Coverage for python/lsst/ctrl/bps/htcondor/lssthtc.py: 2%
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1# This file is part of ctrl_bps_htcondor.
2#
3# Developed for the LSST Data Management System.
4# This product includes software developed by the LSST Project
5# (https://www.lsst.org).
6# See the COPYRIGHT file at the top-level directory of this distribution
7# for details of code ownership.
8#
9# This program is free software: you can redistribute it and/or modify
10# it under the terms of the GNU General Public License as published by
11# the Free Software Foundation, either version 3 of the License, or
12# (at your option) any later version.
13#
14# This program is distributed in the hope that it will be useful,
15# but WITHOUT ANY WARRANTY; without even the implied warranty of
16# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
17# GNU General Public License for more details.
18#
19# You should have received a copy of the GNU General Public License
20# along with this program. If not, see <https://www.gnu.org/licenses/>.
22"""Placeholder HTCondor DAGMan API.
24There is new work on a python DAGMan API from HTCondor. However, at this
25time, it tries to make things easier by assuming DAG is easily broken into
26levels where there are 1-1 or all-to-all relationships to nodes in next
27level. LSST workflows are more complicated.
28"""
30__all__ = [
31 "DagStatus",
32 "JobStatus",
33 "NodeStatus",
34 "RestrictedDict",
35 "HTCJob",
36 "HTCDag",
37 "htc_backup_files",
38 "htc_check_dagman_output",
39 "htc_create_submit_from_cmd",
40 "htc_create_submit_from_dag",
41 "htc_create_submit_from_file",
42 "htc_escape",
43 "htc_write_attribs",
44 "htc_write_condor_file",
45 "htc_version",
46 "htc_submit_dag",
47 "condor_history",
48 "condor_q",
49 "condor_search",
50 "condor_status",
51 "update_job_info",
52 "MISSING_ID",
53 "summary_from_dag",
54 "read_dag_info",
55 "read_dag_log",
56 "read_dag_nodes_log",
57 "read_dag_status",
58 "read_node_status",
59 "write_dag_info",
60 "pegasus_name_to_label",
61]
64import itertools
65import json
66import logging
67import os
68import pprint
69import re
70import subprocess
71from collections import defaultdict
72from collections.abc import MutableMapping
73from datetime import datetime, timedelta
74from enum import IntEnum
75from pathlib import Path
77import classad
78import htcondor
79import networkx
81_LOG = logging.getLogger(__name__)
83MISSING_ID = -99999
86class DagStatus(IntEnum):
87 """HTCondor DAGMan's statuses for a DAG."""
89 OK = 0
90 ERROR = 1 # an error condition different than those listed here
91 FAILED = 2 # one or more nodes in the DAG have failed
92 ABORTED = 3 # the DAG has been aborted by an ABORT-DAG-ON specification
93 REMOVED = 4 # the DAG has been removed by condor_rm
94 CYCLE = 5 # a cycle was found in the DAG
95 SUSPENDED = 6 # the DAG has been suspended (see section 2.10.8)
98class JobStatus(IntEnum):
99 """HTCondor's statuses for jobs."""
101 UNEXPANDED = 0 # Unexpanded
102 IDLE = 1 # Idle
103 RUNNING = 2 # Running
104 REMOVED = 3 # Removed
105 COMPLETED = 4 # Completed
106 HELD = 5 # Held
107 TRANSFERRING_OUTPUT = 6 # Transferring_Output
108 SUSPENDED = 7 # Suspended
111class NodeStatus(IntEnum):
112 """HTCondor's statuses for DAGman nodes."""
114 # (STATUS_NOT_READY): At least one parent has not yet finished or the node
115 # is a FINAL node.
116 NOT_READY = 0
118 # (STATUS_READY): All parents have finished, but the node is not yet
119 # running.
120 READY = 1
122 # (STATUS_PRERUN): The node’s PRE script is running.
123 PRERUN = 2
125 # (STATUS_SUBMITTED): The node’s HTCondor job(s) are in the queue.
126 # StatusDetails = "not_idle" -> running.
127 # JobProcsHeld = 1-> hold.
128 # JobProcsQueued = 1 -> idle.
129 SUBMITTED = 3
131 # (STATUS_POSTRUN): The node’s POST script is running.
132 POSTRUN = 4
134 # (STATUS_DONE): The node has completed successfully.
135 DONE = 5
137 # (STATUS_ERROR): The node has failed. StatusDetails has info (e.g.,
138 # ULOG_JOB_ABORTED for deleted job).
139 ERROR = 6
142HTC_QUOTE_KEYS = {"environment"}
143HTC_VALID_JOB_KEYS = {
144 "universe",
145 "executable",
146 "arguments",
147 "environment",
148 "log",
149 "error",
150 "output",
151 "should_transfer_files",
152 "when_to_transfer_output",
153 "getenv",
154 "notification",
155 "notify_user",
156 "concurrency_limit",
157 "transfer_executable",
158 "transfer_input_files",
159 "transfer_output_files",
160 "request_cpus",
161 "request_memory",
162 "request_disk",
163 "priority",
164 "category",
165 "requirements",
166 "on_exit_hold",
167 "on_exit_hold_reason",
168 "on_exit_hold_subcode",
169 "max_retries",
170 "periodic_release",
171 "periodic_remove",
172 "accounting_group",
173 "accounting_group_user",
174}
175HTC_VALID_JOB_DAG_KEYS = {"vars", "pre", "post", "retry", "retry_unless_exit", "abort_dag_on", "abort_exit"}
178class RestrictedDict(MutableMapping):
179 """A dictionary that only allows certain keys.
181 Parameters
182 ----------
183 valid_keys : `Container`
184 Strings that are valid keys.
185 init_data : `dict` or `RestrictedDict`, optional
186 Initial data.
188 Raises
189 ------
190 KeyError
191 If invalid key(s) in init_data.
192 """
194 def __init__(self, valid_keys, init_data=()):
195 self.valid_keys = valid_keys
196 self.data = {}
197 self.update(init_data)
199 def __getitem__(self, key):
200 """Returns value for given key if exists.
