def get_close(sym):
start = time.time()
try:
symbol = Stock(sym)
symclose = symbol.get_close()
except:
symclose = alternative_close(sym)
end = time.time()
#print(f'{sym} close generation took {end-start} seconds')
return symclose
class TestFieldMethodsBatch(object):
def setup_class(self):
self.batch = Stock(["AAPL", "TSLA"])
self.batch2 = Stock(["AAPL", "TSLA"], output_format='pandas')
self.batch4 = Stock(["AAPL", "TSLA"],
json_parse_int=Decimal,
json_parse_float=Decimal)
def test_get_company_name(self):
data = self.batch.get_company_name()
assert isinstance(data, dict)
assert data["AAPL"] == "Apple Inc."
data2 = self.batch2.get_company_name()
assert isinstance(data2, pd.DataFrame)
assert_index_equal(data2.index, pd.Index(self.batch2.symbols))
def test_get_primary_exchange(self):
data = self.batch.get_primary_exchange()
assert isinstance(data, dict)
assert data["AAPL"] == "Nasdaq Global Select"
data2 = self.batch2.get_primary_exchange()
assert isinstance(data2, pd.DataFrame)
assert_index_equal(data2.index, pd.Index(self.batch2.symbols))
def test_get_sector(self):
data = self.batch.get_sector()
assert isinstance(data, dict)
assert data["AAPL"] == "Technology"
data2 = self.batch2.get_sector()
assert isinstance(data2, pd.DataFrame)
assert_index_equal(data2.index, pd.Index(self.batch2.symbols))
def test_get_open(self):
data = self.batch.get_open()
assert isinstance(data, dict)
assert data["AAPL"] > 0
data2 = self.batch2.get_open()
assert isinstance(data2, pd.DataFrame)
assert_index_equal(data2.index, pd.Index(self.batch2.symbols))
assert data2.loc["AAPL"].dtype == "float64"
def test_get_close(self):
data = self.batch.get_close()
assert isinstance(data, dict)
assert data["AAPL"] > 0
data2 = self.batch2.get_close()
assert isinstance(data2, pd.DataFrame)
assert_index_equal(data2.index, pd.Index(self.batch2.symbols))
assert data2.loc["AAPL"].dtype == "float64"
def test_get_years_high(self):
data = self.batch.get_years_high()
assert isinstance(data, dict)
assert data["AAPL"] > 0
data2 = self.batch2.get_years_high()
assert isinstance(data2, pd.DataFrame)
assert_index_equal(data2.index, pd.Index(self.batch2.symbols))
assert data2.loc["AAPL"].dtype == "float64"
def test_get_years_low(self):
data = self.batch.get_years_low()
assert isinstance(data, dict)
assert data["AAPL"] > 0
data2 = self.batch2.get_years_low()
assert isinstance(data2, pd.DataFrame)
assert_index_equal(data2.index, pd.Index(self.batch2.symbols))
assert data2.loc["AAPL"].dtype == "float64"
def test_get_ytd_change(self):
data = self.batch.get_ytd_change()
assert isinstance(data, dict)
data2 = self.batch2.get_ytd_change()
assert isinstance(data2, pd.DataFrame)
assert_index_equal(data2.index, pd.Index(self.batch2.symbols))
assert data2.loc["AAPL"].dtype == "float64"
def test_get_volume(self):
data = self.batch.get_volume()
assert isinstance(data, dict)
assert data["AAPL"] > 50000
data2 = self.batch2.get_volume()
assert isinstance(data2, pd.DataFrame)
assert_index_equal(data2.index, pd.Index(self.batch2.symbols))
assert data2.loc["AAPL"].dtype == "int64"
def test_get_market_cap(self):
data = self.batch.get_market_cap()
assert isinstance(data, dict)
assert data["AAPL"] > 1000000
data2 = self.batch2.get_market_cap()
assert isinstance(data2, pd.DataFrame)
assert_index_equal(data2.index, pd.Index(self.batch2.symbols))
assert data2.loc["AAPL"].dtype == "int64"
def test_get_beta(self):
data = self.batch.get_beta()
assert isinstance(data, dict)
assert isinstance(data["AAPL"], float)
data2 = self.batch2.get_beta()
assert isinstance(data2, pd.DataFrame)
assert_index_equal(data2.index, pd.Index(self.batch2.symbols))
assert data2.loc["AAPL"].dtype == "float64"
data4 = self.batch4.get_beta()
assert isinstance(data4, dict)
assert isinstance(data4["AAPL"], Decimal)
def test_get_short_interest(self):
data = self.batch.get_short_interest()
assert isinstance(data, dict)
assert data["AAPL"] > 50000
data2 = self.batch2.get_short_interest()
assert isinstance(data2, pd.DataFrame)
assert_index_equal(data2.index, pd.Index(self.batch2.symbols))
assert data2.loc["AAPL"].dtype == "int64"
def test_get_short_ratio(self):
