a34_email_higher_alert.py

#%%
from datetime import datetime,timedelta
import sys,os,copy,ast,socket,random,math,webbrowser,getpass,time,shutil,ast,subprocess,requests
import numpy as np
import pandas as pd
from pytz import timezone
import matplotlib.pyplot as plt


def reset_index(df):
    df=df.reset_index()    
    if 'index' in df.columns:
        df=df.drop(columns=["index"])
    if 'level_0' in df.columns:
        df=df.drop(columns=["level_0"])
    if 'Unnamed: 0' in df.columns:
        df=df.drop(columns=['Unnamed: 0'])
    return df

def read_excel(path):
    if path.endswith(".csv"):

        df=pd.read_csv(path,index_col=0)
    else:
        df=pd.read_excel(path,index_col=0)
    if 'index' in df.columns:
        df=df.drop(columns=["index"])
    if 'level_0' in df.columns:
        df=df.drop(columns=["level_0"])
    if 'Unnamed: 0' in df.columns:
        df=df.drop(columns=['Unnamed: 0'])    
    return df


def dump1(*varnames):
    python_script=os.path.basename(__file__)
    if not os.path.exists(f't7_print/{python_script}'):
        os.makedirs(f't7_print/{python_script}')
    global_vars = globals()
    string1=''
    for varname in varnames:
        if varname in global_vars:
            dict1={varname: global_vars[varname]}
            string1=string1+str(dict1)+', '
    print(string1)
    filename=string1
    with open(f't7_print/{python_script}/{filename}','w') as f:
        f.write(string1)

def print1(content_dict,filename):
    if '.txt' not in filename:
        filename=filename+'.txt'
    path='data/log/'
    if not os.path.exists(path):
        os.makedirs(path)
    fullpath=path+filename
    timedelta1=0
    timedelta2=100
    script_name = os.path.basename(__file__)
    today1=((datetime.now(timezone('US/Eastern'))-timedelta(timedelta1)).strftime("%Y-%m-%d %H:%M:%S"))
    today2=((datetime.now(timezone('US/Eastern'))-timedelta(timedelta1))).timestamp()
    past1=((datetime.now(timezone('US/Eastern'))-timedelta(timedelta2)).strftime("%Y-%m-%d"))
    past2=datetime.strptime('20210218', "%Y%m%d").timestamp()

    with open(fullpath,'a+') as f:
        f.write(str(content_dict))
        f.write(f' <-- {today1} {script_name} -->')   
        f.write('\n') 



def list_minus(list1, list2):
    # Convert lists to sets and find the difference
    set_difference = set(list1) - set(list2)
    # Convert the set back to a list
    return list(set_difference)



def base_list_save(filename,list1):
    
    content=str(list1)

    if filename.endswith('txt'):
        filename=filename.replace('.txt','')
    path='log/lists'
    if not os.path.exists(path):
        os.makedirs(path)

    with open(f'log/lists/{filename}.txt','w') as f:
        f.write(content)

def base_list_collections():
    return os.listdir('log/lists')

def base_list_read(filename):
    with open(f'log/lists/{filename}.txt','r') as f:
        data=f.readline()
    data=ast.literal_eval(data)
    return data



def csv_update_insert_one(database_name,collection_name,dn,no_duplicate_column):
    

    # csv_update_insert_one
    if 'cjs' in getpass.getuser():
        path3='C:/Users/cjsdl/Documents/data/'
    elif 'linux' in getpass.getuser():
        path3='/home/linux1/Documents/data/'
    else:
        path3=f'/Users/{getpass.getuser()}/Documents/data/'
    
    path=path3+database_name+'/'
    if not os.path.exists(path):
        os.makedirs(path)



    fullpath=path+collection_name+'.csv'
    try:
        do=read_excel(fullpath)
        
        do.set_index(no_duplicate_column, inplace=True)
        dn.set_index(no_duplicate_column, inplace=True)
        # print("dn: ",dn)
        # Update 'do' with the values from 'dn' where the indices match, then concatenate the rest of 'dn'
        do.update(dn)
        do = pd.concat([do, dn[~dn.index.isin(do.index)]])

