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|
import configparser as ConfigParser
import argparse
import shelve
import sys
import os
import subprocess
import threading
import shutil
import time
import re
from helpers import *
shelve_name = "dump.shelve" # contains all the measurement objects
history_file = "history.log"
clock_interval = 20 # in seconds
delete_logs_after_finish = False # if it is not desired to keep the log and submit script files
use_caf = False
def save(name, object):
# in case of multiple threads running this stops potentially problematic file access
global lock
lock.acquire()
try:
sh = shelve.open(shelve_name)
sh[name] = object
sh.close()
finally:
lock.release()
class Dataset:
def __init__(self, config, name):
dsDict = dict(config.items("dataset:{}".format(name)))
self.name = name
self.baseDirectory = dsDict["baseDirectory"].replace("$CMSSW_BASE", os.environ['CMSSW_BASE'])
self.fileList = []
names = dsDict["fileNames"].split(" ")
for name in names:
parsedNames = replaceAllRanges(name)
for fileName in parsedNames:
self.fileList.append(self.baseDirectory+"/"+fileName)
self.nFiles = len(self.fileList)
self.maxEvents = -1
if "maxEvents" in dsDict:
self.maxEvents = int(dsDict["maxEvents"])
self.sampleType ="data1"
if "isMC" in dsDict and dsDict["isMC"] == "True":
self.sampleType = "MC"
self.isCosmics = False
if "isCosmics" in dsDict:
self.isCosmics = (dsDict["isCosmics"] == "True")
self.conditions, self.validConditions = loadConditions(dsDict)
# check if any of the sources used for conditions is invalid
if not self.validConditions:
print("Invalid conditions defined for dataset {}".format(self.name))
# check if all files specified exist
self.existingFiles, missingFiles = allFilesExist(self)
if not self.existingFiles:
for fileName in missingFiles:
print("Invalid file name {} defined for dataset {}".format(fileName, self.name))
class Alignment:
def __init__(self, config, name):
alDict = dict(config.items("alignment:{}".format(name)))
self.name = name
self.globalTag = "None"
if "globalTag" in alDict:
self.globalTag = alDict["globalTag"]
self.baselineDir = "Design"
if "baselineDir" in alDict:
self.baselineDir= alDict["baselineDir"]
self.isDesign = False
if "isDesign" in alDict:
self.isDesign= (alDict["isDesign"] == "True")
# If self.hasAlignmentCondition is true, no other Alignment-Object is loaded in apeEstimator_cfg.py using the
self.conditions, self.validConditions = loadConditions(alDict)
# check if any of the sources used for conditions is invalid
if not self.validConditions:
print("Invalid conditions defined for alignment {}".format(self.name))
class ApeMeasurement:
name = "workingArea"
curIteration = 0
firstIteration = 0
maxIterations = 15
maxEvents = None
dataset = None
alignment = None
runningJobs = None
failedJobs = None
startTime = ""
finishTime = ""
def __init__(self, name, config, settings):
self.name = name
self.status_ = STATE_ITERATION_START
self.runningJobs = []
self.failedJobs = []
self.startTime = subprocess.check_output(["date"]).decode().strip()
# load conditions from dictionary, overwrite defaults if defined
for key, value in settings.items():
if not key.startswith("condition "):
setattr(self, key, value)
# Replace names with actual Dataset and Alignment objects
self.dataset = Dataset(config, settings["dataset"])
self.alignment = Alignment(config, settings["alignment"])
# If not defined here, replace by setting from Dataset
if not "maxEvents" in settings:
self.maxEvents = self.dataset.maxEvents
self.firstIteration=int(self.firstIteration)
self.maxIterations=int(self.maxIterations)
self.curIteration = self.firstIteration
self.maxEvents = int(self.maxEvents)
if self.alignment.isDesign:
self.maxIterations = 0
self.conditions, self.validConditions = loadConditions(settings)
