def SearchPERatio(self):
for x in range(8,1503,5):
# for x in range(8,self.soup.select('.basic2').__len__(),5):
if self.soup.select('.basic2')[x].text != '-':
if float(self.soup.select('.basic2')[x].text) <=float(self.TargetPERatio) :
QueryPrice = Share(self.soup.select('.basic2')[x-2].text+'.TW') #Query the API
if QueryPrice.get_earnings_share()!=None and float(QueryPrice.get_earnings_share())>=self.TargetEPS: # Get EPS
self.AllData.append(self.soup.select('.basic2')[x-2].text) # StockNumber
self.AllData.append(QueryPrice.get_open()) # Get FinalPrice
self.AllData.append(self.soup.select('.basic2')[x].text) # Get PERatio
self.AllData.append(QueryPrice.get_earnings_share())
def createInfos():
if db.infos.count() == 0:
print("Creating Infos!!")
with open('static/sp100.json', 'rb') as f:
ls = json.load(f)
for i in ls:
timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
symbol = Share(i['name'])
item = {
'name': i['name'],
'price': symbol.get_price(),
'time': timestamp,
'prev_close': symbol.get_prev_close(),
'open': symbol.get_open(),
'volume': symbol.get_volume(),
'pe': symbol.get_price_earnings_ratio(),
'eps': symbol.get_earnings_share(),
'price_sales': symbol.get_price_sales(),
'ebitda': symbol.get_ebitda(),
'hotness': ms.hotness_function(i['name']),
'BS': ms.bs_function(i['name'])}
db.infos.insert_one({
"name": i['name'],
"sector": i['sector'],
"data": [item]
})
print('Collection Infos Created.')
return Response('Collection Infos Created.')
def updateInfos():
print("Updating Infos!")
with open('static/sp100.json', 'rb') as f:
ls = json.load(f)
for i in ls:
timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
print (i['name'])
symbol = Share(i['name'])
item = {
'name': i['name'],
'price': symbol.get_price(),
'time': timestamp,
'prev_close': symbol.get_prev_close(),
'open': symbol.get_open(),
'volume': symbol.get_volume(),
'pe': symbol.get_price_earnings_ratio(),
'eps': symbol.get_earnings_share(),
'price_sales': symbol.get_price_sales(),
'ebitda': symbol.get_ebitda(),
'hotness': ms.hotness_function(i['name']),
'BS': ms.bs_function(i['name'])}
db.infos.update(
{"name": i['name']},
{
"$push": {"data": item}
}
)
print('Collection Infos Updated.')
return Response('Collection Infos Updated.')
def fundamentalStats(stock):
try:
stokOutput = Share(stock)
openPrice = stokOutput.get_open()
closePrice = stokOutput.get_prev_close()
dailyDelta = stokOutput.get_change()
earningsShare = stokOutput.get_earnings_share()
fiddyDay = stokOutput.get_50day_moving_avg()
priceBook = stokOutput.get_price_book()
peeEee = stokOutput.get_price_earnings_ratio()
pegRatio = stokOutput.get_price_earnings_growth_ratio()
if (float(priceBook) < 1.5 and float(peeEee) < 50 and float(pegRatio) < 2 and float(peeEee) > 0):
csvList = [stock, "open price:", openPrice, "previous close:", closePrice, "daily deltas:", dailyDelta, "earnings per share:", earningsShare, "50 day moving avg:", fiddyDay, "price/book:", priceBook, "price/earnings:", peeEee, "peg:", pegRatio, "\n"]
print (stock, "will be imported to Excel.")
stockPicks = open("picks.csv", "a", newline='')
writeCSV = csv.writer(stockPicks, dialect='excel')
for stock in csvList:
writeCSV.writerow([stock])
else:
print (stock, "does not meet criteria.")
except:
print(stock, "is missing a defined key statistic.")
def tesfile(self,event):
count =0
f = open("export.csv","r")
for row in csv.reader(f):
# print(row)
count+=1
if count >=4 and (row[2]!='-' and float(row[2])<=self.TargetPERatio):
QueryPrice=Share(row[0]+'.TW')
# volumetemp = self.InTimeObject.GetInTimeStockInfo(row[0])
# print(volumetemp)
if QueryPrice.get_earnings_share()!=None and float(QueryPrice.get_earnings_share())>=self.TargetEPS and float: #float(QueryPrice.get_earnings_share())>=self.TargetEPS:
if float(QueryPrice.get_volume())>=self.TargetVolume and float(QueryPrice.get_price())<=self.TargetPrice:
information = row[0] + row[1]+"\t" + QueryPrice.get_earnings_share() +" "+ QueryPrice.get_volume()+" " + QueryPrice.get_price()
self.ThreemenBox.insert(END,information)
if count==50:
break
def SelectStock(self):
wb = Workbook()
ws = wb.active
with open('export.csv',newline='') as f:
reader = csv.reader(f)
index = 2
title = ["代號","名稱","股價","本益比","EPS"]
for x in range(0,5,1):
ws.cell(row=1,column=x+1,value=title[x])
for row in reader:
if row!=[]:
try:
if int(row[0]) < 10000:
# print(row[2])
if "-" not in (row[2]) and float(row[2]) < 20:
# print(row)
Query = Share(row[0]+'.TW')
#print(float(Query.get_earnings_share()))
#print(float(Query.get_open()))
#print("******************")
if float(Query.get_open()) >= 20 and float(Query.get_open()) <= 90 and float(Query.get_earnings_share())>1.2:
print(row)
ws.cell(row=index , column=1 , value = row[0])
ws.cell(row=index , column=2 , value = row[1])
ws.cell(row=index , column=3 , value = Query.get_open())
ws.cell(row=index , column=4 , value = row[2])
ws.cell(row=index , column=5 , value = Query.get_earnings_share())
index = index + 1
except:
pass
wb.save("Final.xlsx")
def report_current_from_yahoo(symbol):
yahoo = Share(symbol)
price_cur = yahoo.get_price()
eps = yahoo.get_earnings_share()
pe = yahoo.get_price_earnings_ratio()
print 'yahoo: price=%s eps=%s, pe=%s'%(price_cur, eps, pe)
def stock_summary(request, symbol=None):
if symbol == None:
symbol = request.POST['symbol']
current_stock = Stock()
stock = Share(symbol)
current_stock.symbol = symbol.upper()
current_stock.price = stock.get_price()
current_stock.change = stock.get_change()
current_stock.volume = stock.get_volume()
current_stock.prev_close = stock.get_prev_close()
current_stock.stock_open = stock.get_open()
current_stock.avg_daily_volume = stock.get_avg_daily_volume()
current_stock.stock_exchange = stock.get_stock_exchange()
current_stock.market_cap = stock.get_market_cap()
current_stock.book_value = stock.get_book_value()
current_stock.ebitda = stock.get_ebitda()
current_stock.dividend_share = stock.get_dividend_share()
current_stock.dividend_yield = stock.get_dividend_yield()
current_stock.earnings_share = stock.get_earnings_share()
current_stock.days_high = stock.get_days_high()
current_stock.days_low = stock.get_days_low()
current_stock.year_high = stock.get_year_high()
current_stock.year_low = stock.get_year_low()
current_stock.fifty_day_moving_avg = stock.get_50day_moving_avg()
current_stock.two_hundred_day_moving_avg = stock.get_200day_moving_avg()
current_stock.price_earnings_ratio = stock.get_price_earnings_ratio()
current_stock.price_earnings_growth_ratio = stock.get_price_earnings_growth_ratio()
current_stock.price_sales = stock.get_price_sales()
current_stock.price_book = stock.get_price_book()
current_stock.short_ratio = stock.get_short_ratio()
date_metrics = []
url = 'http://chartapi.finance.yahoo.com/instrument/1.0/'+symbol+'/chartdata;type=quote;range=1y/csv'
page = urllib2.urlopen(url).read()
pagebreaks = page.split('\n')
for line in pagebreaks:
items = line.split(',')
if 'Company-Name:' in line:
current_stock.company_name = line[13:len(line)]
current_stock.save()
if 'values' not in items:
if len(items)==6:
hd = HistoricalData(
stock_id = Stock.objects.get(id=int(current_stock.id)).id,
date = items[0][4:6]+'/'+items[0][6:9]+'/'+items[0][0:4],
close = items[1][0:(len(items[1])-2)],
high = items[2][0:(len(items[2])-2)],
price_open = items[3][0:(len(items[3])-2)],
low = items[4][0:(len(items[4])-2)],
volume = items[5][0:-6]+","+items[5][-6:-3]+","+items[5][-3:len(items[5])])
hd.save()
date_metrics.append(hd)
del date_metrics[0]
return render(request, "stock_summary.html", {'current_stock': current_stock, 'date_metrics': date_metrics})
def getAllStockData(ticker):
'''Get a few random tickers.'''
