def setUp(self):
self.fb = Feedback()
# coding=utf-8
from feedback import Feedback
import urllib2
import urllib
import json
import sys
import os.path
import costants
if len(sys.argv) == 2:
query = urllib.quote(sys.argv[1])
feeds = Feedback()
for project in costants.PROJECTS:
ticket_url = "%s-%s" % (project, query)
feeds.add_item(title="%s-%s" % (project, query),
subtitle=ticket_url,
valid='YES',
arg=ticket_url,
icon='icon.png')
print feeds
CACHE_FILE = "ubuntu_ec2_instances.cache"
MAX_CACHE_AGE = 60 * 60 * 24 * 7 #1 week
def get_amis():
if not os.path.isfile(CACHE_FILE) or time.time() - os.stat(
CACHE_FILE).st_mtime > MAX_CACHE_AGE:
data = urlopen(
'http://cloud-images.ubuntu.com/locator/ec2/releasesTable').read()
open(CACHE_FILE, 'w').write(data)
return open(CACHE_FILE).read()
fb = Feedback()
query = sys.argv[1:]
data = literal_eval(get_amis())['aaData']
for item in data:
ami = re.search('ami-[a-f0-9]{8}', item[6]).group()
matches = 0
for q in query:
matches = matches + 1 if any(q in i for i in item) else matches
if matches == len(query):
fb.add_item(subtitle=ami,
title=' '.join(item[:5] + [item[7]]),
arg=ami)
print fb
def exitWithFeedback(**kwargs):
retcode = kwargs.pop('retcode', 0)
fb = Feedback()
fb.addItem(**kwargs)
fb.output()
sys.exit(retcode)
'buffer_sampling_size'),
number_training_iterations=config_transition_model.getint(
'number_training_iterations'),
train_end_episode=config_transition_model.getboolean('train_end_episode'))
# Create Agent
agent = agent_selector(agent_type, config_agent)
# Create Transition Model buffer
transition_model_buffer = Buffer(
min_size=config_transition_model.getint('buffer_min_size'),
max_size=config_transition_model.getint('buffer_max_size'))
# Create feedback object
env = gym.make(environment) # create environment
observation = env.reset()
if render:
env.render()
human_feedback = Feedback(env=env,
key_type=config_feedback['key_type'],
h_up=config_feedback['h_up'],
h_down=config_feedback['h_down'],
h_right=config_feedback['h_right'],
h_left=config_feedback['h_left'],
h_null=config_feedback['h_null'])
# Create saving directory if it does no exist
if save_results:
if not os.path.exists(eval_save_path):
os.makedirs(eval_save_path)
