def sell():
if 'username' in session:
# Get symbol name
s = request.args.get('symbol')
# recreate users stock information
if not models.new_stock:
models.Users.reload_user()
# symbol name is valid
if s is not None and s != '':
symbol = Share(s)
if symbol.get_price() is None:
return render_template('apology.html', message=['Something went wrong. Please try again.'])
else:
# Get user's stock info
holding = models.Stockholding.objects.get(username=session['username'], symbol=s)
amount_to_add = int(holding.shares) * float(symbol.get_price())
# add value of shares to user's cash
models.Users.objects(username=session['username']).update(inc__cash=amount_to_add)
# log transaction
transaction = models.Transaction(username=session['username'], date=time.strftime("%d/%m/%Y"), \
type=models.Transaction.SELL, symbol=s, shares=holding.shares)
transaction.save()
holding.delete() # Remove stock
flash('Stock sold successfully', 'text-success')
models.Users.reload_user()
print models.new_stock
return redirect('portfolio')
return render_template('sell.html', stocks=models.new_stock)
return render_template('apology.html', message=['Log In to see this page'])
def get_item_info(self, item):
name = ""
if (item >= self.top):
yahoo = Share(self.updated_list[item])
name = self.updated_list[item]
else:
yahoo = Share(self.list_indexes[item])
name = self.list_indexes[item]
string = name + " " + str(yahoo.get_price()) + " " + str(
yahoo.get_change())
symbol_info = []
symbol_info.append(name)
symbol_info.append(str(yahoo.get_price()))
symbol_info.append(str(yahoo.get_change()))
symbol_info.append(str(yahoo.get_trade_datetime()))
if "None" in symbol_info[2]:
symbol_info[2] = symbol_info[2][:-4]
for i in range(0, len(symbol_info)):
if i == 3:
font = pygame.font.Font(self.display_font,
self.font_size_lower)
else:
font = pygame.font.Font(self.display_font, self.font_size)
font.set_bold(self.bold)
symbol_info[i] = (symbol_info[i], font.size(symbol_info[i]))
return symbol_info
def get_quote(symbol):
share = Share(symbol)
if not share.get_price():
return {}
change_f = float(share.get_change())
change_str = '+%.02f' % change_f if change_f >= 0 else '%.02f' % change_f
change_percent_f = change_f / float(share.get_open()) * 100
change_percent = '+%.02f' % change_percent_f if change_percent_f >= 0 else '%.02f' % change_percent_f
return {
'price': share.get_price(),
'change': change_str,
'change_percent': change_percent,
'open_price': share.get_open(),
'market_cap': share.get_market_cap(),
'year_low': share.get_year_low(),
'year_high': share.get_year_high(),
'day_low': share.get_days_low(),
'day_high': share.get_days_high(),
'volume': share.get_volume(),
'pe_ratio': share.get_price_earnings_ratio() or '-'
}
def getTodaysPortfolio(portfolio):
port_today = []
for stock in portfolio:
ticker = stock.Ticker
stock_yhoo = Share(ticker)
port_today.append({
"id":
stock.id,
"Ticker":
ticker,
"CurrentPrice":
stock_yhoo.get_price(),
"pct_change":
stock_yhoo.get_change(),
"Quote_Each":
stock.Quote_Each,
"Number_of_Shares":
stock.Number_of_Shares,
"Value":
stock.Value,
"Today_Value":
float(stock.Number_of_Shares) * float(stock_yhoo.get_price()),
"Date_Time":
stock.Date_Time,
})
return port_today
def recentdata(companyname):
try:
companydata = Share(companyname)
print "This morning, it opened for $" + companydata.get_open() + ", and right now is at $" + companydata.get_price() + "."
if companydata.get_open() > companydata.get_price():
difference = float(companydata.get_open()) - float(companydata.get_price())
if len(str(difference)) < 3:
print "Since this morning, the price has fallen by $" + str(difference) + "0"
else:
print "Since this morning, the price has fallen by $" + str(difference)
elif companydata.get_open() < companydata.get_price():
difference = float(companydata.get_price()) - float(companydata.get_open())
if len(str(difference)) < 3:
print "Since this morning, the price has risen by $" + str(difference) + "0"
else:
print "Since this morning, the price has risen by $" + str(difference)
print ""
selection = raw_input(
"Would you like some info about what the stock has been like in the past few days? Yes/No: ")
if str.lower(selection) == "no":
end()
elif str.lower(selection) == "yes":
print "Okay, please wait a moment"
except (RuntimeError, TypeError, NameError):
print "Whoops, something went wrong there. Are you sure you entered a valid company abbreviation?"
finally:
longterm(companyname)
def get_info_share(symbol): #print symbol #symbol = sys.argv[1] share1 = Share(symbol) try: share1.get_info() if not share1:# is None: print symbol," is not a valid share symbol. \nPlease re-run the program with correct share symbol" else: #print "here" print(datetime.datetime.now()) company = get_symbol(symbol) print company print share1.get_price() print share1.get_change() #print share1.get_short_ratio() open = share1.get_open() price = share1.get_price() percChange = float(Decimal(price) - Decimal(open))/float(Decimal(open)) print "%f" % percChange +"%" except Exception as e: print symbol," is not a valid share symbol. \nPlease re-run the program with correct share symbol" except AttributeError as ae: print "att error" except yahoo_finance.YQLQueryError as ye: print symbol," is not a valid share symbol in ye error. \nPlease re-run the program with correct share symbol"
def buy(self, symbol, trader, share):
stock = Share(symbol)
price = stock.get_price()
trade_time = time.strftime("%Y-%m-%d %H:%M:%S")
print stock.get_price()
self.traderDAO.insertValues(symbol, "B", trader, share, trade_time,
price)
def move_target_realworldmapping():
REAL_WORLD_ENVIRONMENT = "stocks"
# REAL_WORLD_ENVIRONMENT = "stocks" # pulls stocks/indices datastream from Yahoo Finance
if (REAL_WORLD_ENVIRONMENT == "stocks"):
#print("mapping to Yahoo Finance datastreams")
from yahoo_finance import Share
ftse = Share('^FTSE')
ftse_price = float(ftse.get_price())
#print (ftse_price)
ndx = Share('^NDX')
ndx_price = float(ndx.get_price())
#print (ndx_price)
n225 = Share('^N225')
n225_price = float(n225.get_price())
#print (n225_price)
#ftse.refresh()
#ndx.refresh()
#n225.refresh()
params['DYNAMIC_ENVIRONMENT_TARGET'] = (ftse_price, ndx_price,
n225_price)
else:
# don't move_target
print(
"Error, in the fitness function move_target_realworldmapping() the REAL_WORLD_ENVIRONMENT is not implmented!"
