10383: Several fixes/enhancements to arv-put:
[arvados.git] / sdk / cwl / arvados_cwl / arvjob.py
1 import logging
2 import re
3 import copy
4 import json
5 import time
6
7 from cwltool.process import get_feature, shortname
8 from cwltool.errors import WorkflowException
9 from cwltool.draft2tool import revmap_file, CommandLineTool
10 from cwltool.load_tool import fetch_document
11 from cwltool.builder import Builder
12
13 import arvados.collection
14
15 from .arvdocker import arv_docker_get_image
16 from .runner import Runner, arvados_jobs_image
17 from .pathmapper import InitialWorkDirPathMapper
18 from .perf import Perf
19 from . import done
20 from ._version import __version__
21
22 logger = logging.getLogger('arvados.cwl-runner')
23 metrics = logging.getLogger('arvados.cwl-runner.metrics')
24
25 tmpdirre = re.compile(r"^\S+ \S+ \d+ \d+ stderr \S+ \S+ crunchrunner: \$\(task\.tmpdir\)=(.*)")
26 outdirre = re.compile(r"^\S+ \S+ \d+ \d+ stderr \S+ \S+ crunchrunner: \$\(task\.outdir\)=(.*)")
27 keepre = re.compile(r"^\S+ \S+ \d+ \d+ stderr \S+ \S+ crunchrunner: \$\(task\.keep\)=(.*)")
28
29 class ArvadosJob(object):
30     """Submit and manage a Crunch job for executing a CWL CommandLineTool."""
31
32     def __init__(self, runner):
33         self.arvrunner = runner
34         self.running = False
35         self.uuid = None
36
37     def run(self, dry_run=False, pull_image=True, **kwargs):
38         script_parameters = {
39             "command": self.command_line
40         }
41         runtime_constraints = {}
42
43         with Perf(metrics, "generatefiles %s" % self.name):
44             if self.generatefiles["listing"]:
45                 vwd = arvados.collection.Collection(api_client=self.arvrunner.api,
46                                                     keep_client=self.arvrunner.keep_client,
47                                                     num_retries=self.arvrunner.num_retries)
48                 script_parameters["task.vwd"] = {}
49                 generatemapper = InitialWorkDirPathMapper([self.generatefiles], "", "",
50                                                           separateDirs=False)
51
52                 with Perf(metrics, "createfiles %s" % self.name):
53                     for f, p in generatemapper.items():
54                         if p.type == "CreateFile":
55                             with vwd.open(p.target, "w") as n:
56                                 n.write(p.resolved.encode("utf-8"))
57
58                 with Perf(metrics, "generatefiles.save_new %s" % self.name):
59                     vwd.save_new()
60
61                 for f, p in generatemapper.items():
62                     if p.type == "File":
63                         script_parameters["task.vwd"][p.target] = p.resolved
64                     if p.type == "CreateFile":
65                         script_parameters["task.vwd"][p.target] = "$(task.keep)/%s/%s" % (vwd.portable_data_hash(), p.target)
66
67         script_parameters["task.env"] = {"TMPDIR": self.tmpdir, "HOME": self.outdir}
68         if self.environment:
69             script_parameters["task.env"].update(self.environment)
70
71         if self.stdin:
72             script_parameters["task.stdin"] = self.stdin
73
74         if self.stdout:
75             script_parameters["task.stdout"] = self.stdout
76
77         if self.stderr:
78             script_parameters["task.stderr"] = self.stderr
79
80         if self.successCodes:
81             script_parameters["task.successCodes"] = self.successCodes
82         if self.temporaryFailCodes:
83             script_parameters["task.temporaryFailCodes"] = self.temporaryFailCodes
84         if self.permanentFailCodes:
85             script_parameters["task.permanentFailCodes"] = self.permanentFailCodes
86
87         with Perf(metrics, "arv_docker_get_image %s" % self.name):
88             (docker_req, docker_is_req) = get_feature(self, "DockerRequirement")
89             if docker_req and kwargs.get("use_container") is not False:
90                 runtime_constraints["docker_image"] = arv_docker_get_image(self.arvrunner.api, docker_req, pull_image, self.arvrunner.project_uuid)
91             else:
92                 runtime_constraints["docker_image"] = arvados_jobs_image(self.arvrunner)
93
94         resources = self.builder.resources
95         if resources is not None:
96             runtime_constraints["min_cores_per_node"] = resources.get("cores", 1)
97             runtime_constraints["min_ram_mb_per_node"] = resources.get("ram")
98             runtime_constraints["min_scratch_mb_per_node"] = resources.get("tmpdirSize", 0) + resources.get("outdirSize", 0)
99
100         runtime_req, _ = get_feature(self, "http://arvados.org/cwl#RuntimeConstraints")
101         if runtime_req:
102             if "keep_cache" in runtime_req:
103                 runtime_constraints["keep_cache_mb_per_task"] = runtime_req["keep_cache"]
104             if "outputDirType" in runtime_req:
105                 if runtime_req["outputDirType"] == "local_output_dir":
106                     script_parameters["task.keepTmpOutput"] = False
