def create_datasets(company): # 'AAPL','GOOG' df_1 = (intrinio.prices(company)) df_2 = (intrinio.financials(company)) df_1.to_csv(company+'_prices.csv') df_2.to_csv(company+'_financials.csv') return
def test_prices(self):
if local:
inject_response("prices_aapl.json")
r = intrinio.prices("AAPL")
if local:
self.assertEqual(len(r), 2)
self.assertEqual(r[0].date, "2016-09-23")
self.assertEqual(r[1].adj_open, 114.35)
else:
self.assertGreater(len(r), 0)
def price_extract(ticker):
price = intrinio.prices(ticker, start_date=2008, frequency="yearly", sort_order='asc')
price.index = pd.to_datetime(price.index, format="%Y-%m-%d")
price["year"] = pd.DatetimeIndex(price.index).year
price = price[price.index > "2008-12-31"]
price_norm = pd.concat((Normalisation(price.drop("year", axis=1)), price["year"]), axis=1)
return price, price_norm
def getData(self, ticker):
data = {}
dataTag = "yearlyprices"
if not os.path.exists(self.cacheData.filename(ticker, dataTag)):
print "getting %s data for %s" % (dataTag, ticker)
data[dataTag] = intrinio.prices(ticker,
start_date=PRICES_PULL_START_DATE,
frequency="yearly")
self.cacheData.save(data[dataTag], ticker, dataTag)
else:
data[dataTag] = self.cacheData.open(ticker, dataTag)
dataTag = "income_statement"
if not os.path.exists(self.cacheData.filename(ticker, dataTag)):
print "getting %s data for %s" % (dataTag, ticker)
data[dataTag] = intrinio.financials(ticker, "FY", dataTag)
self.cacheData.save(data[dataTag], ticker, dataTag)
else:
data[dataTag] = self.cacheData.open(ticker, dataTag)
dataTag = "balance_sheet"
if not os.path.exists(self.cacheData.filename(ticker, dataTag)):
print "getting %s data for %s" % (dataTag, ticker)
data[dataTag] = intrinio.financials(ticker, "FY", dataTag)
self.cacheData.save(data[dataTag], ticker, dataTag)
else:
data[dataTag] = self.cacheData.open(ticker, dataTag)
dataTag = "cash_flow_statement"
if not os.path.exists(self.cacheData.filename(ticker, dataTag)):
print "getting %s data for %s" % (dataTag, ticker)
data[dataTag] = intrinio.financials(ticker, "FY", dataTag)
self.cacheData.save(data[dataTag], ticker, dataTag)
else:
data[dataTag] = self.cacheData.open(ticker, dataTag)
dataTag = "calculations"
if not os.path.exists(self.cacheData.filename(ticker, dataTag)):
print "getting %s data for %s" % (dataTag, ticker)
data[dataTag] = intrinio.financials(ticker, "FY", dataTag)
self.cacheData.save(data[dataTag], ticker, dataTag)
else:
data[dataTag] = self.cacheData.open(ticker, dataTag)
return data
def run(self):
offscreen_canvas = self.matrix.CreateFrameCanvas()
font = graphics.Font()
font.LoadFont("../../../fonts/5x8.bdf")
stockColor = graphics.Color(0, 50, 255)
pos = offscreen_canvas.width
intrinio.client.username = '******'
intrinio.client.password = '******'
value = intrinio.prices('GOOGL', start_date='2018-04-13')
stock_text = 'GOOGL '
stock_text = stock_text + str(value.iloc[0][5])
percentChange = (
(value.iloc[0][5] - value.iloc[0][9]) / value.iloc[0][5]) * 100
if (percentChange < 0):
percent_text = '∇'
percentColor = graphics.Color(255, 0, 0)
elif (percentChange > 0):
percent_text = 'Δ'
percentColor = graphics.Color(0, 255, 0)
else:
percentColor = graphics.Color(0, 0, 255)
percent_text = percent_text + str(abs(round(Decimal(percentChange),
2)))
percent_text = (' ' *
(len(stock_text) - len(percent_text))) + percent_text
while True:
offscreen_canvas.Clear()
length = graphics.DrawText(offscreen_canvas, font, pos, 7,
stockColor, stock_text)
len2 = graphics.DrawText(offscreen_canvas, font, pos, 14,
percentColor, percent_text)
pos -= 1
if (pos + length < 0):
pos = offscreen_canvas.width
time.sleep(0.05)
offscreen_canvas = self.matrix.SwapOnVSync(offscreen_canvas)
x for x in input_fields[input_fields["parent"] == "Yes"]["code_or_ticker"]
]
tick = [x for x in input_fields[input_fields["parent"] == "Yes"]["ticker"]]
year = int(2007)
import intrinio
intrinio.client.username = '******'
intrinio.client.password = '******'