# see if sanity checks passed
if not self.alignment.validConditions or not self.dataset.validConditions or not self.dataset.existingFiles or not self.validConditions:
self.setStatus(STATE_INVALID_CONDITIONS, True)
return
if unitTest:
return
if self.alignment.isDesign and self.dataset.sampleType != "MC":
# For now, this won't immediately shut down the program
print("APE Measurement {} is scheduled to to an APE baseline measurement with a dataset that is not marked as isMC=True. Is this intended?".format(self.name))
ensurePathExists('{}/hists/{}'.format(base, self.name))
if not self.alignment.isDesign:
ensurePathExists('{}/hists/{}/apeObjects'.format(base, self.name))
def status(self):
return status_map[self.status_]
def printStatus(self):
print("APE Measurement {} in iteration {} is now in status {}".format(self.name, self.curIteration, self.status()))
def setStatus(self, status, terminal=False):
if self.status_ != status:
self.status_ = status
self.printStatus()
if terminal:
self.finishTime = subprocess.check_output(["date"]).decode().strip()
# submit jobs for track refit and hit categorization
def submitJobs(self):
toSubmit = []
allConditions = self.alignment.conditions+self.dataset.conditions+self.conditions
allConditions = list({v['record']:v for v in allConditions}.values()) # Removes double definitions of Records
ensurePathExists("{}/test/autoSubmitter/workingArea".format(base))
# If conditions are made, create file to load them from
rawFileName = "None"
conditionsFileName = "None"
if len(allConditions) > 0:
conditionsFileName = "{base}/python/conditions/conditions_{name}_iter{iterNo}_cff.py".format(base=base,name=self.name, iterNo=self.curIteration)
rawFileName = "conditions_{name}_iter{iterNo}_cff".format(name=self.name, iterNo=self.curIteration)
with open(conditionsFileName, "w") as fi:
from autoSubmitterTemplates import conditionsFileHeader
fi.write(conditionsFileHeader)
from autoSubmitterTemplates import conditionsTemplate
for condition in allConditions:
fi.write(conditionsTemplate.format(record=condition["record"], connect=condition["connect"], tag=condition["tag"]))
alignmentNameToUse = "fromConditions"
lastIter = (self.curIteration==self.maxIterations) and not self.alignment.isDesign
inputCommands = "sample={sample} fileNumber={fileNo} iterNumber={iterNo} lastIter={lastIter} alignRcd={alignRcd} maxEvents={maxEvents} globalTag={globalTag} measurementName={name} conditions={conditions} cosmics={cosmics}".format(sample=self.dataset.sampleType,fileNo="$1",iterNo=self.curIteration,lastIter=lastIter,alignRcd=alignmentNameToUse, maxEvents=self.maxEvents, globalTag=self.alignment.globalTag, name=self.name, conditions=rawFileName,cosmics=self.dataset.isCosmics)
from autoSubmitterTemplates import condorJobTemplate
jobFileContent = condorJobTemplate.format(base=base, inputFile="$2", inputCommands=inputCommands)
jobFileName = "{}/test/autoSubmitter/workingArea/batchscript_{}_iter{}.tcsh".format(base, self.name,self.curIteration)
with open(jobFileName, "w") as jobFile:
jobFile.write(jobFileContent)
# create a batch job file for each input file
arguments = ""
from autoSubmitterTemplates import condorArgumentTemplate
for i in range(self.dataset.nFiles):
inputFile = self.dataset.fileList[i]
fileNumber = i+1
arguments += condorArgumentTemplate.format(fileNumber=fileNumber, inputFile=inputFile)
# build condor submit script
date = subprocess.check_output(["date", "+%m_%d_%H_%M_%S"]).decode().strip()
sub = "{}/test/autoSubmitter/workingArea/job_{}_iter{}".format(base, self.name, self.curIteration)
errorFileTemp = sub+"_error_{}.txt"
errorFile = errorFileTemp.format("$(ProcId)")
outputFile = sub+"_output_$(ProcId).txt"
logFileTemp= sub+"_condor_{}.log"
logFile = logFileTemp.format("$(ProcId)")
jobFile = sub+".tcsh"
jobName = "{}_{}".format(self.name, self.curIteration)
