def do_ok(self, event):
"""Actually performs the connection."""
if not self.host.GetValue():
return wx.MessageBox('Hostname cannot be blank.', 'Error')
if not self.port.GetValue().isdigit() or int(self.port.GetValue()) < 1 or int(self.port.GetValue()) > 65535:
return wx.MessageBox('Port must be a value between 1 and 65535.', 'Error')
if not self.timeout.GetValue().isdigit() or int(self.timeout.GetValue()) < 1:
return wx.MessageBox('Timeout must be a positive integer.', 'Error')
try:
functions.connect(self.host.GetValue(), int(self.port.GetValue()), int(self.timeout.GetValue()))
except Exception as e:
logger.exception(e)
finally:
self.Close(True)
def main():
db, coll = connect('datamad1019','chats')
with open('./chats.json') as f:
chats_json = json.load(f)
for chatmsg in chats_json:
coll.insert_one(chatmsg)
def main():
conn, cur = functions.connect()
status = True
functions.print_menu()
while status:
choice = int(input('Choice: '))
if choice == 1:
functions.create_table(conn, cur, 'teachers')
elif choice == 2:
functions.insert_data(conn, cur, 'teachers')
elif choice == 3:
keys = input('SELECT BY: ')
records = functions.select_from_db(conn, cur, 'teachers', keys)
functions.print_selected_data(records, keys)
elif choice == 4:
records = functions.select_from_db(conn, cur, 'teachers')
functions.print_selected_data(records)
elif choice == 5:
functions.disconnect(conn, cur)
break
functions.print_menu()
######################################################
(n_neurons_rec_spike,
n_neurons_rec_voltage) = functions.derive_parameters(model)
######################################################
# Create nodes
######################################################
print("Create nodes")
all_GIDs = functions.create_nodes(model, pyrngs)
###################################################
# Connect
###################################################
print("Connect")
t_connect_0 = time.time()
functions.connect(model, all_GIDs, n_neurons_rec_spike, n_neurons_rec_voltage,
verbose)
T_connect = time.time() - t_connect_0
print("T_connect = ", T_connect)
###################################################
# Get connection numbers
###################################################
print("Count synapse numbers")
t_count_0 = time.time()
data_sup_path = sim.data_dir
sub_path = "micro"
data_path = os.path.join(data_sup_path, sub_path)
file_name = "synapse_numbers.hdf5"
neuron_GIDs = all_GIDs[0]
import datetime
print("Content-Type: text/plain\n\n")
# Note this line. It's the important one
sys.stdout = codecs.getwriter("utf-8")(sys.stdout.detach())
try:
data = json.load(sys.stdin)
cookie = data["cookie"]
time_before = (datetime.datetime.now() - datetime.timedelta(minutes=10)).strftime('%Y-%m-%d %H:%M:%S')
connection = functions.connect()
sql_select = "SELECT * FROM `sessions` WHERE `sid` LIKE '" + cookie + "' AND logged_out = 0 AND update_time >= '" + time_before + "'"
cursor = connection.cursor()
cursor.execute(sql_select)
records = cursor.fetchall()
if records:
connect = True
else:
connect = False
json_res = {'ok': connect}
print(json.dumps(json_res, indent=4, default=str, ensure_ascii=False).encode('utf-8').decode())
sys.stdout = codecs.getwriter("utf-8")(sys.stdout.detach())
print("Content-Type: text/plain; charset=UTF-8\n\n")
try:
uid=functions.get_user_id()
sid = functions.get_cookie_value('LoggedIn')
if not functions.check_logged():
json_res = {"ok": False, "data": []}
print(json.dumps(json_res, indent=4, default=str, ensure_ascii=False).encode('utf-8').decode())
sys.exit()
list_friends_query = "SELECT friend1 FROM friends WHERE status = 2 AND friend2 = '"+str(uid)+"' UNION SELECT friend2 FROM friends WHERE status = 2 AND friend1 = '"+str(uid)+"' "
sql = "SELECT id, nickname, picture_number FROM users WHERE id IN ("+list_friends_query+") "
mydb = functions.connect()
mycursor = mydb.cursor()
mycursor.execute(sql)
all_details = mycursor.fetchall()
friend = []
list_of_columens = [i[0] for i in mycursor.description]
for row in all_details:
user = {key: val for key, val in zip(list_of_columens, row)}
friend.append(user)
json_res = {"ok": True,"id":uid, "data": friend}
print(json.dumps(json_res, indent=4, default=str, ensure_ascii=False).encode('utf-8').decode())
except Exception as e:
print(e)
######################################################
(n_neurons_rec_spike, n_neurons_rec_voltage) = functions.derive_parameters(model)
######################################################
# Create nodes
######################################################
print("Create nodes")
all_GIDs = functions.create_nodes(model, pyrngs)
###################################################
# Connect
###################################################
print("Connect")
t_connect_0 = time.time()
functions.connect(model, all_GIDs,
n_neurons_rec_spike, n_neurons_rec_voltage,
verbose)
T_connect = time.time() - t_connect_0
###################################################
# Simulate
###################################################
print("Simulate")
t_simulate_0 = time.time()
nest.Simulate(sim.t_sim)
T_simulate = time.time() - t_simulate_0
###################################################
# Save recorded data
###################################################
print("Save data")
pass
count_vectorizer = CountVectorizer()
sparse_matrix = count_vectorizer.fit_transform(dict_users.values())
doc_term_matrix = sparse_matrix.todense()
df = pd.DataFrame(doc_term_matrix,
columns=count_vectorizer.get_feature_names(),
index=dict_users.keys())
similarity_matrix = distance(df, df)
sim_df = pd.DataFrame(similarity_matrix,
columns=dict_users.keys(),
index=dict_users.keys())
recommendation = list(sim_df.sort_values(by=[user_id]).index[0:3])
return {"recommendation": recommendation}
database, collection = connect('datamad1019', 'chats')
run(host='localhost', port=8080, debug=True)
# @route('/plot/users')
# def server_static(filename="output.png"):
# dic = list(collection.find({"idChat": 0},{"Sentiment":1, "_id":0, "userName": 1}))
# polarity = [e["Sentiment"][0] for e in dic]
# subjectivity = [e["Sentiment"][1] for e in dic]
# labels = [e["userName"] for e in dic]
# df = pd.DataFrame(list(zip(subjectivity, polarity)), columns=["subjectivity", "polarity"])
# sns.set()
# cmap = sns.cubehelix_palette(rot=-.2, as_cmap=True)
# fig, ax = plt.subplots(figsize=(8,5))
# ax = sns.scatterplot(x="polarity", y="subjectivity", size="subjectivity", hue="polarity",
# palette=cmap, sizes=(80, 200),
# data=df, legend="brief")
import classes, paths, socket, functions
files = {}
host = ""
port = 0
dirOrFile = int(input("Do you wish to scan a (1)File or a (2)Directory: "))
if dirOrFile == 1:
inputFile = str(input("Please input the location of your file: "))
file = classes.mediaFile()
file.idmedia(inputFile)
functions.connect(host, port)
elif dirOrFile == 2:
directoryInput = str(input("Please input the directory you wish to scan: "))
print(dir(directoryInput))