107                 elif runtime_req["outputDirType"] == "keep_output_dir":
108                     script_parameters["task.keepTmpOutput"] = True
109
110         filters = [["repository", "=", "arvados"],
111                    ["script", "=", "crunchrunner"],
112                    ["script_version", "in git", "9e5b98e8f5f4727856b53447191f9c06e3da2ba6"]]
113         if not self.arvrunner.ignore_docker_for_reuse:
114             filters.append(["docker_image_locator", "in docker", runtime_constraints["docker_image"]])
115
116         try:
117             with Perf(metrics, "create %s" % self.name):
118                 response = self.arvrunner.api.jobs().create(
119                     body={
120                         "owner_uuid": self.arvrunner.project_uuid,
121                         "script": "crunchrunner",
122                         "repository": "arvados",
123                         "script_version": "master",
124                         "minimum_script_version": "9e5b98e8f5f4727856b53447191f9c06e3da2ba6",
125                         "script_parameters": {"tasks": [script_parameters]},
126                         "runtime_constraints": runtime_constraints
127                     },
128                     filters=filters,
129                     find_or_create=kwargs.get("enable_reuse", True)
130                 ).execute(num_retries=self.arvrunner.num_retries)
131
132             self.arvrunner.processes[response["uuid"]] = self
133
134             self.update_pipeline_component(response)
135
136             logger.info("Job %s (%s) is %s", self.name, response["uuid"], response["state"])
137
138             if response["state"] in ("Complete", "Failed", "Cancelled"):
139                 with Perf(metrics, "done %s" % self.name):
140                     self.done(response)
141         except Exception as e:
142             logger.error("Got error %s" % str(e))
143             self.output_callback({}, "permanentFail")
144
145     def update_pipeline_component(self, record):
146         if self.arvrunner.pipeline:
147             self.arvrunner.pipeline["components"][self.name] = {"job": record}
148             with Perf(metrics, "update_pipeline_component %s" % self.name):
149                 self.arvrunner.pipeline = self.arvrunner.api.pipeline_instances().update(uuid=self.arvrunner.pipeline["uuid"],
150                                                                                  body={
151                                                                                     "components": self.arvrunner.pipeline["components"]
152                                                                                  }).execute(num_retries=self.arvrunner.num_retries)
153         if self.arvrunner.uuid:
154             try:
155                 job = self.arvrunner.api.jobs().get(uuid=self.arvrunner.uuid).execute()
156                 if job:
157                     components = job["components"]
158                     components[self.name] = record["uuid"]
159                     self.arvrunner.api.jobs().update(uuid=self.arvrunner.uuid,
160                         body={
161                             "components": components
162                         }).execute(num_retries=self.arvrunner.num_retries)
163             except Exception as e:
164                 logger.info("Error adding to components: %s", e)
165
166     def done(self, record):
167         try:
168             self.update_pipeline_component(record)
169         except:
170             pass
171
172         try:
173             if record["state"] == "Complete":
174                 processStatus = "success"
175             else:
176                 processStatus = "permanentFail"
177
178             outputs = {}
179             try:
180                 if record["output"]:
181                     with Perf(metrics, "inspect log %s" % self.name):
182                         logc = arvados.collection.CollectionReader(record["log"],
183                                                                    api_client=self.arvrunner.api,
184                                                                    keep_client=self.arvrunner.keep_client,
185                                                                    num_retries=self.arvrunner.num_retries)
186                         log = logc.open(logc.keys()[0])
187                         tmpdir = None
188                         outdir = None
189                         keepdir = None
190                         for l in log:
191                             # Determine the tmpdir, outdir and keepdir paths from
192                             # the job run.  Unfortunately, we can't take the first
193                             # values we find (which are expected to be near the
194                             # top) and stop scanning because if the node fails and
195                             # the job restarts on a different node these values
196                             # will different runs, and we need to know about the
197                             # final run that actually produced output.