for i in range(self.dataset.nFiles):
# make file empty if it existed before
with open(logFileTemp.format(i), "w") as fi:
pass
# create submit file
from autoSubmitterTemplates import condorSubTemplate
from autoSubmitterTemplates import condorSubTemplateCAF
if use_caf:
submitFileContent = condorSubTemplateCAF.format(jobFile=jobFileName, outputFile=outputFile, errorFile=errorFile, logFile=logFile, arguments=arguments, jobName=jobName)
else:
submitFileContent = condorSubTemplate.format(jobFile=jobFileName, outputFile=outputFile, errorFile=errorFile, logFile=logFile, arguments=arguments, jobName=jobName)
submitFileName = "{}/test/autoSubmitter/workingArea/submit_{}_jobs_iter{}.sub".format(base, self.name, self.curIteration)
with open(submitFileName, "w") as submitFile:
submitFile.write(submitFileContent)
# submit batch
from autoSubmitterTemplates import submitCondorTemplate
subOut = subprocess.check_output(submitCondorTemplate.format(subFile=submitFileName), shell=True).decode().strip()
if len(subOut) == 0:
print("Running on environment that does not know bsub command or ssh session is timed out (ongoing for longer than 24h?), exiting")
sys.exit()
cluster = subOut.split(" ")[-1][:-1]
for i in range(self.dataset.nFiles):
# list contains condor log files from which to read when job is terminated to detect errors
self.runningJobs.append((logFileTemp.format(i), errorFileTemp.format(i), "{}.{}".format(cluster, i)))
self.setStatus(STATE_BJOBS_WAITING)
def checkJobs(self):
stillRunningJobs = []
# check all still running jobs
for logName, errName, jobId in self.runningJobs:
# read condor logs instead of doing condor_q or similar, as it is much faster
if not os.path.isfile(logName):
print("{} does not exist even though it should, marking job as failed".format(logName))
self.failedJobs.append( (logName, errName) )
break
with open(logName, "r") as logFile:
log = logFile.read()
if not "submitted" in log:
print("{} was apparently not submitted, did you empty the log file or is condor not working?".format(jobId))
self.failedJobs.append( (logName, errName) )
if "Job was aborted" in log:
print("Job {} of measurement {} in iteration {} was aborted".format(jobId, self.name, self.curIteration))
self.failedJobs.append( (logName, errName) )
elif "Job terminated" in log:
if "Normal termination (return value 0)" in log:
foundErr = False
with open(errName, "r") as err:
for line in err:
if "Fatal Exception" in line.strip():
foundErr = True
break
if not foundErr:
print("Job {} of measurement {} in iteration {} finished successfully".format(jobId, self.name, self.curIteration))
else:
# Fatal error in stderr
print("Job {} of measurement {} in iteration {} has a fatal error, check stderr".format(jobId, self.name, self.curIteration))
self.failedJobs.append( (logName, errName) )
else:
# nonzero return value
print("Job {} of measurement {} in iteration {} failed, check stderr".format(jobId, self.name, self.curIteration))
self.failedJobs.append( (logName, errName) )
else:
stillRunningJobs.append( (logName, errName, jobId) )
self.runningJobs = stillRunningJobs
# at least one job failed
if len(self.failedJobs) > 0:
self.setStatus(STATE_BJOBS_FAILED, True)
elif len(self.runningJobs) == 0:
self.setStatus(STATE_BJOBS_DONE)
print("All condor jobs of APE measurement {} in iteration {} are done".format(self.name, self.curIteration))
# remove files
if delete_logs_after_finish:
submitFile = "{}/test/autoSubmitter/workingArea/submit_{}_jobs_iter{}.sub".format(base, self.name, self.curIteration)
jobFile = "{}/test/autoSubmitter/workingArea/batchscript_{}_iter{}.tcsh".format(base, self.name,self.curIteration)
os.remove(submitFile)
os.remove(jobFile)
for i in range(self.dataset.nFiles):
sub = "{}/test/autoSubmitter/workingArea/job_{}_iter{}".format(base, self.name, self.curIteration)