202 Parameters
203 ----------
204 key : `str`
205 Identifier for value to return.
207 Returns
208 -------
209 value : `Any`
210 Value associated with given key.
212 Raises
213 ------
214 KeyError
215 If key doesn't exist.
216 """
217 return self.data[key]
219 def __delitem__(self, key):
220 """Deletes value for given key if exists.
222 Parameters
223 ----------
224 key : `str`
225 Identifier for value to delete.
227 Raises
228 ------
229 KeyError
230 If key doesn't exist.
231 """
232 del self.data[key]
234 def __setitem__(self, key, value):
235 """Stores key,value in internal dict only if key is valid
237 Parameters
238 ----------
239 key : `str`
240 Identifier to associate with given value.
241 value : `Any`
242 Value to store.
244 Raises
245 ------
246 KeyError
247 If key is invalid.
248 """
249 if key not in self.valid_keys:
250 raise KeyError(f"Invalid key {key}")
251 self.data[key] = value
253 def __iter__(self):
254 return self.data.__iter__()
256 def __len__(self):
257 return len(self.data)
259 def __str__(self):
260 return str(self.data)
263def htc_backup_files(wms_path, subdir=None, limit=100):
264 """Backup select HTCondor files in the submit directory.
266 Files will be saved in separate subdirectories which will be created in
267 the submit directory where the files are located. These subdirectories
268 will be consecutive, zero-padded integers. Their values will correspond to
269 the number of HTCondor rescue DAGs in the submit directory.
271 Hence, with the default settings, copies after the initial failed run will
272 be placed in '001' subdirectory, '002' after the first restart, and so on
273 until the limit of backups is reached. If there's no rescue DAG yet, files
274 will be copied to '000' subdirectory.
276 Parameters
277 ----------
278 wms_path : `str` or `pathlib.Path`
279 Path to the submit directory either absolute or relative.
280 subdir : `str` or `pathlib.Path`, optional
281 A path, relative to the submit directory, where all subdirectories with
282 backup files will be kept. Defaults to None which means that the backup
283 subdirectories will be placed directly in the submit directory.
284 limit : `int`, optional
285 Maximal number of backups. If the number of backups reaches the limit,
286 the last backup files will be overwritten. The default value is 100
287 to match the default value of HTCondor's DAGMAN_MAX_RESCUE_NUM in
288 version 8.8+.
290 Raises
291 ------
292 FileNotFoundError
293 If the submit directory or the file that needs to be backed up does not
294 exist.
295 OSError
296 If the submit directory cannot be accessed or backing up a file failed
297 either due to permission or filesystem related issues.
299 Notes
300 -----
301 This is not a generic function for making backups. It is intended to be
302 used once, just before a restart, to make snapshots of files which will be
303 overwritten by HTCondor after during the next run.
304 """
305 width = len(str(limit))
307 path = Path(wms_path).resolve()
308 if not path.is_dir():
309 raise FileNotFoundError(f"Directory {path} not found")
311 # Initialize the backup counter.
312 rescue_dags = list(Path(wms_path).glob("*.rescue*"))
313 counter = min(len(rescue_dags), limit)
315 # Create the backup directory and move select files there.
316 dest = Path(wms_path)
317 if subdir:
318 # PurePath.is_relative_to() is not available before Python 3.9. Hence
319 # we need to check is 'subdir' is in the submit directory in some other
320 # way if it is an absolute path.
321 subdir = Path(subdir)
322 if subdir.is_absolute():
323 if dest not in subdir.parents:
324 _LOG.warning(
325 "Invalid backup location: '%s' not in the submit directory, will use '%s' instead.",
326 subdir,
327 wms_path,
328 )
329 else:
330 dest /= subdir
331 else:
332 dest /= subdir
333 dest /= f"{counter:0{width}}"
334 try:
335 dest.mkdir(parents=True, exist_ok=False if counter < limit else True)
336 except FileExistsError:
337 _LOG.warning("Refusing to do backups: target directory '%s' already exists", dest)
338 else:
339 for patt in ["*.info.*", "*.dag.metrics", "*.dag.nodes.log", "*.node_status"]:
340 for source in path.glob(patt):
341 if source.is_file():
342 target = dest / source.relative_to(path)
343 try:
344 source.rename(target)
345 except OSError as exc:
346 raise type(exc)(f"Backing up '{source}' failed: {exc.strerror}") from None
347 else:
348 raise FileNotFoundError(f"Backing up '{source}' failed: not a file")
351def htc_escape(value):
352 """Escape characters in given value based upon HTCondor syntax.
354 Parameters
355 ----------
356 value : `Any`
357 Value that needs to have characters escaped if string.
359 Returns
360 -------
361 new_value : `Any`
362 Given value with characters escaped appropriate for HTCondor if string.
363 """
364 if isinstance(value, str):
365 newval = value.replace('"', '""').replace("'", "''").replace(""", '"')
366 else:
367 newval = value
369 return newval
372def htc_write_attribs(stream, attrs):
373 """Write job attributes in HTCondor format to writeable stream.
375 Parameters
376 ----------
377 stream : `TextIOBase`
378 Output text stream (typically an open file)
379 attrs : `dict`
380 HTCondor job attributes (dictionary of attribute key, value)
381 """
382 for key, value in attrs.items():
383 # Make sure strings are syntactically correct for HTCondor.
384 if isinstance(value, str):
385 pval = f'"{htc_escape(value)}"'
386 else:
387 pval = value
389 print(f"+{key} = {pval}", file=stream)
392def htc_write_condor_file(filename, job_name, job, job_attrs):
393 """Main function to write an HTCondor submit file.
395 Parameters
396 ----------
397 filename : `str`
398 Filename for the HTCondor submit file
399 job_name : `str`
400 Job name to use in submit file
401 job : `RestrictedDict`
402 Submit script information.
403 job_attrs : `dict`
404 Job attributes.
405 """
406 os.makedirs(os.path.dirname(filename), exist_ok=True)
407 with open(filename, "w") as fh:
408 for key, value in job.items():
409 if value is not None:
410 if key in HTC_QUOTE_KEYS:
411 print(f'{key}="{htc_escape(value)}"', file=fh)
412 else:
413 print(f"{key}={value}", file=fh)
414 for key in ["output", "error", "log"]:
415 if key not in job:
416 filename = f"{job_name}.$(Cluster).${key[:3]}"
417 print(f"{key}={filename}", file=fh)
419 if job_attrs is not None:
420 htc_write_attribs(fh, job_attrs)
421 print("queue", file=fh)
424def htc_version():
425 """Return the version given by the HTCondor API.