stock = Share(ticker)
stock.refresh()
data = {
'name': stock.get_name(),
'price': stock.get_price(),
'change': stock.get_change(),
'volume': stock.get_volume(),
'prev_close': stock.get_prev_close(),
'open': stock.get_open(),
'avg_daily_volume': stock.get_avg_daily_volume(),
'stock_exchange': stock.get_stock_exchange,
'market_cap': stock.get_market_cap(),
'book_value': stock.get_book_value(),
'ebitda': stock.get_ebitda(),
'dividend_share': stock.get_dividend_share(),
'dividend_yield': stock.get_dividend_yield(),
'earnings_share': stock.get_earnings_share(),
'days_high': stock.get_days_high(),
'days_low': stock.get_days_low(),
'year_high': stock.get_year_high(),
'year_low': stock.get_year_low(),
'50day_moving_avg': stock.get_50day_moving_avg(),
'200day_moving_avg': stock.get_200day_moving_avg(),
'price_earnings_ratio': stock.get_price_earnings_ratio(),
'price_earnings_growth_ratio': stock.get_price_earnings_growth_ratio(),
'get_price_sales': stock.get_price_sales(),
'get_price_book': stock.get_price_book(),
'get_short_ratio': stock.get_short_ratio(),
'trade_datetime': stock.get_trade_datetime(),
'percent_change_from_year_high': stock.get_percent_change_from_year_high(),
'percent_change_from_year_low': stock.get_percent_change_from_year_low(),
'change_from_year_low': stock.get_change_from_year_low(),
'change_from_year_high': stock.get_change_from_year_high(),
'percent_change_from_200_day_moving_average': stock.get_percent_change_from_200_day_moving_average(),
'change_from_200_day_moving_average': stock.get_change_from_200_day_moving_average(),
'percent_change_from_50_day_moving_average': stock.get_percent_change_from_50_day_moving_average(),
'change_from_50_day_moving_average': stock.get_change_from_50_day_moving_average(),
'EPS_estimate_next_quarter': stock.get_EPS_estimate_next_quarter(),
'EPS_estimate_next_year': stock.get_EPS_estimate_next_year(),
'ex_dividend_date': stock.get_ex_dividend_date(),
'EPS_estimate_current_year': stock.get_EPS_estimate_current_year(),
'price_EPS_estimate_next_year': stock.get_price_EPS_estimate_next_year(),
'price_EPS_estimate_current_year': stock.get_price_EPS_estimate_current_year(),
'one_yr_target_price': stock.get_one_yr_target_price(),
'change_percent_change': stock.get_change_percent_change(),
'divended_pay_date': stock.get_dividend_pay_date(),
'currency': stock.get_currency(),
'last_trade_with_time': stock.get_last_trade_with_time(),
'days_range': stock.get_days_range(),
'years_range': stock.get_year_range()
}
return data
def rec(p):
yahoo = Share(p)
a = yahoo.get_prev_close()
b = yahoo.get_year_high()
c = yahoo.get_year_low()
d = yahoo.get_open()
e = yahoo.get_ebitda()
f = yahoo.get_market_cap()
g = yahoo.get_avg_daily_volume()
h = yahoo.get_dividend_yield()
i = yahoo.get_earnings_share()
j = yahoo.get_days_low()
k = yahoo.get_days_high()
l = yahoo.get_50day_moving_avg()
m = yahoo.get_200day_moving_avg()
n = yahoo.get_price_earnings_ratio()
o = yahoo.get_price_earnings_growth_ratio()
print p
print "Previous Close: ", a
print "Year High", b
print "Year Low", c
print "Open:", d
print "EBIDTA", e
print "Market Cap", f
print "Average Daily Volume", g
print "Dividend Yield", h
print "Earnings per share", i
print "Days Range:", j, "-", k
print "50 Days Moving Average", l
print "200 Days Moving Average", m
print "Price Earnings Ratio", n
print "Price Earnings Growth Ratio", o
import MySQLdb
db = MySQLdb.connect(host="127.0.0.1",
user="******",
passwd="1111",
db="stocks",
local_infile=1)
cur = db.cursor()
cur.execute(
"""
INSERT INTO stockapp_info (symbol, prev_close, year_high, year_low, open_price , ebidta, market_cap, avg_daily_vol , dividend_yield, eps , days_low ,days_high, moving_avg_50, moving_avg_200, price_earnings_ratio, price_earnings_growth_ratio)
VALUES
(%s, %s, %s, %s, %s, %s, %s,%s,%s,%s,%s,%s,%s,%s,%s,%s)
""", (p, a, b, c, d, e, f, g, h, i, j, k, l, m, n, o))
db.commit()
cur.close()
def stocks(dict_response):
message = ""
try:
query_text = dict_response['_text'].lower()
if query_text.find("stocks ") != -1:
query_text = query_text[7:]
y = Share(query_text)
message += "Trading information for " + y.get_name(
) + " (" + query_text + ") :\n"
message += "Opened: " + y.get_open() + "\n"
message += "Current: " + y.get_price() + "\n"
message += "Earnings share: " + y.get_earnings_share() + "\n"
message += "Short ratio: " + y.get_short_ratio() + "\n"
message += "Previous close: " + y.get_prev_close() + "\n"
except:
message = technical_issues()
return message
def get_company_info(ticker):
try:
s = Share(ticker)
data = {
'Market_cap': s.get_market_cap(),
'Average_volume': s.get_avg_daily_volume(),
'EPS': s.get_earnings_share(),
'Short_ratio': s.get_short_ratio(),
'PE': s.get_price_earnings_ratio(),
'PEG': s.get_price_earnings_growth_ratio(),
}
return DataFetcher._extract_company_info(data)
except YQLQueryError:
logger.error("Company info not found for {}".format(ticker))
except Exception as e:
logger.error("Unexpected error occured: {}".format(e))
return {}
def get_company_info(ticker):
try:
s = Share(ticker)
data = {
'Market_cap': s.get_market_cap(),
'Average_volume': s.get_avg_daily_volume(),
'EPS': s.get_earnings_share(),
'Short_ratio': s.get_short_ratio(),
'PE': s.get_price_earnings_ratio(),
'PEG': s.get_price_earnings_growth_ratio(),
}
return DataFetcher._extract_company_info(data)
except YQLQueryError:
logger.error("Company info not found for {}".format(ticker))
except Exception as e:
logger.error("Unexpected error occured: {}".format(e))
return {}
def rec(p):
yahoo = Share(p)
a=yahoo.get_prev_close()
b=yahoo.get_year_high()
c=yahoo.get_year_low()
d=yahoo.get_open()
e=yahoo.get_ebitda()
f=yahoo.get_market_cap()
g=yahoo.get_avg_daily_volume()
h=yahoo.get_dividend_yield()
i=yahoo.get_earnings_share()
j=yahoo.get_days_low()
k=yahoo.get_days_high()
l=yahoo.get_50day_moving_avg()
m=yahoo.get_200day_moving_avg()
n=yahoo.get_price_earnings_ratio()
o=yahoo.get_price_earnings_growth_ratio()
print p
print "Previous Close: ",a
print "Year High",b
print "Year Low",c
print "Open:",d
print "EBIDTA",e
print "Market Cap",f
print "Average Daily Volume",g
print "Dividend Yield",h
print "Earnings per share",i
print "Days Range:", j ,"-",k
print "50 Days Moving Average",l
print "200 Days Moving Average",m
print"Price Earnings Ratio", n
print"Price Earnings Growth Ratio",o
import MySQLdb
db = MySQLdb.connect(host="127.0.0.1", user="******",passwd="1111", db="stocks",local_infile = 1)
cur=db.cursor()
cur.execute ("""
INSERT INTO stockapp_info (symbol, prev_close, year_high, year_low, open_price , ebidta, market_cap, avg_daily_vol , dividend_yield, eps , days_low ,days_high, moving_avg_50, moving_avg_200, price_earnings_ratio, price_earnings_growth_ratio)
VALUES
(%s, %s, %s, %s, %s, %s, %s,%s,%s,%s,%s,%s,%s,%s,%s,%s)
""", (p,a,b,c,d,e,f,g,h,i,j,k,l,m,n,o))
db.commit()
cur.close()
def get_symbol_yahoo_stats_yql(symbols, exclude_name=False):
"""
Get the symbols' basic statistics from Yahoo Finance.