for tic, cod in zip(tick, code):
# for tic, code in zip(["BKC"],["BKC"]):
start = datetime(year, 1, 1)
end = datetime.now()
r = intrinio.prices(tic, start_date=str(year) + '-01-01')
df_tick = r.rename(columns={'adj_volume': 'volume'})
df_tick = df_tick.reset_index()
df_tick = df_tick.rename(
columns={
'Volume': 'volume',
'Close': 'close',
'High': 'high',
'Low': 'low',
'Open': 'open',
'Date': 'date'
})
my_path = os.path.abspath(os.path.dirname('__file__'))
path = os.path.join(my_path, "../data/stock/")
df_tick.to_csv(path + cod + "_parent_tick_df.csv")
import intrinio
import psycopg2
import pandas as pd
intrinio.client.username = ''
intrinio.client.password = ''
Location = "./NAS.csv"
Location2 = "./NYSE.csv"
df = pd.read_csv(Location)
df2 = pd.read_csv(Location2)
dfticker = df["Symbol"]
df2ticker = df2["Symbol"]
lista = dfticker.append(df2ticker)
password = input("Please Enter the Password for the Postgres Database: ")
connectionSTR = "dbname='postgres' user='******' host='dev-datafactory-postgresql.csodrrohkuas.us-east-1.rds.amazonaws.com' password="******"INSERT INTO historical VALUES ('{i}', '{prices}');"
cur.execute(insert)
conn.commit()
pass
print(start_line)
# reads the file of all stocks, retrieves symbol, uses intrinio api to retrieve historical data from january 1, 2016 to present, and writes to csv
with open("../data/all_stocks.txt", "r") as f:
for i, line in enumerate(f):
if i < start_line:
continue # passes through until last line parsed is reached
print(line)
sym, rest = line.split("|", 1) # retrieves symbol
print(sym)
try:
x = intrinio.prices(sym)
x.to_csv('../data/raw/' + sym)
except requests.exceptions.HTTPError as err:
# if the api limit is reached, write ending line and exit
if err.response.status_code == 429:
print("limit reached at line " + str(i) + "...exiting")
with open('../data/start_line.txt', 'w') as outfile:
outfile.write(str(i))
sys.exit()
else:
with open('../errors', 'a') as outfile:
outfile.write("error with " + sym + ", code: " +
str(err.response.status_code))
# first install the required package via this cli command: # pip install requests import intrinio intrinio.client.username = "******" intrinio.client.password = "******" company = "Apple" ticker = "AAPL" start_date = "2018-07-01" prices = intrinio.prices(ticker, start_date) info = intrinio.companies(ticker) search = intrinio.companies(query=company) financials = intrinio.financials(ticker) print(info) print(search) print(financials)
def run(self):
offscreen_canvas = self.matrix.CreateFrameCanvas()
font = graphics.Font()
# load the font displayed to screen (letter dimension
font.LoadFont("../../../fonts/5x8.bdf")
pos = offscreen_canvas.width
# important data for accessing the stock API (pulls information)
intrinio.client.username = '******'
intrinio.client.password = '******'
# get the yesterday
yesterday = date.today() - timedelta(7)
dateCheck = yesterday.strftime("%Y-%m-%d")
# print the current date
print("dateCheck = " + str(dateCheck))
# list to hold stocks
stockdata = []
# list to hold the percentage change
changedata = []
# list to hold colors of the stock
stockcolors = []
# list to hold color of percent
percentcolors = []
# loop thru the stocks listed in
for i in stockConfig.stocks:
# get value for current day (today)
value = intrinio.prices(i['symbol'], dateCheck)
stock_text = i['symbol']
stock_text = stock_text + ' ' + str(value.iloc[0][5])
stockdata.append(stock_text)
stockColor = graphics.Color(i['red'], i['green'], i['blue'])
stockcolors.append(stockColor)
percentChange = (
(value.iloc[0][5] - value.iloc[0][9]) / value.iloc[0][5]) * 100
if (percentChange < 0):
percent_text = '∇'
percentColor = graphics.Color(255, 0, 0)
elif (percentChange > 0):
percent_text = 'Δ'
percentColor = graphics.Color(0, 255, 0)
else:
percentColor = graphics.Color(0, 0, 255)
percent_text = percent_text + str(
abs(round(Decimal(percentChange), 2)))
percent_text = (
' ' * (len(stock_text) - len(percent_text))) + percent_text