427 Returns
428 -------
429 version : `str`
430 HTCondor version as easily comparable string.
432 Raises
433 ------
434 RuntimeError
435 Raised if fail to parse htcondor API string.
436 """
437 # Example string returned by htcondor.version:
438 # $CondorVersion: 8.8.6 Nov 13 2019 BuildID: 489199 PackageID: 8.8.6-1 $
439 version_info = re.match(r"\$CondorVersion: (\d+).(\d+).(\d+)", htcondor.version())
440 if version_info is None:
441 raise RuntimeError("Problems parsing condor version")
442 return f"{int(version_info.group(1))}.{int(version_info.group(2))}.{int(version_info.group(3))}"
445def htc_submit_dag(sub):
446 """Submit job for execution.
448 Parameters
449 ----------
450 sub : `htcondor.Submit`
451 An object representing a job submit description.
453 Returns
454 -------
455 schedd_job_info : `dict` [`str`, `dict` [`str`, `dict` [`str` Any]]]
456 Information about jobs satisfying the search criteria where for each
457 Scheduler, local HTCondor job ids are mapped to their respective
458 classads.
459 """
460 coll = htcondor.Collector()
461 schedd_ad = coll.locate(htcondor.DaemonTypes.Schedd)
462 schedd = htcondor.Schedd(schedd_ad)
464 jobs_ads = []
465 with schedd.transaction() as txn:
466 sub.queue(txn, ad_results=jobs_ads)
468 # Submit.queue() above will raise RuntimeError if submission fails, so
469 # 'jobs_ads' should contain the ad at this point.
470 dag_ad = jobs_ads[0]
472 # Sadly, the ClassAd from Submit.queue() (see above) does not have
473 # 'GlobalJobId' so we need to run a regular query to get it anyway.
474 schedd_name = schedd_ad["Name"]
475 schedd_dag_info = condor_q(
476 constraint=f"ClusterId == {dag_ad['ClusterId']}", schedds={schedd_name: schedd}
477 )
478 return schedd_dag_info
481def htc_create_submit_from_dag(dag_filename, submit_options=None):
482 """Create a DAGMan job submit description.
484 Parameters
485 ----------
486 dag_filename : `str`
487 Name of file containing HTCondor DAG commands.
488 submit_options : `dict` [`str`, Any], optional
489 Contains extra options for command line (Value of None means flag).
491 Returns
492 -------
493 sub : `htcondor.Submit`
494 An object representing a job submit description.
496 Notes
497 -----
498 Use with HTCondor versions which support htcondor.Submit.from_dag(),
499 i.e., 8.9.3 or newer.
500 """
501 return htcondor.Submit.from_dag(dag_filename, submit_options)
504def htc_create_submit_from_cmd(dag_filename, submit_options=None):
505 """Create a DAGMan job submit description.
507 Create a DAGMan job submit description by calling ``condor_submit_dag``
508 on given DAG description file.
510 Parameters
511 ----------
512 dag_filename : `str`
513 Name of file containing HTCondor DAG commands.
514 submit_options : `dict` [`str`, Any], optional
515 Contains extra options for command line (Value of None means flag).
517 Returns
518 -------
519 sub : `htcondor.Submit`
520 An object representing a job submit description.
522 Notes
523 -----
524 Use with HTCondor versions which do not support htcondor.Submit.from_dag(),
525 i.e., older than 8.9.3.
526 """
527 # Run command line condor_submit_dag command.
528 cmd = "condor_submit_dag -f -no_submit -notification never -autorescue 1 -UseDagDir -no_recurse "
530 if submit_options is not None:
531 for opt, val in submit_options.items():
532 cmd += f" -{opt} {val or ''}"
533 cmd += f"{dag_filename}"
535 process = subprocess.Popen(
536 cmd.split(), shell=False, stdout=subprocess.PIPE, stderr=subprocess.STDOUT, encoding="utf-8"
537 )
538 process.wait()
540 if process.returncode != 0:
541 print(f"Exit code: {process.returncode}")
542 print(process.communicate()[0])
543 raise RuntimeError("Problems running condor_submit_dag")
545 return htc_create_submit_from_file(f"{dag_filename}.condor.sub")
548def htc_create_submit_from_file(submit_file):
549 """Parse a submission file.
551 Parameters
552 ----------
553 submit_file : `str`
554 Name of the HTCondor submit file.
556 Returns
557 -------
558 sub : `htcondor.Submit`
559 An object representing a job submit description.
560 """
561 descriptors = {}
562 with open(submit_file, "r") as fh:
563 for line in fh:
564 line = line.strip()
565 if not line.startswith("#") and not line == "queue":
566 (key, val) = re.split(r"\s*=\s*", line, 1)
567 descriptors[key] = val
569 # Avoid UserWarning: the line 'copy_to_spool = False' was
570 # unused by Submit object. Is it a typo?
571 try:
572 del descriptors["copy_to_spool"]
573 except KeyError:
574 pass
576 return htcondor.Submit(descriptors)
579def _htc_write_job_commands(stream, name, jobs):
580 """Output the DAGMan job lines for single job in DAG.
582 Parameters
583 ----------
584 stream : `TextIOBase`
585 Writeable text stream (typically an opened file).
586 name : `str`
587 Job name.
588 jobs : `RestrictedDict`
589 DAG job keys and values.
590 """
591 if "pre" in jobs:
592 print(
593 f"SCRIPT {jobs['pre'].get('defer', '')} PRE {name}"
594 f"{jobs['pre']['executable']} {jobs['pre'].get('arguments', '')}",
595 file=stream,
596 )
598 if "post" in jobs:
599 print(
600 f"SCRIPT {jobs['post'].get('defer', '')} PRE {name}"
601 f"{jobs['post']['executable']} {jobs['post'].get('arguments', '')}",
602 file=stream,
603 )
605 if "vars" in jobs:
606 for key, value in jobs["vars"]:
607 print(f'VARS {name} {key}="{htc_escape(value)}"', file=stream)
609 if "pre_skip" in jobs:
610 print(f"PRE_SKIP {name} {jobs['pre_skip']}", file=stream)
612 if "retry" in jobs and jobs["retry"]:
613 print(f"RETRY {name} {jobs['retry']} ", end="", file=stream)
614 if "retry_unless_exit" in jobs:
615 print(f"UNLESS-EXIT {jobs['retry_unless_exit']}", end="", file=stream)
616 print("\n", file=stream)
618 if "abort_dag_on" in jobs and jobs["abort_dag_on"]:
619 print(
620 f"ABORT-DAG-ON {name} {jobs['abort_dag_on']['node_exit']}"
621 f" RETURN {jobs['abort_dag_on']['abort_exit']}",
622 file=stream,
623 )
626class HTCJob:
627 """HTCondor job for use in building DAG.