        # Reset the index if needed
        do.reset_index(inplace=True)
        # print("do: ",do)        
        do

    except:
        # do=pd.DataFrame()
        do=dn

    do.to_csv(fullpath)
    # print('success csv')
    return do


def open_excel(df):
    random1=random.randint(1,10)

    temp_file=f'temp_sample_{random1}.xlsx'
    if 'cjsdl' in getpass.getuser():
        export_path='G:/My Drive/ibkr/1_total_data/8 temp/'
        print('start - to_excel a large file maybe ...')
        df.to_excel(export_path+temp_file)
        print('success - to_excel a large file maybe ...')
        excel1=fr"G:\My Drive\ibkr\1_total_data\8 temp\temp_sample_{random1}.xlsx"
        # r"C:\Users\cjsdl\AppData\Roaming\Microsoft\Windows\Start Menu\Programs\Anaconda3 (64-bit)\Anaconda Prompt (miniconda3).lnk"
        os.startfile(excel1)
        
    else:
        export_path=f'/Users/{getpass.getuser()}/Library/CloudStorage/GoogleDrive-ryan.ichun9@gmail.com/My Drive/ibkr/1_total_data/8 temp/'
        print('start - to_excel a large file maybe ...')

        df.to_excel(export_path+temp_file)
        os.system("open -a 'Microsoft Excel.app' '{}{}'".format(export_path,temp_file))

from websocket import create_connection
import json,string,re

def datainput(func,paramList):
    #func="set_auth_token"
    #paramList=["unauthorized_user_token"]
    data1=json.dumps({"m":func,"p":paramList}, separators=(',', ':'))
    data1
    data2="~m~" + str(len(data1)) + "~m~" + data1
    return data2
def tradingview_simple(fullname,minute1):

    if "CME" in fullname or "CBOT" in fullname or "COMEX" in fullname or "NYMEX" in fullname:
        extended_or_regular="regular"
    else:
        extended_or_regular="extended"


    headers = json.dumps({'Origin': 'https://data.tradingview.com'})
    connector=create_connection('wss://data.tradingview.com/socket.io/websocket',headers=headers)
    stringLength=12
    letters = string.ascii_lowercase
    random_string= ''.join(random.choice(letters) for i in range(stringLength))
    session= "qs_" +random_string

    stringLength=12
    letters = string.ascii_lowercase
    random_string= ''.join(random.choice(letters) for i in range(stringLength))
    chart_session= "cs_" +random_string
    #chart_session= "cs_" +"ZHlTeGX28izS"
    #ZHlTeGX28izS

    #connector.send(datainput('set_auth_token',["eyJhbGciOiJSUzUxMiIsImtpZCI6IkdaeFUiLCJ0eXAiOiJKV1QifQ.eyJ1c2VyX2lkIjoxMjgyNzE5MywiZXhwIjoxNjQ3OTM2MDQ2LCJpYXQiOjE2NDc5MjE2NDYsInBsYW4iOiJwcm9fcHJlbWl1bSIsImV4dF9ob3VycyI6MSwicGVybSI6ImNib3RfbWluaSxjbWUsY21lLWZ1bGwsY29tZXgsbnltZXgsbnlzZSxueW1leF9taW5pLGNtZV9taW5pLGNib3QsbmFzZGFxLGNvbWV4X21pbmksa3J4X3N0b2NrcyIsInN0dWR5X3Blcm0iOiJ0di12b2x1bWVieXByaWNlLHR2LXByb3N0dWRpZXMiLCJtYXhfc3R1ZGllcyI6MjUsIm1heF9mdW5kYW1lbnRhbHMiOjAsIm1heF9jaGFydHMiOjgsIm1heF9hY3RpdmVfYWxlcnRzIjo0MDAsIm1heF9zdHVkeV9vbl9zdHVkeSI6MjR9.ps5_xiYSdN_1FQnC1C98KwtTE3vHMRA0hDyHnCXbg3cyP0RHT6P4O4EBIGCeW-ZsrWkLrCdVN5ZJTgH9jfG9IaSviiDhkhS8rh6iFvqPS-NZ5rdcJ8--tbSLMcLcSHxfonrMO6BXB_yAh3fDePaWFFmJoaDh7D9_-iLgDC_jtoI"]))
    connector.send(datainput('set_auth_token',['unauthorized_user_token']))
    connector.send(datainput("chart_create_session",[chart_session, ""]))
    connector.send(datainput('quote_create_session',[session]))
    #connector.send(datainput('quote_set_fields',[session,"ch","chp","current_session","description","local_description","language","exchange","fractional","is_tradable","lp","lp_time","minmov","minmove2","original_name","pricescale","pro_name","short_name","type","update_mode","volume","currency_code","rchp","rtc"]))
    connector.send(datainput('quote_set_fields',[session,"short_name","pro_name","logoid","currency-logoid","base-currency-logoid","symbol-primaryname","type"]))
    "qs_pzepkyh89H2l"
    connector.send(datainput('quote_add_symbols',[session, fullname, "={\"symbol\":"+"\"{}\"".format(fullname) + ",\"currency-id\":\"USD\",\"adjustment\":\"splits\"}"]))

