay,
polling_interval=polling_interval)
# create WorkflowLoader
self._workflow_loader = _common.WorkflowLoader.get_instance(
self._galaxy_instance)
# logger
self._logger = _common.LoggerManager.get_logger(self)
# runner reference
self._runner = _ExtendedXMLTestRunner(output=output_folder,
stream=stream,
verbosity=verbosity,
descriptions=descriptions,
elapsed_times=elapsed_times)
def cleanup_test_workflow_data(galaxy_url=None, galaxy_api_key=None):
_logger.debug("Cleaning saved histories ...")
galaxy_instance = _common.get_galaxy_instance(galaxy_url, galaxy_api_key)
hslist = galaxy_instance.histories.list()
for history in [
h for h in hslist
if _core.WorkflowTestCase.DEFAULT_HISTORY_NAME_PREFIX in h.name
]:
galaxy_instance.histories.delete(history.id)
def cleanup_test_workflows(galaxy_url=None, galaxy_api_key=None):
_logger.debug("Cleaning workflow library ...")
galaxy_instance = _common.get_galaxy_instance(galaxy_url, galaxy_api_key)
workflow_loader = _common.WorkflowLoader.get_instance(galaxy_instance)
wflist = galaxy_instance.workflows.list()
workflows = [
w for w in wflist
if _core.WorkflowTestCase.DEFAULT_WORKFLOW_NAME_PREFIX in w.name
]
for wf in workflows:
workflow_loader.unload_workflow(wf.id)
def _get_history_info(config):
result = None
gi = _common.get_galaxy_instance(config["galaxy_url"],
config["galaxy_api_key"])
_logger.info("Loading Galaxy history info ...")
candidate_histories = [
h for h in gi.histories.list() if config["history"] in h.name
]
candidate_count = len(candidate_histories)
if candidate_count == 0:
print("\n No history found with name: \"{0}\"".format(
config["history"]))
elif candidate_count == 1:
result = candidate_histories[0]
else:
while True:
print(
"\nNOTICE:".ljust(10),
"More than one history matches the name \"{0}\".".format(
config["history"]))
print("".ljust(9), "Please select one of the following options:\n")
for opt, h in enumerate(candidate_histories):
print(
"".ljust(3), "{0})".format(opt + 1).ljust(4),
h.name.ljust(30), "".ljust(4), "create-time:",
_datetime.datetime.strptime(
h.wrapped["create_time"],
"%Y-%m-%dT%H:%M:%S.%f").strftime("%Y-%m-%d %H:%M:%S"))
print("\n".ljust(4), "0)".ljust(4), "Exit")
try:
# get the user choice as int
# notice that `input` in python3 is equivalent to `raw_input` in python2
choice = int(input("\n ==> Choice: "))
if choice in range(0, candidate_count + 1):
if choice > 0:
result = candidate_histories[choice - 1]
print("\n")
break
except ValueError:
print("\nWARNING: ".ljust(10), "Your choice is not valid!!!")
except NameError:
print("\nWARNING: ".ljust(10), "Your choice is not valid!!!")
except SyntaxError:
print("\nWARNING: ".ljust(10), "Your choice is not valid!!!")
except KeyboardInterrupt:
break
else:
print("\nWARNING: ".ljust(10), "Your choice is not valid!!!")
return result
def __init__(self, history_id, galaxy_url=None, galaxy_api_key=None):
super(History, self).__init__()
# configure logger
self._logger = _common.LoggerManager.get_logger(self)
# set the Galaxy instance
self._gi = _common.get_galaxy_instance(galaxy_url, galaxy_api_key)
# set wrapped history
self._logger.info("Loading history %s info", history_id)
self._history = self._gi.histories.get(history_id)
# job info
self.job_tool = {}
self.creating_jobs = {}
# datasets
self.datasets = None
self.input_datasets = _collections.OrderedDict()
self.output_datasets = _collections.OrderedDict()
self.intermediate_datasets = _collections.OrderedDict()
# map dataset inputs to their order
self._input_order_map = {}
# job info
self._jobs = {}
self.job_input_ids = {}
self.job_output_ids = {}
self.creating_jobs = {}
self.processing_jobs = _collections.OrderedDict()
self.processing_job_levels = {}
# tool cache
self._tools = {}
# labels
self.input_dataset_labels = {}
self.output_dataset_labels = {}
self.intermediate_dataset_labels = {}
# process history
self._logger.info("Processing history info...")