629 Parameters
630 ----------
631 name : `str`
632 Name of the job
633 label : `str`
634 Label that can used for grouping or lookup.
635 initcmds : `RestrictedDict`
636 Initial job commands for submit file.
637 initdagcmds : `RestrictedDict`
638 Initial commands for job inside DAG.
639 initattrs : `dict`
640 Initial dictionary of job attributes.
641 """
643 def __init__(self, name, label=None, initcmds=(), initdagcmds=(), initattrs=None):
644 self.name = name
645 self.label = label
646 self.cmds = RestrictedDict(HTC_VALID_JOB_KEYS, initcmds)
647 self.dagcmds = RestrictedDict(HTC_VALID_JOB_DAG_KEYS, initdagcmds)
648 self.attrs = initattrs
649 self.subfile = None
651 def __str__(self):
652 return self.name
654 def add_job_cmds(self, new_commands):
655 """Add commands to Job (overwrite existing).
657 Parameters
658 ----------
659 new_commands : `dict`
660 Submit file commands to be added to Job.
661 """
662 self.cmds.update(new_commands)
664 def add_dag_cmds(self, new_commands):
665 """Add DAG commands to Job (overwrite existing).
667 Parameters
668 ----------
669 new_commands : `dict`
670 DAG file commands to be added to Job
671 """
672 self.dagcmds.update(new_commands)
674 def add_job_attrs(self, new_attrs):
675 """Add attributes to Job (overwrite existing).
677 Parameters
678 ----------
679 new_attrs : `dict`
680 Attributes to be added to Job
681 """
682 if self.attrs is None:
683 self.attrs = {}
684 if new_attrs:
685 self.attrs.update(new_attrs)
687 def write_submit_file(self, submit_path, job_subdir=""):
688 """Write job description to submit file.
690 Parameters
691 ----------
692 submit_path : `str`
693 Prefix path for the submit file.
694 job_subdir : `str`, optional
695 Template for job subdir.
696 """
697 if not self.subfile:
698 self.subfile = f"{self.name}.sub"
699 job_subdir = job_subdir.format(self=self)
700 if job_subdir:
701 self.subfile = os.path.join(job_subdir, self.subfile)
702 htc_write_condor_file(os.path.join(submit_path, self.subfile), self.name, self.cmds, self.attrs)
704 def write_dag_commands(self, stream):
705 """Write DAG commands for single job to output stream.
707 Parameters
708 ----------
709 stream : `IO` or `str`
710 Output Stream
711 """
712 print(f"JOB {self.name} {self.subfile}", file=stream)
713 _htc_write_job_commands(stream, self.name, self.dagcmds)
715 def dump(self, fh):
716 """Dump job information to output stream.
718 Parameters
719 ----------
720 fh : `TextIOBase`
721 Output stream
722 """
723 printer = pprint.PrettyPrinter(indent=4, stream=fh)
724 printer.pprint(self.name)
725 printer.pprint(self.cmds)
726 printer.pprint(self.attrs)
729class HTCDag(networkx.DiGraph):
730 """HTCondor DAG.
732 Parameters
733 ----------
734 data : networkx.DiGraph.data
735 Initial graph.
736 name : `str`
737 Name for DAG.
738 """
740 def __init__(self, data=None, name=""):
741 super().__init__(data=data, name=name)
743 self.graph["attr"] = {}
744 self.graph["run_id"] = None
745 self.graph["submit_path"] = None
746 self.graph["final_job"] = None
748 def __str__(self):
749 """Represent basic DAG info as string.
751 Returns
752 -------
753 info : `str`
754 String containing basic DAG info.
755 """
756 return f"{self.graph['name']} {len(self)}"
758 def add_attribs(self, attribs=None):
759 """Add attributes to the DAG.
761 Parameters
762 ----------
763 attribs : `dict`
764 DAG attributes
765 """
766 if attribs is not None:
767 self.graph["attr"].update(attribs)
769 def add_job(self, job, parent_names=None, child_names=None):
770 """Add an HTCJob to the HTCDag.
772 Parameters
773 ----------
774 job : `HTCJob`
775 HTCJob to add to the HTCDag
776 parent_names : `Iterable` [`str`], optional
777 Names of parent jobs
778 child_names : `Iterable` [`str`], optional
779 Names of child jobs
780 """
781 assert isinstance(job, HTCJob)
783 # Add dag level attributes to each job
784 job.add_job_attrs(self.graph["attr"])
786 self.add_node(job.name, data=job)
788 if parent_names is not None:
789 self.add_job_relationships(parent_names, job.name)
791 if child_names is not None:
792 self.add_job_relationships(child_names, job.name)
794 def add_job_relationships(self, parents, children):
795 """Add DAG edge between parents and children jobs.
797 Parameters
798 ----------
799 parents : `list` [`str`]
800 Contains parent job name(s).
801 children : `list` [`str`]
802 Contains children job name(s).
803 """
804 self.add_edges_from(itertools.product(parents, children))
806 def add_final_job(self, job):
807 """Add an HTCJob for the FINAL job in HTCDag.
809 Parameters
810 ----------
811 job : `HTCJob`
812 HTCJob to add to the HTCDag as a FINAL job.
813 """
814 # Add dag level attributes to each job
815 job.add_job_attrs(self.graph["attr"])
817 self.graph["final_job"] = job
819 def del_job(self, job_name):
820 """Delete the job from the DAG.
822 Parameters
823 ----------
824 job_name : `str`
825 Name of job in DAG to delete
826 """
827 # Reconnect edges around node to delete
828 parents = self.predecessors(job_name)
829 children = self.successors(job_name)
830 self.add_edges_from(itertools.product(parents, children))
832 # Delete job node (which deletes its edges).
