default=1, help='Files per job') farmout_group.add_argument('--clean-crab-dupes', action='store_true', default=False, dest='cleancrab', help='Clean crab dupes') args = parser.parse_args() sys.stdout.write('# Condor submission script\n') sys.stdout.write('# Generated with submit_job.py at %s\n' % datetime.datetime.now()) sys.stdout.write('# The command was: %s\n' % ' '.join(sys.argv)) sys.stdout.write('export TERMCAP=screen\n') for sample, sample_info in reversed( sorted(datadefs.iteritems(), key=lambda (x,y): x)): passes_filter = True # Filter by analysis if args.analysis: passes_ana = sample_info['analysis'] == args.analysis passes_filter = passes_filter and passes_ana # Filter by sample wildcards if args.samples: passes_wildcard = False for pattern in args.samples: if fnmatch.fnmatchcase(sample, pattern): passes_wildcard = True passes_filter = passes_wildcard and passes_filter if not passes_filter: continue
cfg = 'patTuple_cfg.py' jobId = args.jobid print " # Job ID: %s Version: %s" % (jobId, fsa_version()) print 'export TERMCAP=screen' def any_matches(regexes, string): for regex in regexes: if fnmatch.fnmatchcase(string, regex): return True return False to_be_used = [] for key, info in datadefs.iteritems(): if args.samples: if any_matches(args.samples, key): to_be_used.append(key) if 'datasetpath' in info and args.dbsnames: dbs = info['datasetpath'] if any_matches(args.dbsnames, dbs): to_be_used.append(key) production_info = {} for sample in sorted(to_be_used): sample_info = datadefs[sample] if args.ignoreRunRange and 'firstRun' in sample_info: del sample_info['firstRun']
args = parser.parse_args() cfg = 'patTuple_cfg.py' jobId = args.jobid print " # Job ID: %s Version: %s" % (jobId, fsa_version()) print 'export TERMCAP=screen' def any_matches(regexes, string): for regex in regexes: if fnmatch.fnmatchcase(string, regex): return True return False to_be_used = [] for key, info in datadefs.iteritems(): if args.samples: if any_matches(args.samples, key): to_be_used.append(key) if 'datasetpath' in info and args.dbsnames: dbs = info['datasetpath'] if any_matches(args.dbsnames, dbs): to_be_used.append(key) production_info = {} for sample in sorted(to_be_used): sample_info = datadefs[sample] if args.ignoreRunRange and 'firstRun' in sample_info: del sample_info['firstRun']