def index():
start_date = "2016-10-02"
end_date = "2016-10-16"
company = "AAPL"
if request.method == 'POST':
if len(request.form.get("company")) <= 4:
topic_name = get_symbol(request.form.get("company").upper())
company_stock_symbol = request.form.get("company").upper()
company_stock_price = ystockquote.get_all(request.form.get("company").upper())["price"]
else:
topic_name = request.form.get("company").title()
company_stock_symbol = False
company_stock_price = False
company = request.form.get("company")
descriptions,articles_with_images = get_search_results(company)
sentiments = get_sentiment_scores([x["description"] for x in descriptions])
sentiment = sum(sentiments) / len(sentiments)
# text_blob_sentiment = get_textblob_sentiment(descriptions)
# print sum([x for x in text_blob_sentiment if x != 0]) / len(text_blob_sentiment)
return render_template("index.html", company=company, topic_name=topic_name, symbol=company_stock_symbol, price=company_stock_price, sentiment=sentiment, imaged_articles=articles_with_images, startdate=start_date, enddate=end_date)
company_stock_price = ystockquote.get_all(company)["price"]
descriptions,articles_with_images = get_search_results(company)
return render_template("index.html", imaged_articles=articles_with_images, price=company_stock_price, company=company, startdate=start_date, enddate=end_date)
def get(self):
stock_name = self.request.path[7:]
# Checking if request is from valid user
if 'HMAC' not in self.request.headers:
self.request.headers['HMAC'] = None
hmac_sign = self.request.headers['HMAC']
if 'PKEY' not in self.request.headers:
self.request.headers['PKEY'] = None
public_key = self.request.headers['PKEY']
data_dict = {'stock': stock_name}
response = {}
if not is_valid_user_request(hmac_sign,
public_key,
data_dict):
response['status'] = False
response['unathorized'] = True
self.response.out.write(json.dumps(response))
return
response["name"] = stock_name
try:
if len(stock_name) < 1:
raise Exception()
details = ystockquote.get_all(stock_name)
response["status"] = True
response["details"] = details
except:
response["status"] = False
self.response.out.write(json.dumps(response))
def test_get_all_alignment(self):
""" Compare bulk 'all_info' values to individual values.
Currently broken due to misalignment from invalid CSV in
fields: f6, k3, and maybe j2, a5, b6.
"""
symbol = 'GOOG'
all_info = ystockquote.get_all(symbol)
self.assertIsInstance(all_info, dict)
self.assertEquals(
all_info['previous_close'],
ystockquote.get_previous_close(symbol))
self.assertEquals(
all_info['volume'],
ystockquote.get_volume(symbol))
self.assertEquals(
all_info['bid_realtime'],
ystockquote.get_bid_realtime(symbol))
self.assertEquals(
all_info['ask_realtime'],
ystockquote.get_ask_realtime(symbol))
self.assertEquals(
all_info['last_trade_price'],
ystockquote.get_last_trade_price(symbol))
self.assertEquals(
all_info['today_open'],
ystockquote.get_today_open(symbol))
self.assertEquals(
all_info['todays_high'],
ystockquote.get_todays_high(symbol))
self.assertEquals(
all_info['last_trade_date'],
ystockquote.get_last_trade_date(symbol))
def percent_change(self):
tick_data = []
repull_all = raw_input("Would you like to pull ticker data? (Y/N): ")
ask_print = raw_input("Show after pull? (Y/N): ")
if "y" in repull_all:
pbar = ProgressBar()
for ticker in pbar(self.ticker_list):
# print str(ticker_list.index(ticker) + 1) + ' / ' + str(len(ticker_list)) + ' ' + str((float(ticker_list.index(ticker) + 1) / len(ticker_list))) + '%'
try:
tick_data = ysq.get_all(ticker)
percentage = (
float(tick_data["change"]) / (float(tick_data["price"]) - float(tick_data["change"]))
) * 100
if percentage > 0:
self.rising.append([ticker, tick_data["price"]])
if percentage > 3:
self.rising_three.append([ticker, tick_data["price"]])
if percentage < 0:
self.dipping.append([ticker, tick_data["price"]])
if percentage < -3:
self.dipping_three.append([ticker, tick_data["price"]])
except Exception, e:
# print "Data Pull Error For: " + str(ticker)
self.error_list.append(ticker)
pass
self.write_cache()
def handle(text, mic, profile):
"""
Responds to user-input, typically speech text, with a summary of
the day's top news headlines, sending them to the user over email
if desired.
Arguments:
text -- user-input, typically transcribed speech
mic -- used to interact with the user (for both input and output)
profile -- contains information related to the user (e.g., phone
number)
"""
mic.say("Getting Stock Info")
try:
output = ''
for symbol in profile['stocks']:
print symbol
stock_info = ys.get_all(symbol)
print stock_info
current_out = symbol + " Current Price is " + stock_info['price'] + \
" with a daily change of " + stock_info['change'] + " ... "
print current_out
output = output + current_out
mic.say(output)
except:
mic.say("Error retrieving stocks")
def compact_quote(symbol):
a = y.get_all(symbol)
try:
L52 = int(round(float(a['fifty_two_week_low']), 0))
except ValueError:
L52 = '_'
try:
P = round(float(a['price']), 1)
except ValueError:
P = '_'
try:
C = a['change']
except ValueError:
C = '_'
try:
H52 = int(round(float(a['fifty_two_week_high']), 0))
except ValueError:
H52 = '_'
try:
PE = round(float(a['price_earnings_ratio']), 1)
except ValueError:
PE = '_'
try:
Cp = int(round(float(C) / float(P) * 100))
except ValueError:
Cp = '_'
return '{} {} {}% [{} {}] PE {}'.format(symbol, P, Cp, L52, H52, PE)[0:31]
def test_get_all(self):
symbol = 'GOOG'
all_info = ystockquote.get_all(symbol)
self.assertIsInstance(all_info, dict)
pc = all_info['previous_close']
self.assertNotEqual(pc, 'N/A')
self.assertGreater(float(pc), 0)
def get_fundamental_data(stock: str) -> dict:
"""
Gets fundamental Data from yahoo finance. Some fundamentals and a lot af real-live prices.