    connector.send(datainput('quote_fast_symbols',[session,fullname]))
    #connector.send(datainput('resolve_symbol',[chart_session,"sds_sym_1","={\"symbol\":"+"\"{}\"".format(fullname) +",\"adjustment\":\"splits\",\"session\":\"extended\"}"]))
    #connector.send(datainput('resolve_symbol',[chart_session,"sds_sym_1","={\"symbol\":"+"\"{}\"".format(fullname) +",\"adjustment\":\"splits\",\"session\":\"regular\"}"]))
    connector.send(datainput('resolve_symbol',[chart_session,"symbol_1","={\"symbol\":"+"\"{}\"".format(fullname) +",\"adjustment\":\"splits\",\"session\":" +"\"{}\"".format(extended_or_regular)+"}"]))
    connector.send(datainput('create_series',[chart_session, "s1", "s1", "symbol_1", minute1, 5000]))
    time1=[time.monotonic()]
    while True:
        #time.sleep(1)
        list1=[]
        result = connector.recv()
        list2=""+result+'\n'
        
        list1.append(result)
        #print(result)
        #print("helo##############################")

        if len(result)>10000:
            break
        elif len(result)==0:
            break
        else:
            
            if time.monotonic()-time1[0]>(60):
                print(fullname, "error here5")
                break

            else:
                continue
    result1=list1[0]
    a1=""+result1+'\n'
    out= re.search('"s":\[(.+?)\}\]', a1).group(1)
    x=out.split(',{\"')

    list4=[]

    for i in range(len(x)):


        xi=x[i]
        xi

        xi2= re.split('\[|:|,|\]', xi)
        

        index1= int(xi2[1])
        index1

        date2=xi2[4]
        date2

        date1=datetime.fromtimestamp(float(date2)).strftime("%Y/%m/%d, %H:%M:%S")
                
        date1=datetime.strptime(date1, "%Y/%m/%d, %H:%M:%S")
        date1

        list3=[index1,date1,float(xi2[5]), float(xi2[6]), float(xi2[7]), float(xi2[8]), float(xi2[9]),float(date2)]
        list3

        list4.append(list3)
        list4

    df=pd.DataFrame(list4)
    df.rename(columns={0:"Index",1:'Date',2:"Open",3:"High",4:"Low",5:"Close",6:"Volume",7:"Timestamp"}, inplace=True)


    df = df.drop('Index', axis=1)
    df

    while True:
        tot=len(df)-1
        date2=df['Date'][tot]
        date2
        if 'nan' in str(date2).lower() or 'nat' in str(date2).lower():
            print('drop last row')
            df = df.iloc[:-1 , :]
        else:
            break

    return df

def find_exchange_v2(ticker):


    url = f"https://finance.yahoo.com/quote/{ticker}"

    querystring = {"p":ticker}

    payload = ""
    headers = {"User-Agent": "insomnia/8.5.0"}
    
    response = requests.request("GET", url, data=payload, headers=headers, params=querystring)

