def success(name):
import time
from datetime import datetime as dat
# change hosts path according to your OS
hosts_path = "C:\Windows\System32\Drivers\etc\hosts"
# localhost's IP
localIP = "127.0.0.1"
website_list = [name]
while True:
if dat(dat.now().year, dat.now().month, dat.now().day, 1) < dat.now() < dat(dat.now().year, dat.now().month,
dat.now().day, 11):
print("Process Executed...")
with open(hosts_path, 'r+') as file:
content = file.read()
for website in website_list:
if website in content:
pass
else:
file.write(localIP + " " + website + "\n")
else:
with open(hosts_path, 'r+') as file:
content = file.readlines()
file.seek(0)
for line in content:
if not any(website in line for website in website_list):
file.write(line)
# removing hostnmes from host file
file.truncate()
print("Process not executing...")
time.sleep(5)
def run(self):
with ThreadPoolExecutor(max_workers=2) as pool:
q = {
pool.submit(self.stat, self.name, dat(self.year, m, 1)): m
for m in range(1, 13)
}
def passesLeapDay(today):
thisYear = today.timetuple()[0]
if isLeapYear(thisYear):
sixMonthsAgo = today - datetime.timedelta(days=183)
leapDay = datetime.dat(thisYear, 2, 29)
return leapDay >= sixMonthsAgo
else:
return False
def get_all_hisData(interval="1d",startin=dat(2020,1,1,00,1,1),endin=dat.now()):
address = update_Main_Chart()
df =pd.read_csv(address)
addressBook=[]
for x in range(0,df.size-1):
tempdata={}
symbol=df["symbol"][x]
interval="1d"
symdata=get_Kline_csv(symbol,interval=interval,startin=startin,endin=dat.now())
tempdata={"symbol":symbol,"address":symdata,"start":startin.strftime("%Y-%m-%d %H:%M:%S"),"end":endin.strftime("%Y-%m-%d %H:%M:%S")}
addressBook.append(tempdata)
return addressBook
def get_mean_performance(df):
"""
Take the filtered dataframe and calculate mean performance per mouse on each day.
:param df:
:return:
"""
result = []
i = 0
for mouse in df.mouse.unique():
i = 0
# Get subset of dataset for each mouse
curr_mouse = df.loc[df['mouse'] == mouse]
for date in curr_mouse.session_date.unique():
# For each mouse, get a subset of every session
curr_sess = curr_mouse.loc[curr_mouse['session_date'] == date]
# Get the distance in days from stroke surgery (data is sorted to that there are 5 prestroke sessions
if i < 5:
norm_day = i - 5
stroke_day = dat(int(date[:4]), int(date[4:6]), int(date[6:]))
else:
norm_day = (dat(int(date[:4]), int(date[4:6]), int(date[6:])) -
stroke_day).days
# Store the data in a pd.Series which is concatenated to one DF in the end
result.append(
pd.DataFrame(
{
"mouse": mouse,
"date": date,
"performance": curr_sess["licking_binned"].mean(),
"norm_day": norm_day
},
index=[i]))
i += 1
return pd.concat(result)
def get_Kline_csv(name,interval="1h",startin=dat(2020,1,1,00,1,1),endin=dat.now()):
start=startin.strftime("%d %m,%Y")
startff=startin.strftime("%d%m%Y")
endff=endin.strftime("%d%m%Y")
end=endin.strftime("%d %m,%Y")
dirc=mainPath+"/data/csvs/"+name+"/"+interval
filename="data"
fileformat=".csv"
##info = client.get_symbol_info(name) ## check for is trading or not !
print("from "+start+" -> "+end)
##get_historical_klines(symbol, interval, start_str, end_str=None, limit=500)
flag=1
while flag==1:
try:
data=client.get_historical_klines(name,interval,start,end)
flag=0
except:
print("check your connection - ctrl-c for exit - we are retrying")
print("date resived!!!")
for x in range(len(data)):
data[x][0]=dat.strptime(dat.fromtimestamp(int(data[x][0])/1000).strftime('%Y-%m-%d %H:%M:%S'),"%Y-%m-%d %H:%M:%S")
for xx in range(1,len(data[0])-1):
data[x][xx]=float(data[x][xx])
dfdata=[]
for x in range(len(data)):
themplis=[]
for xx in range(0,len(data[0])-1):
if(xx<=5 or xx==8):
themplis.append(data[x][xx])
dfdata.append(themplis)
if not os.path.exists(dirc):
os.makedirs(dirc)
print("path successfuly created")
else:
print("folder found ")
## noft -> number of trades
address=dirc+"/"+filename+fileformat
df=pd.DataFrame(columns=["date","open","high","low","close","volume","noft"],data=dfdata)
df.set_index("date",drop=True,inplace=True)
df.to_csv(address,mode="w")
print("successfuly created")
return address
def stat(self, ind, d):
a = []
for i in range(1, 13):
start_date = dat(self.year, i, 1)
a.append(stat(start_date, self.name))
d[ind] = a
import backtrader as bt
import backtrader.feeds as btfeeds
import pandas as pd
import requests as req
import time
from analisys.control import TestStrategy
from notfication.control import notfication
# ----------------------------------
bot = notfication()
# ---------------------------
if __name__ == '__main__':
datapath = ctrl.dirc
data = btfeeds.GenericCSVData(dataname=get_Kline_csv(name="BTCUSDT",
interval="1h"),
fromdate=dat(2021, 1, 1),
todate=dat.now(),
nullvalue=0.0,
dtformat=('%Y-%m-%d %H:%M:%S'),
datetime=0,
open=3,
high=1,
low=2,
close=4,
volume=5,
openinterest=-1)
# Create a Data Feed
cerebro = bt.Cerebro()
cerebro.addstrategy(TestStrategy)
cerebro.broker.setcash(100000)
cerebro.adddata(data)
def date(dd, mm, yyyy):
try:
dat(year=yyyy, month=mm, day=dd)
return True
except ValueError:
return False
import time
from datetime import datetime as dat
hostp = "hosts"
host_path="/etc/hosts"
redirect = "127.0.0.1"
websites = ["www.facebook.com", "facebook.com", "www.primevideo.com", "primevideo.com"]
while True:
#creating datetime object
if dat(dat.now().year, dat.now().month, dat.now().day, 8) < dat.now() < dat(dat.now().year, dat.now().month, dat.now().day, 17,15):
print("Study hours.....")
with open(host_path,'r+') as file:
info = file.read()
for website in websites:
if website in info:
pass
else:
file.write(redirect+" "+website+"\n")
else:
with open(host_path,'r+') as file:
info = file.readlines()
file.seek(0)
for line in info:
if not any(website in line for website in websites):
file.write(line)
# deletes the content of the file from current point and downwards
file.truncate()
print("Time to relax..")