Enter a starting point and an endpoint as args after entering the symbol of a stock or an index.
The result will look like this:
avg_daily_volume: 17735800,
book_value: 9.33,
change: -0.13,
dividend_per_share: 0.12,
dividend_yield: 1.23,
earnings_per_share: -0.44,
ebitda: 2.63B,
fifty_day_moving_avg: 10.28,
fifty_two_week_high: 11.50,
fifty_two_week_low: 6.14,
market_cap: 12.35B,
price: 9.39,
price_book_ratio: 1.02,
price_earnings_growth_ratio: 2.50,
price_earnings_ratio: N/A,
price_sales_ratio: 0.59,
short_ratio: 8.07,
stock_exchange: "NYQ",
two_hundred_day_moving_avg: 9.91,
volume: 15300774},
"""
try:
return ystockquote.get_all(stock)
except:
print("Something went wrong!")
def fetchQuotes(sym, start=FROM_DATE, end=CURRENT_DATE):
his = None
data = None
try:
# print start, end
data = ystockquote.get_historical_prices(sym, start, end)
except Exception:
print "Please check the dates. Data might not be available. 404 returned"
# 404 due to data yet not available
if data:
his = DataFrame(collections.OrderedDict(sorted(data.items()))).T
his = his.convert_objects(convert_numeric=True)
his.index = pd.to_datetime(his.index)
his.insert(0, 'symbol', sym, allow_duplicates=True)
# insert the date as dataframe too
his.insert(1, 'date', his.index)
# his.columns = getColumns('stock_quote_historical') # Removing as db dependency is removed
his.columns = getColumnsNoSql('stock_quote_historical')
daily = ystockquote.get_all(sym)
# print daily
# persist(his, daily, sym, end)
return his, daily
def banner():
d = feedparser.parse('http://weather.yahooapis.com/forecastrss?w=9807&u=c')
temp = d['feed'][u'yweather_location']['city'] + ': ' + d['entries'][0][u'yweather_condition']['text'] + ' ' + \
d['entries'][0][u'yweather_condition']['temp'] + 'C'
s = ystockquote.get_all('abt.to')
stock = ['Abt: $' + s['price'], 'Change: ' + s['change'], temp]
return stock
def stock(bot, trigger):
if not trigger.group(2):
bot.reply("Please enter a stock ticker. Ex. TWTR")
else:
ticker = trigger.group(2).upper()
s = ystockquote.get_all(ticker)
bot.reply("%s %s, Price: $%s, Change: %s, Volume: %s, 52 Week High: $%s. " % (ticker, s['stock_exchange'], s['price'], s['change'], s['volume'], s['52_week_high']))
def main():
# ticker_file = "input/tickers.txt"
# bucket_name = "edgarsentimentbucket"
# conn = S3Connection(argv[1], argv[2])
# path_bucket = conn.get_bucket(bucket_name)
# k = Key(path_bucket)
# k.key = ticker_file
# pathfile = k.get_contents_as_string()
# try:
# lines = pathfile.split('\n')
# except AttributeError:
# lines = pathfile
try:
print "started"
# for linie in open(ticker_file, "r"):
for linie in sys.stdin:
try:
print linie
ticker_arr = linie.split('\t')
curr_ticker = ticker_arr[1]
curr_cik = ticker_arr[2]
curr_date = ticker_arr[3]
if not '-' in curr_date:
curr_date = curr_date[0:4] + '-' + curr_date[4:6] + '-' + curr_date[6:8]
curr_date = curr_date.strip()
curr_date_obj = crteDateObj(curr_date)
yest_date_obj = curr_date_obj - timedelta(days=1)
yest_date = crteDateStr(yest_date_obj)
try:
price_dict = ystockquote.get_historical_prices(curr_ticker, yest_date, curr_date)
curr_close = price_dict[curr_date]['Close']
curr_adj_close = price_dict[curr_date]['Adj Close']
curr_open = price_dict[curr_date]['Open']
yest_close = price_dict[yest_date]['Close']
yest_adj_close = price_dict[yest_date]['Adj Close']
yest_open = price_dict[yest_date]['Close']
except:
curr_close = "NA"
curr_adj_close = "NA"
curr_open = "NA"
yest_close = "NA"
yest_adj_close = "NA"
yest_open = "NA"
try:
all_dict = ystockquote.get_all(curr_ticker)
curr_mkt_cap = all_dict['market_cap']
except:
curr_mkt_cap = "NA"
print curr_ticker + '\t' + curr_cik + '\t' + curr_date + '\t' + curr_open + '\t' + \
curr_close + '\t' + curr_adj_close + '\t' + yest_open + '\t' + yest_close + '\t' + \
yest_adj_close + '\t' + curr_mkt_cap
except:
print "bad"
except:
print "didn't start"
def getStockLine (self, stocks):
stock_list = stocks.split()
stockLine = ""
for stock in stock_list:
stockData = ystockquote.get_all(stock)
stockLine += stock + '[' + stockData['price'] + '/' + stockData['change'] + "] "
return stockLine
def get_quote(self):
if self.quote is None:
try:
self.quote = ystockquote.get_all(self.symbol)
except:
self.quote = None
return self.quote
def fetchQuotes(sym, start=FROM_DATE, end=CURRENT_DATE):
his = None
data = None
try:
# print start, end
data = ystockquote.get_historical_prices(sym, start, end)
except Exception:
print "Please check the dates. Data might not be available. 404 returned"
# 404 due to data yet not available
if data:
his = DataFrame(collections.OrderedDict(sorted(data.items()))).T
his = his.convert_objects(convert_numeric=True)
his.index = pd.to_datetime(his.index)
his.insert(0, 'symbol', sym, allow_duplicates=True)
# insert the date as dataframe too
his.insert(1, 'date', his.index)
# his.columns = getColumns('stock_quote_historical') # Removing as db dependency is removed
his.columns = getColumnsNoSql('stock_quote_historical')
daily = ystockquote.get_all(sym)
# print daily
# persist(his, daily, sym, end)
return his, daily
def test_get_all(self):
symbol = 'GOOG'
all_info = ystockquote.get_all(symbol)
self.assertIsInstance(all_info, dict)
pc = all_info['previous_close']
self.assertNotEqual(pc, 'N/A')