833 self.remove_node(job_name)
835 def write(self, submit_path, job_subdir=""):
836 """Write DAG to a file.
838 Parameters
839 ----------
840 submit_path : `str`
841 Prefix path for dag filename to be combined with DAG name.
842 job_subdir : `str`, optional
843 Template for job subdir.
844 """
845 self.graph["submit_path"] = submit_path
846 self.graph["dag_filename"] = os.path.join(submit_path, f"{self.graph['name']}.dag")
847 os.makedirs(submit_path, exist_ok=True)
848 with open(self.graph["dag_filename"], "w") as fh:
849 for _, nodeval in self.nodes().items():
850 job = nodeval["data"]
851 job.write_submit_file(submit_path, job_subdir)
852 job.write_dag_commands(fh)
853 for edge in self.edges():
854 print(f"PARENT {edge[0]} CHILD {edge[1]}", file=fh)
855 print(f"DOT {self.name}.dot", file=fh)
856 print(f"NODE_STATUS_FILE {self.name}.node_status", file=fh)
858 # Add bps attributes to dag submission
859 for key, value in self.graph["attr"].items():
860 print(f'SET_JOB_ATTR {key}= "{htc_escape(value)}"', file=fh)
862 if self.graph["final_job"]:
863 job = self.graph["final_job"]
864 job.write_submit_file(submit_path, job_subdir)
865 print(f"FINAL {job.name} {job.subfile}", file=fh)
866 if "pre" in job.dagcmds:
867 print(f"SCRIPT PRE {job.name} {job.dagcmds['pre']}", file=fh)
868 if "post" in job.dagcmds:
869 print(f"SCRIPT POST {job.name} {job.dagcmds['post']}", file=fh)
871 def dump(self, fh):
872 """Dump DAG info to output stream.
874 Parameters
875 ----------
876 fh : `IO` or `str`
877 Where to dump DAG info as text.
878 """
879 for key, value in self.graph:
880 print(f"{key}={value}", file=fh)
881 for name, data in self.nodes().items():
882 print(f"{name}:", file=fh)
883 data.dump(fh)
884 for edge in self.edges():
885 print(f"PARENT {edge[0]} CHILD {edge[1]}", file=fh)
886 if self.graph["final_job"]:
887 print(f'FINAL {self.graph["final_job"].name}:', file=fh)
888 self.graph["final_job"].dump(fh)
890 def write_dot(self, filename):
891 """Write a dot version of the DAG.
893 Parameters
894 ----------
895 filename : `str`
896 dot filename
897 """
898 pos = networkx.nx_agraph.graphviz_layout(self)
899 networkx.draw(self, pos=pos)
900 networkx.drawing.nx_pydot.write_dot(self, filename)
903def condor_q(constraint=None, schedds=None):
904 """Query HTCondor for current jobs.
906 Parameters
907 ----------
908 constraint : `str`, optional
909 Constraints to be passed to job query.
910 schedds : `dict` [`str`, `htcondor.Schedd`], optional
911 HTCondor schedulers which to query for job information. If None
912 (default), the query will be run against local scheduler only.
914 Returns
915 -------
916 job_info : `dict` [`str`, `dict` [`str`, `dict` [`str` Any]]]
917 Information about jobs satisfying the search criteria where for each
918 Scheduler, local HTCondor job ids are mapped to their respective
919 classads.
920 """
921 if not schedds:
922 coll = htcondor.Collector()
923 schedd_ad = coll.locate(htcondor.DaemonTypes.Schedd)
924 schedds = {schedd_ad["Name"]: htcondor.Schedd(schedd_ad)}
926 queries = [schedd.xquery(requirements=constraint) for schedd in schedds.values()]
928 job_info = {}
929 for query in htcondor.poll(queries):
930 schedd_name = query.tag()
931 job_info.setdefault(schedd_name, {})
932 for job_ad in query.nextAdsNonBlocking():
933 del job_ad["Environment"]
934 del job_ad["Env"]
935 id_ = f"{int(job_ad['ClusterId'])}.{int(job_ad['ProcId'])}"
936 job_info[schedd_name][id_] = dict(job_ad)
937 _LOG.debug("condor_q returned %d jobs", sum(len(val) for val in job_info.values()))
939 # When returning the results filter out entries for schedulers with no jobs
940 # matching the search criteria.
941 return {key: val for key, val in job_info.items() if val}
944def condor_history(constraint=None, schedds=None):
945 """Get information about completed jobs from HTCondor history.
947 Parameters
948 ----------
949 constraint : `str`, optional
950 Constraints to be passed to job query.
951 schedds : `dict` [`str`, `htcondor.Schedd`], optional
952 HTCondor schedulers which to query for job information. If None
953 (default), the query will be run against the history file of
954 the local scheduler only.
956 Returns
957 -------
958 job_info : `dict` [`str`, `dict` [`str`, `dict` [`str` Any]]]
959 Information about jobs satisfying the search criteria where for each
960 Scheduler, local HTCondor job ids are mapped to their respective
961 classads.
962 """
963 if not schedds:
964 coll = htcondor.Collector()
965 schedd_ad = coll.locate(htcondor.DaemonTypes.Schedd)
966 schedds = {schedd_ad["Name"]: htcondor.Schedd(schedd_ad)}
968 job_info = {}
969 for schedd_name, schedd in schedds.items():
970 job_info[schedd_name] = {}
971 for job_ad in schedd.history(requirements=constraint, projection=[]):
972 del job_ad["Environment"]
973 del job_ad["Env"]
974 id_ = f"{int(job_ad['ClusterId'])}.{int(job_ad['ProcId'])}"
975 job_info[schedd_name][id_] = dict(job_ad)
976 _LOG.debug("condor_history returned %d jobs", sum(len(val) for val in job_info.values()))
978 # When returning the results filter out entries for schedulers with no jobs
979 # matching the search criteria.
980 return {key: val for key, val in job_info.items() if val}
983def condor_search(constraint=None, hist=None, schedds=None):
984 """Search for running and finished jobs satisfying given criteria.
