sto.py

import yfinance as yf
import pandas as pd
import numpy as np
import warnings
import sys
from datetime import datetime, timedelta

#These 3 lines need to be in sync its the build the DF (pandas) as well as print out to match
days =(365,240,120,60,60,30,0)
df = pd.DataFrame(columns=['Ticker','0','30','60','90','120'])
print('Ticker,1 year, 240 Days,120 days, 90 days, 60 Days, 30 Days, 0 Days')


#this is for debugging - use input file or other code later on..
#words = ('MSFT','MS','O','QYLD')
words = []
inputfile = "t1.txt"
with open(inputfile) as k:
    for line in k:
        words.append(line.strip())

#make life easy so the system knows Line is a string. 
line = ""
for word in words:
    try:
        y_data = yf.Ticker(word)
        y_info = y_data.info
        line = word
        for day in days:
            #figure start and end dates- using 20 days back as that should be around 14 working days (two weeknds)
            daystart = datetime.now() - timedelta(days=day)
            dayend = datetime.now() - timedelta(days=(day+20))
            isPast = dayend.date()
            isNow = daystart.date()
            #put the history into a pandas data frame.
            df1 = y_data.history(start=isPast, end=isNow, actions=False)
            #add ain index this way we know the max line to find 
            df1['index_ct'] = range(1, len(df1)+1)

            #find the values -max of index, The low of the period, the high of the period and the closing price of the earliest data
            imax = df1['index_ct'].max()
            L14 = df1['Low'].min()
            H14 = df1['High'].max()
            c_price = df1.loc[df1.index_ct == imax,'Close'].values[0]
            #this is the stoic calc from investopedia
            k = ((c_price - L14)/(H14 - L14))*100
            #for now not putting it into a pandas dataframe ist adding it to the line 
            line = line  + ',' + str(k)
            #debugging this if for me to figure out if something fgoes wrong 
            #print(df1)
            #print(L14)
            #print(H14)
            #print(imax)
            #print(df1[df1['index_ct']==imax])
            #df.loc[df.Unit_Price >= 1000,'Product_Name'].tolist()
            #print('closing price of newest date',df1.loc[df1.index_ct == imax,'Close'].values[0])
        #after each ticker print the line.
        print(line)
    except Exception as e:
        print(line, " ", "excpetion didnt finish")
print("End of analysis")