)
def displayFinance(self, yearStart, yearEnd):
yahoo = Share(self.companyCode)
#declare
textReturn = ""
textReturn += "Opening price: " + str(yahoo.get_open()) + '\n'
textReturn += "Current price: " + str(yahoo.get_price()) + '\n'
textReturn += "Dividend Share: " + str(
yahoo.get_dividend_share()) + '\n'
textReturn += "Year High: " + str(yahoo.get_year_high()) + '\n'
textReturn += "Year Low: " + str(yahoo.get_year_low()) + '\n'
self.jsonObj.append({
"openPrice": str(yahoo.get_open()),
"currPrice": str(yahoo.get_price()),
"dividendPrice": str(yahoo.get_dividend_share()),
"yearHigh": str(yahoo.get_year_high()),
"yearLow": str(yahoo.get_year_low())
})
#historical data returns a jSON object
jsonHistorical = yahoo.get_historical(
str(yearStart) + '-04-25',
str(yearEnd) + '-04-29')
textReturn += "Historical Data: " + '\n'
#To limit the number of historical datapoints sent
numHist = 0
maxHist = 10
for dict in jsonHistorical:
numHist += 1
if numHist < maxHist:
textReturn += "For year " + dict['Date'] + " High was: " + dict[
'High'] + " Low was: " + dict['Low'] + '\n'
#self.jsonObj[0][dict['Date'] + "High"] = dict['High']
#self.jsonObj[0][dict['Date'] + "Low"] = dict['Low']
self.jsonObj.append({
"Highd": dict['Date'],
"Lowd": dict['Date'],
"Highp": dict['High'],
"Lowp": dict['Low']
})
if textReturn == "":
self.jsonObj.append({"success": "false"})
else:
self.jsonObj.append({"success": "true"})
return textReturn
def getPrice(share): for x in range(0, 30): price = Share(share) print price.get_price() stocks_price.append(price.get_price) time.sleep(60) print 'Share information recieved'
def print_stats(ticker,is_trading_hours):
stock = Share(ticker)
stock.refresh()
if(is_trading_hours == True):
print("Current Price: $" + stock.get_price() + "\n--------------------------------------")
else:
print("Previous Close: $" + stock.get_prev_close())
print("Opening Price: $" + stock.get_open())
print("Current Price: $" + stock.get_price() + "\n--------------------------------------")
def get_stock_prices(stock_symbol_list):
"""Returns a string that includes a list of stocks and their prices"""
stock_response_line_list = []
for stock_symbol in stock_symbol_list:
stock = Share(stock_symbol)
stock_response_line = stock_symbol + ": " + (
stock.get_price() if stock.get_price() is not None else "Not Found")
stock_response_line_list.append(stock_response_line)
return "\n".join(stock_response_line_list)
def andrews_algo():
"""
Various metrics for a given ticker
:param tickers:
:return:
"""
global ticker_list
for ticker in ticker_list:
stock = Share(ticker)
print(line_separator)
print(stock.get_name())
print("Current Price: " + str(stock.get_price()))
# Dollar volume == momentum
dollar_volume = float(stock.get_price()) * float(stock.get_volume())
if dollar_volume > 20000000.0:
print("High Trading Liquidity, dollar volume: " + num_to_short_text(dollar_volume))
else:
print("Low Trading Liquidity, dollar volume: " + num_to_short_text(dollar_volume))
# PEG is apparently inaccurate need to implement checks/also check conditional logic
peg = float(stock.get_price_earnings_growth_ratio())
if peg > 1.5:
print("Undervalued, Large Growth Potential, PEG ratio: " + str(peg))
elif peg < 1:
print("Overvalued, High Risk Potential, PEG ratio: " + str(peg))
else:
print("Fairly Priced, Low Growth Potential, PEG ratio: " + str(peg))
# TODO: ROE (increasing ROE signals regular profit generation)
# TODO: Beta value to determine volatility
# TODO: Actual EPS vs next quarter estimated EPS (to predict imminent stock jump or crash)
# TODO: Formula to calculate future theoretical earnings
# Converting textual numbers to floats
market_cap = short_text_to_float(stock.get_market_cap())
if market_cap > 200000000000.0:
print("Mega Cap")
elif market_cap > 10000000000.0:
print("Large Cap")
elif market_cap > 2000000000.0:
print("Mid Cap")
elif market_cap > 300000000.0:
print("Small Cap")
elif market_cap > 50000000.0:
print("Micro Cap")
else:
print("Nano Cap")
print("Market Capitalization: " + num_to_short_text(market_cap))
print(line_separator)
def get_initial_company_info(self):
"""Gets the initial information for each company"""
company_dict = tf.open_json()
driver = webdriver.PhantomJS(
service_args=['--ignore-ssl-errors=true', '--ssl-protocol=any'])
url = "https://uk.finance.yahoo.com/"
for company in company_dict:
driver.get(url)
# Gets symbol for company
if company_dict[company]["Symbol"] == "unknown":
time.sleep(3) # allows time for page to load
try:
elem = driver.find_element_by_name("p")
elem.send_keys(company)
elem.send_keys(Keys.RETURN)
time.sleep(3) # allows time for the page to load
symbol = driver.current_url.split("=")[-1]
company_dict[company]["Symbol"] = symbol
except Exception:
pass
# Gets initial share price
if company_dict[company]["Initial-share-price"] == 1:
try:
yahoo = Share(company_dict[company]["Symbol"])
share = yahoo.get_price()
company_dict[company]["Initial-share-price"] = float(share)
except Exception:
