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
18 logger = logging.getLogger('arvados.cwl-runner')
20 tmpdirre = re.compile(r"^\S+ \S+ \d+ \d+ stderr \S+ \S+ crunchrunner: \$\(task\.tmpdir\)=(.*)")
21 outdirre = re.compile(r"^\S+ \S+ \d+ \d+ stderr \S+ \S+ crunchrunner: \$\(task\.outdir\)=(.*)")
22 keepre = re.compile(r"^\S+ \S+ \d+ \d+ stderr \S+ \S+ crunchrunner: \$\(task\.keep\)=(.*)")
24 class ArvadosJob(object):
25 """Submit and manage a Crunch job for executing a CWL CommandLineTool."""
27 def __init__(self, runner):
28 self.arvrunner = runner
32 def run(self, dry_run=False, pull_image=True, **kwargs):
34 "command": self.command_line
36 runtime_constraints = {}
38 if self.generatefiles["listing"]:
39 vwd = arvados.collection.Collection()
40 script_parameters["task.vwd"] = {}
41 generatemapper = InitialWorkDirPathMapper([self.generatefiles], "", "",
43 for f, p in generatemapper.items():
44 if p.type == "CreateFile":
45 with vwd.open(p.target, "w") as n:
46 n.write(p.resolved.encode("utf-8"))
48 for f, p in generatemapper.items():
50 script_parameters["task.vwd"][p.target] = p.resolved
51 if p.type == "CreateFile":
52 script_parameters["task.vwd"][p.target] = "$(task.keep)/%s/%s" % (vwd.portable_data_hash(), p.target)
54 script_parameters["task.env"] = {"TMPDIR": "$(task.tmpdir)"}
56 script_parameters["task.env"].update(self.environment)
59 script_parameters["task.stdin"] = self.stdin
62 script_parameters["task.stdout"] = self.stdout
65 script_parameters["task.stderr"] = self.stderr
68 script_parameters["task.successCodes"] = self.successCodes
69 if self.temporaryFailCodes:
70 script_parameters["task.temporaryFailCodes"] = self.temporaryFailCodes
71 if self.permanentFailCodes:
72 script_parameters["task.permanentFailCodes"] = self.permanentFailCodes
74 (docker_req, docker_is_req) = get_feature(self, "DockerRequirement")
75 if docker_req and kwargs.get("use_container") is not False:
76 runtime_constraints["docker_image"] = arv_docker_get_image(self.arvrunner.api, docker_req, pull_image, self.arvrunner.project_uuid)
78 runtime_constraints["docker_image"] = "arvados/jobs"
80 resources = self.builder.resources
81 if resources is not None:
82 runtime_constraints["min_cores_per_node"] = resources.get("cores", 1)
83 runtime_constraints["min_ram_mb_per_node"] = resources.get("ram")
84 runtime_constraints["min_scratch_mb_per_node"] = resources.get("tmpdirSize", 0) + resources.get("outdirSize", 0)
86 filters = [["repository", "=", "arvados"],
87 ["script", "=", "crunchrunner"],
88 ["script_version", "in git", "9e5b98e8f5f4727856b53447191f9c06e3da2ba6"]]
89 if not self.arvrunner.ignore_docker_for_reuse:
90 filters.append(["docker_image_locator", "in docker", runtime_constraints["docker_image"]])
93 response = self.arvrunner.api.jobs().create(
95 "owner_uuid": self.arvrunner.project_uuid,
96 "script": "crunchrunner",
97 "repository": "arvados",
98 "script_version": "master",
99 "minimum_script_version": "9e5b98e8f5f4727856b53447191f9c06e3da2ba6",
100 "script_parameters": {"tasks": [script_parameters]},
101 "runtime_constraints": runtime_constraints
104 find_or_create=kwargs.get("enable_reuse", True)
105 ).execute(num_retries=self.arvrunner.num_retries)
107 self.arvrunner.processes[response["uuid"]] = self
109 self.update_pipeline_component(response)
111 logger.info("Job %s (%s) is %s", self.name, response["uuid"], response["state"])
113 if response["state"] in ("Complete", "Failed", "Cancelled"):
115 except Exception as e:
116 logger.error("Got error %s" % str(e))
117 self.output_callback({}, "permanentFail")
119 def update_pipeline_component(self, record):
120 if self.arvrunner.pipeline:
121 self.arvrunner.pipeline["components"][self.name] = {"job": record}
122 self.arvrunner.pipeline = self.arvrunner.api.pipeline_instances().update(uuid=self.arvrunner.pipeline["uuid"],
124 "components": self.arvrunner.pipeline["components"]
125 }).execute(num_retries=self.arvrunner.num_retries)
126 if self.arvrunner.uuid:
128 job = self.arvrunner.api.jobs().get(uuid=self.arvrunner.uuid).execute()
130 components = job["components"]
131 components[self.name] = record["uuid"]
132 self.arvrunner.api.jobs().update(uuid=self.arvrunner.uuid,
134 "components": components
135 }).execute(num_retries=self.arvrunner.num_retries)
136 except Exception as e:
137 logger.info("Error adding to components: %s", e)
139 def done(self, record):
141 self.update_pipeline_component(record)
146 if record["state"] == "Complete":
147 processStatus = "success"
149 processStatus = "permanentFail"
154 logc = arvados.collection.Collection(record["log"])
155 log = logc.open(logc.keys()[0])
160 # Determine the tmpdir, outdir and keepdir paths from
161 # the job run. Unfortunately, we can't take the first
162 # values we find (which are expected to be near the
163 # top) and stop scanning because if the node fails and
164 # the job restarts on a different node these values
165 # will different runs, and we need to know about the
166 # final run that actually produced output.