errorFile = sub+"_error_{}.txt".format(i)
outputFile = sub+"_output_{}.txt".format(i)
logFile = sub+"_condor_{}.log".format(i)
os.remove(errorFile)
os.remove(outputFile)
os.remove(logFile)
# merges files from jobs
def mergeFiles(self):
self.setStatus(STATE_MERGE_WAITING)
if self.alignment.isDesign:
folderName = '{}/hists/{}/baseline'.format(base, self.name)
else:
folderName = '{}/hists/{}/iter{}'.format(base, self.name, self.curIteration)
# (re)move results from previous measurements before creating folder
if os.path.isdir(folderName):
if os.path.isdir(folderName+"_old"):
shutil.rmtree("{}_old".format(folderName))
os.rename(folderName, folderName+"_old")
os.makedirs(folderName)
# This is so that the structure of the tree can be retrieved by ApeEstimatorSummary.cc and the tree does not have to be rebuilt
if self.curIteration > 0 and not self.alignment.isDesign: # don't have to check for isDesign here because it always ends after iteration 0...
shutil.copyfile('{}/hists/{}/iter{}/allData_iterationApe.root'.format(base, self.name, self.curIteration-1),folderName+"/allData_iterationApe.root")
fileNames = ['{}/hists/{}/{}{}.root'.format(base, self.name, self.dataset.sampleType, str(i)) for i in range(1, self.dataset.nFiles+1)]
fileString = " ".join(fileNames)
from autoSubmitterTemplates import mergeTemplate
merge_result = subprocess.call(mergeTemplate.format(path=folderName, inputFiles=fileString), shell=True) # returns exit code (0 if no error occured)
for name in fileNames:
os.remove(name)
if rootFileValid("{}/allData.root".format(folderName)) and merge_result == 0:
self.setStatus(STATE_MERGE_DONE)
else:
self.setStatus(STATE_MERGE_FAILED, True)
# calculates APE
def calculateApe(self):
self.status_ = STATE_SUMMARY_WAITING
from autoSubmitterTemplates import summaryTemplate
if self.alignment.isDesign:
#use measurement name as baseline folder name in this case
inputCommands = "iterNumber={} setBaseline={} measurementName={} baselineName={}".format(self.curIteration,self.alignment.isDesign,self.name, self.name)
else:
inputCommands = "iterNumber={} setBaseline={} measurementName={} baselineName={}".format(self.curIteration,self.alignment.isDesign,self.name, self.alignment.baselineDir)
summary_result = subprocess.call(summaryTemplate.format(inputCommands=inputCommands), shell=True) # returns exit code (0 if no error occured)
if summary_result == 0:
self.setStatus(STATE_SUMMARY_DONE)
else:
self.setStatus(STATE_SUMMARY_FAILED, True)
# saves APE to .db file so it can be read out next iteration
def writeApeToDb(self):
self.setStatus(STATE_LOCAL_WAITING)
from autoSubmitterTemplates import localSettingTemplate
inputCommands = "iterNumber={} setBaseline={} measurementName={}".format(self.curIteration,self.alignment.isDesign,self.name)
local_setting_result = subprocess.call(localSettingTemplate.format(inputCommands=inputCommands), shell=True) # returns exit code (0 if no error occured)
if local_setting_result == 0:
self.setStatus(STATE_LOCAL_DONE)
else:
self.setStatus(STATE_LOCAL_FAILED, True)
def finishIteration(self):
print("APE Measurement {} just finished iteration {}".format(self.name, self.curIteration))
if self.curIteration < self.maxIterations:
self.curIteration += 1
self.setStatus(STATE_ITERATION_START)
else:
self.setStatus(STATE_FINISHED, True)
print("APE Measurement {}, which was started at {} was finished after {} iterations, at {}".format(self.name, self.startTime, self.curIteration, self.finishTime))
def kill(self):
from autoSubmitterTemplates import killJobTemplate
for log, err, jobId in self.runningJobs:
subprocess.call(killJobTemplate.format(jobId=jobId), shell=True)
self.runningJobs = []
self.setStatus(STATE_NONE)
def purge(self):
self.kill()
folderName = '{}/hists/{}'.format(base, self.name)
shutil.rmtree(folderName)
