def run(spool):
# notify("I'm alive!")
jobs = [Job(name, data, spool) for name, data in config['jobs'].items()]
due_jobs = [job for job in jobs if job.is_due()]
for job in due_jobs:
print(f'⏲ {job} is due!')
try:
with time_limit(job.time_limit):
job.execute()
dur = job.last_success - job.last_executed
notify(job.name,
f'ran successfully in {dur}',
icon='dialog-positive')
job.status = 'SUCCESS'
except subprocess.CalledProcessError as e:
print(f'Error executing {job}: {e}', file=sys.stderr)
notify(job.name,
f'encountered an error: {e}',
icon='dialog-error',
urgency='CRITICAL')
with open(f'{SCHED_DIR}/{job.name}_log.txt',
'w') as error_log_file:
error_log_file.write(job.output)
job.status = 'ERROR'
has_errors = True
except TimeoutException as e:
print(f'Timeout executing {job}: {e}', file=sys.stderr)
notify(job.name,
'timed out',
icon='dialog-error',
urgency='CRITICAL')
job.status = 'ERROR'
has_errors = True
job_to_last_executed = {job.name: job.to_spool() for job in jobs}
return {
'jobs': job_to_last_executed,
'did_something': len(due_jobs) > 0,
# We don't want to signal an error if it's not from the current execution.
# Therefore, only due_jobs are considered.
'has_errors': any(job.status == 'ERROR' for job in due_jobs),
}
if __name__ == '__main__':
nodes, connections, degrees, freedoms = read_graph_data('Graph500.txt')
data_storage = join('data', 'mls')
solutions = pd.DataFrame()
limit_in_seconds = 15
for j in range(25):
tic2 = perf_counter()
graph = Graph(nodes=nodes,
connections=connections,
freedoms=freedoms,
degrees=degrees)
previous_solution = {}
try:
with (time_limit(limit_in_seconds, 'MLS')):
while True:
if previous_solution:
graph.init_partition(previous_solution['solution'])
else:
graph.init_partition()
graph.setup_gains()
result = graph.fiduccia_mattheyses()
previous_solution = result
except TimeoutException:
pass
solution = previous_solution['solution']
solution['cutstate'] = previous_solution['cutstate']
solution = previous_solution['solution']
current_position = update_position(current_position, user_move, False)
# show the current view
view = create_view(current_position, False)
print_position(view)
# update the information of the computer
computer_view = create_view(current_position, True)
possible = engine.update_possible(possible, True, computer_view)
print(len(possible))
# come up with computer move
node = engine.Node(view=computer_view, possible=possible, turn=True)
try:
with time_limit(30):
engine.iterative_deepening(node, 10)
except TimeoutError as e:
print("Timed out!")
print(engine.lookup_table["principal_variation"])
computer_move = engine.lookup_table["principal_variation"][0]
# play computer move
current_position = update_position(current_position, computer_move, True)
# update the information of the computer
computer_view = create_view(current_position, True)
new_possible = set()
for position in possible:
new_position = update_position(position, computer_move, True)