    # print(response.text)
    # //div[@class="C($tertiaryColor) Fz(12px)"]
    TAG='div'
    class_name = "C($tertiaryColor) Fz(12px)"

    from bs4 import BeautifulSoup
    soup = BeautifulSoup(response.text, 'html.parser')
    text = soup.text

    elements = soup.find_all(TAG, class_=class_name)
    exchange_info=elements[0].find('span').text
    exchange_info=exchange_info.lower()

    exchange='NYSE'
    if exchange_info.startswith('nasdaq'):
        exchange='NASDAQ'
    elif exchange_info.startswith('nyse'):
        exchange='NYSE'
    return exchange



def find_exchange_v3(ticker):
    print("ticker: ",ticker)
    #https://polygon.io/docs/stocks/get_v3_reference_tickers__ticker
    import requests,json
    url=f'https://api.polygon.io/v3/reference/tickers/{ticker}?apiKey={polygon_api_key}'
    response=requests.get(url)

    json1=response.json()
    stock_name=json1['results']

    exchange1=stock_name['primary_exchange']
    exchange1

    if exchange1=='XNAS':
        exchange='NASDAQ'
    elif exchange1=='XNYS':
        exchange='NYSE'
    else:
        exchange='AMEX'
    return exchange
def generate_fullname_tradingview(ticker):
    try:
        exchange=find_exchange_v3(ticker)
    except:
        exchange=find_exchange_v2(ticker)
    return f'{exchange}:{ticker}'


def feature_engineering(df):
    df['Close1']=df["Close"].shift(periods=1)

    df['Close5'] = df["Close"].rolling(min_periods=1, window=5).mean()
    df['Close10'] = df["Close"].rolling(min_periods=1, window=10).mean()
    df['SMA50'] = df["Close"].rolling(min_periods=1, window=50).mean()
    df['SMA200'] = df["Close"].rolling(min_periods=1, window=200).mean()
    df['SMA300'] = df["Close"].rolling(min_periods=1, window=300).mean()
    df['SMA500'] = df["Close"].rolling(min_periods=1, window=500).mean()
    df['SMA100'] = df["Close"].rolling(min_periods=1, window=100).mean()
    df['SMA1000'] = df["Close"].rolling(min_periods=1, window=1000).mean()
    df['SMA2000'] = df["Close"].rolling(min_periods=1, window=2000).mean()

    df["High5"] = df["High"].rolling(min_periods=1, window=5).max()
    df["High10"] = df["High"].rolling(min_periods=1, window=10).max()
    df["MAX200"] = df["High"].rolling(min_periods=1, window=200).max()

    df["Low5"] = df["Low"].rolling(min_periods=1, window=5).min()
    df["Low10"] = df["Low"].rolling(min_periods=1, window=10).min()
    df["MIN200"] = df["Low"].rolling(min_periods=1, window=200).min()
    

    df['Close2'] = df['Close'].pct_change()
    df['High2'] = df['High'].pct_change()
    df['Low2'] = df['Low'].pct_change()
    df['Open2'] = df['Open'].pct_change()
    df['Volume2'] = df['Volume'].pct_change()

    # p2 getting 'down2' value from 'low' and 2sd away from 'low'
    ROLLING_N=10
    df['Low5_mean'] = df['Low'].rolling(window=ROLLING_N).mean()
    df['Low5_sd'] = df['Low'].rolling(window=ROLLING_N).std()
    z_score=2
    df['up1'] = df['High'] + z_score * df['Low5_sd']
    df['down1'] = df['Low'] - z_score * df['Low5_sd']
    df
    df['down1']=df['down1'].shift(1)
    df['up1']=df['up1'].shift(1)
    
    return df
from twilio.rest import Client
import yagmail
from datetime import datetime,timedelta
import pandas as pd
# Your Account SID from twilio.com/console
account_sid = "{account_sid_twilio}"
auth_token  = "{auth_token_twilio}"
client = Client(account_sid, auth_token)
sender='{id_yagmail}'
#receiver='bluerand3@gmail.com'
email1=sender
passw1='{password_yagmail}'
passw1='{password_yagmail}'
yag = yagmail.SMTP(user=sender,password=passw1)
content1='1'
subject1='1'
def send_email(to_email,title,content):
    yag.send(to=to_email,subject=title,contents=content)

def email_send(ticker,alert_price,link1):
    title= f'ALERT! {ticker} crossed higher price v1'
    content=f'''
    {ticker} crossed {alert_price}.
    {link1}