self._process_history()
self._logger.info("History info processing: done")
def _get_workflow_info(filename,
galaxy_url,
galaxy_api_key,
tool_folder=DEFAULT_TOOLS_FOLDER):
inputs = []
params = _CommentedMap()
outputs = {}
# loading wf info start
_logger.debug("Loading workflow definition from %s file...", filename)
# setup galaxy instance
galaxy_instance = _common.get_galaxy_instance(galaxy_url, galaxy_api_key)
galaxy_tool_client = _ToolClient(
galaxy_instance.gi) # get the non-object version of the GI
if not _os.path.exists(DEFAULT_TOOLS_FOLDER):
_os.makedirs(DEFAULT_TOOLS_FOLDER)
with open(filename) as fp:
wf_config = _json.load(fp)
for sid, step in _iteritems(wf_config["steps"]):
# tool = gi.tools.get()
_logger.debug("Processing step '%s' -- '%s'", sid, step["name"])
# an input step....
if not step["tool_id"] and step["type"] == "data_input":
for input_ in step["inputs"]:
_logger.debug("Processing input: '%s' (%s)", input_["name"],
input_["description"])
inputs.append(input_)
# a processing step (with outputs) ...
if step["tool_id"] and step["type"] == "tool":
# tool parameters
tool_params = _CommentedMap()
# process tool info to extract parameters
tool_id = step["tool_id"]
# tool = galaxy_instance.tools.get(tool_id)
## LP: re-write this using the bioblend.objects API to fetch the tool
# inputs. See the comment above `def _process_tool_param_element`
# tool_config_xml = _os.path.basename(tool.wrapped["config_file"])
# _logger.debug("Processing step tool '%s'", tool_id)
#
# try:
# _logger.debug("Download TOOL '%s' definition file XML: %s....", tool_id, tool_config_xml)
# targz_filename = _os.path.join(DEFAULT_TOOLS_FOLDER, tool_id + ".tar.gz")
# targz_content = galaxy_tool_client._get(_os.path.join(tool_id, "download"), json=False)
# if targz_content.status_code == 200:
# with open(targz_filename, "w") as tfp:
# tfp.write(targz_content.content)
# tar = _tarfile.open(targz_filename)
# tar.extractall(path=tool_folder)
# tar.close()
# _os.remove(targz_filename)
# _logger.debug("Download TOOL '%s' definition file XML: %s....: DONE", tool_id, tool_config_xml)
# else:
# _logger.debug("Download TOOL '%s' definition file XML: %s....: ERROR %r",
# tool_id, tool_config_xml, targz_content.status_code)
#
# tool_config_xml = _os.path.join(DEFAULT_TOOLS_FOLDER, tool_config_xml)
# if _os.path.exists(tool_config_xml):
# tree = _etree.parse(tool_config_xml)
# root = tree.getroot()
# inputs_el = root.find("inputs")
# for input_el in inputs_el:
# _process_tool_param_element(input_el, tool_params)
# if len(tool_params) > 0:
# params.insert(int(sid), sid, tool_params)
#
# except _StandardError as e:
# _logger.debug("Download TOOL '%s' definition file XML: %s....: ERROR", tool_id, tool_config_xml)
# _logger.error(e)
# process
outputs[str(sid)] = {}
for output in step["workflow_outputs"]:
outputs[str(sid)][output["uuid"]] = output
# loading wf info end
_logger.debug("Workflow definition loaded from %s file...", filename)
# return loaded info
return wf_config, inputs, params, outputs