Financials_Extractor.py

'''Complete financial data extraction concurrently and storing them in csv collectively for further operations. On line 54, make sure to slice tickers appropriately by using indexses from Tickers.csv. Data extraction altogether will produce undesired results.'''

from yahoofinancials import YahooFinancials
import csv
import concurrent.futures
import yfinance as yf 
from datetime import date
from itertools import zip_longest


symbol=0
remover=list()
tickers_list=list()

def financials_fetcher(ticker):

        try:

            yahoo_financials=YahooFinancials(ticker)
            hold=yahoo_financials.get_key_statistics_data()
            hold2=yahoo_financials.get_summary_data()
            hold3=yahoo_financials.get_financial_stmts('annual', 'income')
            book_value=hold[ticker]['bookValue']
            EVtoEBITDA=hold[ticker]['enterpriseToEbitda']
            priceToBookR=hold[ticker]['priceToBook']
            market_cap=(hold2[ticker]['marketCap'])//10000000
            priceToSales=(hold2[ticker]['priceToSalesTrailing12Months'])
            previous_Close=(hold2[ticker]['previousClose'])
            sharesOutstanding=hold[ticker]['sharesOutstanding']
            total_revenue=hold3["incomeStatementHistory"][ticker][0]['2021-03-31']['totalRevenue']
            #print(book_value)    
            #print("\n")

        except:
            remover.append(ticker)
            print(remover)
        
        try:
            return ticker,book_value,EVtoEBITDA,priceToBookR,market_cap,priceToSales,previous_Close,sharesOutstanding,total_revenue
        except:
            return ticker,None,None,None,None,None,None,None,None


#----------------------------------------------------------------------------------------------------------
#Preparation of key financial ratios dataset for all tickers using thread pool executors for quicker output

def thread_pool_executor():

    comp=csv.reader(open("Tickers.csv"))

    for c in comp:
        tickers_list.extend(c)

    with concurrent.futures.ThreadPoolExecutor() as executor:
    
        tickers=tickers_list[200:400]
        results=executor.map(financials_fetcher,tickers)

        ticker_results=list()
        tickers_book_value=list()
        tickers_evtoebitda=list()
        tickers_priceToBook=list()
        tickers_close=list()
        tickers_marketcap=list()
        tickers_priceToSales=list()
        tickers_sharesoutstanding=[]
        tickers_total_revenue=[]

        for result in results:
                
                    ticker_results.append(result[0])
                    tickers_book_value.append(result[1])
                    tickers_evtoebitda.append(result[2])
                    tickers_priceToBook.append(result[3])
                    tickers_marketcap.append(result[4])
                    tickers_priceToSales.append(result[5])
                    tickers_close.append(result[6])
                    tickers_sharesoutstanding.append(result[7])
                    tickers_total_revenue.append(result[8])


    list_clubber=[ticker_results,tickers_book_value,tickers_evtoebitda,tickers_priceToBook,tickers_marketcap,tickers_priceToSales,tickers_close,tickers_sharesoutstanding,tickers_total_revenue]
    export_data=zip_longest(*list_clubber,fillvalue='')

    with open("Financials.csv",'a',encoding="ISO-8859-1",newline='') as myfile:
        wr=csv.writer(myfile)
        #wr.writerow(("Ticker","Book Value"))
        wr.writerows(export_data)
    myfile.close()

    holder=list()

    with open("Financials.csv",'r') as f:
        csvreader=csv.reader(f)
        for row in csvreader:
            holder.append(row)
            if not row[1]:
                holder.remove(row)

    with open("Financials.csv",'w',newline='') as fw:
        writer=csv.writer(fw)
        writer.writerows(holder) 
    print("Success")


#------------------------------------------------------------------------------------------------------------------------------
#The below commented piece of code is written as backup for sitation where the close prices are not being updated appropriately. 

'''ticker_names_reader=list()
ticker_book_values_reader=list()
ticker_evToEBITDA_reader=list()
ticker_priceToBook_reader=list()
ticker_marketcap=list()

with open("Auto generated Dataset\Financials.csv",'r') as csvfile:
 data = csv.DictReader(csvfile)
 print("---------------------------------")
 for row in data:
   ticker_names_reader.append(row['Ticker'])
   ticker_book_values_reader.append(row['Book Value'])
   ticker_evToEBITDA_reader.append(row['EV/EBITDA'])
   ticker_priceToBook_reader.append(row['P/BV'])
   ticker_marketcap.append(row["MarketCap"])
   

#print(ticker_names_reader)
#print(ticker_book_values_reader)

recent_closes=list() 

with open("Auto generated Dataset\Financials.csv",'r') as file1:
    csvreaderf=csv.reader(file1)
    for row in csvreaderf:
        if(row[0]=='Ticker'):
            continue 
        symbol=row[0]
        print(symbol)

        with open("Auto generated Dataset\{}.csv".format(symbol),'r') as file2:
            csv_inner_object=csv.reader(file2)
            hold=list()
            for line in csv_inner_object:
                hold.append(line[0:6])
            hold=hold[-1:]

            hold=numpy.column_stack(hold)
            close_type_nd=hold[4].astype(float)
            #print(type(close_type_nd))
            close_list=close_type_nd.tolist()
            recent_closes.extend(close_list)
    #print(recent_closes)

list_clubber_final=[ticker_names_reader,ticker_book_values_reader,ticker_evToEBITDA_reader,ticker_priceToBook_reader,recent_closes,ticker_marketcap]
export_data_complete=zip_longest(*list_clubber_final,fillvalue='')

with open("Auto generated Dataset\Financials.csv",'w',encoding="ISO-8859-1",newline='') as myfile:
    wr=csv.writer(myfile)
    wr.writerow(("Ticker","Book Value","EV/EBITDA","P/BV","Close","MarketCap"))
    wr.writerows(export_data_complete)
myfile.close()
'''