self.assertGreater(float(pc), 0)
def addRow(self, stockSym):
self.sysmTextIn.delete(0, END)
searchterms = [('Symbol', stockSym.upper(), '=', 'AND')]
symbolCol = self.model.getColumnData(columnIndex=self.model.getColumnIndex(columnName="Symbol"),
columnName="Symbol", filters=searchterms)
if stockSym.upper() in symbolCol:
return
result = ystockquote.get_all(stockSym.upper())
row = Rows(result, stockSym.upper())
dictrow = row.getRow()
colIndex = self.model.getColumnIndex(columnName="Symbol")
stockSym = self.model.getValueAt(rowIndex=0, columnIndex=colIndex)
if stockSym == " ":
row0 = self.table.getSelectedRow()
self.model.deleteRow(row0)
self.table.setSelectedRow(row0-1)
self.table.clearSelected()
else:
self.currentRow = self.currentRow + 1
self.model.importDict({ "%s%d" % ("rec", self.currentRow) : dictrow})
change = float(dictrow['Change'])
if change > 0:
self.model.setColorAt(rowIndex=self.model.getRecordIndex("%s%d" % ("rec", self.currentRow)),
columnIndex=self.model.getColumnIndex(columnName="Change"),color="green", key="fg")
self.model.setColorAt(rowIndex=self.model.getRecordIndex("%s%d" % ("rec", self.currentRow)),
columnIndex=self.model.getColumnIndex(columnName="%Change"),color="green", key="fg")
if change < 0:
self.model.setColorAt(rowIndex=self.model.getRecordIndex("%s%d" % ("rec", self.currentRow)),
columnIndex=self.model.getColumnIndex(columnName="Change"),color="red", key="fg")
self.model.setColorAt(rowIndex=self.model.getRecordIndex("%s%d" % ("rec", self.currentRow)),
columnIndex=self.model.getColumnIndex(columnName="%Change"),color="red", key="fg")
self.table.redrawTable()
self.after(5000, self.updateTableValue, "%s%d" % ("rec", self.currentRow))
def getStockLine(self, stocks):
stock_list = stocks.split()
stockLine = ""
for stock in stock_list:
stockData = ystockquote.get_all(stock)
stockLine += stock + '[' + stockData['price'] + '/' + stockData[
'change'] + "] "
return stockLine
def test_get_all_multiple(self):
symbols = ['GOOG', 'TSLA']
all_info = ystockquote.get_all(symbols)
self.assertIsInstance(all_info, list)
for row in all_info:
self.assertIsInstance(row, dict)
pc = row['previous_close']
self.assertNotEqual(pc, 'N/A')
self.assertGreater(float(pc), 0)
def main():
args = parse_args()
if args.startDate and args.endDate:
values = get_historical_prices(
args.symbol, args.startDate, args.endDate).items()
else:
values = get_all(args.symbol).items()
for val in sorted(values):
print val
def yahoo(symbols):
"""
Downloads the latest quote for the given symbols
"""
all = None
try:
return ystockquote.get_all(symbols)
except Exception, e:
logging.error('Could not download quote %s:%s', symbols, e)
return None
def main(tickers): for ticker in tickers: allInfo = ystockquote.get_all(ticker) print ticker + ":Exchange=" + allInfo["stock_exchange"] \ + ":Cap=" + allInfo["market_cap"] \ + ":P-Earn=" + allInfo["price_earnings_ratio"] \ + ":P-Sales=" + allInfo["price_sales_ratio"] \ + ":Range52=" + allInfo["fifty_two_week_low"] \ + "-" + allInfo["fifty_two_week_high"] \ + ":Price=" + allInfo["price"]
def get_ticks():
print "%(1)s %(2)s %(3)s %(4)s %(5)s %(6)s" % {"1" : "SYMBOLS".ljust(12), "2" : "Price".rjust(8), "3" : "Change".rjust(8), "4" : "Bought".rjust(8), "5" : "Vol(%)".rjust(8), "6" : "Action".ljust(5)}
for stock in stocks:
data= ystockquote.get_all(stock[1])
prices.append((stock[0], data['price']))
thisprices = []
for price in prices:
if price[0] == stock[0]:
thisprices.append(float(price[1]))
thisprevsma = data['price']
for price in prevsma:
if price[0] == stock[0]:
thisprevsma=price[1]
thisprevema = data['price']
for price in prevema:
if price[0] == stock[0]:
thisprevema=price[1]
bar =len(thisprices)-1
currentsma = running_sma(bar, thisprices, 3, float(thisprevsma))
currentema = ema(bar, thisprices, period, float(thisprevema), smoothing=None)
Hit = False
for i,value in enumerate(prevsma):
if prevsma[i] == stock[0]:
Hit=True
prevsma[i] = currentsma
if Hit==False:
prevema.append((stock[0], currentsma))
Hit = False
for i,value in enumerate(prevema):
if prevema[i] == stock[0]:
Hit=True
prevema[i] = currentema
if Hit==False:
prevema.append((stock[0], currentema))
action = ""
if float(currentsma) > float(currentema) :
action = "long"
elif float(currentema) > float(currentsma) :
action = "short"
vol=0
if float(data['volume']) > 0 and float(data['avg_daily_volume']) > 0:
vol = "{0:.2f}".format((float(data['volume']) /float(data['avg_daily_volume']))*100)
color=Color_It(data['price'], stock[2])
print colored("%(1)s %(2)s %(3)s %(4)s %(5)s %(6)s" % {"1" : stock[0].ljust(12), "2" : data['price'].rjust(8), "3" : data['change'].rjust(8), "4" : str(stock[2]).rjust(8), "5" : str(vol).rjust(8), "6" : action.ljust(5)}, color)
def main(argv):
ticker_file = "input/tickers.txt"
bucket_name = "edgarsentimentbucket"
conn = S3Connection(argv[1], argv[2])
path_bucket = conn.get_bucket(bucket_name)
k = Key(path_bucket)
k.key = ticker_file
pathfile = k.get_contents_as_string()
try:
lines = pathfile.split('\n')
except AttributeError:
lines = pathfile
for linie in lines:
try:
ticker_arr = linie.split('\t')
curr_ticker = ticker_arr[0]
curr_cik = ticker_arr[1]
curr_date = ticker_arr[2]
if not '-' in curr_date:
curr_date = curr_date[0:4] + '-' + curr_date[
4:6] + '-' + curr_date[6:8]