data = self.batch.get_short_ratio()
assert isinstance(data, dict)
assert isinstance(data["AAPL"], float)
data2 = self.batch2.get_short_ratio()
assert isinstance(data2, pd.DataFrame)
assert_index_equal(data2.index, pd.Index(self.batch2.symbols))
assert data2.loc["AAPL"].dtype == "float64"
data4 = self.batch4.get_short_ratio()
assert isinstance(data4, dict)
assert isinstance(data4["AAPL"], Decimal)
def test_get_latest_eps(self):
data = self.batch.get_latest_eps()
assert isinstance(data, dict)
assert isinstance(data["TSLA"], float)
data2 = self.batch2.get_latest_eps()
assert isinstance(data2, pd.DataFrame)
assert_index_equal(data2.index, pd.Index(self.batch2.symbols))
assert data2.loc["TSLA"].dtype == "float64"
data4 = self.batch4.get_latest_eps()
assert isinstance(data4, dict)
assert isinstance(data4["AAPL"], Decimal)
def test_get_shares_outstanding(self):
data = self.batch.get_shares_outstanding()
assert isinstance(data, dict)
assert data["AAPL"] > 100000
data2 = self.batch2.get_shares_outstanding()
assert isinstance(data2, pd.DataFrame)
assert_index_equal(data2.index, pd.Index(self.batch2.symbols))
assert data2.loc["AAPL"].dtype == "int64"
def test_get_float(self):
data = self.batch.get_float()
assert isinstance(data, dict)
assert data["AAPL"] > 1000000
data2 = self.batch2.get_float()
assert isinstance(data2, pd.DataFrame)
assert_index_equal(data2.index, pd.Index(self.batch2.symbols))
assert data2.loc["AAPL"].dtype == "int64"
def test_get_eps_consensus(self):
data = self.batch.get_eps_consensus()
assert isinstance(data, dict)
assert isinstance(data["AAPL"], float)
data2 = self.batch2.get_eps_consensus()
assert isinstance(data2, pd.DataFrame)
assert_index_equal(data2.index, pd.Index(self.batch2.symbols))
assert data2.loc["AAPL"].dtype == "float64"
data4 = self.batch4.get_eps_consensus()
assert isinstance(data4, dict)
assert isinstance(data4["AAPL"], Decimal)
class TestFieldMethodsShare(object):
def setup_class(self):
self.share = Stock("AAPL")
self.share2 = Stock("AAPL", output_format='pandas')
self.share4 = Stock("AAPL",
json_parse_int=Decimal,
json_parse_float=Decimal)
self.share5 = Stock("TSLA")
def test_get_company_name(self):
data = self.share.get_company_name()
print(type(data))
assert isinstance(data, six.string_types)
assert data == "Apple Inc."
data2 = self.share2.get_company_name()
assert isinstance(data2, pd.DataFrame)
def test_get_primary_exchange(self):
data = self.share.get_primary_exchange()
assert isinstance(data, six.string_types)
assert data == "Nasdaq Global Select"
data2 = self.share2.get_primary_exchange()
assert isinstance(data2, pd.DataFrame)
def test_get_sector(self):
data = self.share.get_sector()
assert isinstance(data, six.string_types)
assert data == "Technology"
data2 = self.share2.get_sector()
assert isinstance(data2, pd.DataFrame)
def test_get_open(self):
data = self.share.get_open()
assert isinstance(data, float)
assert data > 0
data2 = self.share2.get_open()
assert isinstance(data2, pd.DataFrame)
assert data2.loc["AAPL"].dtype == "float64"
data4 = self.share4.get_open()
assert isinstance(data4, Decimal)
assert data4 > 0
def test_get_close(self):
data = self.share.get_close()
assert isinstance(data, float)
assert data > 0
data2 = self.share2.get_close()
assert isinstance(data2, pd.DataFrame)
assert data2.loc["AAPL"].dtype == "float64"
data4 = self.share4.get_close()
assert isinstance(data4, Decimal)
assert data4 > 0
def test_get_years_high(self):
data = self.share.get_years_high()
assert isinstance(data, float)
assert data > 0
data2 = self.share2.get_years_high()
assert isinstance(data2, pd.DataFrame)
assert data2.loc["AAPL"].dtype == "float64"
data4 = self.share4.get_years_high()
assert isinstance(data4, Decimal)
assert data4 > 0
def test_get_years_low(self):
data = self.share.get_years_low()
assert isinstance(data, float)
assert data > 0
data2 = self.share2.get_years_low()
assert isinstance(data2, pd.DataFrame)
assert data2.loc["AAPL"].dtype == "float64"
data4 = self.share4.get_years_low()
assert isinstance(data4, Decimal)
assert data4 > 0
def test_get_ytd_change(self):
