5 from cwltool.process import get_feature, shortname
6 from cwltool.errors import WorkflowException
7 from cwltool.draft2tool import revmap_file, CommandLineTool
8 from cwltool.load_tool import fetch_document
9 from cwltool.builder import Builder
11 import arvados.collection
13 from .arvdocker import arv_docker_get_image
14 from .runner import Runner
15 from .pathmapper import InitialWorkDirPathMapper
16 from .perf import Perf
19 logger = logging.getLogger('arvados.cwl-runner')
21 tmpdirre = re.compile(r"^\S+ \S+ \d+ \d+ stderr \S+ \S+ crunchrunner: \$\(task\.tmpdir\)=(.*)")
22 outdirre = re.compile(r"^\S+ \S+ \d+ \d+ stderr \S+ \S+ crunchrunner: \$\(task\.outdir\)=(.*)")
23 keepre = re.compile(r"^\S+ \S+ \d+ \d+ stderr \S+ \S+ crunchrunner: \$\(task\.keep\)=(.*)")
25 class ArvadosJob(object):
26 """Submit and manage a Crunch job for executing a CWL CommandLineTool."""
28 def __init__(self, runner):
29 self.arvrunner = runner
33 def run(self, dry_run=False, pull_image=True, **kwargs):
35 "command": self.command_line
37 runtime_constraints = {}
39 if self.generatefiles["listing"]:
40 vwd = arvados.collection.Collection()
41 script_parameters["task.vwd"] = {}
42 generatemapper = InitialWorkDirPathMapper([self.generatefiles], "", "",
44 for f, p in generatemapper.items():
45 if p.type == "CreateFile":
46 with vwd.open(p.target, "w") as n:
47 n.write(p.resolved.encode("utf-8"))
49 for f, p in generatemapper.items():
51 script_parameters["task.vwd"][p.target] = p.resolved
52 if p.type == "CreateFile":
53 script_parameters["task.vwd"][p.target] = "$(task.keep)/%s/%s" % (vwd.portable_data_hash(), p.target)
55 script_parameters["task.env"] = {"TMPDIR": self.tmpdir, "HOME": self.outdir}
57 script_parameters["task.env"].update(self.environment)
60 script_parameters["task.stdin"] = self.stdin
63 script_parameters["task.stdout"] = self.stdout
66 script_parameters["task.stderr"] = self.stderr
69 script_parameters["task.successCodes"] = self.successCodes
70 if self.temporaryFailCodes:
71 script_parameters["task.temporaryFailCodes"] = self.temporaryFailCodes
72 if self.permanentFailCodes:
73 script_parameters["task.permanentFailCodes"] = self.permanentFailCodes
75 (docker_req, docker_is_req) = get_feature(self, "DockerRequirement")
76 if docker_req and kwargs.get("use_container") is not False:
77 runtime_constraints["docker_image"] = arv_docker_get_image(self.arvrunner.api, docker_req, pull_image, self.arvrunner.project_uuid)
79 runtime_constraints["docker_image"] = "arvados/jobs"
81 resources = self.builder.resources
82 if resources is not None:
83 runtime_constraints["min_cores_per_node"] = resources.get("cores", 1)
84 runtime_constraints["min_ram_mb_per_node"] = resources.get("ram")
85 runtime_constraints["min_scratch_mb_per_node"] = resources.get("tmpdirSize", 0) + resources.get("outdirSize", 0)
87 filters = [["repository", "=", "arvados"],
88 ["script", "=", "crunchrunner"],
89 ["script_version", "in git", "9e5b98e8f5f4727856b53447191f9c06e3da2ba6"]]
90 if not self.arvrunner.ignore_docker_for_reuse:
91 filters.append(["docker_image_locator", "in docker", runtime_constraints["docker_image"]])
94 with Perf(logger, "create %s" % self.name):
95 response = self.arvrunner.api.jobs().create(
97 "owner_uuid": self.arvrunner.project_uuid,
98 "script": "crunchrunner",