pass
# current-share-price
if company_dict[company]["Current-share-price"] == 1:
try:
yahoo = Share(company_dict[company]["Symbol"])
share = yahoo.get_price()
company_dict[company]["Current-share-price"] = float(share)
except Exception:
pass
# writes info back into the monitor json
tf.write_to_json(company_dict)
def check_sell(self):
#UNCOMMENT WHEN USING ACTUAL DATA
if self.owned_shares == 0:
return False
share = Share(self.code)
current_price_u = share.get_price()
if current_price_u is None:
self.log('Current Price is None for Stock')
return 0
current_price = float(current_price_u)
#UNCOMMENT WHEN USING ACTUAL DATA
if self.bought_value < current_price:
return False
avg50 = self.get_short_moving_avg()
avg200 = self.get_long_moving_avg()
if avg50 < avg200:
#trend change, buy
sell(self, self.owned_shares,current_price)
return True
return False
def check_buy(self):
#one-time buy
if self.owned_shares != 0:
return False
share = Share(self.code)
avg50 = self.get_short_moving_avg()
avg200 = self.get_long_moving_avg()
if avg50 == -1.0 or avg200 == -1.0:
self.log('Short or Long moving average cannot be obtained due to yahoo API error')
return 0
current_price_u = share.get_price()
if current_price_u is None:
self.log('Current Price is None for Stock')
return 0
current_price = float(current_price_u)
if avg50 > avg200:
#trend change, buy
buy_count = self.how_many_shares_to_buy(current_price)
if buy_count != 0:
if buy(self, buy_count, current_price) == True:
self.owned_shares = buy_count
self.bought_value = float(current_price * self.owned_shares)
return self.owned_shares
return 0
def __init__(self, symbol, priceBought, countBought, dateBought):
self.symbol = symbol
self.priceBought = priceBought
self.countBought = countBought
self.dateBought = dateBought
yhoEntity = Share(self.symbol)
self.currPrice = float(yhoEntity.get_price())
def addTransaction(self, trade, tradeCount, assetSymbol):
asset = Asset.objects.get(symbol=assetSymbol)
portfolioAssetMapping = PortfolioAssetMapping.objects.get(asset=asset)
timestamp = "2016-01-06"
initialCount = portfolioAssetMapping.currentCount
finalCount = initialCount
if trade == "buy":
finalCount = initialCount + tradeCount
if trade == "sell":
finalCount = initialCount - tradeCount
portfolioAssetMapping.currentCount = finalCount
assetInfo = Share(assetSymbol)
price = finalCount * float(assetInfo.get_price())
transaction = Transaction(mapping=portfolioAssetMapping,
trade=trade,
timestamp=timestamp,
initialCount=initialCount,
finalCount=finalCount,
tradeCount=tradeCount,
price=price)
transaction.save()
portfolioAssetMapping.save()
def get(self):
self.response.headers['Content-Type'] = 'text/plain'
gs = pygsheets.authorize(service_file=SERVICE_CREDS, no_cache=True)
sh = gs.open(SHEET_FILE_NAME)
ws = sh.worksheet_by_title(SHEET_WORK_NAME)
try:
shares = ['^AORD', 'FXJ.AX', 'TLS.AX', 'REA.AX', 'CBA.AX']
for symbol in shares:
share = Share(symbol)
s_price = share.get_price()
s_name = share.get_name()
symbol_cells = sh.find(symbol)
if len(symbol_cells) == 0:
ws.append_table(values=[s_name, symbol, s_price])
else:
symbol_cell = symbol_cells[0]
symbol_cell.neighbour('left').value = s_name
symbol_cell.neighbour('right').value = s_price
self.response.write('OK')
except:
logging.exception('Caught exception in fetch')
self.response.write('EXCEPTION')
def get_updates(self):
dict = {}
r_list = []
for symbol in self.list:
try:
s = Share(symbol)
tmp = s.get_trade_datetime().split()
timestamp = tmp[0] + 'T' + tmp[1] + '.00'
price = int(s.get_price().split(".")[self.PRICE])
#print("type for price:{}".format(type(price)))
dict[symbol] = [price, timestamp]
del s
except:
pass
#print ("Could not find {} in yahoo finance".format(symbol))
for item in dict:
r_list.append((item,
datetime.strptime(dict[item][self.TIME],
"%Y-%m-%dT%H:%M:%S.%f"),
dict[item][self.PRICE]))
# r_list.append((item, datetime.now(), dict[item]))
for i in r_list:
yield i
return ["GOOG", datetime(2104, 2, 13), 37]
class stocktw(object):
CaptialCashYear = 3
def __init__(self, stockNum):
self.stockNum = str(stockNum)
self.share = Share(self.stockNum + ".tw")
self.share.refresh()
def getPrice(self):
price = 0
try:
price = self.share.get_price()
except:
print("get price error:" + self.stockNum)
return price
def isIncrease(self, x, key=lambda x: x):
return all([key(x[i]) <= key(x[i + 1]) for i in self.CaptialCashYear])
def isCaptialCashDecrease(self):
url = str('http://easyfun.concords.com.tw/z/zc/zcb/zcb_%s.djhtm' %
self.stockNum)
soup = BeautifulSoup(requests.get(url).text, 'lxml')
table = pd.read_html(str(soup.find_all('table')[0]))
df = table[2]
df = df.ix[1:, :2]
df.columns = df.iloc[0]
df = df[1:]
ds = df["比重"].str[:-1].apply(pd.to_numeric)
decreasing = lambda L: all(x <= y for x, y in zip(L, L[1:]))
check = decreasing(ds[:self.CaptialCashYear])
return check
def get_initial_company_info():
"""Gets the initial information for each company"""
company_dict = utils.open_json(MONITOR)
for company in company_dict:
# Gets symbol for company
if company_dict[company]["Symbol"] == "unknown":
try:
with urllib.request.urlopen(
f'https://finance.yahoo.com/_finance_doubledown/'
f'api/resource/searchassist;searchTerm={company}'
) as response:
html = response.read().decode()
d = json.loads(html)
company_dict[company]["Symbol"] = d['items'][0][
'symbol']
except urllib.error.HTTPError as error:
utils.write_to_log(f'Error opening URL: {error}')
# Gets initial share price
if company_dict[company]["Initial-share-price"] == 1:
yahoo = Share(company_dict[company]["Symbol"])
share = yahoo.get_price()
company_dict[company]["Initial-share-price"] = float(share)
company_dict[company]["Current-share-price"] = float(share)
utils.write_to_json(MONITOR, company_dict)
def find_quote(word):
"""Given an individual symbol,
find and return the corresponding financial data
word -- the symbol for which you're finding the data (ex. "GOOG")
"""
cleanword=re.sub('[@<>]', '', word)
share = Share(cleanword)
price = share.get_price()
if price != None:
# Extract data
day_high = share.get_days_high()
day_low = share.get_days_low()
market_cap = share.get_market_cap()
year_high = share.get_year_high()
year_low = share.get_year_low()
yoy = calculate_YoY(share)
output_string = ('*Stock*: \'{}\' \n*Current Price*: ${} \n*Day Range*: '
'${} - ${} \n*52 Wk Range*: ${} - ${} \n*YoY Change*: {}\n*Market Cap*: '
'${}').format(word.upper(), str(price), str(day_low), str(day_high),
str(year_low), str(year_high), str(yoy), str(market_cap))
else:
output_string = "Can't find a stock with the symbol \'" + cleanword.upper() + "\'"
return output_string
def combine(onedayago, twodaysago, threedaysago, fivedaysago, oneweekago, companyname):
print "Analyzing data from the past few days..."
dates = [onedayago, twodaysago, threedaysago, fivedaysago, oneweekago]
for i in dates:
i == i.format('YYYY-MM-DD')
# Just gets the info and puts it into programmer friendly names
def getclosing(date, company):
# Thanks to stackoverflow user 'TessellatingHeckler' for helping me out with this next function! At the time dictionaries were a foreign concept to me.
readings = company.get_historical(date, date)
for reading in readings:
close = reading['Close']
return close
company = Share(companyname)
closingonedayago = getclosing(str(dates[0]), company)
closingtwodaysago = getclosing(str(dates[1]), company)
closingthreedaysago = getclosing(str(dates[2]), company)
closingfivedaysago = getclosing(str(dates[3]), company)
closingoneweekago = getclosing(str(dates[4]), company)
twohundredavg = company.get_200day_moving_avg()
fiftyavg = company.get_50day_moving_avg()
today = company.get_price()
decision(today, closingonedayago, closingtwodaysago, closingthreedaysago, closingfivedaysago, closingoneweekago, twohundredavg, fiftyavg)
def main():
""" Reads in a CSV file specifying the portfolio of stocks
and their respective ratios within the portfolio."""
stocks = {}
with open(STOCK_RATIO_FILE) as csvfile:
reader = csv.reader(csvfile, delimiter=',')
for row in reader:
ticker, fraction = row[0].strip(), float(row[1].strip())
stocks[ticker] = {}
share = Share(ticker)
scurr = share.get_currency()
if scurr != CURRENCY:
xchrate = float(Currency(scurr + CURRENCY).get_rate())
else:
xchrate = 1.0
price = float(share.get_price()) * xchrate
stocks[ticker]['price'] = price
stocks[ticker]['in_currency'] = CURRENCY
stocks[ticker]['target_ratio'] = fraction
stocks[ticker]['name'] = share.get_name()
stocks[ticker]['target_number'] = np.round(fraction * TOTAL_CASH /
price)
print(json.dumps(stocks, indent=2))
total_value = 0
for stock in stocks:
s = stocks[stock]
total_value += s['price'] * s['target_number']
print('Total Portfolio Value:')
print(total_value)
def get_stock_info(symbols, moreInfo=False): """ Scrape stock info from Yahoo finance @Param 'moreInfo': False for getting price, True for getting more information @Return 'message': "symbol: Price-number, Open Price-number, Pre Close Price-number, High Price-number, Low price-number" """ message = '' for symbol in symbols: try: stock = Share(symbol) price = stock.get_price() except AttributeError: price = None if price == None: # Stock symbol not exists, replace with an alert message message += '#' + symbol + ': ' + 'The stock symbol does not exit' + '\n' elif moreInfo: message += '#%s: Price-%s, Open Price-%s, Pre Close Price-%s, High Price-%s, Low price-%s\n' \ % (symbol, price, stock.get_open(), stock.get_prev_close(), stock.get_days_high(), stock.get_days_low()) else: message += '#' + symbol + ': ' + price + '\n' alert_message = 'Please type #1 followed by stock symbols to get more information' if moreInfo == True else \ 'Please type #0 followed by stock symbols to get stock price' return message if message != '' else alert_message
def populate_stocks():
ticker_list = []
for i in range(1, 6):
ticker_list.extend(
list(map(''.join, product(ascii_uppercase, repeat=i))))
for tick in ticker_list:
print("Checking " + tick + ".")