168 g = tmpdirre.match(l)
171 g = outdirre.match(l)
178 outputs = done.done(self, record, tmpdir, outdir, keepdir)
179 except WorkflowException as e:
180 logger.error("Error while collecting job outputs:\n%s", e, exc_info=(e if self.arvrunner.debug else False))
181 processStatus = "permanentFail"
182 except Exception as e:
183 logger.exception("Got unknown exception while collecting job outputs:")
184 processStatus = "permanentFail"
186 self.output_callback(outputs, processStatus)
188 del self.arvrunner.processes[record["uuid"]]
191 class RunnerJob(Runner):
192 """Submit and manage a Crunch job that runs crunch_scripts/cwl-runner."""
194 def arvados_job_spec(self, dry_run=False, pull_image=True, **kwargs):
195 """Create an Arvados job specification for this workflow.
197 The returned dict can be used to create a job (i.e., passed as
198 the +body+ argument to jobs().create()), or as a component in
199 a pipeline template or pipeline instance.
202 workflowmapper = super(RunnerJob, self).arvados_job_spec(dry_run=dry_run, pull_image=pull_image, **kwargs)
204 self.job_order["cwl:tool"] = workflowmapper.mapper(self.tool.tool["id"])[1]
206 "script": "cwl-runner",
207 "script_version": "master",
208 "repository": "arvados",
209 "script_parameters": self.job_order,
210 "runtime_constraints": {
211 "docker_image": "arvados/jobs"
215 def run(self, *args, **kwargs):
216 job_spec = self.arvados_job_spec(*args, **kwargs)
217 job_spec.setdefault("owner_uuid", self.arvrunner.project_uuid)
219 response = self.arvrunner.api.jobs().create(
221 find_or_create=self.enable_reuse
222 ).execute(num_retries=self.arvrunner.num_retries)
224 self.uuid = response["uuid"]
225 self.arvrunner.processes[self.uuid] = self
227 logger.info("Submitted job %s", response["uuid"])
229 if kwargs.get("submit"):
230 self.pipeline = self.arvrunner.api.pipeline_instances().create(
232 "owner_uuid": self.arvrunner.project_uuid,
233 "name": shortname(self.tool.tool["id"]),
234 "components": {"cwl-runner": {"job": {"uuid": self.uuid, "state": response["state"]} } },
235 "state": "RunningOnClient"}).execute(num_retries=self.arvrunner.num_retries)
237 if response["state"] in ("Complete", "Failed", "Cancelled"):
241 class RunnerTemplate(object):
242 """An Arvados pipeline template that invokes a CWL workflow."""
244 type_to_dataclass = {
245 'boolean': 'boolean',
252 def __init__(self, runner, tool, job_order, enable_reuse):
255 self.job = RunnerJob(
259 enable_reuse=enable_reuse)
261 def pipeline_component_spec(self):
262 """Return a component that Workbench and a-r-p-i will understand.
264 Specifically, translate CWL input specs to Arvados pipeline
265 format, like {"dataclass":"File","value":"xyz"}.
267 spec = self.job.arvados_job_spec()
269 # Most of the component spec is exactly the same as the job
270 # spec (script, script_version, etc.).
271 # spec['script_parameters'] isn't right, though. A component
272 # spec's script_parameters hash is a translation of
273 # self.tool.tool['inputs'] with defaults/overrides taken from
274 # the job order. So we move the job parameters out of the way
275 # and build a new spec['script_parameters'].
276 job_params = spec['script_parameters']
277 spec['script_parameters'] = {}
279 for param in self.tool.tool['inputs']:
280 param = copy.deepcopy(param)
282 # Data type and "required" flag...
283 types = param['type']
284 if not isinstance(types, list):
286 param['required'] = 'null' not in types
287 non_null_types = set(types) - set(['null'])
288 if len(non_null_types) == 1:
289 the_type = [c for c in non_null_types][0]
290 dataclass = self.type_to_dataclass.get(the_type)
292 param['dataclass'] = dataclass
293 # Note: If we didn't figure out a single appropriate
294 # dataclass, we just left that attribute out. We leave
295 # the "type" attribute there in any case, which might help
298 # Title and description...
299 title = param.pop('label', '')
300 descr = param.pop('doc', '').rstrip('\n')
302 param['title'] = title
304 param['description'] = descr
306 # Fill in the value from the current job order, if any.
307 param_id = shortname(param.pop('id'))
308 value = job_params.get(param_id)
311 elif not isinstance(value, dict):
312 param['value'] = value
313 elif param.get('dataclass') == 'File' and value.get('location'):
314 param['value'] = value['location']
316 spec['script_parameters'][param_id] = param
317 spec['script_parameters']['cwl:tool'] = job_params['cwl:tool']
321 job_spec = self.pipeline_component_spec()
322 response = self.runner.api.pipeline_templates().create(body={
324 self.job.name: job_spec,
326 "name": self.job.name,
327 "owner_uuid": self.runner.project_uuid,
328 }, ensure_unique_name=True).execute(num_retries=self.runner.num_retries)
329 self.uuid = response["uuid"]
330 logger.info("Created template %s", self.uuid)