def rem(id, masterpass):
cn = connector()
cur = cn.cursor()
query = "SELECT acc_id, website_name FROM tbl_cryptostore WHERE id = \'" + str(
id) + "\'"
cur.execute(query)
res = cur.fetchall()
cn.close()
if (len(res) == 0):
print("No passwords stored yet", end='\n\n')
session_start(id, masterpass)
else:
print("\nAvailable Accounts:")
for i in range(len(res)):
print(str(i + 1) + " " + str(res[i][1]))
i = int(input())
i = i - 1
if (i >= len(res)):
print("Wrong Option")
else:
acc_id = res[i][0]
query = "DELETE FROM tbl_cryptostore WHERE acc_id = " + str(acc_id)
cn = connector()
cur = cn.cursor()
cur.execute(query)
cn.commit()
cn.close()
a = input("Press enter to continue")
session_start(id, masterpass)
def graphOfChosenStockOverTime():
# try:
conn = connect.connector()
cursor = conn.cursor()
names = retTableList()
for nam in names:
cursor.execute("SELECT * FROM " + nam)
row = cursor.fetchone()
dates = []
values = []
while row is not None:
dates.append(row[0].strftime('%Y-%m-%d'))
values.append(row[1])
row = cursor.fetchone()
# dates = dates.loc[:, 3].apply(lambda x: x.toordinal())
X = []
for i in dates:
X.append(days_between(i, dates[0]))
model = linregress(X, values) #x and y are arrays or lists.
slope, intercept = model.slope, model.intercept
print("\nPredictions for upcoming 5 days for " + nam + ":")
new_x = [143, 144, 145, 146, 147]
predictions = []
for i in new_x:
predict = slope * i + intercept
predictions.append(predict)
return predictions
def retTableList():
conn = connect.connector()
cursor = conn.cursor()
cursor.execute("show tables")
row = cursor.fetchone()
allTables = []
while row is not None:
allTables.append(row[0])
row = cursor.fetchone()
return allTables
def add(id, masterpass):
web = input("Enter website name: ")
username = input("Enter username or email id used for this website: ")
passGen(random.randint(10, 14))
password = input("Enter password used for this website: ")
crypto_pass = encrypt(masterpass, username, password)
userid_hash = hashlib.sha256(username.encode())
query = "INSERT INTO tbl_cryptostore(website_name, userid_hash, crypto_pass, id) VALUES(\'" + web + "\', \'" + userid_hash.hexdigest(
) + "\', \'" + crypto_pass + "\', " + str(id) + ")"
cn = connector()
cur = cn.cursor()
cur.execute(query)
cn.commit()
cn.close()
print("Done...")
a = input("Press enter to continue")
session_start(id, masterpass)
def graphOfChosenStockOverTime():
conn = connect.connector()
cursor = conn.cursor()
cursor.execute("SELECT * FROM abbdaily")
row = cursor.fetchone()
dates = []
values = []
while row is not None:
dates.append(row[0].strftime('%Y-%m-%d'))
values.append(row[1])
row = cursor.fetchone()
# print (values)
plt.plot(dates, values)
plt.xticks([], [])
plt.show()
def cryptocheck(id, acc_id, masterpass):
print("Enter username/email id used for this account")
username = input()
user_hash = hashlib.sha256(username.encode())
cn = connector()
cur = cn.cursor()
query = "SELECT crypto_pass FROM tbl_cryptostore WHERE userid_hash = \'" + user_hash.hexdigest(
) + "\'"
cur.execute(query)
res = cur.fetchall()
cn.close()
if (len(res) <= 0):
print("Invalid username entered\n\n")
sleep(2)
session_start(id, masterpass)
else:
print("Password: "******"Press enter to continue")
def login():
print("USER LOGIN")
print("Enter your name:")
name = input().lower()
print("Enter your mater key:")
mkey = input()
mkeyhash = hashlib.sha256(mkey.encode())
masterpass = hashlib.shake_256(mkey.encode())
cn = connector()
cur = cn.cursor()
query = "SELECT id FROM tbl_users WHERE master_hash = \'" + mkeyhash.hexdigest(
) + "\' and username = \'" + name + "\'"
cur.execute(query)
res = cur.fetchall()
cn.close()
if (len(res) == 0):
print("Invalid credentials entered...")