if Share(tick).get_name():
try:
if Stock.objects.get(ticker=tick):
print(tick + " already exists. Skipping database entry.")
continue
except:
stock_info = Share(tick)
stock = Stock(
name=stock_info.get_name(),
ticker=tick,
price=stock_info.get_price(),
price_target=stock_info.get_one_yr_target_price(),
is_bullish=None,
last_updated=timezone.now())
stock.save()
print(tick + " " + Share(tick).get_name())
def main():
outfile = open('process.txt', 'w')
ticker = []
infile = open('NASDAQ.txt', 'r')
for line in infile:
line.rstrip('\n')
share = Share(line)
price = share.get_price()
if price != None:
if float(share.get_price()) > 10:
outfile.write(line)
infile.close()
outfile.close()
def combine(onedayago, twodaysago, threedaysago, fivedaysago, oneweekago,
companyname):
print "Analyzing data from the past few days..."
dates = [onedayago, twodaysago, threedaysago, fivedaysago, oneweekago]
for i in dates:
i == i.format('YYYY-MM-DD')
# Just gets the info and puts it into programmer friendly names
def getclosing(date, company):
# Thanks to stackoverflow user 'TessellatingHeckler' for helping me out with this next function! At the time dictionaries were a foreign concept to me.
readings = company.get_historical(date, date)
for reading in readings:
close = reading['Close']
return close
company = Share(companyname)
closingonedayago = getclosing(str(dates[0]), company)
closingtwodaysago = getclosing(str(dates[1]), company)
closingthreedaysago = getclosing(str(dates[2]), company)
closingfivedaysago = getclosing(str(dates[3]), company)
closingoneweekago = getclosing(str(dates[4]), company)
twohundredavg = company.get_200day_moving_avg()
fiftyavg = company.get_50day_moving_avg()
today = company.get_price()
decision(today, closingonedayago, closingtwodaysago, closingthreedaysago,
closingfivedaysago, closingoneweekago, twohundredavg, fiftyavg)
def getPrice(bodyList, from_number):
retStr = ""
#interate over bodyList
for ticker in bodyList:
quote = Share(str(ticker))
price = quote.get_price()
#construct return string with price ticker if found
#appended the comma and space in the front, will remove preceeding comma after loop
if price:
retStr += ", " + ticker + " Price: " + price
else:
retStr += ", ticker not found"
#update last_lookup field so the "more info" feature works
conn = mysql.connect()
cur = conn.cursor()
q = '''INSERT INTO last_lookup (phone, ticker)
VALUES (%s, %s)
ON DUPLICATE KEY UPDATE
ticker = VALUES(ticker)
'''
try:
cur.execute(q, (from_number, ticker))
conn.commit()
except:
conn.rollback()
#strip preceeding comma and space
retStr = retStr[2:]
return retStr
def get_stock_info(name, abbr):
x = Share(abbr)
x.refresh()
price = x.get_price()
change = x.get_percent_change()
print(change[0] == '-')
if change[0] == '-':
color = '#B22222'
else:
color = '#006400'
url = "https://news.google.com/news?q={0}&output=rss".format(name)
feed = feedparser.parse(url)
entries = []
i = 0
while i < len(feed.entries) and i < 7:
title = feed.entries[i]['title']
index = title.index('-')
author = title[index + 2:]
title = title[:index - 1]
link = feed.entries[i]['link']
entries.append({'title': title, 'author': author, 'link': link})
i += 1
return {
'price': price,
'change': change,
'color': color,
'entries': entries
}
def get_price_YAHOO(ticker):
#for ticker in list_of_symbols:
try:
from yahoo_finance import Share
yahoo = Share(ticker)
yahoo.refresh()
price_finance = yahoo.get_price()
print("IN->", ticker)
print("Open -> ", yahoo.get_open())
print("Current Price -> ", yahoo.get_price())
print("Ave Volume -> ", yahoo.get_avg_daily_volume())
print("Volume -> ", yahoo.get_volume())
print("Time -> ", yahoo.get_trade_datetime())
return float(price_finance)
except:
get_price_YAHOO(ticker)
def stocks(self, message, params=None, **kwargs):
"""Display current stock value for user provided symbol(s)
(ex: .stock rax,yhoo,aapl)
"""
if not params:
message.dispatch("No stock symbol provided, please provide "
"at least one symbol. Example: .stock rax or "
".stock rax,yhoo,aapl")
return
text = ""
try:
symbols = params.upper().split(',')
for s in symbols:
share = Share(s)
text = (text + "%s: %s (%s) | " %
(s, share.get_price(), share.get_change()))
text = text.rstrip(" ")
text = text.rstrip("|")
except Exception:
text = ("Unable to fetch stocks data. "
"Please ensure the symbols you've provided are valid")
message.dispatch(text)
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 combine(onedayago, twodaysago, threedaysago, fivedaysago, oneweekago,
companyname):
print("Analyzing data from the past few days...")
