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Trade_NSe.py
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Trade_NSe.py
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# -*- coding: utf-8 -*-
"""
Created on Fri Sep 27 19:48:29 2019
@author: visha
"""
import yfinance as yf
import pandas as pd
import csv
import os
from datetime import date
today = date.today()
today_str=str(today)
os.chdir(r"F:\\Algo_trading\\DataBase")
###########Merge old and new###################################
path = os.path.join(os.getcwd(), today_str)
os.mkdir(path)
with open('Stock_List.csv','rt')as f:
data = csv.reader(f)
for row in data:
ticker=row[2]
filename=row[1]
data = yf.download(tickers=ticker, period="1d", interval="5m")
while data.shape[0] < 74:
data = yf.download(tickers=ticker, period="1d", interval="5m")
data['Date'] = data.index
data['Date'] = data['Date'].astype(str).str[:-6]
#data['Date']=data['Date'].astype(str).str[6:]
data['Date']= pd.to_datetime(data['Date'])
data.reset_index(drop=True, inplace=True)
#cols = list(data.columns.values)
data = data[['Date','Open', 'High', 'Low', 'Close', 'Adj Close', 'Volume']]
olddata=pd.read_csv(filename+'.csv')
olddata['Date']= pd.to_datetime(olddata['Date'])
data_new=pd.concat([olddata,data]).drop_duplicates(subset='Date', keep='first').reset_index(drop=True)
data_new = data_new[['Date','Open', 'High', 'Low', 'Close', 'Adj Close', 'Volume']]
file_current=path+'\\'+filename+'.csv'
data_new.to_csv(file_current,index=False)
###################Single Get of all FNO 5 minute 60 days##########################
with open('Stock_List.csv','rt')as f:
data = csv.reader(f)
for row in data:
ticker=row[2]
filename=row[1]
data = yf.download(tickers=ticker, period="60d", interval="5m")
data['Date'] = data.index
data['Date'] = data['Date'].astype(str).str[:-6]
#data['Date']=data['Date'].astype(str).str[6:]
data['Date']= pd.to_datetime(data['Date'])
data.reset_index(drop=True, inplace=True)
#cols = list(data.columns.values)
data = data[['Date','Open', 'High', 'Low', 'Close', 'Adj Close', 'Volume']]
file_current=filename+'.csv'
data.to_csv(file_current,index=False)
##############1 day recurring############
os.chdir(r"F:\\Algo_trading\\DataBase-1D")
path = os.path.join(os.getcwd(), today_str)
os.mkdir(path)
with open('Stock_List-1D.csv','rt')as f:
data = csv.reader(f)
for row in data:
ticker=row[2]
filename=row[1]
data = yf.download(tickers=ticker, period="7d", interval="1d")
while data.shape[0] < 1:
data = yf.download(tickers=ticker, period="7d", interval="1d")
data['Date'] = data.index
data['Date']= pd.to_datetime(data['Date'])
data.reset_index(drop=True, inplace=True)
#cols = list(data.columns.values)
data = data[['Date','Open', 'High', 'Low', 'Close', 'Adj Close', 'Volume']]
olddata=pd.read_csv(filename+'.csv')
olddata['Date']= pd.to_datetime(olddata['Date'])
data_new=pd.concat([olddata,data]).drop_duplicates(subset='Date', keep='first').reset_index(drop=True)
data_new = data_new[['Date','Open', 'High', 'Low', 'Close', 'Adj Close', 'Volume']]
file_current=path+'\\'+filename+'.csv'
data_new.to_csv(file_current,index=False)
###################Single Get of all FNO 1D 1000 Days ##########################
with open('Stock_List-1D.csv','rt')as f:
data = csv.reader(f)
for row in data:
ticker=row[2]
filename=row[1]
data = yf.download(tickers=ticker, period="999d", interval="1d")
data['Date'] = data.index
#data['Date']=data['Date'].astype(str).str[6:]
data['Date']= pd.to_datetime(data['Date'])
data.reset_index(drop=True, inplace=True)
#cols = list(data.columns.values)
data = data[['Date','Open', 'High', 'Low', 'Close', 'Adj Close', 'Volume']]
file_current=filename+'.csv'
data.to_csv(file_current,index=False)
#################NINJA##################
os.chdir(r"F:\\Algo_trading\\Ninja")
path = os.path.join(os.getcwd(), today_str)
os.mkdir(path)
with open('Stock_List.csv','rt')as f:
data = csv.reader(f)
for row in data:
ticker=row[2]
filename=row[1]
data = yf.download(tickers=ticker, period="1d", interval="1m")
#while data.shape[0] < 1499:
# data = yf.download(tickers=ticker, period="1d", interval="1m")
data['Date'] = data.index
data['Date']= pd.to_datetime(data['Date'])
data.reset_index(drop=True, inplace=True)
#cols = list(data.columns.values)