curr_date_obj = crteDateObj(curr_date)
yest_date_obj = curr_date_obj - timedelta(days=1)
yest_date = crteDateStr(yest_date_obj)
try:
price_dict = ystockquote.get_historical_prices(
curr_ticker, yest_date, curr_date)
curr_close = price_dict[curr_date]['Close']
curr_adj_close = price_dict[curr_date]['Adj Close']
curr_open = price_dict[curr_date]['Open']
yest_close = price_dict[yest_date]['Close']
yest_adj_close = price_dict[yest_date]['Adj Close']
yest_open = price_dict[yest_date]['Close']
except:
curr_close = "NA"
curr_adj_close = "NA"
curr_open = "NA"
yest_close = "NA"
yest_adj_close = "NA"
yest_open = "NA"
try:
all_dict = ystockquote.get_all(curr_ticker)
curr_mkt_cap = all_dict['market_cap']
except:
curr_mkt_cap = "NA"
print curr_ticker + '\t' + curr_cik + '\t' + curr_date + '\t' + curr_open + '\t' + \
curr_close + '\t' + curr_adj_close + '\t' + yest_open + '\t' + yest_close + '\t' + \
yest_adj_close + '\t' + curr_mkt_cap
except:
pass
def get_cached_quote(self, symbol):
key = "quote_" + symbol
valstr = memcache.get(key)
if valstr is None:
fullquote = None
try:
fullquote = ystockquote.get_all(symbol)
valstr = "%s,%s,%s,%s,%s,%s" % (fullquote['price'], fullquote['52_week_high'], fullquote['52_week_low'], fullquote['50day_moving_avg'], fullquote['200day_moving_avg'], fullquote['change'])
memcache.add(key, valstr, 60*10)
except Exception, e:
logging.error('error retrieving quote for %s (%s)', symbol, e)
def compact_quote(symbol):
symbol = 'SYK'
a = y.get_all(symbol)
L52 = int(round(float(a['fifty_two_week_low']), 0))
P = round(float(a['price']), 1)
C = a['change']
H52 = int(round(float(a['fifty_two_week_high']), 0))
PE = round(float(a['price_earnings_ratio']), 1)
Cp = int(round(float(C) / float(P) * 100))
return '{} {} {}% [{} {}] PE {}'.format(symbol, P, Cp, L52, H52, PE)
def get_bid(self, symbol):
try:
bid = yt.get_all(symbol)['bid_realtime']
except:
bid = 'No data available'
if bid == 'N/A':
print 'THE MARKET IS CLOSED - NO SALE POSSIBLE'
return -1
elif bid == 'No data available':
print bid
return -1
else:
return float(bid)
def get_ask(self, symbol):
try:
ask = yt.get_all(symbol)['ask_realtime']
except:
ask = 'No data available'
if ask == 'N/A':
print 'THE MARKET IS CLOSED - NO PURCHASE POSSIBLE'
return -1
elif ask == 'No data available':
print ask
return -1
else:
return float(ask)
def test_get_all(self):
symbol = 'GOOG'
all_info = ystockquote.get_all(symbol)
self.assertIsInstance(all_info, dict)
self.assertEqual(all_info['dividend_yield'],
ystockquote.get_dividend_yield(symbol))
self.assertEqual(all_info['fifty_sma'],
ystockquote.get_50_sma(symbol))
self.assertEqual(all_info['company_name'],
ystockquote.get_company_name(symbol))
self.assertEqual(all_info['book_value'],
ystockquote.get_book_value(symbol))
def get_bid(self, symbol):
try:
bid = yt.get_all(symbol)['bid_realtime']
except:
bid = 'No data available'
if bid=='N/A':
print 'THE MARKET IS CLOSED - NO SALE POSSIBLE'
return -1
elif bid == 'No data available':
print bid
return -1
else:
return float(bid)
def main(argv):
ticker_file = "input/tickers.txt"
bucket_name = "edgarsentimentbucket"
conn = S3Connection(argv[1], argv[2])
path_bucket = conn.get_bucket(bucket_name)
k = Key(path_bucket)
k.key = ticker_file
pathfile = k.get_contents_as_string()
try:
lines = pathfile.split('\n')
except AttributeError:
lines = pathfile
for linie in lines:
try:
ticker_arr = linie.split('\t')
curr_ticker = ticker_arr[0]
curr_cik = ticker_arr[1]
curr_date = ticker_arr[2]
if not '-' in curr_date:
curr_date = curr_date[0:4] + '-' + curr_date[4:6] + '-' + curr_date[6:8]
curr_date_obj = crteDateObj(curr_date)
yest_date_obj = curr_date_obj - timedelta(days=1)
yest_date = crteDateStr(yest_date_obj)
try:
price_dict = ystockquote.get_historical_prices(curr_ticker, yest_date, curr_date)
curr_close = price_dict[curr_date]['Close']
curr_adj_close = price_dict[curr_date]['Adj Close']
curr_open = price_dict[curr_date]['Open']
yest_close = price_dict[yest_date]['Close']
yest_adj_close = price_dict[yest_date]['Adj Close']
yest_open = price_dict[yest_date]['Close']
except:
curr_close = "NA"
curr_adj_close = "NA"
curr_open = "NA"
yest_close = "NA"
yest_adj_close = "NA"
yest_open = "NA"
try:
all_dict = ystockquote.get_all(curr_ticker)
curr_mkt_cap = all_dict['market_cap']
except:
curr_mkt_cap = "NA"
print curr_ticker + '\t' + curr_cik + '\t' + curr_date + '\t' + curr_open + '\t' + \
curr_close + '\t' + curr_adj_close + '\t' + yest_open + '\t' + yest_close + '\t' + \
yest_adj_close + '\t' + curr_mkt_cap
except:
pass
def get_ask(self, symbol):
try:
ask = yt.get_all(symbol)['ask_realtime']
except:
ask = 'No data available'
if ask=='N/A':
print 'THE MARKET IS CLOSED - NO PURCHASE POSSIBLE'
return -1
elif ask == 'No data available':
print ask
return -1
else:
return float(ask)
return 26.78
def run_sim(self,user_money,stock,price_new):
allInfo = ystockquote.get_all(tickerSymbol)
price_old = float(allInfo["price"])
time.sleep(0.3)
allInfo = ystockquote.get_all(tickerSymbol)
price_new = float(allInfo["price"])
print price_new
if price_old > price_new:
if user_money > (2*price_new):
stock += 2
user_money = user_money - (2 * price_new)
if price_old < price_new:
if stock > 0:
stock -= 1
user_money = user_money + price_new
else:
pass
print "I'm still running!"