Input:
symbols - a list of symbol strings, e.g. ['AAPL']
Output: stats in Pandas DataFrame.
This function is ported from pandas_datareader/yahoo/components.py
"""
sym_list = str2list(symbols)
if sym_list == None:
return DataFrame()
# Yahoo Finance tags, refer to http://www.financialwisdomforum.org/gummy-stuff/Yahoo-data.htm
tags = ['Symbol']
if not exclude_name:
tags += ['Name']
tags += ['Exchange', 'MarketCap', 'Volume', 'AverageDailyVolume', 'BookValue', 'P/E', 'PEG', 'Price/Sales',
'Price/Book', 'EBITDA', 'EPS', 'EPSEstimateNextQuarter', 'EPSEstimateCurrentYear', 'EPSEstimateNextYear',
'OneyrTargetPrice', 'PriceEPSEstimateCurrentYear', 'PriceEPSEstimateNextYear', 'ShortRatio',
'Dividend/Share', 'DividendYield', 'DividendPayDate', 'ExDividendDate']
lines = []
for sym in sym_list:
stock = Share(sym)
line = [sym]
if not exclude_name:
line += [stock.get_name()]
line += [stock.get_stock_exchange(), str2num(stock.get_market_cap(), m2b=True),
str2num(stock.get_volume()), str2num(stock.get_avg_daily_volume()), str2num(stock.get_book_value()),
str2num(stock.get_price_earnings_ratio()), str2num(stock.get_price_earnings_growth_ratio()),
str2num(stock.get_price_sales()), str2num(stock.get_price_book()), str2num(stock.get_ebitda()),
str2num(stock.get_earnings_share()), str2num(stock.get_EPS_estimate_next_quarter()),
str2num(stock.get_EPS_estimate_current_year()), str2num(stock.get_EPS_estimate_next_year()),
str2num(stock.get_one_yr_target_price()), str2num(stock.get_price_EPS_estimate_current_year()),
str2num(stock.get_price_EPS_estimate_next_year()), str2num(stock.get_short_ratio()),
str2num(stock.get_dividend_share()), str2num(stock.get_dividend_yield()), stock.get_dividend_pay_date(),
stock.get_ex_dividend_date()]
lines.append(line)
stats = DataFrame(lines, columns=tags)
stats = stats.drop_duplicates()
stats = stats.set_index('Symbol')
return stats
def getStat(stockTicker):
StatDict = dict()
ticker = Share(stockTicker)
mktCap = ticker.get_market_cap()
if (mktCap != None and mktCap != 0):
StatDict["Market cap"] = mktCap
ebitda = ticker.get_ebitda()
if (ebitda != None and ebitda != 0):
StatDict["EBITDA"] = ebitda
peR = ticker.get_price_earnings_ratio()
if (peR != None and peR != 0):
StatDict["Price Earning Ratio"] = peR
EPS = ticker.get_earnings_share()
if (EPS != None and EPS != 0):
StatDict["EPS"] = EPS
divYield = ticker.get_dividend_yield()
if (divYield != None and divYield != 0):
StatDict["Dividend Yield"] = divYield
return StatDict
def main():
# this adds commas to all numbers greater than one thousand
locale.setlocale(locale.LC_ALL, 'en_US')
# if statement that checks for args. error/help message will appear if no args
if (len(sys.argv) == 1):
print "\nPlease supply one or more tickers. Example: python stephan_s_stock_quote.py GOOG\n"
else:
for counter in range(1, len(sys.argv)):
# this is where we fetch our stocks from
y = Share(sys.argv[counter])
# this is the output along with a message regarding the CSV file
print "\nSymbol: " + str(sys.argv[counter])
print "Company Name: " + str(y.get_name())
print "Market Capitalization: $" + str(y.get_market_cap())
print "Earnings Per Share: $" + str(
locale.format(
"%d", float(y.get_earnings_share()), grouping=True))
print "P/E Ratio: " + str(y.get_price_earnings_ratio())
print "Average Volume: " + str(
locale.format(
"%d", float(y.get_avg_daily_volume()), grouping=True))
print "Today's Volume: " + str(
locale.format("%d", float(y.get_volume()), grouping=True))
print "Today's Closing Price: $" + str(y.get_price())
print "Percent Change: " + str(y.get_percent_change()) + "\n"
print "A CSV file of your selected stock tickers has been downloaded to your computer under the name 'stocks.csv'. " + "\n"
print "The CSV file will be downloaded to the same folder that this program was stored in." + "\n"
def on_message(self, message):
print_logger.debug("Received message: %s" % (message))
if "ValidateTicker" in message:
message = message.split(":")
if len(message) != 2:
print_logger.error("Malformed ticker validation request")
self.write_message("ValidationFailed:Malformed")
return
ticker = message[1]
if validate_ticker(ticker):
self.write_message("ValidationSucceeded:%s" % ticker)
print_logger.debug("Ticker was valid")
else:
self.write_message("ValidationFailed:%s" % ticker)
print_logger.debug("Ticker was bad")
return
elif "GetCompanyName" in message:
print_logger.debug("You got here")
message = message.split(":")
company_ticker = message[1]
company_name = get_company_title(company_ticker)
self.write_message("CompanyName:%s" % company_name)
elif "GetStockData" in message:
message = message.split(":")
if len(message) != 2:
print_logger.error("Malformed Message from Client")
return
ticker = message[1]
