def endGame(bot, currentMessage, chat_id): # /quit behavior ends the game for everyone
gameRecords = Base("chatStorage/records.pdl")
gameRecords.open()
rec = gameRecords._groupChatID[str(chat_id)] # select all the records with chat_id (only 1)
if not rec:
botSendFunctions.sendText(bot, chat_id, "Invalid command format")
return
rec = rec[-1] # Strip the last record from the list
pointsBoard = "Here are the scores\n" # Send the final scores to the group
for name, points in zip(rec['memberUsernames'].split(), rec['memberPoints'].split()):
pointsBoard += str(name) + ": " + str(points) + " point(s)\n"
botSendFunctions.sendText(bot, chat_id, pointsBoard)
for player in rec['memberChatIDs'].split(): # Clean out the playerCards global
try:
del globalVars.playerCards[player]
except Exception: # If a player isn't there ignore it
pass
try:
del globalVars.resp[rec['gameID']] # Delete the game's responses key
del globalVars.currBlackCard[rec['gameID']] # Delete the game's current black card key
del globalVars.whiteCards[rec['gameID']]
except Exception:
pass
gameRecords.delete(rec) # Remove the database record
gameRecords.commit() # Save the changes
botSendFunctions.sendText(bot, chat_id, "Goodbye!")
def do_Delete (self, result, request, args):
def transfomType(x):
if isinstance(x, unicode): return str(x)
else: return x
####### Replace this section by your logic #######
db = Base('database_service6.pdl')
db.create('testId', 'testMessage', mode="open")
result = db(testId = int(args['testId']))
if len(result) == 0:
responseCode = 404 #ResponseCode.Ok
responseBody = json.dumps(result, sort_keys=True, indent=4, separators=(',', ': '))
else:
responseCode = 200 #ResponseCode.Ok
responseBody = json.dumps(result[0], sort_keys=True, indent=4, separators=(',', ': '))
db.delete(result[0])
db.commit()
####### Replace this section by your logic #######
request.setResponseCode(responseCode)
resp = utils.serviceResponse(responseCode, responseBody)
return resp
class YahoourlsearcherPipeline(object):
def open_spider(self, spider):
filename = "urls_log.txt"
self.log_target = codecs.open(filename, 'a+', encoding='utf-8')
self.log_target.truncate()
self.db = Base('URL_database.pdl')
self.db.create('url', 'date', mode="open")
self.log_target.write("***New url scraping session started at: "+ str(datetime.datetime.strftime(datetime.datetime.now(), ' %Y-%m-%d %H:%M:%S ')) + " ***" +"\n")
print("***New url scraping session started at: "+ str(datetime.datetime.strftime(datetime.datetime.now(), ' %Y-%m-%d %H:%M:%S ')) + " ***" +"\n")
self.log_target.write("*** Total url in the Database BEFORE new search: "+ str(len(self.db)) + " ***" + "\n")
dispatcher.connect(self.spider_closed, signals.spider_closed)
def process_item(self, item, spider):
self.db.insert(url=item['url'],
date=item['date']
)
self.log_target.write(item['url'] + " " + item['date'] + "\n")
self.db.commit()
return item
def spider_closed(self, spider):
url_structure = []
print ("End of database")
i = 1
for r in self.db:
#print (str(r["url"]) + " " + str(r["date"]) + " \n")
url_structure.append(url_date(r["url"],r["date"]))
i += 1
print (str(i) + "Url in the DB \n")
self.log_target.write("Session ends at: "+ str(datetime.datetime.strftime(datetime.datetime.now(), ' %Y-%m-%d %H:%M:%S ')) + "\n")
print ("Session ends at: "+ str(datetime.datetime.strftime(datetime.datetime.now(), ' %Y-%m-%d %H:%M:%S ')) + "\n")
self.log_target.write("*** Total url in the Database AFTER the search: "+ str(len(self.db)) + " ***" + "\n")
print ("Elementi presenti nel database: "+ str(len(self.db)) + " in struttura: " + str(len(url_structure)))
all_record = []
for r in self.db:
all_record.append(r)
self.db.delete(all_record)
print ("Elementi presenti nel database: "+ str(len(self.db)))
#set qui