self.balance = Label(self, text = ("Balance: $", user_money))
self.stock = Label(self, text = ("Stock:", stock))
self.price = Label(self, text = ("Price:", price_new))
self.after(2000, self.run_sim(user_money,stock,price_new))
def prices(symbol):
"""
Downloads and stores the latest quote for the given symbol
"""
all = ystockquote.get_all(symbol)
try:
download.insert(
symbol,
datetime.strptime(all['date'], '"%m/%d/%Y"').strftime('%Y-%m-%d'),
all['price'], all['high'], all['low'], all['open'])
except IntegrityError:
print "Quote for %s already stored" % symbol
except ValueError:
print "Quote for %s could not be downloaded" % symbol
def get_keystats():
import ystockquote
fi = open('keystats.csv','w')
for sym in get_sp500()[:]:
sym = correctYahoo(sym)
stats = ystockquote.get_all(sym)
for k,v in stats.items():
s = ';'.join([sym,k,v])
print s
fi.write(s + '\n')
fi.close()
'''
def get_morning_data():
"""Retrieve all data available from ystockquote for each known symbol. This
data is classified by pickers and added to past data once evening prices
are obtained. This method should be run in the morning to allow pickers
to make their picks."""
current_data = {}
for symbol in symbol_list:
print(symbol)
while True:
try:
current_data[symbol] = ys.get_all(symbol)
break
except:
sleep(1)
return current_data
def print_portfolios(args):
header = []
for h in ["SYM","PRICE","QTY", "VALUE", "COST PRICE", "COST", "CHANGE",
"TOTAL_CHG","RETURN","% GAIN"]:
header.append(colored(h,'magenta'))
def colorize(val,comparator=lambda x:'red' if x<0 else 'green'):
return colored(str(val),comparator(val))
for name,portfolio in portfolios.items():
myscrips = [
header,]
portfolio_mkt_val = 0
portfolio_pur_val = 0
portfolio_commision_cost = 0
transaction_fee = 29
print colored(name,'cyan')
print "="*80
for scrip in portfolio:
script_details = yq.get_all(scrip['sym'])
scrip_price = float(script_details['price'])
portfolio_mkt_val+=scrip_price*scrip['qty']
portfolio_pur_val+=scrip['value']*scrip['qty']
portfolio_commision_cost += scrip['brokerage']
cost = scrip['value']*scrip['qty']
price = scrip_price*scrip['qty']
total_change = (price)-(cost)
returns = ((scrip_price*scrip['qty'])-(cost))-(scrip['brokerage']*2)
percentage_gain = (float(price-cost)/float(cost))*100.0
myscrips.append([
colored(str(scrip['sym']),'white'),
colored(str(scrip_price),'white'),
colored(scrip['qty'],'white'),
colored(str(scrip_price*scrip['qty']),'white'),
colored(str(scrip['value']),'white'),
colored(cost,'white'),
colorize(scrip_price-scrip['value']),
colorize(total_change),
colorize(returns),
colorize('%.2f%%' %percentage_gain,lambda x:'red' if x.startswith('-') else 'green')
]
)
pprint_table(myscrips)
print "Portfolio: %s (value) %s (cost)" % (portfolio_mkt_val+portfolio_commision_cost,portfolio_pur_val+portfolio_commision_cost)
print "Mkt Gains: %s " % colorize(portfolio_mkt_val-portfolio_pur_val)
print "Act Gains: %s " % colorize(portfolio_mkt_val-(portfolio_pur_val+portfolio_commision_cost))
print "Total Commission:%s" % portfolio_commision_cost
def fetch_stock_data(self):
times = 1
while times == 1:
for ticker in self.stocks:
data = ystockquote.get_all(ticker)
data['ticker'] = ticker
data['time_stamp'] = datetime.datetime.now()
self.save_stock_data(data)
if data['volume'].isdigit() and data['price'].isdigit():
self.ts_volume.onSample(ticker, int( data['volume']))
self.ts_price.onSample(ticker,float(data['price']))
print('.'),
print ''
time.sleep(60)
def prices(symbol):
"""
Downloads and stores the latest quote for the given symbol
"""
all = ystockquote.get_all(symbol)
try:
download.insert(symbol,
datetime.strptime(all['date'], '"%m/%d/%Y"').strftime('%Y-%m-%d'),
all['price'],
all['high'],
all['low'],
all['open'])
except IntegrityError:
print "Quote for %s already stored" % symbol
except ValueError:
print "Quote for %s could not be downloaded" % symbol
def run(self): while not self.done: hour = str(datetime.datetime.now().time())[0:2] weekday = datetime.datetime.today().weekday() if hour == '16' and weekday in (0,1,2,3,4): self.account.getNetWorth() elif hour == '09' and weekday == 0: for stock in self.stockList: dataDict = ys.get_all(stock) if self.checkData(dataDict): sum = self.innerProd(dataDict) if sum > 103910000: self.buy(stock) if sum < 10391: self.sell(stock) time.sleep(3600) else: time.sleep(3600)
def show_news():
display_date = time.strftime("%A %B %d")
URL = 'https://www.google.com/finance/category_news?catid=TRBC%3A54&ei=khXDVOnREfCBsgfA7IHACw'
response = requests.get(URL)
soup = BeautifulSoup(response.content)
story = {'title': None, 'link': None, 'ticker': None,'price':None,
'market_cap':None,'avg_daily_vol':None,'eps':None,
'fiftytwo_low':None,'fiftytwo_high':None,'exchange':None,
'pe_ratio':None,'pe_growth_ratio':None,'short_ratio':None}
stories = []
