def main():
with requests.Session() as s:
response = s.post(settings["base_url"] + settings["default_ext"],
qt_user)
error_check(response)
for count, link in enumerate(settings["links"]):
file_name = settings["files"][count]
response = s.get(settings["base_url"] + link)
error_check(response)
data = DataHandler.DataHandler().convert(response, link)
if DataHandler.DataHandler().compare(data, file_name):
DataHandler.DataHandler().updater(data, file_name)
DataHandler.DataHandler().data_sender(data, settings["email"],
settings["key"],
file_name)
def __init__(self):
self.dh = DataHandler.DataHandler()
self.log = logging.getLogger()
self.log.setLevel(CONST.LOG_LEVEL)
self.base_item_list = self._get_base_item_list()
self._temp_graph = nx.MultiDiGraph()
self._search_terms = []
def main():
env = gym.make(envName)
net = Definitions.loadModel(envName,
iteration=iteration,
loadBest=(iteration is None))
policy = PolicyLearner.PolicyLearner(net)
policy.setConfidenceMul(confidenceMul)
dataHandler = DataHandler.DataHandler(policy, env)
dataHandler.render(episodes=int(1e9))
def get(self):
# ToDo: Return information on how to use the submission of training job for kubenete cluster
parser.add_argument('clusterId')
args = parser.parse_args()
clusterId = args["clusterId"]
datahandler = DataHandler.DataHandler()
datahandler.DeleteCluster(clusterId)
datahandler.Close()
return "Done", 200
def get(self):
# ToDo: Return information on how to use the submission of training job for kubenete cluster
parser.add_argument('key')
parser.add_argument('clusterId')
args = parser.parse_args()
clusterId = args["clusterId"]
key = args["key"]
datahandler = DataHandler.DataHandler()
value = datahandler.GetClusterInfo(clusterId,key)
datahandler.Close()
print value
return value, 200
def get(self):
# ToDo: Return information on how to use the submission of training job for kubenete cluster
parser.add_argument('role')
parser.add_argument('clusterId')
args = parser.parse_args()
clusterId = args["clusterId"]
role = args["role"]
datahandler = DataHandler.DataHandler()
nodes = datahandler.GetNodes(role,clusterId)
datahandler.Close()
ret = {}
ret["nodes"] = nodes
return json.dumps(ret), 200
def __init__(self):
self.raiz = tk.Tk()
self.raiz.rowconfigure(0, weight=1)
self.raiz.columnconfigure(0, weight=1)
self.dataHandler = dh.DataHandler()
self.w = self.raiz.winfo_screenwidth()
self.h = self.raiz.winfo_screenheight()
# Menu da barra principal
self.menubar = Menubar(self.raiz)
self.raiz.config(menu=self.menubar)
# Frames
self.frame_materias = tk.Frame(self.raiz)
#self.frame_filter = tk.Frame(self.raiz)
#self.filter = Filtro(self.frame_filter)
self.frame_materias.rowconfigure(0, weight=1)
# Lista de materias
self.list_box = Lista_materias(self.frame_materias,
materias=self.dataHandler.read_list())
self.frame_materias.grid(sticky=tk.E + tk.N + tk.S)