a = input("Press enter to continue")
os.system('CLS')
else:
os.system('CLS')
session_start(res[0][0], masterpass)
def register():
print("USER REGISTRATION")
print("Enter your name:")
tname = input().lower()
print(
"Enter a masterkey you would like to use: (Should be atleast 8 characters long)"
)
tmkey = input()
tmkeyhash = hashlib.sha256(tmkey.encode())
if (len(tmkey) >= 8):
query = "INSERT INTO tbl_users(master_hash, username) values(\'" + tmkeyhash.hexdigest(
) + "\',\'" + tname + "\')"
cn = connector()
cur = cn.cursor()
cur.execute(query)
cn.commit()
cn.close()
os.system('CLS')
login()
else:
print("Please make sure it is atleast 8 characters long...")
a = input("Press enter to continue")
os.system('CLS')
register()
import wbdata
import datetime
import iso3166
import requests
from bs4 import BeautifulSoup
import sys
sys.path.append('../other/')
import connect
# In[63]:
### Connect to database
con = connect.connector()
# In[14]:
### Web scraper for collecting featured indicators
url = 'http://data.worldbank.org/indicator?tab=featured'
response = requests.get(url)
html = response.content
soup = BeautifulSoup(html)
# In[61]:
### Collect indicatorID
indicatorID = []
all_links = soup.find_all("a")
for link in all_links:
import pandas as pd
import wbdata
import datetime
import sys
sys.path.append('../other/')
import connect
# Connect to database
con = connect.connector()
# Get countries, indicators
countries = wbdata.get_country(display=False)
indicators = wbdata.get_indicator(display=False)
# Collect CountryID
countryID = []
for i in range(len(countries)):
countryID.append(countries[i]['id'])
# Collect indicatorID
indicatorID = []
for i in range(1000, len(indicators)):
indicatorID.append(indicators[i]['id'])
# Make indDict for fetching data
indDict = dict()
for indStr in indicatorID:
indDict[indStr] = indStr.replace('.','_')
# fetch data
# import createNetwork as cnet
# import TweetsTextMining as ttm
import pandas as pd
import datetime
import networkx
import re
from collections import Counter
import EventTree
import connect as cnt
language = 'en'
USER = '******'
PASS = '******'
HOST = 'localhost'
DATABASE = 'db_paris_attack'
connector = cnt.connector(USER, PASS, HOST, DATABASE)
cursor = connector.cursor()
start_time = datetime.date(2015, 11, 1)
end_time = datetime.date(2015, 11, 30)
# df = cnet.extract_dataframe(cursor, start_time, end_time)
# df.to_csv("pairs_"+start_time.strftime("%Y-%m-%d")+".csv", index = False, encoding='utf-8')
# df = pd.read_csv("/Users/xianteng/Downloads/pairs_2015-11-01.csv")
# user_network = cnet.build_user_network(df)
# print("=== number of nodes: " + str(user_network.number_of_nodes()) + "\n")
# print("=== number of edges: " + str(user_network.number_of_edges()) + "\n")
# df = pd.read_csv("/Users/xianteng/Downloads/pairs_2015-11-01.csv")
# df.en = df[df['lang'] == 'en']
# ttm.term_frequency(df.en)
def searchTag(searchedTag):
conn = connect.connector()
# daily analysis restricted to 7 days
cursor = conn.cursor()
daily = searchedTag + "daily"
monthly = searchedTag + "monthly"
cursor.execute("SELECT * FROM " + daily + " order by recordtime desc limit 7")
row = cursor.fetchone()
dates_dail = []
values_dail = []
while row is not None:
dates_dail.append(row[0].strftime('%Y-%m-%d'))
values_dail.append(row[1])
row = cursor.fetchone()
# monthly analysis
cursor.execute("SELECT * FROM " + monthly)
row = cursor.fetchone()
dates_mon = []
values_mon = []
while row is not None:
dates_mon.append(row[0].strftime('%Y-%m-%d'))
values_mon.append(row[1])
row = cursor.fetchone()
plt.plot(dates_mon, values_mon)
plt.xticks([], [])
#-----------------predictions section-----------------------------------------------------------------------
cursor.execute("SELECT * FROM " + daily)
row = cursor.fetchone()
dates = []
values = []
while row is not None:
dates.append(row[0].strftime('%Y-%m-%d'))
values.append(row[1])
row = cursor.fetchone()
X = []
for i in dates:
X.append(days_between(i, dates[0]))
model = linregress(X,values) #x and y are arrays or lists.
slope, intercept = model.slope, model.intercept
new_x = [143, 144, 145, 146, 147]
pred_dates = []
for tt in new_x:
pred_dates.append(dates[0] + datetime.timedelta(days=i))
predictions = []
for i in new_x:
predictions.append(slope*i + intercept)
return dates_dail, values_dail, plt, pred_dates, predictions