# Get ticker information
share_data = Share(ticker)
price = share_data.get_price()
percent_change = share_data.get_change()
previous_close = share_data.get_prev_close()
open_price = share_data.get_open()
volume = share_data.get_volume()
pe_ratio = share_data.get_price_earnings_ratio()
peg_ratio = share_data.get_price_earnings_growth_ratio()
market_cap = share_data.get_market_cap()
book_value = share_data.get_price_book()
average_volume = share_data.get_avg_daily_volume()
dividend_share = share_data.get_dividend_share()
dividend_yield = share_data.get_dividend_yield()
earnings_per_share = share_data.get_earnings_share()
ebitda = share_data.get_ebitda()
fifty_day_ma = share_data.get_50day_moving_avg()
days_high = share_data.get_days_high()
days_low = share_data.get_days_low()
year_high = share_data.get_year_high()
year_low = share_data.get_year_low()
two_hundred_day_ma = share_data.get_200day_moving_avg()
# Build a string to send to the server containing the stock data
share_string = "price:" + str(price) + "|"\
+ "percentChange:" + str(percent_change) + "|"\
+ "previousClose:" + str(previous_close) + "|"\
+ "openPrice:" + str(open_price) + "|"\
+ "volume:" + str(volume) + "|"\
+ "peRatio:" + str(pe_ratio) + "|"\
+ "pegRatio:" + str(peg_ratio) + "|"\
+ "marketCap:" + str(market_cap) + "|"\
+ "bookValue:" + str(book_value) + "|"\
+ "averageVolume:" + str(average_volume) + "|"\
+ "dividendShare:" + str(dividend_share) + "|"\
+ "dividendYield:" + str(dividend_yield) + "|"\
+ "earningsPerShare:" + str(earnings_per_share) + "|"\
+ "ebitda:" + str(ebitda) + "|"\
+ "50DayMa:" + str(fifty_day_ma) + "|"\
+ "daysHigh:" + str(days_high) + "|"\
+ "daysLow:" + str(days_low) + "|"\
+ "yearHigh:" + str(year_high) + "|"\
+ "yearLow:" + str(year_low) + "|"\
+ "200DayMa:" + str(two_hundred_day_ma) + "|"
self.write_message("StockData;%s" % (share_string))
print_logger.debug("Sending Message: StockData;%s" % (share_string))
elif "GetCompanyDesc" in message:
message = message.split(":")
if len(message) != 2:
print_logger.error("Malformed Message from Client")
return
ticker = message[1]
description = update_description_oneoff(ticker)
self.write_message("CompanyDescription:%s" % str(description))
elif "GetCompanyDividend" in message and "Record" not in message:
message = message.split(":")
if len(message) != 2:
print_logger.error("Malformed Message from Client")
return
ticker = message[1]
# Grab the dividend data from dividata.com
dividend_url = "https://dividata.com/stock/%s/dividend" % ticker
# This should potentially be a
dividend_data = requests.get(dividend_url)
dividend_soup = BeautifulSoup(dividend_data.text, 'html5lib')
if len(dividend_soup.find_all("table")) > 0:
dividend_soup = dividend_soup.find_all("table")[0]
else:
dividend_soup = "<h3>No dividend history found.</h3>"
# Send this div up to the server
self.write_message("DividendHistoryData:" + str(dividend_soup))
elif "GetCompanyDividendRecord" in message:
message = message.split(":")
if len(message) != 2:
print_logger.error("Malformed Message from Client")
return
ticker = message[1]
# Get the dividend record html for the table and send it up
#dividend_record = strip_dividends(ticker, req_proxy)
#print_logger.debug("Writing message: " + str(dividend_record))
#self.write_message("DividendRecord:" + str(dividend_record))
elif "GetBollinger" in message:
message = message.split(":")
if len(message) != 2:
print_logger.error("Malformed Message from Client")
return
ticker = message[1]
# Switch into the tmp directory
old_dir = os.getcwd()
os.chdir(TEMP_DIR)
# Update the historical data for the ticker symbol
YAHOO_FINANCE_HISTORICAL_OBJECT.read_ticker_historical(ticker)
bands = BollingerBandStrategy(data_storage_dir="%s/historical_stock_data" % TEMP_DIR\
, ticker_file="%s/stock_list.txt" % TEMP_DIR, filtered_ticker_file=\
"%s/filtered_stock_list.txt" % TEMP_DIR)
# Save the graph so that we can show it on the website
bands.save_stock_chart(ticker, "%s" % TEMP_DIR)
# Also let the server know that we found an answer
result = bands.test_ticker(ticker)
if result is not None:
print_logger.debug("BB:GoodCandidate")
self.write_message("BB:GoodCandidate")
else:
print_logger.debug("BB:BadCandidate")
self.write_message("BB:BadCandidate")
elif "CheckRobinhoodLogin" in message:
print "HELLO WORLD!!! HELLO WORLD!!! HELLO WORLD!!!%s" % ROBINHOOD_INSTANCE
if ROBINHOOD_INSTANCE.is_logged_in() is True:
self.write_message("RobinhoodLoggedIn:%s" % ROBINHOOD_INSTANCE.username)
else:
self.write_message("RobinhoodNotLoggedIn")
elif "GetPosition" in message:
ticker = message.replace("GetPosition:", "")
account_positions = ROBINHOOD_INSTANCE.get_position_history(active=True)
user_owns_stock = False
position_string = ""
for position in account_positions:
# Get data about the position, including current price.
position_data = requests.get(position["instrument"])
position_data = json.loads(position_data._content)
position.update(position_data)
if position["symbol"] != ticker:
continue
quote_data = requests.get(position["quote"]);
quote_data = json.loads(quote_data._content)
position.update(quote_data)
position_string = json.dumps(position)
user_owns_stock = True
if user_owns_stock is True:
self.write_message("Position:%s" % position_string)
else:
self.write_message("Position:None")
def stock_quote_get():
print(request.args.get('symbol'))
symbol = str(request.args.get('symbol'))
# get all the relevant data from the Yahoo Finance API
stock = Share(symbol)
stock_name = stock.get_name()
stock_symbol = stock.symbol
stock_price = stock.get_price()
stock_change = stock.get_change()
stock_change_pct = stock.get_percent_change()
prev_close = stock.get_prev_close()
open = stock.get_open()
day_range = stock.get_days_range()
year_range = stock.get_year_range()
volume = stock.get_volume()
avg_volume = stock.get_avg_daily_volume()
market_cap = stock.get_market_cap()
pe_ratio = stock.get_price_earnings_ratio()
eps = stock.get_earnings_share()
dividend = stock.get_dividend_share()
dividend_yld = stock.get_dividend_yield()
dividend_ex_date = stock.get_ex_dividend_date()
yr_target = stock.get_one_yr_target_price()
historical = stock.get_historical('2017-01-01',
date.isoformat(date.today()))
# put the data into the DynamoDB database
table = dynamodb.Table('Stocks')
response = table.put_item(
Item={
'symbol': symbol,
'date': date.isoformat(date.today()),
'prev_close': prev_close,
'open': open,
'day_range': day_range,
'year_range': year_range,
'volume': volume,
'avg_volume': avg_volume,
'market_cap': market_cap,
'pe_ratio': pe_ratio,
'eps': eps,
'dividend': dividend,
'dividend_yld': dividend_yld,
'dividend_ex_date': dividend_ex_date,
'yr_target': yr_target,
})
close_history = []
for point in historical:
close_date = point['Date']
close_date = int(
time.mktime(datetime.strptime(close_date, "%Y-%m-%d").timetuple()))
close_price = point['Adj_Close']
close_price = float(close_price)
close_history.append([close_date, close_price])
return render_template("stock/stock_detail.html",
stock_name=stock_name,
stock_symbol=stock_symbol,
stock_price=stock_price,
stock_change=stock_change,
stock_change_pct=stock_change_pct,
prev_close=prev_close,
open=open,
day_range=day_range,
year_range=year_range,
volume=volume,
avg_volume=avg_volume,
market_cap=market_cap,
pe_ratio=pe_ratio,
eps=eps,
dividend=dividend,
dividend_yld=dividend_yld,
dividend_ex_date=dividend_ex_date,
yr_target=yr_target,
close_history=close_history)
class Symbol(object):
def __init__(self, symbol, s_date=None, e_date=None):
self.log=Logging()
self.name=symbol
self.created=datetime.datetime.utcnow()
self.log.info("created {}".format(self.name))
try:
self.share=Share(symbol)
except:
self.log.error("platform is offline or not connecting")
if s_date and e_date:
self.begin=s_date
self.end=e_date
try:
self.share=Share(symbol)
self.data=self.share.get_historical(self.begin, self.end)
self.log.refresh("{} data collected".format(self.name))
except:
self.log.error("platform is offline or not connecting")
def refresh_data(self, s_date=None, e_date=None):
if s_date and e_date:
try:
share=Share(self.name)
self.begin=s_date
self.end=e_date
share.get_historical(s_date, e_date)
self.log.refresh("{} data collected".format(self.name))
except:
self.log.error("platform is offline or not connecting")
def market_cap(self):
try:
self.market_cap = self.share.get_market_cap()
self.log.info("{} market cap refreshed".format(self.name))
except:
self.log.error("platform is offline or not connecting")
def earnings_per_share(self):
try:
self.eps = self.share.get_earnings_share()
self.log.info("{} eps refreshed".format(self.name))
except:
self.log.error("platform is offline or not connecting")
def moving_average_50(self):
try:
self.moving_average_50 = self.share.get_50day_moving_average()
self.log.info("{} 50 day moving ave refreshed".format(self.name))
except:
self.log.error("platform is offline or not connecting")
#implement TODO
def nday_moving_average(self, n):
try:
self.moving_average_n = None
self.log.info("{} {} day moving ave refreshed".format(self.name, n))
except:
self.log.error("platform is offline or not connecting")
def price_earnings_ratio(self):
try:
self.price_to_earnings = self.share.get_price_earnings_ratio()
self.log.info("{} price to earnings refreshed".format(self.name))
except:
self.log.error("platform is offline or not connecting")
def book_value(self):
try:
self.book = self.share.get_price_book()
self.log.info("{} book value refreshed".format(self.name))
except:
self.log.error("platform is offline or not connecting")
def year_high(self):
try:
self.year_high = self.share.get_change_from_year_high()
self.log.info("{} year high change refreshed".format(self.name))
except:
self.log.error("platform is offline or not connecting")
def year_low(self):
try:
self.year_low = self.share.get_change_from_year_low()
self.log.info("{} year low change refreshed".format(self.name))
except:
self.log.error("platform is offline or not connecting")
def target_price(self):
try:
self.year_target = self.share.get_change_from_year_high()
self.log.info("{} year target change refreshed".format(self.name))
except:
self.log.error("platform is offline or not connecting")
def year_range(self):
try:
self.year_range = self.share.get_change_from_year_high()
self.log.info("{} year range change refreshed".format(self.name))
except:
self.log.error("platform is offline or not connecting")
except: pass try: russell3000.set_value(s,'Ebitda',shy.get_ebitda()) except: pass try: russell3000.set_value(s,'Dividend share',shy.get_dividend_share()) except: pass #try: # russell3000.set_value(s,'Divident yield',shy.get_dividend_yield()) #except: # pass try: russell3000.set_value(s,'Earnings share',shy.get_earnings_share()) except: pass try: russell3000.set_value(s,'Year high',shy.get_year_high()) except: pass try: russell3000.set_value(s,'Year low',shy.get_year_low()) except: pass try: russell3000.set_value(s,'50 days MA',shy.get_50day_moving_avg()) except: pass try:
# -*- coding: utf-8 -*-
"""
Created on Thu Jul 21 15:17:46 2016
@author: SMALLON
"""
from yahoo_finance import Share
yahoo = Share('YHOO')
goog = Share('GOOG')
print(yahoo.get_ebitda())
print(yahoo.get_earnings_share())
print(yahoo.get_price_book())
print(goog.get_ebitda())
print(goog.get_earnings_share())
print(goog.get_price_book())
from yahoo_finance import Share
IBB = Share('IBB')
print(IBB.get_ebitda())
from yahoo_finance import Share
li = ['YHOO','GOOG']
yahoo = Share('YHOO')
goog = Share('GOOG')
print(yahoo.get_book_value())
for i in li:
t = Share(i)
print(i)
print(t.get_book_value())
import glob, pandas as pd
from yahoo_finance import Share
res = []
for f in glob.glob('data/*.csv'):
market = f.replace("data/", "").replace(".csv", "")
df = pd.read_csv(f)
for line in df.iterrows():
res.append((market, line[1].Symbol, line[1].Name))
for (market, symbol, name) in res:
if market == 'nyse':
x = Share(symbol)
print x.get_book_value()
print x.get_ebitda()
print x.get_earnings_share()
print x.get_price_sales()
from yahoo_finance import Share
#yahoo = Share('YHOO')
#yahoo = Share('SPXC')
yahoo = Share('TFM')
#yahoo = Share('INDU')
#INDEXSP
#yahoo = Share('NDX')
print yahoo
print yahoo.get_open()
#'36.60'
print yahoo.get_price()
print yahoo.get_price_earnings_ratio()
print 'get_dividend_share: ',yahoo.get_dividend_share()
print 'get_dividend_yield: ',yahoo.get_dividend_yield()