url_structure = {x.url: x for x in url_structure}.values()
for any_url in url_structure:
self.db.insert(any_url.url, any_url.date)
print ("Elementi presenti nel database: "+ str(len(self.db)))
self.db.commit()
self.log_target.write("--- After SET operation: "+ str(len(self.db)) + " --- " + "\n" + "\n" + "\n" + "\n")
self.log_target.close()
def yolo(request):
db = Base('backendDB.pdl')
db.create('Type','Log', 'Run', 'Prefix','Rule','Threshold', 'TimeStamp', 'Status', mode="override")
# if db.exists():
# db.open()
records = [];
for r in db:
records.append(r)
db.delete(records)
db.commit()
# encoding.encode("SepsisCasesEventLog.xes", 8)
# prediction.regressior("SepsisCasesEventLog.xes", 8, 'complexIndex', "Kmeans", 'linear')
# prediction.classifier("SepsisCasesEventLog.xes", 8, 'simpleIndex', "None", 'DecisionTree', 'duration', 'default')
# prediction.classifier("SepsisCasesEventLog.xes", 8, 'simpleIndex', "Kmeans", 'DecisionTree', 'duration', 'default')
# prediction.classifier("SepsisCasesEventLog.xes", 8, 'boolean', "Kmeans", 'DecisionTree', 'duration', 'default')
# prediction.classifier("SepsisCasesEventLog.xes", 8, 'simpleIndex', "None", 'DecisionTree', 'remainingTime', 'default')
# prediction.classifier("Production.xes", 5, 'simpleIndex', "Kmeans", 'RandomForest')
# prediction.classifier("Production.xes", 5, 'simpleIndex', "Kmeans", 'DecisionTree')
# prediction.classifier("Production.xes", 13, 'simpleIndex', "None", 'KNN')
# prediction.classifier("Production.xes", 13, 'simpleIndex', "None", 'RandomForest')
# prediction.classifier("Production.xes", 3, 'complexIndex', "Kmeans", 'DecisionTree')
#regression.linear()
# df = pd.read_csv(filepath_or_buffer='core_encodedFiles/simpleIndex_Production.xes_16.csv', header=0)
# data_ = df[["Id", "remainingTime"]]
# estimator = DBSCAN(eps=0.3, min_samples=10, metric='haversine')
# estimator.fit(data_)
# print estimator
# labels = estimator.labels_
# n_clusters = len(set(labels)) - (1 if -1 in labels else 0)
# print n_clusters
# cluster_lists = {i: df.iloc[np.where(estimator.labels_ == i)[0]] for i in range(n_clusters)}
# print len(cluster_lists)
# writeHeader = True
# for cluster_list in cluster_lists:
# clusterd_data = cluster_lists[cluster_list]
# original_cluster_data = cluster_lists[cluster_list]
# lm = Lasso(fit_intercept=True, warm_start=True)
# y = clusterd_data['remainingTime']
# clusterd_data = clusterd_data.drop('remainingTime', 1)
# lm.fit(clusterd_data, y)
# original_cluster_data['prediction'] = lm.predict(clusterd_data)
# if writeHeader is True:
# original_cluster_data.to_csv('core_results/cluster.csv', sep=',', mode='a', header=True, index=False)
# writeHeader = False
# else:
# original_cluster_data.to_csv('core_results/cluster.csv', sep=',', mode='a', header=False, index=False)
#
#regression.linear("Production.xes", 9, 'xg', "sd")
# # regression.linear("Production.xes", 5, 'simple_index', "sd")
# regression.xgboost("Production.xes", 9, 'simpleIndex', "sd")
# # fileName, prefix, encoding, cluster, regression
# # django_rq.enqueue(tasks.regressionTask,"Production.xes", 5, 'simple_index', "sd", "xgboost")
return HttpResponse("YOLO")
for r in db('age') >= 20:
print(r)
print('#######')
print('shortguy')
for r in db('name').ilike('jeremy'):
print(r)
print('#######')
#db support list comprehension
really_really_really_short = next(r for r in db('size') < 1.0)
#update supports record(s) value(s) and updates the indicie
db.update(really_really_really_short, size=0.1)
fp() #even shorter
db.update(db, age='23')
fp()
#delete supports single and multiple records
db.delete(r for r in db('size') >= 0.2)
fp()
del db[next(r for r in db('size') < 0.2)['__id__']]
fp()
#useful utility functions
db.add_field('mood',
default='catcucumber') # adds field, with optional default value