986 Parameters
987 ----------
988 constraint : `str`, optional
989 Constraints to be passed to job query.
990 hist : `float`
991 Limit history search to this many days.
992 schedds : `dict` [`str`, `htcondor.Schedd`], optional
993 The list of the HTCondor schedulers which to query for job information.
994 If None (default), only the local scheduler will be queried.
996 Returns
997 -------
998 job_info : `dict` [`str`, `dict` [`str`, `dict` [`str` Any]]]
999 Information about jobs satisfying the search criteria where for each
1000 Scheduler, local HTCondor job ids are mapped to their respective
1001 classads.
1002 """
1003 if not schedds:
1004 coll = htcondor.Collector()
1005 schedd_ad = coll.locate(htcondor.DaemonTypes.Schedd)
1006 schedds = {schedd_ad["Name"]: htcondor.Schedd(locate_ad=schedd_ad)}
1008 job_info = condor_q(constraint=constraint, schedds=schedds)
1009 if hist is not None:
1010 epoch = (datetime.now() - timedelta(days=hist)).timestamp()
1011 constraint += f" && (CompletionDate >= {epoch} || JobFinishedHookDone >= {epoch})"
1012 hist_info = condor_history(constraint, schedds=schedds)
1013 update_job_info(job_info, hist_info)
1014 return job_info
1017def condor_status(constraint=None, coll=None):
1018 """Get information about HTCondor pool.
1020 Parameters
1021 ----------
1022 constraint : `str`, optional
1023 Constraints to be passed to the query.
1024 coll : `htcondor.Collector`, optional
1025 Object representing HTCondor collector daemon.
1027 Returns
1028 -------
1029 pool_info : `dict` [`str`, `dict` [`str`, Any]]
1030 Mapping between HTCondor slot names and slot information (classAds).
1031 """
1032 if coll is None:
1033 coll = htcondor.Collector()
1034 try:
1035 pool_ads = coll.query(constraint=constraint)
1036 except OSError as ex:
1037 raise RuntimeError(f"Problem querying the Collector. (Constraint='{constraint}')") from ex
1039 pool_info = {}
1040 for slot in pool_ads:
1041 pool_info[slot["name"]] = dict(slot)
1042 _LOG.debug("condor_status returned %d ads", len(pool_info))
1043 return pool_info
1046def update_job_info(job_info, other_info):
1047 """Update results of a job query with results from another query.
1049 Parameters
1050 ----------
1051 job_info : `dict` [`str`, `dict` [`str`, Any]]
1052 Results of the job query that needs to be updated.
1053 other_info : `dict` [`str`, `dict` [`str`, Any]]
1054 Results of the other job query.
1056 Returns
1057 -------
1058 job_info : `dict` [`str`, `dict` [`str`, Any]]
1059 The updated results.
1060 """
1061 for schedd_name, others in other_info.items():
1062 try:
1063 jobs = job_info[schedd_name]
1064 except KeyError:
1065 job_info[schedd_name] = others
1066 else:
1067 for id_, ad in others.items():
1068 jobs.setdefault(id_, {}).update(ad)
1069 return job_info
1072def summary_from_dag(dir_name):
1073 """Build bps_run_summary string from dag file.
1075 Parameters
1076 ----------
1077 dir_name : `str`
1078 Path that includes dag file for a run.
1080 Returns
1081 -------
1082 summary : `str`
1083 Semi-colon separated list of job labels and counts.
1084 (Same format as saved in dag classad.)
1085 job_name_to_pipetask : `dict` [`str`, `str`]
1086 Mapping of job names to job labels
1087 """
1088 dag = next(Path(dir_name).glob("*.dag"))
1090 # Later code depends upon insertion order
1091 counts = defaultdict(int)
1092 job_name_to_pipetask = {}
1093 try:
1094 with open(dag, "r") as fh:
1095 for line in fh:
1096 if line.startswith("JOB"):
1097 m = re.match(r"JOB ([^\s]+) jobs/([^/]+)/", line)
1098 if m:
1099 label = m.group(2)
1100 if label == "init":
1101 label = "pipetaskInit"
1102 job_name_to_pipetask[m.group(1)] = label
1103 counts[label] += 1
1104 else: # Check if Pegasus submission
1105 m = re.match(r"JOB ([^\s]+) ([^\s]+)", line)
1106 if m:
1107 label = pegasus_name_to_label(m.group(1))
1108 job_name_to_pipetask[m.group(1)] = label
1109 counts[label] += 1
1110 else:
1111 _LOG.warning("Parse DAG: unmatched job line: %s", line)
1112 elif line.startswith("FINAL"):
1113 m = re.match(r"FINAL ([^\s]+) jobs/([^/]+)/", line)
1114 if m:
1115 label = m.group(2)
1116 job_name_to_pipetask[m.group(1)] = label
1117 counts[label] += 1
1119 except (OSError, PermissionError, StopIteration):
1120 pass
1122 summary = ";".join([f"{name}:{counts[name]}" for name in counts])
1123 _LOG.debug("summary_from_dag: %s %s", summary, job_name_to_pipetask)
1124 return summary, job_name_to_pipetask
1127def pegasus_name_to_label(name):
1128 """Convert pegasus job name to a label for the report.
1130 Parameters
1131 ----------
1132 name : `str`
1133 Name of job.
1135 Returns
1136 -------
1137 label : `str`
1138 Label for job.
1139 """
1140 label = "UNK"
1141 if name.startswith("create_dir") or name.startswith("stage_in") or name.startswith("stage_out"):
1142 label = "pegasus"
1143 else:
1144 m = re.match(r"pipetask_(\d+_)?([^_]+)", name)
1145 if m:
1146 label = m.group(2)
1147 if label == "init":
1148 label = "pipetaskInit"
1150 return label
1153def read_dag_status(wms_path):
1154 """Read the node status file for DAG summary information
1156 Parameters
1157 ----------
1158 wms_path : `str`
1159 Path that includes node status file for a run.
1161 Returns
1162 -------
1163 dag_ad : `dict` [`str`, Any]
1164 DAG summary information.
1165 """
1166 dag_ad = {}
1168 # While this is probably more up to date than dag classad, only read from
1169 # file if need to.