dates = [onedayago, twodaysago, threedaysago, fivedaysago, oneweekago]
for i in dates:
i == i.format('YYYY-MM-DD')
# Just gets the info and puts it into programmer friendly names
def getclosing(date, company):
readings = company.get_historical(date, date)
for reading in readings:
close = reading['Close']
return close
company = Share(companyname)
closingonedayago = getclosing(str(dates[0]), company)
closingtwodaysago = getclosing(str(dates[1]), company)
closingthreedaysago = getclosing(str(dates[2]), company)
closingfivedaysago = getclosing(str(dates[3]), company)
closingoneweekago = getclosing(str(dates[4]), company)
twohundredavg = company.get_200day_moving_avg()
fiftyavg = company.get_50day_moving_avg()
today = company.get_price()
decision(today, closingonedayago, closingtwodaysago, closingthreedaysago,
closingfivedaysago, closingoneweekago, twohundredavg, fiftyavg)
def get_ma(stock):
prices_10 = []
prices_20 = []
stock = Share(stock)
if (stock.get_price() < 5):
return 0, 0, 0
dma_10 = now - timedelta(days=30)
date10 = str(dma_10.year) + "-" + str(dma_10.month) + "-" + str(dma_10.day)
time.sleep(0.5)
try:
data = stock.get_historical(date10, theDate)
prices_50 = stock.get_50day_moving_avg()
count = 0
for theData in data:
if count < 10:
count = count + 1
prices_10.append(float(theData['Adj_Close']))
else:
continue
count = 0
for theData in data:
if count < 20:
count = count + 1
prices_20.append(float(theData['Adj_Close']))
else:
continue
except:
return 0, 0, 0
print prices_50
return prices_10, prices_20, prices_50
def get_risers_and_fallers(self, account):
print(datetime.now(), 'checking risers and fallers')
risers = []
fallers = []
if account.portfolio != {}:
for key in account.portfolio.keys():
try:
share = account.portfolio[key]
bought_price = float(share.price)
units = float(share.holding)
total_bought_price = bought_price * units
s = Share(key)
price = float(s.get_price())
net_gain = round((price * units) - total_bought_price, 2)
print("net", net_gain)
percent_gain = round(
((price - bought_price) / bought_price) * 100, 2)
print("percent", percent_gain)
if percent_gain > 0:
risers.append((key, percent_gain, net_gain))
else:
fallers.append((key, percent_gain, net_gain))
except:
continue
return risers, fallers
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 data_frame_companies_prices(list_companies,a,b):
# Es una funcion que toma una lista de empresas (codificadas por yahoo.finance) y valor minimo y maximo
# de la distribucion uniforme que sigue la diferencia entre el bid y el ask para las empresas.
list_index=["ask5","ask4","ask3","ask2","ask1","bid1","bid2","bid3","bid4","bid5"]
companies_prices=pd.DataFrame(index=list_index)
for i in list_companies:
company = Share(i)
open_price=company.get_price()
open_price=float(open_price)
a=float(a)
b=float(b)
random1=(np.random.rand(1)+(a/b-a))/(1.0/b-a)
first_ask_price=open_price+(round(random1,2))/2.0
ask_array=np.array([first_ask_price+0.04,first_ask_price+0.03,first_ask_price+0.02,first_ask_price+0.01,first_ask_price])
first_bid_price=open_price-(round(random1,2))/2.0
bid_array=np.array([first_bid_price+0.04,first_bid_price+0.03,first_bid_price+0.02,first_bid_price+0.01,first_bid_price])
ask_bid_array=np.concatenate((ask_array,bid_array))
companies_prices[i]=ask_bid_array
return companies_prices
def get(self, request, symbol):
try:
stock = Stock.objects.get(ticker=symbol)
self.update_stock(stock)
except ObjectDoesNotExist:
stock_info = Share(symbol)
stock = Stock(
name=stock_info.get_name(),
ticker=symbol,
price=stock_info.get_price(),
price_target=stock_info.get_one_yr_target_price(),
is_bullish=None,
last_updated=timezone.now()
)
stock.save()
try:
stock = Stock.objects.get(ticker=symbol)
except ObjectDoesNotExist:
stock = "Still can not pull stock."
return render(request, self.template_name, {
'stock': stock,
'stock_tracked': self.stock_tracked(request, symbol)
})
def getPrice(bodyList, from_number):
retStr = ""
#interate over bodyList
for ticker in bodyList:
quote = Share(str(ticker))
price = quote.get_price()
#construct return string with price ticker if found
#appended the comma and space in the front, will remove preceeding comma after loop
if price:
retStr += ", " + ticker + " Price: " + price
else:
retStr += ", ticker not found"
#update last_lookup field so the "more info" feature works
conn = mysql.connect()
cur = conn.cursor()
q = '''INSERT INTO last_lookup (phone, ticker)
VALUES (%s, %s)
ON DUPLICATE KEY UPDATE
ticker = VALUES(ticker)
'''
try:
cur.execute(q,(from_number,ticker))
conn.commit()
except:
conn.rollback()
#strip preceeding comma and space
retStr = retStr[2:]
return retStr
def create_files():
for i in range(0,TIME_IN_MIN*60/TIME_BETWEEN_ITERATIONS):
reader=csv.DictReader(open('Yahoo_symbols.csv','rb'))
for sym in reader:
company=sym["COMPANY"]
symbol=sym["SYMBOL"]
while(1):
try:
share_name=Share(symbol)
if share_name:
break
except:
time.sleep(1)
filename = "./Q4_files/"+company+".csv"
try:
file=open(filename,"a")
except:
file=open(filename,"w")
file.write("Time,Price")
timestamp = share_name.get_trade_datetime()
price = share_name.get_price()
writer = csv.DictWriter(file, fieldnames=["Time","Price"], delimiter=",", lineterminator="\n")
writer.writerow({"Time":timestamp ,"Price":price})
time.sleep(TIME_BETWEEN_ITERATIONS)
file.close()