print 'get_earnings_share: ',yahoo.get_earnings_share()
print 'get_price_earnings_ratio: ',yahoo.get_price_earnings_ratio()
print 'get_price_earnings_growth_ratio: ',yahoo.get_price_earnings_growth_ratio()
print 'get_year_high: ',yahoo.get_year_high()
print 'get_year_low: ',yahoo.get_year_low()
print 'get_days_high: ',yahoo.get_days_high()
print 'get_days_low: ',yahoo.get_days_low()
print 'get_ebitda: ',yahoo.get_ebitda()
print 'get_book_value: ',yahoo.get_book_value()
#'36.84'
#print yahoo.get_trade_datetime()
#'2014-02-05 20:50:00 UTC+0000'
#get_avg_daily_volume()
def loadKeyStatistics (cls, companyID = 'A'):
'''
dataset
df= pd.DataFrame(columns=['marketCapital','bookValue','ebitda','dividentShare','DividentYield','earningShare',
'BookPrice','SalesPrice','earningsGrowth','earningsRatio', 'symbol', 'date'])
'''
yahoo = Share(companyID)
yahoo.refresh()
try:
a = re.search('[a-zA-Z]+', yahoo.get_market_cap())
b = re.search('[a-zA-Z]+', yahoo.get_ebitda())
if a.group(0) is not None:
p = re.split('[a-zA-Z]+', yahoo.get_market_cap())
if a.group(0) in 'B':
marketCap = float(p[0]) * 10 ** 9
elif a.group(0) in 'M':
marketCap = float(p[0]) * 10 ** 6
else:
marketCap = -1
print ('Market cap: ' + yahoo.get_market_cap())
else:
marketCap = yahoo.get_market_cap()
if b.group(0) is not None:
p = re.split('[a-zA-Z]+', yahoo.get_ebitda())
if b.group(0) in 'B':
ebitda = float(p[0]) * 10 ** 9
elif b.group(0) in 'M':
ebitda = float(p[0]) * 10 ** 6
else:
ebitda = -1
print ('Ebitda: ' +yahoo.get_ebitda())
else:
ebitda = yahoo.get_ebitda()
except (TypeError, AttributeError):
print ('Missing :' + companyID)
e = sys.exc_info()[0]
print( "<p>Error: %s</p>" % e )
ebitda = -1.0
marketCap = -1.0
try:
company = LoadYahooFinance(symbol = companyID, marketCap = marketCap, bookValue = float(yahoo.get_book_value()), ebitda = ebitda,
dividentShare = float(yahoo.get_dividend_share()), dividentYield = float(yahoo.get_dividend_yield()), earningShare = float(yahoo.get_earnings_share()),
bookPrice = float(yahoo.get_price_book()), salesPrice = float(yahoo.get_price_sales()), earningsGrowth = float(yahoo.get_price_earnings_growth_ratio()),
earningRatio = float(yahoo.get_price_earnings_ratio()))
return company
except TypeError:
print ('Missing :' + companyID)
e = sys.exc_info()[0]
print( "<p>Error: %s</p>" % e )
print "The CSV file will be downloaded to the same folder that this program was stored in." + "\n"
# code that creates the CSV file
with open('stocks.csv', 'w') as fp:
outputFile = csv.writer(fp)
data1 = [[
'Symbol', 'Company Name', 'Market Capitalization',
'Earnings Per Share', 'P/E Ratio', 'Average Volume', 'Today\'s Volume',
'Today\'s Closing Price', 'Percent Change'
]]
outputFile.writerows(data1)
for counter in range(1, len(sys.argv)):
y = Share(sys.argv[counter])
data2 = [[
str(sys.argv[counter]),
str(y.get_name()),
str(y.get_market_cap()),
str(y.get_earnings_share()),
str(y.get_price_earnings_ratio()),
str(y.get_avg_daily_volume()),
str(y.get_volume()),
str(y.get_price()),
str(y.get_percent_change())
]]
outputFile.writerows(data2)
if __name__ == '__main__':
main()
print getopen if myargs.getbook is True: getbook = stock.get_book_value() print getbook if myargs.dividendshare is True: getdiv = stock.get_dividend_share() print getdiv if myargs.dividendyield is True: dividendyield = stock.get_dividend_yield() print dividendyield if myargs.eps is True: eps = stock.get_earnings_share() print eps if myargs.dayh is True: dayhigh = stock.get_days_high() print dayhigh if myargs.dayl is True: daylow = stock.get_days_low() print daylow if myargs.yearhigh is True: yearhigh = stock.get_year_high() print yearhigh if myargs.yearlow is True:
def on_message(self, message):
print_logger.debug("Received message: %s" % (message))
self.write_message("Test Message")
if "ValidateTicker" in message:
message = message.split(":")
if len(message) != 2:
print_logger.error("Malformed ticker validation request")
self.write_message("ValidationFailed:Malformed")
return
ticker = message[1]
# The file I have stored didn't end up being a good validation
# option as it does not contain a complete list of all
# securities. I have to acquire the data from yahoo
# finance anyway, so just use that. The Share function
# call will throw a NameError exception if the ticker doesn't exist
# isValid = current_stock_list.is_valid_stock(ticker)
isValid = True
try:
test = Share(str(ticker))
if test.get_price() is None:
isValid = False
except NameError:
isValid = False
if isValid:
self.write_message("ValidationSucceeded:%s" % ticker)
print_logger.debug("Ticker was valid")
else:
self.write_message("ValidationFailed:%s" % ticker)
print_logger.debug("Ticker was bad")
return
elif "GetCompanyName" in message:
print_logger.debug("You got here")
message = message.split(":")
company_ticker = message[1]
company_name = ""
try:
company_info="../task_1/google_search_program/cleaned_data/" + company_ticker + "/company_info"
company_name = " "
f = open(company_info, "r")
line = f.readlines()
company_name = line[0].split(",")
company_name = company_name[0]
company_name = company_name.title()
if '(' not in company_name:
company_name = company_name + " (%s)" % company_ticker
except Exception:
company_name = get_company_title_proxied(company_ticker)
self.write_message("CompanyName:%s" % company_name)
elif "ExecuteQuery" in message:
message = message.split(":")
if len(message) != 2:
print_logger.error("Malformed input query")
self.write_message("QueryResult:Error")
data = current_solr_object.issue_query(str(message[1]))
data = current_solr_object.recover_links(data)
final_string = "QueryResult"
for link in data:
final_string = final_string + ":" + str(link)
self.write_message(final_string)
elif "GetStockData" in message:
message = message.split(":")
if len(message) != 2:
print_logger.error("Malformed Message from Client")
return
ticker = message[1]
# Get ticker information
share_data = Share(ticker)
price = share_data.get_price()
percent_change = share_data.get_change()
previous_close = share_data.get_prev_close()
open_price = share_data.get_open()
volume = share_data.get_volume()
pe_ratio = share_data.get_price_earnings_ratio()
peg_ratio = share_data.get_price_earnings_growth_ratio()
market_cap = share_data.get_market_cap()
book_value = share_data.get_price_book()
average_volume = share_data.get_avg_daily_volume()
dividend_share = share_data.get_dividend_share()
dividend_yield = share_data.get_dividend_yield()
earnings_per_share = share_data.get_earnings_share()
ebitda = share_data.get_ebitda()
fifty_day_ma = share_data.get_50day_moving_avg()
days_high = share_data.get_days_high()
days_low = share_data.get_days_low()
year_high = share_data.get_year_high()
year_low = share_data.get_year_low()
two_hundred_day_ma = share_data.get_200day_moving_avg()
# Build a string to send to the server containing the stock data
share_string = "price:" + str(price) + "|"\
+ "percentChange:" + str(percent_change) + "|"\
+ "previousClose:" + str(previous_close) + "|"\
+ "openPrice:" + str(open_price) + "|"\
+ "volume:" + str(volume) + "|"\
+ "peRatio:" + str(pe_ratio) + "|"\
+ "pegRatio:" + str(peg_ratio) + "|"\
+ "marketCap:" + str(market_cap) + "|"\
+ "bookValue:" + str(book_value) + "|"\
+ "averageVolume:" + str(average_volume) + "|"\
+ "dividendShare:" + str(dividend_share) + "|"\
+ "dividendYield:" + str(dividend_yield) + "|"\
+ "earningsPerShare:" + str(earnings_per_share) + "|"\
+ "ebitda:" + str(ebitda) + "|"\
+ "50DayMa:" + str(fifty_day_ma) + "|"\
+ "daysHigh:" + str(days_high) + "|"\
+ "daysLow:" + str(days_low) + "|"\