data['Date_new'] = data['Date'].dt.strftime('%Y%m%d %H%M%S')
data = data[['Date_new','Open', 'High', 'Low', 'Close','Volume']]
data.loc[data['Volume'] ==0, 'Volume'] = 100
file_current=path+'\\'+filename+'.txt'
data.to_csv(file_current,index=False,sep=';',header=False)
data=pd.read_csv('NIFTY'+'.csv')
filename='NSE1d'
data = yf.download(tickers='ADANIENT.NS', period="4d", interval="5m")
data['Date'] = data.index
data['Date']= pd.to_datetime(data['Date'])
data['Date_new'] = data['Date'].dt.strftime('%Y%m%d %H%M%S')
data = data[['Date_new','Open', 'High', 'Low', 'Close','Volume']]
data.loc[data['Volume'] ==0, 'Volume'] = 100
file_current=path+'\\'+filename+'.txt'
data.to_csv('ACC.txt',index=False,sep=';',header=False)
data.to_csv(filename+'.csv')
data.head()
data = yf.download(tickers="IGL.NS", period="60mo", interval="1d")
data.to_csv('NSE1d.csv')
high=data['High']
max_value=max(high)
low=data['Low']
min_value=min(low)
data['Date'] = data.index
data['Date']= pd.to_datetime(data['Date'])
data.reset_index(drop=True, inplace=True)
Todays_range=abs(max_value-min_value)
level_618=Todays_range*0.618
level_382=Todays_range*0.382
level_113=Todays_range*1.13
level_1618=Todays_range*1.618
level_1382=Todays_range*1.382
level_above_min_382=round(min_value+level_382,2)
level_above_min_618=round(min_value+level_618,2)
level_above_min_113=round(min_value+level_113,2)
level_above_min_1382=round(min_value+level_1382,2)
level_above_min_1618=round(min_value+level_1618,2)
level_below_max_113=round(max_value-level_113,2)
level_below_max_1382=round(max_value-level_1382,2)
level_below_max_1618=round(max_value-level_1618,2)
#plotly.offline.init_notebook_mode()
import plotly.graph_objs as go
import pandas as pd
trace = go.Figure(data=[go.Candlestick(x=data['Date'],
open=data['Open'],
high=data['High'],
low=data['Low'],
close=data['Close'])])
trace.layout.xaxis.type = 'category'
trace.layout.xaxis.showgrid= False
trace.layout.yaxis.showgrid= False
#trace.update_yaxes(nticks=50)
trace.update_yaxes(dtick=20)
trace.update_xaxes(showticklabels=False)
trace.update_layout(xaxis_rangeslider_visible=False)
#trace.update_xaxes(nticks=78)
trace.update_layout(
title='The Nifty Levels',
yaxis_title='Nifty Spot',
xaxis_title='Last 3 days 15 min Chart',
shapes = [dict(
x0=0, x1=1, y0=level_above_min_382, y1=level_above_min_382, xref='paper',
line_width=2)],
annotations=[dict(
x=0, y=level_above_min_382+5, xref='paper',
showarrow=False, xanchor='left', text=str(level_above_min_382)+'level')]
)
trace.update_layout(
title='The Nifty Levels',
yaxis_title='Nifty Spot',
xaxis_title='Last 3 days 15 min Chart',
shapes = [dict(
x0=0, x1=1, y0=level_above_min_382, y1=level_above_min_382, xref='paper',
line_width=2)],
annotations=[dict(
x=0, y=level_above_min_382+5, xref='paper',
showarrow=False, xanchor='left', text=str(level_above_min_382)+'level')]
)
trace.update_layout(
shapes=[
# Line Vertical
go.layout.Shape(
type="line",
x0=0,
y0=level_above_min_382,
x1=1,
y1=level_above_min_382,
xref='paper',
line=dict(
color="RoyalBlue",
width=3
)
),
# Line Horizontal
go.layout.Shape(
type="line",
x0=0,
y0=level_above_min_618,
x1=1,
y1=level_above_min_618,
xref='paper',
line=dict(
color="RoyalBlue",
width=3
)
),
# Line Diagonal
go.layout.Shape(
type="line",
x0=0,
y0=level_above_min_113,
x1=1,
y1=level_above_min_113,
xref='paper',
line=dict(
color="RoyalBlue",
width=3
)
),
]
)
trace.update_layout(
showlegend=False,
annotations=[
go.layout.Annotation(
x=0,
y=level_above_min_382+5,
xref='paper',
text="dict Text",
showarrow=False,
xanchor='left'
)
]
)
trace.write_html('check.html', auto_open=True)
import urllib.request
import threading
def run_check():
threading.Timer(5.0, run_check).start()
urllib.request.urlopen("http://domain.tld?parameter=value¶meter2=value").read()
print("HTTP Request sent.")
run_check()
import requests
def telegram_bot_sendtext(bot_message):
bot_token = '916925173:AAG-CuT8gB78nT9_NjpwHQpUss9A4ZYEJP8'
bot_chatID = '-399094458'
send_text = 'https://api.telegram.org/bot' + bot_token + '/sendMessage?chat_id=' + bot_chatID + '&parse_mode=Markdown&text=' + bot_message
response = requests.get(send_text)
return response.json()
test = telegram_bot_sendtext("This is done!!")
print(test)