def get_stock_price_and_volume(symbol, start_date, end_date, dates): share = Share(symbol) hist_data = share.get_historical(start_date, end_date) hist_data.reverse() volume = [] price = [] i = 0 for d in dates: if i < len(hist_data): if (hist_data[i]['Date'] == d): # Weekday price.append(hist_data[i]['Close']) volume.append(hist_data[i]['Volume']) i += 1 else: # Weekend price.append(0) volume.append(0) else: # Get the current price and volume instead from historical data price.append(share.get_price()) volume.append(share.get_volume()) if len(dates) != len(volume) and len(dates) != len(price): print 'Dates and volume and/or price lists are not of same lenght!' return [price, volume]
def find_quote(word):
"""Given an individual symbol,
find and return the corresponding financial data
word -- the symbol for which you're finding the data (ex. "GOOG")
"""
cleanword = re.sub('[@<>]', '', word)
share = Share(cleanword)
price = share.get_price()
if price != None:
# Extract data
day_high = share.get_days_high()
day_low = share.get_days_low()
market_cap = share.get_market_cap()
year_high = share.get_year_high()
year_low = share.get_year_low()
yoy = calculate_YoY(share)
output_string = (
'*Stock*: \'{}\' \n*Current Price*: ${} \n*Day Range*: '
'${} - ${} \n*52 Wk Range*: ${} - ${} \n*YoY Change*: {}\n*Market Cap*: '
'${}').format(word.upper(), str(price),
str(day_low), str(day_high), str(year_low),
str(year_high), str(yoy), str(market_cap))
else:
output_string = "Can't find a stock with the symbol \'" + cleanword.upper(
) + "\'"
return output_string
def create_files():
for i in range(0, TIME_IN_MIN * 60 / TIME_BETWEEN_ITERATIONS):
reader = csv.DictReader(open('Yahoo_symbols.csv', 'rb'))
for sym in reader:
company = sym["COMPANY"]
symbol = sym["SYMBOL"]
while (1):
try:
share_name = Share(symbol)
if share_name:
break
except:
time.sleep(1)
filename = "./Q4_files/" + company + ".csv"
try:
file = open(filename, "a")
except:
file = open(filename, "w")
file.write("Time,Price")
timestamp = share_name.get_trade_datetime()
price = share_name.get_price()
writer = csv.DictWriter(file,
fieldnames=["Time", "Price"],
delimiter=",",
lineterminator="\n")
writer.writerow({"Time": timestamp, "Price": price})
time.sleep(TIME_BETWEEN_ITERATIONS)
file.close()
def get_title(title, cache=True):
return_dic = {}
# if cache == True, try to open the cached file
if cache:
cached_filename = 'cache/finance_{0}.json'.format(title)
if os.path.exists(cached_filename):
with open(cached_filename) as f:
items = json.loads(f.read())
return items
# if cache == False, or the cached file does not exist, call the API
try:
t = Share(title)
return_dic["symbol"] = title
return_dic["price"] = t.get_price()
return_dic["change"] = t.get_change()
return_dic["name"] = t.data_set["Name"]
except:
return_dic["symbol"] = title
return_dic["price"] = 0
return_dic["change"] = 0
return_dic["name"] = title
# if cache == True but we are down here, it means that the cached file does not exist, so create it
if cache:
with open(cached_filename, 'w') as f:
json.dump(return_dic, f)
return return_dic
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 gather(self):
share = Share(self.code)
price = share.get_price()
if price is None:
self.log('Company gave no price')
return
self.prices.append(float(price))
return
def action(self):
self.yahoo_finance_connect = "RAN"
code = 'GOOG' # stock symbol here
s = Share(code)
price = s.get_price()
self.price = price
def check_price(self, ticker):
try:
company = Share(ticker)
return float(company.get_price())
except:
print 'Failed to check price'
print sys.exc_info()[0];
return 0
def getStockInfo(symbol):
yahoo_finance_client = Share(symbol)
stock_info = {}
stock_info["price"] = yahoo_finance_client.get_price()
stock_info["change"] = yahoo_finance_client.get_change()
return stock_info
def get_database(stock):
"""Return stock database"""
now = date.today()
mystock = Share(stock)
now_price = mystock.get_price() #ราคาปัจจุบัน
import_time = mystock.get_trade_datetime() #เวลาที่ดึงฐานข้อมูล
stock_db = mystock.get_historical("2015-01-01", now.isoformat()) #ฐานข้อมูลหุ้นตั้งแต่วันที่ 1 มกราคม 2558 ถึงปัจจุบัน
return now, stock, now_price, import_time, stock_db
def displayFinance(self, yearStart, yearEnd):
yahoo = Share(self.companyCode)
#declare
textReturn = ""
textReturn += "Opening price: " + str(yahoo.get_open()) + '\n'
textReturn += "Current price: " + str(yahoo.get_price()) + '\n'
textReturn += "Dividend Share: " + str(yahoo.get_dividend_share()) + '\n'
textReturn += "Year High: " + str(yahoo.get_year_high()) + '\n'
textReturn += "Year Low: " + str(yahoo.get_year_low()) + '\n'
self.jsonObj.append({ "openPrice" : str(yahoo.get_open()) , "currPrice" : str(yahoo.get_price()), "dividendPrice" : str(yahoo.get_dividend_share()), "yearHigh" : str(yahoo.get_year_high()), "yearLow" : str(yahoo.get_year_low()) })
#historical data returns a jSON object
jsonHistorical = yahoo.get_historical(str(yearStart) + '-04-25', str(yearEnd) + '-04-29')
textReturn += "Historical Data: " + '\n'
#To limit the number of historical datapoints sent
numHist = 0
maxHist = 10
for dict in jsonHistorical:
numHist += 1
if numHist < maxHist:
textReturn += "For year " + dict['Date'] + " High was: " + dict['High'] + " Low was: " + dict['Low'] + '\n'
#self.jsonObj[0][dict['Date'] + "High"] = dict['High']
#self.jsonObj[0][dict['Date'] + "Low"] = dict['Low']
self.jsonObj.append({ "Highd" : dict['Date'] , "Lowd" : dict['Date'], "Highp" : dict['High'], "Lowp" : dict['Low'] })
if textReturn == "":
self.jsonObj.append({ "success" : "false" })
else:
self.jsonObj.append({ "success" : "true" })
return textReturn
def is_valid_stock_symbol(stock_symbol):
"""Returns true if stock symbol is listed in Yahoo Finance
false otherwise"""
stock = Share(stock_symbol)
if stock.get_price() is None:
return False
else:
return True
def whattodo(figure):
# convert list to string
# do we need to account for each transaction as well
global trader_overhead
key=''.join(str(e) for e in figure)
action=figdict[key][4]
if "-" in action:
action="sell"
else:
action="buy"
elemental=figdict[key][2]
# elemental="Earth"
# action="sell"
whichone=random.choice(company_dict[elemental])
print action,whichone,elemental
if action=="buy":
if portfolio[elemental].has_key(whichone):
portfolio[elemental][whichone]+=1
else:
portfolio.setdefault(elemental, {})[whichone] = 1
print "Buy", whichone
bought=Share(whichone)
print "Price", bought.get_price()
# do buy action if we have da cash
cash = req_admxi.get_cash(ALGO)
if bought.get_price():
if cash>(float(bought.get_price())+trader_overhead): # 50 just in case
exec_buy(whichone)
trader_overhead+=1.0
elif action=="sell":
#choose a random from elemental dict
if portfolio[elemental].has_key(whichone):
print portfolio
# unless it is zero decrement it
if portfolio[elemental][whichone]>0:
portfolio[elemental][whichone]-=1
print "Sell", whichone
sold=Share(whichone)
print "Price", sold.get_price()
exec_sell(whichone)
trader_overhead+=1.0
else:
print "No action taken"
return (' '.join((action,whichone)))
def collect_stocks_data(stocks, ipo_to_present_name, ipo_one_year_name):
f_all_data = create_file("all_data/{}".format(ipo_to_present_name))
f_yearly_data = create_file("year_only_data/{}".format(ipo_one_year_name))
for stock in stocks:
try:
symbol = stock.get_symbol()
name = stock.get_name()
share = Share(symbol)
price = share.get_price()
historical_data = share.get_historical(start_date, end_date)
if len(historical_data) > 1:
oldest_entry_available = historical_data[-1]
oldest_entry_closing_price = oldest_entry_available['Adj_Close']
oldest_entry_date = datetime.strptime(oldest_entry_available['Date'], "%Y-%m-%d")
# Only use companies that IPOed two weeks after the first of january in 2005.
# This was done to account for some missing data.
if (oldest_entry_date - min_ipo_date).total_seconds() > NUM_SECONDS_TWO_WEEKS:
ipo_date = date_to_string(oldest_entry_date)
current_price_rounded = "%.2f" % float(price)
ipo_price_rounded = "%.2f" % float(oldest_entry_closing_price)
data = str((symbol, ipo_date, ipo_price_rounded, current_price_rounded))
write_and_flush(f_all_data, data)
if(len(historical_data) > NUM_WORK_DAYS_ONE_YEAR):
year_after_ipo_entry = historical_data[-NUM_WORK_DAYS_ONE_YEAR]
year_after_ipo_date = datetime.strptime(year_after_ipo_entry['Date'], "%Y-%m-%d")
year_after_ipo_date = date_to_string(year_after_ipo_date)
year_after_ipo_price = "%.2f" % float(year_after_ipo_entry['Adj_Close'])
data = str((symbol, ipo_date, ipo_price_rounded, year_after_ipo_date, year_after_ipo_price))
write_and_flush(f_yearly_data, data)
else:
print "{} has no historical data".format(symbol)
continue
except NameError as e:
print "NameError: ", e
except IndexError as e:
print "IndexError: ", e
except KeyboardInterrupt:
raise
except:
print "GeneralError:", sys.exc_info()[0]
continue
f_all_data.close()
f_yearly_data.close()
class Stock:
"""
"""
def __init__(self, n):
self.name = n
self.confidence_list = []
self.fifty_day_moving_average = None
self.two_hundred_day_moving_average = None
self.price_earnings_growth_ratio = None
self.confidence_string = None
self.current_price = None
self.stock = Share(self.name)
def calculate_confidence_percentage(self):
self.confidence_list = []
self.confidence_list.append(sc.formula_00_is_stock_above_50_day_moving_average(self.get_current_price(), self.get_fifty_day_moving_average()))
self.confidence_list.append(sc.formula_01_is_stock_above_200_day_moving_average(self.get_current_price(), self.get_two_hundred_day_moving_average()))
self.confidence_list.append(sc.formula_02_pattern_guesser_confidence_for_tomorrow(self.name))
confidence_string = ''
for c in self.confidence_list:
confidence_string += str(c) + ", "
self.confidence_string = 'Confidence List: ' + confidence_string + '\tAverage Confidence: ' + str(sum(self.confidence_list) / len(self.confidence_list))
def get_name(self):
"""TODO:...
:return:
"""
return self.name
def get_current_price(self):
if self.current_price is None:
self.current_price = self.stock.get_price()
def get_confidence_string(self):
if self.confidence_string is None:
self.calculate_confidence_percentage()
return self.confidence_string
def get_fifty_day_moving_average(self):
if self.fifty_day_moving_average is None:
self.fifty_day_moving_average = self.stock.get_50day_moving_avg()
return self.fifty_day_moving_average
def get_two_hundred_day_moving_average(self):
if self.two_hundred_day_moving_average is None:
self.two_hundred_day_moving_average = self.stock.get_200day_moving_avg()
return self.two_hundred_day_moving_average
def get_price_earnings_growth_ratio(self):
if self.price_earnings_growth_ratio is None:
self.price_earnings_growth_ratio = self.stock.get_price_earnings_growth_ratio()
return self.price_earnings_growth_ratio
def get_quotes(self):
self.debug("getting quotes")
try:
quotes = {}
for i in self.assets:
yahoo = Share(i)
quotes[i] = {"source": "yahoo", "last": float(yahoo.get_price())}
return quotes
except OSError:
self.error("Network Error")
