import os import urlparse from functools import partial import logging import json import subprocess from StringIO import StringIO from schema_salad.sourceline import SourceLine import cwltool.draft2tool from cwltool.draft2tool import CommandLineTool import cwltool.workflow from cwltool.process import get_feature, scandeps, UnsupportedRequirement, normalizeFilesDirs, shortname from cwltool.load_tool import fetch_document from cwltool.pathmapper import adjustFileObjs, adjustDirObjs from cwltool.utils import aslist from cwltool.builder import substitute from cwltool.pack import pack import arvados.collection import ruamel.yaml as yaml from .arvdocker import arv_docker_get_image from .pathmapper import ArvPathMapper, trim_listing from ._version import __version__ from . import done logger = logging.getLogger('arvados.cwl-runner') def trim_anonymous_location(obj): """Remove 'location' field from File and Directory literals. To make internal handling easier, literals are assigned a random id for 'location'. However, when writing the record back out, this can break reproducibility. Since it is valid for literals not have a 'location' field, remove it. """ if obj.get("location", "").startswith("_:"): del obj["location"] def upload_dependencies(arvrunner, name, document_loader, workflowobj, uri, loadref_run, include_primary=True): """Upload the dependencies of the workflowobj document to Keep. Returns a pathmapper object mapping local paths to keep references. Also does an in-place update of references in "workflowobj". Use scandeps to find $import, $include, $schemas, run, File and Directory fields that represent external references. If workflowobj has an "id" field, this will reload the document to ensure it is scanning the raw document prior to preprocessing. """ loaded = set() def loadref(b, u): joined = document_loader.fetcher.urljoin(b, u) defrg, _ = urlparse.urldefrag(joined) if defrg not in loaded: loaded.add(defrg) # Use fetch_text to get raw file (before preprocessing). text = document_loader.fetch_text(defrg) if isinstance(text, bytes): textIO = StringIO(text.decode('utf-8')) else: textIO = StringIO(text) return yaml.safe_load(textIO) else: return {} if loadref_run: loadref_fields = set(("$import", "run")) else: loadref_fields = set(("$import",)) scanobj = workflowobj if "id" in workflowobj: # Need raw file content (before preprocessing) to ensure # that external references in $include and $mixin are captured. scanobj = loadref("", workflowobj["id"]) sc = scandeps(uri, scanobj, loadref_fields, set(("$include", "$schemas", "location")), loadref, urljoin=document_loader.fetcher.urljoin) normalizeFilesDirs(sc) if include_primary and "id" in workflowobj: sc.append({"class": "File", "location": workflowobj["id"]}) if "$schemas" in workflowobj: for s in workflowobj["$schemas"]: sc.append({"class": "File", "location": s}) mapper = ArvPathMapper(arvrunner, sc, "", "keep:%s", "keep:%s/%s", name=name) def setloc(p): if "location" in p and (not p["location"].startswith("_:")) and (not p["location"].startswith("keep:")): p["location"] = mapper.mapper(p["location"]).resolved adjustFileObjs(workflowobj, setloc) adjustDirObjs(workflowobj, setloc) if "$schemas" in workflowobj: sch = [] for s in workflowobj["$schemas"]: sch.append(mapper.mapper(s).resolved) workflowobj["$schemas"] = sch return mapper def upload_docker(arvrunner, tool): """Uploads Docker images used in CommandLineTool objects.""" if isinstance(tool, CommandLineTool): (docker_req, docker_is_req) = get_feature(tool, "DockerRequirement") if docker_req: if docker_req.get("dockerOutputDirectory"): # TODO: can be supported by containers API, but not jobs API. raise SourceLine(docker_req, "dockerOutputDirectory", UnsupportedRequirement).makeError( "Option 'dockerOutputDirectory' of DockerRequirement not supported.") arv_docker_get_image(arvrunner.api, docker_req, True, arvrunner.project_uuid) elif isinstance(tool, cwltool.workflow.Workflow): for s in tool.steps: upload_docker(arvrunner, s.embedded_tool) def packed_workflow(arvrunner, tool): """Create a packed workflow. A "packed" workflow is one where all the components have been combined into a single document.""" return pack(tool.doc_loader, tool.doc_loader.fetch(tool.tool["id"]), tool.tool["id"], tool.metadata) def tag_git_version(packed): if tool.tool["id"].startswith("file://"): path = os.path.dirname(tool.tool["id"][7:]) try: githash = subprocess.check_output(['git', 'log', '--first-parent', '--max-count=1', '--format=%H'], stderr=subprocess.STDOUT, cwd=path).strip() except (OSError, subprocess.CalledProcessError): pass else: packed["http://schema.org/version"] = githash def upload_job_order(arvrunner, name, tool, job_order): """Upload local files referenced in the input object and return updated input object with 'location' updated to the proper keep references. """ for t in tool.tool["inputs"]: def setSecondary(fileobj): if isinstance(fileobj, dict) and fileobj.get("class") == "File": if "secondaryFiles" not in fileobj: fileobj["secondaryFiles"] = [{"location": substitute(fileobj["location"], sf), "class": "File"} for sf in t["secondaryFiles"]] if isinstance(fileobj, list): for e in fileobj: setSecondary(e) if shortname(t["id"]) in job_order and t.get("secondaryFiles"): setSecondary(job_order[shortname(t["id"])]) jobmapper = upload_dependencies(arvrunner, name, tool.doc_loader, job_order, job_order.get("id", "#"), False) if "id" in job_order: del job_order["id"] # Need to filter this out, gets added by cwltool when providing # parameters on the command line. if "job_order" in job_order: del job_order["job_order"] return job_order def upload_workflow_deps(arvrunner, tool): # Ensure that Docker images needed by this workflow are available upload_docker(arvrunner, tool) document_loader = tool.doc_loader def upload_tool_deps(deptool): if "id" in deptool: upload_dependencies(arvrunner, "%s dependencies" % (shortname(deptool["id"])), document_loader, deptool, deptool["id"], False, include_primary=False) document_loader.idx[deptool["id"]] = deptool tool.visit(upload_tool_deps) def arvados_jobs_image(arvrunner, img): """Determine if the right arvados/jobs image version is available. If not, try to pull and upload it.""" try: arv_docker_get_image(arvrunner.api, {"dockerPull": img}, True, arvrunner.project_uuid) except Exception as e: raise Exception("Docker image %s is not available\n%s" % (img, e) ) return img def upload_workflow_collection(arvrunner, name, packed): collection = arvados.collection.Collection(api_client=arvrunner.api, keep_client=arvrunner.keep_client, num_retries=arvrunner.num_retries) with collection.open("workflow.cwl", "w") as f: f.write(json.dumps(packed, indent=2, sort_keys=True, separators=(',',': '))) filters = [["portable_data_hash", "=", collection.portable_data_hash()], ["name", "like", name+"%"]] if arvrunner.project_uuid: filters.append(["owner_uuid", "=", arvrunner.project_uuid]) exists = arvrunner.api.collections().list(filters=filters).execute(num_retries=arvrunner.num_retries) if exists["items"]: logger.info("Using collection %s", exists["items"][0]["uuid"]) else: collection.save_new(name=name, owner_uuid=arvrunner.project_uuid, ensure_unique_name=True, num_retries=arvrunner.num_retries) logger.info("Uploaded to %s", collection.manifest_locator()) return collection.portable_data_hash() class Runner(object): """Base class for runner processes, which submit an instance of arvados-cwl-runner and wait for the final result.""" def __init__(self, runner, tool, job_order, enable_reuse, output_name, output_tags, submit_runner_ram=0, name=None, on_error=None, submit_runner_image=None): self.arvrunner = runner self.tool = tool self.job_order = job_order self.running = False self.enable_reuse = enable_reuse self.uuid = None self.final_output = None self.output_name = output_name self.output_tags = output_tags self.name = name self.on_error = on_error self.jobs_image = submit_runner_image or "arvados/jobs:"+__version__ if submit_runner_ram: self.submit_runner_ram = submit_runner_ram else: self.submit_runner_ram = 3000 if self.submit_runner_ram <= 0: raise Exception("Value of --submit-runner-ram must be greater than zero") def update_pipeline_component(self, record): pass def done(self, record): """Base method for handling a completed runner.""" try: if record["state"] == "Complete": if record.get("exit_code") is not None: if record["exit_code"] == 33: processStatus = "UnsupportedRequirement" elif record["exit_code"] == 0: processStatus = "success" else: processStatus = "permanentFail" else: processStatus = "success" else: processStatus = "permanentFail" outputs = {} if processStatus == "permanentFail": logc = arvados.collection.CollectionReader(record["log"], api_client=self.arvrunner.api, keep_client=self.arvrunner.keep_client, num_retries=self.arvrunner.num_retries) done.logtail(logc, logger, "%s error log:" % self.arvrunner.label(self), maxlen=40) self.final_output = record["output"] outc = arvados.collection.CollectionReader(self.final_output, api_client=self.arvrunner.api, keep_client=self.arvrunner.keep_client, num_retries=self.arvrunner.num_retries) if "cwl.output.json" in outc: with outc.open("cwl.output.json") as f: if f.size() > 0: outputs = json.load(f) def keepify(fileobj): path = fileobj["location"] if not path.startswith("keep:"): fileobj["location"] = "keep:%s/%s" % (record["output"], path) adjustFileObjs(outputs, keepify) adjustDirObjs(outputs, keepify) except Exception as e: logger.exception("[%s] While getting final output object: %s", self.name, e) self.arvrunner.output_callback({}, "permanentFail") else: self.arvrunner.output_callback(outputs, processStatus) finally: if record["uuid"] in self.arvrunner.processes: del self.arvrunner.processes[record["uuid"]]