def __init__(self):

self.job_directory = JOB_DIRECTORY

self.results_directory = RESULTS_DIRECTORY

self.sleep_time = SLEEP_TIME

def check_for_jobs(self):

print(self.get_time() + "Checking for jobs...")

job_count = len(next(os.walk(self.job_directory))[2])

if job_count > 0:

print(self.get_time() + "Found jobs...")

self.process_jobs()

@staticmethod

def get_time():

return str(datetime.datetime.now().time()) + " "

def process_jobs(self):

for file_name in os.listdir(self.job_directory):

print(self.get_time() + "Processing job file " + str(file_name) +

"...")

with open(self.job_directory + file_name, 'r') as file:

file_base_name = os.path.splitext(file_name)[0]

results = list()

indexes = list()

header = list()

result_len = 0

generation_len = 0

"""

Calculate results for each line

"""

for line in file:

args = [int(s) for s in line.split()]

r = CA.main(args[0], args[1], args[2], args[3], args[4])

r = [val for sublist in r for val in sublist]

results.append(r)

indexes.append(args[2])

if args[3] > result_len:

result_len = args[3]

if args[4] > generation_len:

# add one for zero based indexing

generation_len = args[4]+1

"""

Construct header

"""

for i in range(0, generation_len):

for j in range(0, result_len):

header.append("x" + str(j) + "t" + str(i))

"""

Construct data frame

"""

df = pd.DataFrame(results, columns=header, index=indexes)

"""

Write data frame to CSV

"""

self.write_job_csv(file_base_name, df)

def sleep(self):

time.sleep(self.sleep_time)

def start(self):

print(self.get_time() + "Starting CA Processor...")

while True:

self.check_for_jobs()

self.sleep()

def stop(self):

print(self.get_time() + "Stopping CA Processor...")

def write_job_csv(self, file_base_name, df_results):

print(self.get_time() + "Writing results to csv file...\n")

file_path = self.results_directory + file_base_name + ".csv"