for listing in soup.find_all('div',{'class':'g-section news sfe-break-bottom-16'}):
headline = listing.find('span',{'class':'name'})
clean = unicodedata.normalize('NFKD', headline.text).encode('ascii','ignore')
stripped= clean.strip('\n')
story['title'] = stripped
story['link'] =headline.a['href']
match = re.compile( "\((.*)\)" ).search(stripped)
if match is not None:
ticker = match.group(1)
story['ticker'] = ticker
if len(ticker)<6:
ydata = ystockquote.get_all(ticker)
story['price'] = ydata['price']
story['exchange'] = ydata['stock_exchange']
story['market_cap'] = ydata['market_cap']
story['avg_daily_vol'] = ydata['avg_daily_volume']
story['eps'] = ydata['earnings_per_share']
story['fiftytwo_low'] = ydata['fifty_two_week_low']
story['fiftytwo_high'] = ydata['fifty_two_week_high']
story['pe_ratio'] = ydata['price_earnings_ratio']
story['pe_growth_ratio'] = ydata['price_earnings_growth_ratio']
story['short_ratio'] = ydata['short_ratio']
else:
story['ticker'] = None
stories.append(story.copy())
return render_template('index.html', estimates=stories, date = display_date)
s.quit()
"""
Fetch data (from yahoo) and determine if this is a reversal indicator
"""
# yesterday's date
end = current_datetime - datetime.timedelta(days=1)
# 30 days ago from today
start = current_datetime - datetime.timedelta(days=30)
# fetch the historical data from yahoo
data = ystockquote.get_historical_prices('^' + SYMBOL,
start.strftime("%Y-%m-%d"),
end.strftime("%Y-%m-%d"))
all_data = ystockquote.get_all('^' + SYMBOL)
# validate that we have enough historical data to continue
if len(data) < days_back:
print 'Not enough historical data available to continue (need at least 15 days of market data)'
sys.exit(1)
current = ystockquote.get_last_trade_price('^' + SYMBOL)
open = float(all_data['today_open'])
high = float(all_data['todays_high'])
low = all_data['todays_low']
# if the current price is higher than the open and today is a new 15-day low,
# then this is a SELL indicator
if (isCurrentHigherThanOpen(current, open) & isNewLow(low, data)):
#print 'today is a 15-day low (' + str(low) + ') & the current price (' + str(current) + ') is higher than the open (' + str(open) + ')'
def convert(x, from_symbol, to_symbol):
from_symbol = from_symbol.upper()
to_symbol = to_symbol.upper()
from_type = identify_symbol(from_symbol)
to_type = identify_symbol(to_symbol)
y = None
if from_symbol == to_symbol:
return x
if from_type is None:
warn('converter: did not recognise from_symbol "%s", returning NaN!' %
from_symbol)
return np.nan
elif from_type == 'ISIN' or to_type == 'ISIN':
warn('converter: cannot currently convert assets to or from ISIN, '
'returning NaN!')
return np.nan
elif from_type == 'altcoin' or to_type == 'altcoin':
warn('converter: cannot currently convert assets to or from altcoins, '
'returning NaN!')
return np.nan
elif to_type is None:
warn('converter: did not recognise to_symbol "%s", returning NaN!' %
to_symbol)
return np.nan
else:
try:
# from bitcoin to something
if from_type == 'bitcoin':
bconv = fx.bitcoin.BtcConverter()
if to_type != 'currency':
x = bconv.convert_btc_to_cur(x, 'EUR')
y = convert(x, 'EUR', to_symbol)
else:
y = bconv.convert_btc_to_cur(x, to_symbol)
# from something to bitcoin
elif to_type == 'bitcoin':
if from_type != 'currency':
x = convert(x, from_symbol, 'EUR')
from_symbol = 'EUR'
bconv = fx.bitcoin.BtcConverter()
y = bconv.convert_to_btc(x, from_symbol)
# from stock/fund to something
elif from_type == 'yahoo':
from_groups = symbol_re.match(from_symbol).groups()
stock_info = ystockquote.get_all(from_symbol)
price = convert(float(stock_info['price']),
currency_map[from_groups[1]], to_symbol)
y = x * price
# from something to stock/fund
elif to_type == 'yahoo':
to_groups = symbol_re.match(to_symbol).groups()
stock_info = ystockquote.get_all(to_symbol)
price = convert(float(stock_info['price']),
currency_map[to_groups[1]], from_symbol)
y = x / price
# from currency to currency
elif from_type == 'currency' and to_type == 'currency':
cconv = fx.converter.CurrencyRates()
y = cconv.convert(from_symbol, to_symbol, x)
except Exception as err:
warn('converter: unexpected error ({}) during conversion, '
'returning NaN!'.format(err))
return np.nan
if y is None:
y = np.nan
warn('converter: did not recognise one of the symbols, returning NaN!')
return y
#print colored(elem + ": " + price + " " + change, 'green')
except Exception:
print("Debug: Post Quote exception")
pass
# Quote on first line + price info on second line
lcd.message(empty_space + quote + '\n' + empty_space + price + ' ' +
change)
for i in range(lcd_columns):
time.sleep(0.35)
lcd.move_left()
return 0
##############################################################################
# Run in a loop
while 1:
with open('/home/pi/StockQuote/quotelist') as f:
tickerSymbol = f.read().splitlines()