# remove log-files as well?
def runIteration(self):
global threadcounter
global measurements
threadcounter.acquire()
try:
if self.status_ == STATE_ITERATION_START:
# start bjobs
print("APE Measurement {} just started iteration {}".format(self.name, self.curIteration))
try:
self.submitJobs()
save("measurements", measurements)
except Exception as e:
# this is needed in case the scheduler goes down
print("Error submitting jobs for APE measurement {}".format(self.name))
print(e)
return
if self.status_ == STATE_BJOBS_WAITING:
# check if bjobs are finished
self.checkJobs()
save("measurements", measurements)
if self.status_ == STATE_BJOBS_DONE:
# merge files
self.mergeFiles()
save("measurements", measurements)
if self.status_ == STATE_MERGE_DONE:
# start summary
self.calculateApe()
save("measurements", measurements)
if self.status_ == STATE_SUMMARY_DONE:
# start local setting (only if not a baseline measurement)
if self.alignment.isDesign:
self.setStatus(STATE_LOCAL_DONE)
else:
self.writeApeToDb()
save("measurements", measurements)
if self.status_ == STATE_LOCAL_DONE:
self.finishIteration()
save("measurements", measurements)
# go to next iteration or finish measurement
if self.status_ == STATE_BJOBS_FAILED or \
self.status_ == STATE_MERGE_FAILED or \
self.status_ == STATE_SUMMARY_FAILED or \
self.status_ == STATE_LOCAL_FAILED or \
self.status_ == STATE_INVALID_CONDITIONS or \
self.status_ == STATE_FINISHED:
with open(history_file, "a") as fi:
fi.write("APE measurement {name} which was started at {start} finished at {end} with state {state} in iteration {iteration}\n".format(name=self.name, start=self.startTime, end=self.finishTime, state=self.status(), iteration=self.curIteration))
if self.status_ == STATE_FINISHED:
global finished_measurements
finished_measurements[self.name] = self
save("finished", finished_measurements)
else:
global failed_measurements
failed_measurements[self.name] = self
self.setStatus(STATE_NONE)
save("failed", failed_measurements)
save("measurements", measurements)
if self.status_ == STATE_ITERATION_START: # this ensures that jobs do not go into idle if many measurements are done simultaneously
# start bjobs
print("APE Measurement {} just started iteration {}".format(self.name, self.curIteration))
self.submitJobs()
save("measurements", measurements)
finally:
threadcounter.release()
def main():
parser = argparse.ArgumentParser(description="Automatically run APE measurements")
parser.add_argument("-c", "--config", action="append", dest="configs", default=[],
help="Config file that has list of measurements")
parser.add_argument("-k", "--kill", action="append", dest="kill", default=[],
help="List of measurement names to kill (=remove from list and kill all bjobs)")
parser.add_argument("-p", "--purge", action="append", dest="purge", default=[],
help="List of measurement names to purge (=kill and remove folder)")
parser.add_argument("-r", "--resume", action="append", dest="resume", default=[],
help="Resume interrupted APE measurements which are stored in shelves (specify shelves)")
parser.add_argument("-d", "--dump", action="store", dest="dump", default=None,
help='Specify in which .shelve file to store the measurements')
parser.add_argument("-n", "--ncores", action="store", dest="ncores", default=1, type=int,
help='Number of threads running in parallel')
parser.add_argument("-C", "--caf",action="store_true", dest="caf", default=False,
help="Use CAF queue for condor jobs")
parser.add_argument("-u", "--unitTest", action="store_true", dest="unitTest", default=False,
help='If this is used, as soon as a measurement fails, the program will exit and as exit code the status of the measurement, i.e., where it failed')