1170 try:
1171 try:
1172 node_stat_file = next(Path(wms_path).glob("*.node_status"))
1173 _LOG.debug("Reading Node Status File %s", node_stat_file)
1174 with open(node_stat_file, "r") as infh:
1175 dag_ad = classad.parseNext(infh) # pylint: disable=E1101
1176 except StopIteration:
1177 pass
1179 if not dag_ad:
1180 # Pegasus check here
1181 try:
1182 metrics_file = next(Path(wms_path).glob("*.dag.metrics"))
1183 with open(metrics_file, "r") as infh:
1184 metrics = json.load(infh)
1185 dag_ad["NodesTotal"] = metrics.get("jobs", 0)
1186 dag_ad["NodesFailed"] = metrics.get("jobs_failed", 0)
1187 dag_ad["NodesDone"] = metrics.get("jobs_succeeded", 0)
1188 dag_ad["pegasus_version"] = metrics.get("planner_version", "")
1189 except StopIteration:
1190 try:
1191 metrics_file = next(Path(wms_path).glob("*.metrics"))
1192 with open(metrics_file, "r") as infh:
1193 metrics = json.load(infh)
1194 dag_ad["NodesTotal"] = metrics["wf_metrics"]["total_jobs"]
1195 dag_ad["pegasus_version"] = metrics.get("version", "")
1196 except StopIteration:
1197 pass
1198 except (OSError, PermissionError):
1199 pass
1201 _LOG.debug("read_dag_status: %s", dag_ad)
1202 return dict(dag_ad)
1205def read_node_status(wms_path):
1206 """Read entire node status file.
1208 Parameters
1209 ----------
1210 wms_path : `str`
1211 Path that includes node status file for a run.
1213 Returns
1214 -------
1215 jobs : `dict` [`str`, Any]
1216 DAG summary information.
1217 """
1218 # Get jobid info from other places to fill in gaps in info from node_status
1219 _, job_name_to_pipetask = summary_from_dag(wms_path)
1220 wms_workflow_id, loginfo = read_dag_log(wms_path)
1221 loginfo = read_dag_nodes_log(wms_path)
1222 _LOG.debug("loginfo = %s", loginfo)
1223 job_name_to_id = {}
1224 for jid, jinfo in loginfo.items():
1225 if "LogNotes" in jinfo:
1226 m = re.match(r"DAG Node: ([^\s]+)", jinfo["LogNotes"])
1227 if m:
1228 job_name_to_id[m.group(1)] = jid
1229 jinfo["DAGNodeName"] = m.group(1)
1231 try:
1232 node_status = next(Path(wms_path).glob("*.node_status"))
1233 except StopIteration:
1234 return loginfo
1236 jobs = {}
1237 fake_id = -1.0 # For nodes that do not yet have a job id, give fake one
1238 try:
1239 with open(node_status, "r") as fh:
1240 ads = classad.parseAds(fh)
1242 for jclassad in ads:
1243 if jclassad["Type"] == "DagStatus":
1244 # skip DAG summary
1245 pass
1246 elif "Node" not in jclassad:
1247 if jclassad["Type"] != "StatusEnd":
1248 _LOG.debug("Key 'Node' not in classad: %s", jclassad)
1249 break
1250 else:
1251 if jclassad["Node"] in job_name_to_pipetask:
1252 try:
1253 label = job_name_to_pipetask[jclassad["Node"]]
1254 except KeyError:
1255 _LOG.error("%s not in %s", jclassad["Node"], job_name_to_pipetask.keys())
1256 raise
1257 elif "_" in jclassad["Node"]:
1258 label = jclassad["Node"].split("_")[1]
1259 else:
1260 label = jclassad["Node"]
1262 # Make job info as if came from condor_q
1263 if jclassad["Node"] in job_name_to_id:
1264 job_id = job_name_to_id[jclassad["Node"]]
1265 else:
1266 job_id = str(fake_id)
1267 fake_id -= 1
1269 job = dict(jclassad)
1270 job["ClusterId"] = int(float(job_id))
1271 job["DAGManJobID"] = wms_workflow_id
1272 job["DAGNodeName"] = jclassad["Node"]
1273 job["bps_job_label"] = label
1275 jobs[str(job_id)] = job
1276 except (OSError, PermissionError):
1277 pass
1279 return jobs
1282def read_dag_log(wms_path):
1283 """Read job information from the DAGMan log file.
1285 Parameters
1286 ----------
1287 wms_path : `str`
1288 Path containing the DAGMan log file.
1290 Returns
1291 -------
1292 wms_workflow_id : `str`
1293 HTCondor job id (i.e., <ClusterId>.<ProcId>) of the DAGMan job.
1294 dag_info : `dict` [`str`, `Any`]
1295 HTCondor job information read from the log file mapped to HTCondor
1296 job id.
1298 Raises
1299 ------
1300 FileNotFoundError
1301 If cannot find DAGMan log in given wms_path.
1302 """
1303 wms_workflow_id = 0
1304 dag_info = {}
1306 path = Path(wms_path)
1307 if path.exists():
1308 try:
1309 filename = next(path.glob("*.dag.dagman.log"))
1310 except StopIteration as exc:
1311 raise FileNotFoundError(f"DAGMan log not found in {wms_path}") from exc
1312 _LOG.debug("dag node log filename: %s", filename)
1314 info = {}
1315 job_event_log = htcondor.JobEventLog(str(filename))
1316 for event in job_event_log.events(stop_after=0):
1317 id_ = f"{event['Cluster']}.{event['Proc']}"
1318 if id_ not in info:
1319 info[id_] = {}
1320 wms_workflow_id = id_ # taking last job id in case of restarts
1321 info[id_].update(event)
1322 info[id_][f"{event.type.name.lower()}_time"] = event["EventTime"]
1324 # only save latest DAG job
1325 dag_info = {wms_workflow_id: info[wms_workflow_id]}
1326 for job in dag_info.values():
1327 _tweak_log_info(filename, job)
1329 return wms_workflow_id, dag_info
1332def read_dag_nodes_log(wms_path):
1333 """Read job information from the DAGMan nodes log file.
1335 Parameters
1336 ----------
1337 wms_path : `str`
1338 Path containing the DAGMan nodes log file.
1340 Returns
1341 -------
1342 info : `dict` [`str`, Any]
1343 HTCondor job information read from the log file mapped to HTCondor
1344 job id.