+ "yearHigh:" + str(year_high) + "|"\
+ "yearLow:" + str(year_low) + "|"\
+ "200DayMa:" + str(two_hundred_day_ma) + "|"
self.write_message("StockData;%s" % (share_string))
print_logger.debug("Sending Message: StockData;%s" % (share_string))
elif "GetCompanyDesc" in message:
message = message.split(":")
if len(message) != 2:
print_logger.error("Malformed Message from Client")
return
ticker = message[1]
# Read in the company description
description = ""
try:
f = open("../task_1/google_search_program/cleaned_data/%s/company_description" % str(ticker), "r")
description = f.read()
except Exception:
# If the file does not exist, get the data manually
description = update_description_oneoff(ticker)
self.write_message("CompanyDescription:%s" % str(description))
elif "GetCompanyDividend" in message and "Record" not in message:
message = message.split(":")
if len(message) != 2:
print_logger.error("Malformed Message from Client")
return
ticker = message[1]
# Grab the dividend data from dividata.com
dividend_url = "https://dividata.com/stock/%s/dividend" % ticker
# This should potentially be a
dividend_data = requests.get(dividend_url)
dividend_soup = BeautifulSoup(dividend_data.text, 'html5lib')
if len(dividend_soup.find_all("table")) > 0:
dividend_soup = dividend_soup.find_all("table")[0]
else:
dividend_soup = "<h3>No dividend history found.</h3>"
# Send this div up to the server
self.write_message("DividendHistoryData:" + str(dividend_soup))
elif "GetCompanyDividendRecord" in message:
message = message.split(":")
if len(message) != 2:
print_logger.error("Malformed Message from Client")
return
ticker = message[1]
# Get the dividend record html for the table and send it up
dividend_record = strip_dividends(ticker, req_proxy)
print_logger.debug("Writing message: " + str(dividend_record))
self.write_message("DividendRecord:" + str(dividend_record))
elif "GetBollinger" in message:
message = message.split(":")
if len(message) != 2:
print_logger.error("Malformed Message from Client")
return
ticker = message[1]
# Get the bollinger band history along with the 5 day moving average
close, lower_band, five_day_ma = calculate_bands(ticker)
last_5_days_5_day_ma = []
last_5_days_bb = []
last_5_days_close = []
for i in range(0, 5):
last_5_days_5_day_ma.append(five_day_ma[i])
last_5_days_bb.append(lower_band[i])
last_5_days_close.append(close[i])
condition_1 = False
condition_2 = False
# Condition 1: Has the stock price at close been below the lower bollinger band
# at market close within the last 5 days
for i in range(0, 5):
if last_5_days_close[i] < last_5_days_bb[i]:
condition_1 = True
# Condition 2: Has the current stock price been above the 5 day moving average sometime in the last 3 days
for i in range(0, 3):
if last_5_days_close[i] > last_5_days_5_day_ma[i]:
condition_2 = True
if condition_1 is True and condition_2 is True:
self.write_message("BB:GoodCandidate")
else:
self.write_message("BB:BadCandidate")
elif "GetSentiment" in message:
message = message.split(":")
if len(message) != 2:
print_logger.error("Malformed Message from Client")
return
ticker = message[1]
# Lists of sentiment based words
good_words = ["buy", "bull", "bullish", "positive", "gain", "gains", "up"]
bad_words = ["sell", "bear", "bearish", "negative", "loss", "losses", "down"]
DATA_DIRECTORY = "../task_1/google_search_program/cleaned_data/%s" % ticker.upper()
positive_file_stats = []
negative_file_stats = []
positive_files = 0
negative_files = 0
neutral_files = 0
trump_count = 0
files_examined = 0
for root, dirs, files in os.walk(DATA_DIRECTORY):
path = root.split(os.sep)
print((len(path) - 1) * '---', os.path.basename(root))
for file in files:
if "article" in file:
f = open('/'.join(path) + '/' + file)
title = f.readline()
article_text = " ".join(f.readlines())
if article_text.count("trump") > 0:
trump_count = trump_count + 1
positive_word_count = 0
negative_word_count = 0
files_examined = files_examined + 1
for word in good_words:
if word in article_text:
positive_word_count = positive_word_count + article_text.count(word)
print "Word: %s, %s" % (word, article_text.count(word))
for word in bad_words:
if word in article_text:
negative_word_count = negative_word_count + article_text.count(word)
if positive_word_count > negative_word_count:
positive_ratio = float(positive_word_count) / float(negative_word_count + positive_word_count)
if positive_ratio > 0.7:
positive_files = positive_files + 1
positive_file_stats.append((positive_word_count, negative_word_count))
else:
neutral_files = neutral_files + 1
elif positive_word_count == negative_word_count:
neutral_files = neutral_files + 1
else:
negative_ratio = float(negative_word_count) / float(negative_word_count + positive_word_count)
if negative_ratio > 0.7:
negative_files = negative_files + 1
negative_file_stats.append((positive_word_count, negative_word_count))
else:
neutral_files = neutral_files + 1
print_logger.debug("Sentiment:" + str(positive_files) + ":" + str(negative_files) +\
":" + str(neutral_files) + ":" + str(trump_count) + ":" + str(files_examined))
self.write_message("Sentiment:" + str(positive_files) + ":" + str(negative_files) +\
":" + str(neutral_files) + ":" + str(trump_count) + ":" + str(files_examined))
# Determine functionality
from yahoo_finance import Share
tesla = Share('TSLA')
print tesla.get_price()
print tesla.get_market_cap()
print "get_book_value:", tesla.get_book_value()
print "get_ebitda:", tesla.get_ebitda()
print "get_dividend_share:", tesla.get_dividend_share()
print "get_dividend_yield:", tesla.get_dividend_yield()
print "get_earnings_share:", tesla.get_earnings_share()
print "get_days_high:", tesla.get_days_high()
print "get_days_low:", tesla.get_days_low()
print "get_year_high:", tesla.get_year_high()
print "get_year_low:", tesla.get_year_low()
print "get_50day_moving_avg:", tesla.get_50day_moving_avg()
print "get_200day_moving_avg:", tesla.get_200day_moving_avg()
print "get_price_earnings_ratio:", tesla.get_price_earnings_ratio()
print "get_price_earnings_growth_ratio:", tesla.get_price_earnings_growth_ratio(
)
print "get_price_sales:", tesla.get_price_sales()
print "get_price_book:", tesla.get_price_book()
print "get_short_ratio:", tesla.get_short_ratio()
print "get_trade_datetime:", tesla.get_trade_datetime()
# "a:", print tesla.get_historical(start_date, end_date)
# "a:", print tesla.get_info()
print "get_name:", tesla.get_name()
print "refresh:", tesla.refresh()
print "get_percent_change_from_year_high:", tesla.get_percent_change_from_year_high(
)
import glob, pandas as pd
from yahoo_finance import Share
res = []
for f in glob.glob('data/*.csv'):
market = f.replace("data/","").replace(".csv","")
df = pd.read_csv(f)
for line in df.iterrows():
res.append((market, line[1].Symbol, line[1].Name))
for (market,symbol,name) in res:
if market=='nyse':
x = Share(symbol)
print x.get_book_value()
print x.get_ebitda()
print x.get_earnings_share()
print x.get_price_sales()
def populateStock(shareString, sqlConnection):
timedout = True
curShare = None
while timedout:
try:
curShare = Share(shareString)
timedout=False
except:
timedout=True
time.sleep(5)
print('Stock querry timed out, retrying')
if curShare.get_price() == 0:
return
detailShare = None
try:
detailShare = stockretriever.get_current_info([shareString])
pprint(detailShare)
except:
print('Yql error caught, continuing excluding analyst estimates for ' + shareString)
EPSEstimateNextYear = None
EPSEstimateCurrentYear = None
EPSEstimateNextQuarter = None
if(detailShare != None):
if(detailShare['PriceBook']==None):
print('No data on this stock, will not populate table.')