# parse the ticker symbol list for individual symbols and print out current price and change since previous days close.
for elem in tickerSymbol:
try:
allInfo = ystockquote.get_all(elem)
except Exception:
print("Debug: Hit Exception...ignore")
pass
post_quote(elem, allInfo["price"], allInfo["change"])
def test_get_all(self):
all_info = ystockquote.get_all(self.symbol)
self.assertIsInstance(all_info, dict)
p = all_info['price']
self.assertIsInstance(p, str)
self.assertGreater(float(p), 0.0)
def test_get_all(self):
all_info = ystockquote.get_all(self.symbol)
self.assertIsInstance(all_info, dict)
p = all_info['dividend_yield']
self.assertIsInstance(p, str)
def main():
# ticker_file = "input/tickers.txt"
# bucket_name = "edgarsentimentbucket"
# conn = S3Connection(argv[1], argv[2])
# path_bucket = conn.get_bucket(bucket_name)
# k = Key(path_bucket)
# k.key = ticker_file
# pathfile = k.get_contents_as_string()
# try:
# lines = pathfile.split('\n')
# except AttributeError:
# lines = pathfile
try:
print "started"
# for linie in open(ticker_file, "r"):
for linie in sys.stdin:
try:
print linie
ticker_arr = linie.split('\t')
curr_ticker = ticker_arr[1]
curr_cik = ticker_arr[2]
curr_date = ticker_arr[3]
if not '-' in curr_date:
curr_date = curr_date[0:4] + '-' + curr_date[
4:6] + '-' + curr_date[6:8]
curr_date = curr_date.strip()
curr_date_obj = crteDateObj(curr_date)
yest_date_obj = curr_date_obj - timedelta(days=1)
yest_date = crteDateStr(yest_date_obj)
try:
price_dict = ystockquote.get_historical_prices(
curr_ticker, yest_date, curr_date)
curr_close = price_dict[curr_date]['Close']
curr_adj_close = price_dict[curr_date]['Adj Close']
curr_open = price_dict[curr_date]['Open']
yest_close = price_dict[yest_date]['Close']
yest_adj_close = price_dict[yest_date]['Adj Close']
yest_open = price_dict[yest_date]['Close']
except:
curr_close = "NA"
curr_adj_close = "NA"
curr_open = "NA"
yest_close = "NA"
yest_adj_close = "NA"
yest_open = "NA"
try:
all_dict = ystockquote.get_all(curr_ticker)
curr_mkt_cap = all_dict['market_cap']
except:
curr_mkt_cap = "NA"
print curr_ticker + '\t' + curr_cik + '\t' + curr_date + '\t' + curr_open + '\t' + \
curr_close + '\t' + curr_adj_close + '\t' + yest_open + '\t' + yest_close + '\t' + \
yest_adj_close + '\t' + curr_mkt_cap
except:
print "bad"
except:
print "didn't start"
def lightsOut():
# Turn off all the LEDs.
if debug == 1:
print ('Turning off all LEDs.')
sense.clear()
def marketClosed():
print "Stock Market Closed.", now
lightsOut()
time.sleep(60)
atexit.register(lightsOut)
if debug == 1:
allInfo = ystockquote.get_all(tickerSymbol)
print allInfo
# quote = ystockquote.get_change(tickerSymbol)
# print quote
# print tickerSymbol + " Price = " + allInfo["price"]
# print tickerSymbol + " Change = " + allInfo["change"]
# print allInfo["change"]
# print allInfo
getcontext().prec = 8
def getQuote(change):
if debug == 1:
print "Function getQuote"
self.counter = counter
self.target_value = target_value
def run(self):
print "Starting Polling"
stock_polling(self.name, self.target_value)
print "exiting polling"
def stock_polling(stock_name,target_value):
while float(ystockquote.get_price(stock_name)) <= float(target_value):
print "stock value not reached" + ystockquote.get_price(stock_name)
time.sleep(60)
print "yay - stock value at " + ystockquote.get_price(stock_name)
stock_name = raw_input('Enter the stock name: ')
stock_target = raw_input ('Enter the stock target price: ')
#email = raw_input('Enter your email address')
#stock_name = "AAPL"
#stock_target = "25"
print stock_name, stock_target
pprint.pprint(ystockquote.get_all(stock_name))
thread1 = StockPollingThread(1,stock_name,stock_target,1)
thread1.start()
sys.exit()
#!/usr/bin/python
#coding=utf8
import ystockquote
#获取该股票所有信息
print ystockquote.get_all('GOOG')
#获取当前股价
print ystockquote.get_ask_realtime('GOOG')
#获取2012.11.22到2013.10.1历史报价
print ystockquote.get_historical_prices("GOOG", '2012.11.22', '2013.10.1')
def getStockPrice(self):
allInfo = ystockquote.get_all(self.name)
return float(allInfo["price"])
#print("\nReading Dropbox account access token from external file...")
#access_token = open(access_token, "r")
#print("Done.")
# Link script to my Dropbox account
#dbx = dropbox.Dropbox('access_token')
#print("\nSuccessfully linked to Dropbox account.")
# Open file with data
data_file = open(data_file, "w")
# Dictionary for pure stock data
pure_stock_data = {}
# Save stock data to dictionary keys
pure_stock_data['ORCL'] = ystockquote.get_all('ORCL')
pure_stock_data['GOOG'] = ystockquote.get_all('GOOG')
pure_stock_data['FB'] = ystockquote.get_all('FB')
pure_stock_data['YHOO'] = ystockquote.get_all('YHOO')
pure_stock_data['MSFT'] = ystockquote.get_all('MSFT')
pure_stock_data['AAPL'] = ystockquote.get_all('AAPL')
pure_stock_data['BIDU'] = ystockquote.get_all('BIDU')
pure_stock_data['ATVI'] = ystockquote.get_all('ATVI')
pure_stock_data['ADBE'] = ystockquote.get_all('ADBE')
# Write data with ticker symbol label to file
data_file.write("ORCL:\n")
data_file.write(str(pure_stock_data.get('ORCL', "!")))
data_file.write("\n\nGOOG:\n")
data_file.write(str(pure_stock_data.get('GOOG', "!")))