198
199                             g = tmpdirre.match(l)
200                             if g:
201                                 tmpdir = g.group(1)
202                             g = outdirre.match(l)
203                             if g:
204                                 outdir = g.group(1)
205                             g = keepre.match(l)
206                             if g:
207                                 keepdir = g.group(1)
208
209                     with Perf(metrics, "output collection %s" % self.name):
210                         outputs = done.done(self, record, tmpdir, outdir, keepdir)
211             except WorkflowException as e:
212                 logger.error("Error while collecting job outputs:\n%s", e, exc_info=(e if self.arvrunner.debug else False))
213                 processStatus = "permanentFail"
214                 outputs = None
215             except Exception as e:
216                 logger.exception("Got unknown exception while collecting job outputs:")
217                 processStatus = "permanentFail"
218                 outputs = None
219
220             self.output_callback(outputs, processStatus)
221         finally:
222             del self.arvrunner.processes[record["uuid"]]
223
224
225 class RunnerJob(Runner):
226     """Submit and manage a Crunch job that runs crunch_scripts/cwl-runner."""
227
228     def arvados_job_spec(self, dry_run=False, pull_image=True, **kwargs):
229         """Create an Arvados job specification for this workflow.
230
231         The returned dict can be used to create a job (i.e., passed as
232         the +body+ argument to jobs().create()), or as a component in
233         a pipeline template or pipeline instance.
234         """
235
236         workflowmapper = super(RunnerJob, self).arvados_job_spec(dry_run=dry_run, pull_image=pull_image, **kwargs)
237
238         # Need to filter this out, gets added by cwltool when providing
239         # parameters on the command line, and arv-run-pipeline-instance doesn't
240         # like it.
241         if "job_order" in self.job_order:
242             del self.job_order["job_order"]
243
244         self.job_order["cwl:tool"] = workflowmapper.mapper(self.tool.tool["id"]).target[5:]
245         if self.output_name:
246             self.job_order["arv:output_name"] = self.output_name
247         return {
248             "script": "cwl-runner",
249             "script_version": __version__,
250             "repository": "arvados",
251             "script_parameters": self.job_order,
252             "runtime_constraints": {
253                 "docker_image": arvados_jobs_image(self.arvrunner)
254             }
255         }
256
257     def run(self, *args, **kwargs):
258         job_spec = self.arvados_job_spec(*args, **kwargs)
259
260         job_spec.setdefault("owner_uuid", self.arvrunner.project_uuid)
261
262         job = self.arvrunner.api.jobs().create(
263             body=job_spec,
264             find_or_create=self.enable_reuse
265         ).execute(num_retries=self.arvrunner.num_retries)
266
267         for k,v in job_spec["script_parameters"].items():
268             if v is False or v is None or isinstance(v, dict):
269                 job_spec["script_parameters"][k] = {"value": v}
270
271         del job_spec["owner_uuid"]
272         job_spec["job"] = job
273         self.arvrunner.pipeline = self.arvrunner.api.pipeline_instances().create(
274             body={
275                 "owner_uuid": self.arvrunner.project_uuid,
276                 "name": shortname(self.tool.tool["id"]),
277                 "components": {"cwl-runner": job_spec },
278                 "state": "RunningOnServer"}).execute(num_retries=self.arvrunner.num_retries)
279         logger.info("Created pipeline %s", self.arvrunner.pipeline["uuid"])
280
281         if kwargs.get("wait") is False:
282             self.uuid = self.arvrunner.pipeline["uuid"]
283             return
284
285         self.uuid = job["uuid"]
286         self.arvrunner.processes[self.uuid] = self
287
288         if job["state"] in ("Complete", "Failed", "Cancelled"):
289             self.done(job)
290
291
292 class RunnerTemplate(object):
293     """An Arvados pipeline template that invokes a CWL workflow."""