data = self.share.get_ytd_change()
assert isinstance(data, float)
data2 = self.share2.get_ytd_change()
assert isinstance(data2, pd.DataFrame)
assert data2.loc["AAPL"].dtype == "float64"
data4 = self.share4.get_ytd_change()
assert isinstance(data4, Decimal)
def test_get_volume(self):
data = self.share.get_volume()
assert isinstance(data, int)
assert data > 1000
data2 = self.share2.get_volume()
assert isinstance(data2, pd.DataFrame)
assert data2.loc["AAPL"].dtype == "int64"
data4 = self.share4.get_volume()
assert isinstance(data4, Decimal)
assert data4 > 1000
def test_get_market_cap(self):
data = self.share.get_market_cap()
assert isinstance(data, int)
data2 = self.share2.get_market_cap()
assert isinstance(data2, pd.DataFrame)
assert data2.loc["AAPL"].dtype == "int64"
data4 = self.share4.get_market_cap()
assert isinstance(data4, Decimal)
def test_get_beta(self):
data = self.share.get_beta()
assert isinstance(data, float)
data2 = self.share2.get_beta()
assert isinstance(data2, pd.DataFrame)
assert data2.loc["AAPL"].dtype == "float64"
data4 = self.share4.get_beta()
assert isinstance(data4, Decimal)
def test_get_short_interest(self):
data = self.share.get_short_interest()
assert isinstance(data, int)
data2 = self.share2.get_short_interest()
assert isinstance(data2, pd.DataFrame)
assert data2.loc["AAPL"].dtype == "int64"
data4 = self.share4.get_short_interest()
assert isinstance(data4, Decimal)
def test_get_short_ratio(self):
data = self.share.get_short_ratio()
assert isinstance(data, float)
data2 = self.share2.get_short_ratio()
assert isinstance(data2, pd.DataFrame)
assert data2.loc["AAPL"].dtype == "float64"
data4 = self.share4.get_short_ratio()
assert isinstance(data4, Decimal)
def test_get_latest_eps(self):
data = self.share5.get_latest_eps()
assert isinstance(data, float)
data4 = self.share4.get_latest_eps()
assert isinstance(data4, Decimal)
def test_get_shares_outstanding(self):
data = self.share.get_shares_outstanding()
assert isinstance(data, int)
data2 = self.share2.get_shares_outstanding()
assert isinstance(data2, pd.DataFrame)
assert data2.loc["AAPL"].dtype == "int64"
data4 = self.share4.get_shares_outstanding()
assert isinstance(data4, Decimal)
def test_get_float(self):
data = self.share.get_float()
assert isinstance(data, int)
data2 = self.share2.get_float()
assert isinstance(data2, pd.DataFrame)
assert data2.loc["AAPL"].dtype == "int64"
data4 = self.share4.get_float()
assert isinstance(data4, Decimal)
def test_get_eps_consensus(self):
data = self.share.get_eps_consensus()
assert isinstance(data, float)
data2 = self.share2.get_eps_consensus()
assert isinstance(data2, pd.DataFrame)
assert data2.loc["AAPL"].dtype == "float64"
data4 = self.share4.get_eps_consensus()
assert isinstance(data4, Decimal)
'DATA', 'CRM', 'SPLK', 'WDAY', 'HLT', 'BLL', 'MFGP', 'WEX', 'DXC', 'MSFT',
'AAPL', 'SBUX', 'NKE', 'T', 'GOOGL', 'FB', 'TWTR', 'AKAM', 'LLNW', 'GD',
'LDOS', 'BA', 'MSTR', 'BMCH', 'CTSH', 'WIT', 'OTEX', 'SPOT', 'AYX', 'SATS',
'MAR', 'TENB', 'CBLK', 'ZS', 'GCI', 'VRNT'
]
# Create separate Dictionaries for 'Open' and 'Close' prices
qOpen = {}
qClose = {}
qNews = {} # Attributes={datetime, headline, source, url, summary, related}
for x in myList:
print('Retrieving quote info for %s...' % x)
theQuote = Stock(x) #x, output_format='pandas')
resOpen = theQuote.get_open()
resClose = theQuote.get_close(
) #get_quote(filter_=['ytdChange', 'open', 'close', 'avgTotalVolume'])
qOpen[x] = resOpen
qClose[x] = resClose
newsList = theQuote.get_news(last=7)
print('')
print('Formatting output...')
for key in qOpen.keys():
val = qOpen[key]
print("Key: ", key, "\t Open:", val, "\t Close:",
qClose[key]) #, "\t News:", qNews[key])
print('')
del qOpen
del qClose
#End
from iexfinance import Stock
from iexfinance import get_historical_data
from datetime import datetime
tsla = Stock('TSLA')
print("open", tsla.get_open())
print("volume", tsla.get_volume())
print("price", tsla.get_price())
print("close", tsla.get_close())
start = datetime(2018,10,11)
end = datetime(2018,10,13)
df = get_historical_data("AAPL", start = start, end = end, output_format = 'pandas')
print(df.head())