99 "repository": "arvados",
100 "script_version": "master",
101 "minimum_script_version": "9e5b98e8f5f4727856b53447191f9c06e3da2ba6",
102 "script_parameters": {"tasks": [script_parameters]},
103 "runtime_constraints": runtime_constraints
106 find_or_create=kwargs.get("enable_reuse", True)
107 ).execute(num_retries=self.arvrunner.num_retries)
109 self.arvrunner.processes[response["uuid"]] = self
111 self.update_pipeline_component(response)
113 logger.info("Job %s (%s) is %s", self.name, response["uuid"], response["state"])
115 if response["state"] in ("Complete", "Failed", "Cancelled"):
116 with Perf(logger, "done %s" % self.name):
118 except Exception as e:
119 logger.error("Got error %s" % str(e))
120 self.output_callback({}, "permanentFail")
122 def update_pipeline_component(self, record):
123 if self.arvrunner.pipeline:
124 self.arvrunner.pipeline["components"][self.name] = {"job": record}
125 with Perf(logger, "update_pipeline_component %s" % self.name):
126 self.arvrunner.pipeline = self.arvrunner.api.pipeline_instances().update(uuid=self.arvrunner.pipeline["uuid"],
128 "components": self.arvrunner.pipeline["components"]
129 }).execute(num_retries=self.arvrunner.num_retries)
130 if self.arvrunner.uuid:
132 job = self.arvrunner.api.jobs().get(uuid=self.arvrunner.uuid).execute()
134 components = job["components"]
135 components[self.name] = record["uuid"]
136 self.arvrunner.api.jobs().update(uuid=self.arvrunner.uuid,
138 "components": components
139 }).execute(num_retries=self.arvrunner.num_retries)
140 except Exception as e:
141 logger.info("Error adding to components: %s", e)
143 def done(self, record):
145 self.update_pipeline_component(record)
150 if record["state"] == "Complete":
151 processStatus = "success"
153 processStatus = "permanentFail"
158 with Perf(logger, "inspect log %s" % self.name):
159 logc = arvados.collection.Collection(record["log"])
160 log = logc.open(logc.keys()[0])
165 # Determine the tmpdir, outdir and keepdir paths from
166 # the job run. Unfortunately, we can't take the first
167 # values we find (which are expected to be near the
168 # top) and stop scanning because if the node fails and
169 # the job restarts on a different node these values
170 # will different runs, and we need to know about the
171 # final run that actually produced output.
173 g = tmpdirre.match(l)
176 g = outdirre.match(l)
183 with Perf(logger, "output collection %s" % self.name):
184 outputs = done.done(self, record, tmpdir, outdir, keepdir)
185 except WorkflowException as e:
186 logger.error("Error while collecting job outputs:\n%s", e, exc_info=(e if self.arvrunner.debug else False))
187 processStatus = "permanentFail"
188 except Exception as e:
189 logger.exception("Got unknown exception while collecting job outputs:")
190 processStatus = "permanentFail"
192 self.output_callback(outputs, processStatus)
194 del self.arvrunner.processes[record["uuid"]]
197 class RunnerJob(Runner):
198 """Submit and manage a Crunch job that runs crunch_scripts/cwl-runner."""
200 def arvados_job_spec(self, dry_run=False, pull_image=True, **kwargs):
201 """Create an Arvados job specification for this workflow.
203 The returned dict can be used to create a job (i.e., passed as
204 the +body+ argument to jobs().create()), or as a component in
205 a pipeline template or pipeline instance.