294
295     type_to_dataclass = {
296         'boolean': 'boolean',
297         'File': 'File',
298         'Directory': 'Collection',
299         'float': 'number',
300         'int': 'number',
301         'string': 'text',
302     }
303
304     def __init__(self, runner, tool, job_order, enable_reuse):
305         self.runner = runner
306         self.tool = tool
307         self.job = RunnerJob(
308             runner=runner,
309             tool=tool,
310             job_order=job_order,
311             enable_reuse=enable_reuse,
312             output_name=None)
313
314     def pipeline_component_spec(self):
315         """Return a component that Workbench and a-r-p-i will understand.
316
317         Specifically, translate CWL input specs to Arvados pipeline
318         format, like {"dataclass":"File","value":"xyz"}.
319         """
320         spec = self.job.arvados_job_spec()
321
322         # Most of the component spec is exactly the same as the job
323         # spec (script, script_version, etc.).
324         # spec['script_parameters'] isn't right, though. A component
325         # spec's script_parameters hash is a translation of
326         # self.tool.tool['inputs'] with defaults/overrides taken from
327         # the job order. So we move the job parameters out of the way
328         # and build a new spec['script_parameters'].
329         job_params = spec['script_parameters']
330         spec['script_parameters'] = {}
331
332         for param in self.tool.tool['inputs']:
333             param = copy.deepcopy(param)
334
335             # Data type and "required" flag...
336             types = param['type']
337             if not isinstance(types, list):
338                 types = [types]
339             param['required'] = 'null' not in types
340             non_null_types = set(types) - set(['null'])
341             if len(non_null_types) == 1:
342                 the_type = [c for c in non_null_types][0]
343                 dataclass = self.type_to_dataclass.get(the_type)
344                 if dataclass:
345                     param['dataclass'] = dataclass
346             # Note: If we didn't figure out a single appropriate
347             # dataclass, we just left that attribute out.  We leave
348             # the "type" attribute there in any case, which might help
349             # downstream.
350
351             # Title and description...
352             title = param.pop('label', '')
353             descr = param.pop('doc', '').rstrip('\n')
354             if title:
355                 param['title'] = title
356             if descr:
357                 param['description'] = descr
358
359             # Fill in the value from the current job order, if any.
360             param_id = shortname(param.pop('id'))
361             value = job_params.get(param_id)
362             if value is None:
363                 pass
364             elif not isinstance(value, dict):
365                 param['value'] = value
366             elif param.get('dataclass') in ('File', 'Collection') and value.get('location'):
367                 param['value'] = value['location'][5:]
368
369             spec['script_parameters'][param_id] = param
370         spec['script_parameters']['cwl:tool'] = job_params['cwl:tool']
371         return spec
372
373     def save(self):
374         job_spec = self.pipeline_component_spec()
375         response = self.runner.api.pipeline_templates().create(body={
376             "components": {
377                 self.job.name: job_spec,
378             },
379             "name": self.job.name,
380             "owner_uuid": self.runner.project_uuid,
381         }, ensure_unique_name=True).execute(num_retries=self.runner.num_retries)
382         self.uuid = response["uuid"]
383         logger.info("Created template %s", self.uuid)