return
if(detailShare['EPSEstimateNextYear']!=None):
EPSEstimateNextYear = float(detailShare['EPSEstimateNextYear'])
if(detailShare['EPSEstimateCurrentYear']!=None):
EPSEstimateCurrentYear = float(detailShare['EPSEstimateCurrentYear'])
if(detailShare['EPSEstimateNextQuarter']!=None):
EPSEstimateNextQuarter = float(detailShare['EPSEstimateNextQuarter'])
sqlStatement = 'default statement'
if EPSEstimateNextYear != None and EPSEstimateCurrentYear != None and EPSEstimateNextQuarter != None:
sqlStatement = ("REPLACE INTO SM_Stock_Data \n"
"VALUES('%s',\"%f\",%i,%i,\"%f\",\"%f\",'%s',\"%f\",\"%f\",\"%f\");" % (shareString, moneyStringToFloat(curShare.get_price()), moneyStringToInt(curShare.get_volume()), moneyStringToInt(curShare.get_market_cap()), moneyStringToFloat(curShare.get_earnings_share()), moneyStringToFloat(curShare.get_dividend_share()), curShare.get_trade_datetime(), EPSEstimateNextYear, EPSEstimateCurrentYear, EPSEstimateNextQuarter))
else:
sqlStatement = ("REPLACE INTO SM_Stock_Data (ticker,price,volume,mktcap,eps,dividend,refreshdate) \n"
"VALUES('%s',\"%f\",%i,%i,\"%f\",\"%f\",'%s');" % (shareString, moneyStringToFloat(curShare.get_price()), moneyStringToInt(curShare.get_volume()), moneyStringToInt(curShare.get_market_cap()), moneyStringToFloat(curShare.get_earnings_share()), moneyStringToFloat(curShare.get_dividend_share()), curShare.get_trade_datetime()))
print('Populating stock with command: ' + sqlStatement)
sqlConnection.execute(("REPLACE INTO SM_Stock \n"
"VALUES('%s','%s')") % (shareString, doubleApost(nameForTicker(shareString))))
sqlConnection.execute(sqlStatement)
def write_technical_files(stock_code, start_time, end_time):
# """ Experiment on quandl """
# print('quandl data')
# mydata = quandl.get("FRED/GDP")
# print(mydata)
# print('hello')
# data = quandl.get("WIKI/FB.11", start_date="2014-01-01", end_date="2014-12-31", collapse="monthly", transform="diff")
# print(data)
stock = Share(stock_code)
print('stock.get_info()')
print(stock.get_info())
print('get_price()')
print(stock.get_price())
print('get_change()')
print(stock.get_change())
print('get_stock_exchange()')
print(stock.get_stock_exchange())
print('get_market_cap()')
print(stock.get_market_cap())
print('get_book_value()')
print(stock.get_book_value())
print('get_ebitda()')
print(stock.get_ebitda())
print('get_dividend_share()')
print(stock.get_dividend_share())
print('get_dividend_yield()')
print(stock.get_dividend_yield())
print('get_earnings_share()')
print(stock.get_earnings_share())
print('get_50day_moving_avg()')
print(stock.get_50day_moving_avg())
print('get_200day_moving_avg()')
print(stock.get_200day_moving_avg())
print('get_price_earnings_ratio()')
print(stock.get_price_earnings_ratio())
print('get_price_earnings_growth_ratio()')
print(stock.get_price_earnings_growth_ratio())
print('get_price_sales()')
print(stock.get_price_sales())
print('get_price_book()')
print(stock.get_price_book())
print('get_short_ratio()')
print(stock.get_short_ratio())
print('historical_data')
print(stock.get_historical(start_time, end_time))
historical_data = stock.get_historical(start_time, end_time)
info_text = "Symbol\t" + "Stock Exchange\t" + "Price\t" + "Market Cap\t" + "Book Value\t" + "EBITDA\t" + "50d Moving Avg\t" + "100d Moving Avg\n"
info_text += str(stock.get_info()['symbol']) + "\t" + str(stock.get_stock_exchange()) + "\t" + str(stock.get_price()) + "\t" + str(stock.get_market_cap()) + "\t" + str(stock.get_book_value()) + "\t";
info_text += str(stock.get_ebitda()) + "\t" + str(stock.get_50day_moving_avg()) + "\t" + str(stock.get_200day_moving_avg()) + "\n";
info_directory = '/data/info.tsv'
write_to_file(info_directory, info_text)
high_low_text = "date\t" + "High\t" + "Low\n"
open_close_text = "date\t" + "Open\t" + "Close\n"
volume_text = "date\t" + "Volume\n"
for index, value in enumerate(historical_data):
date = str(historical_data[len(historical_data) - 1 - index]['Date'])
date = date.replace('-','')
stock_high = str(historical_data[len(historical_data) - 1 - index]['High'])
stock_low = str(historical_data[len(historical_data) - 1 - index]['Low'])
stock_open = str(historical_data[len(historical_data) - 1 - index]['Open'])
stock_close = str(historical_data[len(historical_data) - 1 - index]['Close'])
stock_volume = str(int(historical_data[len(historical_data) - 1 - index]['Volume']) / 1000)
high_low_text += date + "\t" + stock_high + "\t" + stock_low + "\n"
open_close_text += date + "\t" + stock_open + "\t" + stock_close + "\n"
volume_text += date + "\t" + stock_volume + "\n"
high_low_directory = '/data/highlow.tsv'
open_close_directory = '/data/openclose.tsv'
volume_directory = '/data/volume.tsv'
write_to_file(high_low_directory, high_low_text)
write_to_file(open_close_directory, open_close_text)
write_to_file(volume_directory, volume_text)
ratio_text = "name\t" + "value\n"
if stock.get_change() != None:
name = "Change"
value = str(stock.get_change())
ratio_text += name + "\t" + value + "\n"
if stock.get_dividend_share() != None:
name = "Dividend Share"
value = str(stock.get_dividend_share())
ratio_text += name + "\t" + value + "\n"
if stock.get_dividend_yield() != None:
name = "Divident Yield"
value = str(stock.get_dividend_yield())
ratio_text += name + "\t" + value + "\n"
if stock.get_earnings_share() != None:
name = "Earning Share"
value = str(stock.get_earnings_share())
ratio_text += name + "\t" + value + "\n"
if stock.get_price_earnings_ratio() != None:
name = "Price Earning"
value = str(stock.get_price_earnings_ratio())
ratio_text += name + "\t" + value + "\n"
if stock.get_price_earnings_growth_ratio() != None:
name = "Price Earning Growth"
value = str(stock.get_price_earnings_growth_ratio())
ratio_text += name + "\t" + value + "\n"
if stock.get_price_sales() != None:
name = "Price Sales"
value = str(stock.get_price_sales())
ratio_text += name + "\t" + value + "\n"
if stock.get_price_book() != None:
name = "Price Book"
value = str(stock.get_price_book())
ratio_text += name + "\t" + value + "\n"
if stock.get_short_ratio() != None:
name = "Short"
value = str(stock.get_short_ratio())
ratio_text += name + "\t" + value + "\n"
ratio_directory = '/data/ratio.tsv'
write_to_file(ratio_directory, ratio_text)
def get_stock_info():
share = Share('AAPL')
opening = share.get_open()
dividend_yeild = share.get_earnings_share()
print share.get_short_ratio()