208 workflowmapper = super(RunnerJob, self).arvados_job_spec(dry_run=dry_run, pull_image=pull_image, **kwargs)
210 self.job_order["cwl:tool"] = workflowmapper.mapper(self.tool.tool["id"]).target[5:]
212 "script": "cwl-runner",
213 "script_version": "master",
214 "repository": "arvados",
215 "script_parameters": self.job_order,
216 "runtime_constraints": {
217 "docker_image": "arvados/jobs"
221 def run(self, *args, **kwargs):
222 job_spec = self.arvados_job_spec(*args, **kwargs)
223 job_spec.setdefault("owner_uuid", self.arvrunner.project_uuid)
225 response = self.arvrunner.api.jobs().create(
227 find_or_create=self.enable_reuse
228 ).execute(num_retries=self.arvrunner.num_retries)
230 self.uuid = response["uuid"]
231 self.arvrunner.processes[self.uuid] = self
233 logger.info("Submitted job %s", response["uuid"])
235 if kwargs.get("submit"):
236 self.arvrunner.pipeline = self.arvrunner.api.pipeline_instances().create(
238 "owner_uuid": self.arvrunner.project_uuid,
239 "name": shortname(self.tool.tool["id"]),
240 "components": {"cwl-runner": {"job": {"uuid": self.uuid, "state": response["state"]} } },
241 "state": "RunningOnClient"}).execute(num_retries=self.arvrunner.num_retries)
243 if response["state"] in ("Complete", "Failed", "Cancelled"):
247 class RunnerTemplate(object):
248 """An Arvados pipeline template that invokes a CWL workflow."""
250 type_to_dataclass = {
251 'boolean': 'boolean',
253 'Directory': 'Collection',
259 def __init__(self, runner, tool, job_order, enable_reuse):
262 self.job = RunnerJob(
266 enable_reuse=enable_reuse)
268 def pipeline_component_spec(self):
269 """Return a component that Workbench and a-r-p-i will understand.
271 Specifically, translate CWL input specs to Arvados pipeline
272 format, like {"dataclass":"File","value":"xyz"}.
274 spec = self.job.arvados_job_spec()
276 # Most of the component spec is exactly the same as the job
277 # spec (script, script_version, etc.).
278 # spec['script_parameters'] isn't right, though. A component
279 # spec's script_parameters hash is a translation of
280 # self.tool.tool['inputs'] with defaults/overrides taken from
281 # the job order. So we move the job parameters out of the way
282 # and build a new spec['script_parameters'].
283 job_params = spec['script_parameters']
284 spec['script_parameters'] = {}
286 for param in self.tool.tool['inputs']:
287 param = copy.deepcopy(param)
289 # Data type and "required" flag...
290 types = param['type']
291 if not isinstance(types, list):
293 param['required'] = 'null' not in types
294 non_null_types = set(types) - set(['null'])
295 if len(non_null_types) == 1:
296 the_type = [c for c in non_null_types][0]
297 dataclass = self.type_to_dataclass.get(the_type)
299 param['dataclass'] = dataclass
300 # Note: If we didn't figure out a single appropriate
301 # dataclass, we just left that attribute out. We leave
302 # the "type" attribute there in any case, which might help
305 # Title and description...
306 title = param.pop('label', '')
307 descr = param.pop('doc', '').rstrip('\n')
309 param['title'] = title
311 param['description'] = descr
313 # Fill in the value from the current job order, if any.
314 param_id = shortname(param.pop('id'))
315 value = job_params.get(param_id)
318 elif not isinstance(value, dict):
319 param['value'] = value
320 elif param.get('dataclass') in ('File', 'Collection') and value.get('location'):
321 param['value'] = value['location'][5:]
323 spec['script_parameters'][param_id] = param
324 spec['script_parameters']['cwl:tool'] = job_params['cwl:tool']
328 job_spec = self.pipeline_component_spec()
329 response = self.runner.api.pipeline_templates().create(body={
331 self.job.name: job_spec,
333 "name": self.job.name,
334 "owner_uuid": self.runner.project_uuid,
335 }, ensure_unique_name=True).execute(num_retries=self.runner.num_retries)
336 self.uuid = response["uuid"]
337 logger.info("Created template %s", self.uuid)