db.drop_field('mood') # drops field
db.path # path of db, can be changed
db.name # name of db, stripped of path
db.fields # fields of db, excludes __id__ & __version__
len(db) # number of records in db
class DataBase():
def __init__(self, mode):
self.db = Base("./mlfv_hosts.pdl")
self.db.create('ip',
'port',
'libs',
'cpu',
'mem',
'net',
'runs',
mode=mode)
def insert_reg(self, r):
if (len(r) < 6):
print("Bad insertion")
return False
if self.db.exists():
print self.db.insert(ip=r['ip'],
port=r['port'],
libs=r['libs'],
cpu=r['cpu'],
mem=r['mem'],
net=r['net'],
runs=0)
self.db.commit()
return True
def remove_reg(self, r):
if self.db.exists():
for i in self.db:
if i['ip'] == r['ip'] and i['port'] == r['port']:
self.db.delete(i)
self.db.commit()
print str(i['ip']) + " removed\n"
return True
return False
def print_all(self):
if self.db.exists():
for r in self.db:
print r
def get_less_runs(self):
if self.db.exists():
less_runs = sys.maxsize
for r in self.db:
if (r['runs'] < less_runs):
new_host = r
less_runs = r['runs']
new_host['runs'] += 1
self.db.commit()
return new_host
def get_hosts_cpu_mem(self, cpu, mem):
print "cpu", cpu, mem
ret = []
if self.db.exists():
for r in (self.db("cpu") >= cpu) & (self.db("mem") >= mem):
ret.append([
r['ip'], r['port'], r['libs'], r['cpu'], r['mem'], r['net']
])
#ret = [r for r in self.db if r['cpu'] >= cpu and r['mem'] >= mem]
return ret
else:
print("Error: no client!")
return None
def get_registers_values(self):
if self.db.exists():
l = []
for r in self.db:
l.append([
r['ip'], r['port'], r['libs'], r['cpu'], r['mem'], r['net']
])
a = np.array(l, dtype=object)
return a
class YahoourlsearcherPipeline(object):
def open_spider(self, spider):
filename = "urls_log.txt"
self.log_target = codecs.open(filename, 'a+', encoding='utf-8')
self.log_target.truncate()
self.db = Base('URL_database.pdl')
self.db.create('url', 'date', mode="open")
self.log_target.write("***New url scraping session started at: " + str(
datetime.datetime.strftime(datetime.datetime.now(),
' %Y-%m-%d %H:%M:%S ')) + " ***" + "\n")
print("***New url scraping session started at: " + str(
datetime.datetime.strftime(datetime.datetime.now(),
' %Y-%m-%d %H:%M:%S ')) + " ***" + "\n")
self.log_target.write(
"*** Total url in the Database BEFORE new search: " +
str(len(self.db)) + " ***" + "\n")
dispatcher.connect(self.spider_closed, signals.spider_closed)
def process_item(self, item, spider):
self.db.insert(url=item['url'], date=item['date'])
self.log_target.write(item['url'] + " " + item['date'] + "\n")
self.db.commit()
return item
def spider_closed(self, spider):
url_structure = []
print("End of database")
i = 1
for r in self.db:
#print (str(r["url"]) + " " + str(r["date"]) + " \n")
url_structure.append(url_date(r["url"], r["date"]))
i += 1
print(str(i) + "Url in the DB \n")
self.log_target.write("Session ends at: " + str(
datetime.datetime.strftime(datetime.datetime.now(),
' %Y-%m-%d %H:%M:%S ')) + "\n")
print("Session ends at: " + str(
datetime.datetime.strftime(datetime.datetime.now(),
' %Y-%m-%d %H:%M:%S ')) + "\n")
self.log_target.write(
"*** Total url in the Database AFTER the search: " +
str(len(self.db)) + " ***" + "\n")
print("Elementi presenti nel database: " + str(len(self.db)) +
" in struttura: " + str(len(url_structure)))
all_record = []
for r in self.db:
all_record.append(r)
self.db.delete(all_record)
print("Elementi presenti nel database: " + str(len(self.db)))
#set qui
url_structure = {x.url: x for x in url_structure}.values()
for any_url in url_structure:
self.db.insert(any_url.url, any_url.date)
print("Elementi presenti nel database: " + str(len(self.db)))
self.db.commit()
self.log_target.write("--- After SET operation: " + str(len(self.db)) +
" --- " + "\n" + "\n" + "\n" + "\n")
self.log_target.close()