1346 Raises
1347 ------
1348 FileNotFoundError
1349 If cannot find DAGMan node log in given wms_path.
1350 """
1351 try:
1352 filename = next(Path(wms_path).glob("*.dag.nodes.log"))
1353 except StopIteration as exc:
1354 raise FileNotFoundError(f"DAGMan node log not found in {wms_path}") from exc
1355 _LOG.debug("dag node log filename: %s", filename)
1357 info = {}
1358 job_event_log = htcondor.JobEventLog(str(filename))
1359 for event in job_event_log.events(stop_after=0):
1360 id_ = f"{event['Cluster']}.{event['Proc']}"
1361 if id_ not in info:
1362 info[id_] = {}
1363 info[id_].update(event)
1364 info[id_][f"{event.type.name.lower()}_time"] = event["EventTime"]
1366 # Add more condor_q-like info to info parsed from log file.
1367 for job in info.values():
1368 _tweak_log_info(filename, job)
1370 return info
1373def read_dag_info(wms_path):
1374 """Read custom DAGMan job information from the file.
1376 Parameters
1377 ----------
1378 wms_path : `str`
1379 Path containing the file with the DAGMan job info.
1381 Returns
1382 -------
1383 dag_info : `dict` [`str`, `dict` [`str`, Any]]
1384 HTCondor job information.
1386 Raises
1387 ------
1388 FileNotFoundError
1389 If cannot find DAGMan job info file in the given location.
1390 """
1391 try:
1392 filename = next(Path(wms_path).glob("*.info.json"))
1393 except StopIteration as exc:
1394 raise FileNotFoundError(f"File with DAGMan job information not found in {wms_path}") from exc
1395 _LOG.debug("DAGMan job information filename: %s", filename)
1396 try:
1397 with open(filename) as fh:
1398 dag_info = json.load(fh)
1399 except (IOError, PermissionError) as exc:
1400 _LOG.debug("Retrieving DAGMan job information failed: %s", exc)
1401 dag_info = {}
1402 return dag_info
1405def write_dag_info(filename, dag_info):
1406 """Writes custom job information about DAGMan job.
1408 Parameters
1409 ----------
1410 filename : `str`
1411 Name of the file where the information will be stored.
1412 dag_info : `dict` [`str` `dict` [`str` Any]]
1413 Information about the DAGMan job.
1414 """
1415 schedd_name = next(iter(dag_info))
1416 dag_id = next(iter(dag_info[schedd_name]))
1417 dag_ad = dag_info[schedd_name][dag_id]
1418 try:
1419 with open(filename, "w") as fh:
1420 info = {
1421 schedd_name: {
1422 dag_id: {"ClusterId": dag_ad["ClusterId"], "GlobalJobId": dag_ad["GlobalJobId"]}
1423 }
1424 }
1425 json.dump(info, fh)
1426 except (KeyError, IOError, PermissionError) as exc:
1427 _LOG.debug("Persisting DAGMan job information failed: %s", exc)
1430def _tweak_log_info(filename, job):
1431 """Massage the given job info has same structure as if came from condor_q.
1433 Parameters
1434 ----------
1435 filename : `pathlib.Path`
1436 Name of the DAGMan log.
1437 job : `dict` [ `str`, Any ]
1438 A mapping between HTCondor job id and job information read from
1439 the log.
1440 """
1441 _LOG.debug("_tweak_log_info: %s %s", filename, job)
1442 try:
1443 job["ClusterId"] = job["Cluster"]
1444 job["ProcId"] = job["Proc"]
1445 job["Iwd"] = str(filename.parent)
1446 job["Owner"] = filename.owner()
1447 if job["MyType"] == "ExecuteEvent":
1448 job["JobStatus"] = JobStatus.RUNNING
1449 elif job["MyType"] == "JobTerminatedEvent" or job["MyType"] == "PostScriptTerminatedEvent":
1450 job["JobStatus"] = JobStatus.COMPLETED
1451 try:
1452 if not job["TerminatedNormally"]:
1453 if "ReturnValue" in job:
1454 job["ExitCode"] = job["ReturnValue"]
1455 job["ExitBySignal"] = False
1456 elif "TerminatedBySignal" in job:
1457 job["ExitBySignal"] = True
1458 job["ExitSignal"] = job["TerminatedBySignal"]
1459 else:
1460 _LOG.warning("Could not determine exit status for completed job: %s", job)
1461 except KeyError as ex:
1462 _LOG.error("Could not determine exit status for job (missing %s): %s", str(ex), job)
1463 elif job["MyType"] == "SubmitEvent":
1464 job["JobStatus"] = JobStatus.IDLE
1465 elif job["MyType"] == "JobAbortedEvent":
1466 job["JobStatus"] = JobStatus.REMOVED
1467 else:
1468 _LOG.debug("Unknown log event type: %s", job["MyType"])
1469 except KeyError:
1470 _LOG.error("Missing key in job: %s", job)
1471 raise
1474def htc_check_dagman_output(wms_path):
1475 """Check the DAGMan output for error messages.
1477 Parameters
1478 ----------
1479 wms_path : `str`
1480 Directory containing the DAGman output file.
1482 Returns
1483 -------
1484 message : `str`
1485 Message containing error messages from the DAGMan output. Empty
1486 string if no messages.
1488 Raises
1489 ------
1490 FileNotFoundError
1491 If cannot find DAGMan standard output file in given wms_path.
1492 """
1493 try:
1494 filename = next(Path(wms_path).glob("*.dag.dagman.out"))
1495 except StopIteration as exc:
1496 raise FileNotFoundError(f"DAGMan standard output file not found in {wms_path}") from exc
1497 _LOG.debug("dag output filename: %s", filename)
1499 message = ""
1500 try:
1501 with open(filename, "r") as fh:
1502 last_submit_failed = ""
1503 for line in fh:
1504 m = re.match(r"(\d\d/\d\d/\d\d \d\d:\d\d:\d\d) Job submit try \d+/\d+ failed", line)
1505 if m:
1506 last_submit_failed = m.group(1)
1507 if last_submit_failed:
1508 message = f"Warn: Job submission issues (last: {last_submit_failed})"
1509 except (IOError, PermissionError):
1510 message = f"Warn: Could not read dagman output file from {wms_path}."
1511 return message