changedata.append(percent_text)
percentcolors.append(percentColor)
currentStock = 0
while True:
offscreen_canvas.Clear()
length = graphics.DrawText(offscreen_canvas, font, pos, 7,
stockcolors[currentStock],
stockdata[currentStock])
len2 = graphics.DrawText(offscreen_canvas, font, pos, 14,
percentcolors[currentStock],
changedata[currentStock])
pos -= 1
if (pos + length < 0):
pos = offscreen_canvas.width
currentStock += 1
if (currentStock >= len(stockdata)):
currentStock = 0
time.sleep(0.07)
offscreen_canvas = self.matrix.SwapOnVSync(offscreen_canvas)
'username': '',
'password': '',
'provider': 'iex',
'on_quote': on_quote
}
client = IntrinioRealtimeClient(options)
client.join(['AAPL', 'GE', 'MSFT'])
client.connect()
client.keep_alive()
'''
data_stock_prices = intrinio.prices('ATVI')#, start_date='2000-01-01')
data_financials = intrinio.financials('AAPL')
intrinio.companies('GOOG')
data_stock_prices.info()
atvi_adjclose = pd.Series(data_stock_prices.adj_close)
atvi_adjclose_norm = atvi_adjclose/atvi_adjclose[len(atvi_adjclose)-1]*100
atvi_adjclose_norm = atvi_adjclose_norm.rename("ATVI")
spy_prices = intrinio.prices('SPY', start_date='1993-10-25')
try:
fudamentals_calculations = intrinio.financials(
ticker, type='QTR', statement='calculations')
if fudamentals_calculations is not None:
filename = ticker + '_fudamentals_calculations.csv'
file_to_open = os.path.join(data_folder, filename)
fudamentals_calculations.to_csv(file_to_open, encoding='utf-8')
else:
print('%s (%s) Ignored - Doesnt have calcs.' % (ticker, i))
continue
except (AttributeError, ValueError) as e:
print('%s (%s) Ignored - Doesnt have calcs.' % (ticker, i))
continue
# Price
try:
price = intrinio.prices(ticker, frequency='quarterly')
if price.empty == False:
filename = ticker + '_price.csv'
file_to_open = os.path.join(data_folder, filename)
price.to_csv(file_to_open, encoding='utf-8')
else:
print('%s (%s) Ignored - Doesnt have price.' % (ticker, i))
continue
except (AttributeError, ValueError) as e:
print('%s (%s) Ignored - Doesnt have price.' % (ticker, i))
continue
# Cash
try:
fudamentals_caseflow = intrinio.financials(
ticker, type='QTR', statement='cash_flow_statement')
if fudamentals_caseflow is not None:
intrinio.client.password = #Get your own password!
#Extract common dates and adjusted closing
#prices; adjusted closes allow total return
#computation
#returns will start one period later than startdate
startdate='1997-12-31'
#Intrinio uses 12-31 even if it's not a business day
enddate=LastYearEnd()[:4]+'-12-31'
tickerlist=['ORCL','ED','F']
for i,t in enumerate(tickerlist):
#This can be very slow
print('Getting ticker',t)
df1=intrinio.prices(t,sort_order='ASC', \
start_date=startdate,end_date=enddate, \
frequency='monthly')
#Get rid of everything except adjusted close
df1.drop(['adj_high','adj_low','adj_open', \
'adj_volume','adj_factor','close', \
'high','low','open','split_ratio', \
'volume','ex_dividend'],axis='columns',inplace=True)
df1.rename({'adj_close':t},axis='columns',inplace=True)
if i==0:
dfcomb=df1
else:
dfcomb=dfcomb.join(df1)
#Combined dataframe dfcomb now has a column
#with adjusted closes of each ticker.
#Form log-returns
# base_url = "https://api.intrinio.com"
#
# # Get the latest FY Income Statement for AAPL
# ticker = "AAPL"
# request_url = base_url + "/financials/standardized"
# query_params = {
# 'ticker': ticker,
# 'statement': 'income_statement',
# 'type': 'FY'
# }
#
# response = requests.get(request_url, params=query_params, auth=(api_username, api_password))
# if response.status_code == 401: print("Unauthorized! Check your username and password."); exit()
#
# data = response.json()['data']
#
# for row in data:
# tag = row['tag']
# value = row['value']
# print(tag + ": " + str(value))
import intrinio
#
intrinio.client.username = ''
intrinio.client.password = ''
print(intrinio.prices('AAPL'))
#print(intrinio.companies('GOOG'))
#print(intrinio.companies(query='Popeyes'))