args = parser.parse_args()
global base
global clock_interval
global shelve_name
global threadcounter
global lock
global use_caf
global unitTest
use_caf = args.caf
unitTest = args.unitTest
threadcounter = threading.BoundedSemaphore(args.ncores)
lock = threading.Lock()
if args.dump != None: # choose different file than default
shelve_name = args.dump
elif args.resume != []:
shelve_name = args.resume[0]
try:
base = os.environ['CMSSW_BASE']+"/src/Alignment/APEEstimation"
except KeyError:
print("No CMSSW environment was set, exiting")
sys.exit(1)
killTargets = []
purgeTargets = []
for toConvert in args.kill:
killTargets += replaceAllRanges(toConvert)
for toConvert in args.purge:
purgeTargets += replaceAllRanges(toConvert)
global measurements
measurements = []
global finished_measurements
finished_measurements = {}
global failed_measurements
failed_measurements = {}
if args.resume != []:
for resumeFile in args.resume:
try:
sh = shelve.open(resumeFile)
resumed = sh["measurements"]
resumed_failed = sh["failed"]
resumed_finished = sh["finished"]
sh.close()
for res in resumed:
measurements.append(res)
print("Measurement {} in state {} in iteration {} was resumed".format(res.name, res.status(), res.curIteration))
# Killing and purging is done here, because it doesn't make
# sense to kill or purge a measurement that was just started
for to_kill in args.kill:
if res.name == to_kill:
res.kill()
for to_purge in args.purge:
if res.name == to_purge:
res.purge()
failed_measurements.update(resumed_failed)
finished_measurements.update(resumed_finished)
except IOError:
print("Could not resume because {} could not be opened, exiting".format(shelve_name))
sys.exit(2)
# read out from config file
if args.configs != []:
config = ConfigParser.RawConfigParser()
config.optionxform = str
config.read(args.configs)
# read measurement names
meas = [str(x.split("ape:")[1]) for x in list(config.keys()) if x.startswith("ape:")]
for name in meas:
if name in [x.name for x in measurements]:
print("Error: APE Measurement with name {} already exists, skipping".format(name))
continue
settings = dict(config.items("ape:{}".format(name)))
measurement = ApeMeasurement(name, config, settings)
if measurement.status_ >= STATE_ITERATION_START:
measurements.append(measurement)
print("APE Measurement {} was started".format(measurement.name))
if unitTest:
# status is 0 if successful, 101 if wrongly configured
sys.exit(measurement.status_)
initializeModuleLoading()
enableCAF(use_caf)
while True:
# remove finished and failed measurements
measurements = [measurement for measurement in measurements if not (measurement.status_==STATE_NONE or measurement.status_ == STATE_FINISHED)]
save("measurements", measurements)
save("failed", failed_measurements)
save("finished", finished_measurements)
list_threads = []
for measurement in measurements:
t = threading.Thread(target=measurement.runIteration)
list_threads.append(t)
t.start()
# wait for iterations to finish
for t in list_threads:
t.join()
if len(measurements) == 0:
print("No APE measurements are active, exiting")
sys.exit(0)
try: # so that interrupting does not give an error message and just ends the program
time_remaining = clock_interval
while time_remaining > 0:
print("Sleeping for {} seconds, you can safely [CTRL+C] now".format(time_remaining))
time.sleep(1)
time_remaining -= 1
sys.stdout.write("\033[F")
sys.stdout.write("\033[K")
print("")
sys.stdout.write("\033[F")
sys.stdout.write("\033[K")
except KeyboardInterrupt:
sys.exit(0)
if __name__ == "__main__":
main()
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