def get_ticks():
print "%(1)s %(2)s %(3)s %(4)s %(5)s %(6)s" % {
"1": "SYMBOLS".ljust(12),
"2": "Price".rjust(8),
"3": "Change".rjust(8),
"4": "Bought".rjust(8),
"5": "Vol(%)".rjust(8),
"6": "Action".ljust(5)
}
for stock in stocks:
data = ystockquote.get_all(stock[1])
prices.append((stock[0], data['price']))
thisprices = []
for price in prices:
if price[0] == stock[0]:
thisprices.append(float(price[1]))
thisprevsma = data['price']
for price in prevsma:
if price[0] == stock[0]:
thisprevsma = price[1]
thisprevema = data['price']
for price in prevema:
if price[0] == stock[0]:
thisprevema = price[1]
bar = len(thisprices) - 1
currentsma = running_sma(bar, thisprices, 3, float(thisprevsma))
currentema = ema(bar,
thisprices,
period,
float(thisprevema),
smoothing=None)
Hit = False
for i, value in enumerate(prevsma):
if prevsma[i] == stock[0]:
Hit = True
prevsma[i] = currentsma
if Hit == False:
prevema.append((stock[0], currentsma))
Hit = False
for i, value in enumerate(prevema):
if prevema[i] == stock[0]:
Hit = True
prevema[i] = currentema
if Hit == False:
prevema.append((stock[0], currentema))
action = ""
if float(currentsma) > float(currentema):
action = "long"
elif float(currentema) > float(currentsma):
action = "short"
vol = 0
if float(data['volume']) > 0 and float(data['avg_daily_volume']) > 0:
vol = "{0:.2f}".format(
(float(data['volume']) / float(data['avg_daily_volume'])) *
100)
color = Color_It(data['price'], stock[2])
print colored(
"%(1)s %(2)s %(3)s %(4)s %(5)s %(6)s" % {
"1": stock[0].ljust(12),
"2": data['price'].rjust(8),
"3": data['change'].rjust(8),
"4": str(stock[2]).rjust(8),
"5": str(vol).rjust(8),
"6": action.ljust(5)
}, color)
#exemplo de utilizacao da biblioteca ystockquote
import ystockquote
print "Google share price: " + ystockquote.get_price('GOOG')
print "OGX share price: " + ystockquote.get_price('OGXP3.SA')
print "Petrobras share price: " + ystockquote.get_price('PETR4.SA')
print
print "Petrobras details"
print ystockquote.get_all('PETR4.SA')
# -*- coding: utf8 -*-
import ystockquote
# print(ystockquote.get_price_book("PETR4"))
# print(ystockquote.get_bid_realtime('GOOGL'))
print("Ola --- ooo989898")
v = ystockquote.get_all("RAPT4.sa")
p = v['price']
c = v['change']
print("Valor:")
print v
print("Preço: %s") % (str(p))
print("Oscilação: %s") % (str(c))
d = p + (c * -1)
print("Preço Fechamento: %s") % (str(d))
def plot_price(name):
f, axs = plt.subplots(4, 1, figsize=(8, 10))
url = 'http://chartapi.finance.yahoo.com/instrument/1.0/' + name + '/chartdata;type=quote;range=1d/csv'
req = ystockquote.Request(url)
resp = ystockquote.urlopen(url)
content = resp.read().split('\n')[:-1]
for n in range(len(content)):
if content[n].find('previous_close') == 0:
previous_close = float(content[n].replace('previous_close:', ''))
if content[n].find(':') == -1:
break
content = content[n:]
timestamp, close, high, low, open1, volume = array(
[tmp.split(',') for tmp in content], dtype=float).T
url = 'http://finance.yahoo.com/d/quotes.csv?s=' + name + '&f=aba5b6'
req = ystockquote.Request(url)
resp = ystockquote.urlopen(url)
content = resp.read().split('\n')[0].split(',')
ask, bid, askSize, bidSize = content
# 1 day
datime = [datetime.datetime.fromtimestamp(tmp) for tmp in timestamp]
axs[0].plot(datime, open1)
axs[0].plot([datime[0], datime[0] + datetime.timedelta(0, 23400)],
previous_close * ones(2), ':')
axs[0].grid('on')
axs[0].set_xlim(datime[0], datime[0] + datetime.timedelta(0, 23400))
# duo days
for n, N in enumerate([30, 365, 1826]):
datime = [
datetime.datetime.now() + datetime.timedelta(days=i)
for i in range(-N, 1)
]
quote = ystockquote.get_historical_prices(
name, datime[0].strftime('%Y-%m-%d'),
datime[-1].strftime('%Y-%m-%d'))
datime = sorted([
datetime.datetime.strptime(tmp, '%Y-%m-%d')
for tmp in quote.keys()
])
quote = [quote[tmp]['Adj Close'] for tmp in sorted(quote)]
axs[n + 1].plot(datime, quote)
axs[n + 1].grid('on')
for ax in axs:
plt.setp(ax.xaxis.get_majorticklabels(), rotation=12)
plt.subplots_adjust(left=0.06,
bottom=0.05,
right=0.95,
top=0.98,
wspace=0.05,
hspace=0.3)
f.canvas.set_window_title(name)
# bid
axs[0].text(0.95,
0.95,
'bid: ' + bid + 'x' + bidSize + ' ' + 'ask: ' + ask + 'x' +
askSize,
verticalalignment='top',
horizontalalignment='right',
transform=axs[0].transAxes,
fontsize=15)
axs[0].text(0.70,
0.80,
str(close[-1]),
verticalalignment='top',
horizontalalignment='right',
color='b',
transform=axs[0].transAxes,
fontsize=15)
color = 'r' * int(close[-1] < previous_close) + 'g' * int(
close[-1] > previous_close) + '0.5' * int(close[-1] == previous_close)
axs[0].text(
0.95,
0.80,
'%+-.2f' % (close[-1] - previous_close) + ' %+-.2f' %
(float(close[-1] - previous_close) / float(previous_close) * 100) +
'%',
verticalalignment='top',
horizontalalignment='right',
color=color,
transform=axs[0].transAxes,
fontsize=15)
# stuff
all1 = ystockquote.get_all(name)
print bcolors.Bold + name + ' ' + bcolors.Blue + str(
close[-1]) + bcolors.ENDC
if float(all1['change']) > 0:
print bcolors.Green + all1['change'] + ' +' + '%.2f' % (
float(close[-1] - previous_close) / float(all1['price']) *
100) + '%' + bcolors.ENDC
else:
print bcolors.Red + all1['change'] + ' ' + '%.2f' % (
float(close[-1] - previous_close) / float(all1['price']) *
100) + '%' + bcolors.ENDC
print '---------------------'
# pprint(all1)
return close[-1]
def __init__(self, symbol="TSLA"):
self.symbol = symbol
self.all_info = ystockquote.get_all(self.symbol)
def collect_firmo(self):
return ystockquote.get_all(self.symbol)