    '''
    send_email(sender,title,content)
#%%
def screen_for_stock_alert():
    path1=f'/Users/{getpass.getuser()}/Library/CloudStorage/GoogleDrive-ryan.ichun9@gmail.com/My Drive/ibkr/2 import data/6 twilio/stock_alert.xlsx'
    df=read_excel(path1)
    df=reset_index(df)
    df
    #%%
    for i in range(len(df)):
        ticker=df['ticker'][i]
        alert_price=df['alert_price'][i]
        # ticker='AAPL'
        fullname=generate_fullname_tradingview(ticker)
        minute1='1D'
        dt=tradingview_simple(fullname,minute1)

        dt1=reset_index(dt.iloc[-200:])
        dt1
        highest=max(dt1['High'].values.tolist())
        highest
        exchange=fullname.split(':')[0]
        link1=f'https://www.tradingview.com/chart/tMeJexox/?symbol={exchange}%3A{ticker}'
        print(ticker,alert_price,highest)
        if alert_price<highest:
            email_send(ticker,alert_price,link1)
    #%%
    # https://www.tradingview.com/chart/tMeJexox/?symbol=NASDAQ%3AAAPL
            
import pytz
#%%
def screen_for_stock_alert_1W_sma50():
    path1=f'/Users/{getpass.getuser()}/Library/CloudStorage/GoogleDrive-ryan.ichun9@gmail.com/My Drive/ibkr/2 import data/6 twilio/stock_alert.xlsx'
    df=read_excel(path1)
    df=reset_index(df)
    df
    #%%
    for i in range(len(df)):
        ticker=df['ticker'][i]
        alert_price=df['alert_price'][i]
        # ticker='AAPL'
        if int(alert_price)<1:
                
            fullname=generate_fullname_tradingview(ticker)
            minute1='1W'
            dt=tradingview_simple(fullname,minute1)
            dt=feature_engineering(dt)
            # dt1=reset_index(dt.iloc[-200:])
            # dt1
            highest=dt['High'][-1:].values[0]
            highest
            sma50=dt['SMA50'][-1:].values[0]
            sma50

            exchange=fullname.split(':')[0]
            link1=f'https://www.tradingview.com/chart/tMeJexox/?symbol={exchange}%3A{ticker}'
            print(ticker,sma50,highest)
            if highest>sma50:
                email_send(ticker,sma50,link1)
    #%%
# ticker=df['ticker'][i]
# alert_price=df['alert_price'][i]
ticker='AAPL'
fullname=generate_fullname_tradingview(ticker)
minute1='1W'
dt=tradingview_simple(fullname,minute1)
dt
#%%
dt=feature_engineering(dt)
dt
#%%
sma50=dt['SMA50'][-1:].values[0]
sma50
#%%
    
# Setting the timezone to US Eastern
timezone1 = pytz.timezone('US/Eastern')

while True:
    # Getting the current time in US Eastern Time Zone
    now_eastern = datetime.now(timezone1).strftime("%H:%M:%S")
    print(now_eastern)
    time.sleep(1)

    # Execute once everyday at 06:25:59 AM Eastern Time
    if datetime.now(timezone1).strftime("%H%M%S") == '062559':
        try:
            print('''> try: screen_for_stock_alert()''', datetime.now(timezone1))
            screen_for_stock_alert()
        except Exception as e:
            print('''>> error: screen_for_stock_alert(): ''', e, datetime.now(timezone1))
    
    # Execute once every hour
    HR = 1
    if int(datetime.now(timezone1).strftime("%H")) % HR == 0 and int(datetime.now(timezone1).strftime("%M")) == 0:
        # Your hourly code here
        pass

    # Execute once every minute
    MI = 1
    if int(datetime.now(timezone1).strftime("%M")) % MI == 0 and int(datetime.now(timezone1).strftime("%S")) == 1:
        # Your minutely code here
        pass