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)
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)
from iexfinance import get_available_symbols as gas
# Documentation on iexfinance: https://addisonlynch.github.io/iexfinance/stable/ref.html
# load all symbols - list
symbols = gas()
# look at Tesla
tsla = Stock('TSLA')
opn = tsla.get_open()
pri = tsla.get_price()
print('Tesla: open price %f, current price %f' % (opn, pri))
# look at AA (Alcoa?)
aa = Stock('AA')
eps = aa.get_latest_eps()
pri = aa.get_price()
print('AA: latest EPS %f, current price %f' % (eps, pri))
# show symbols and company name for each
# for s in symbols:
# if s['isEnabled'] == True: print(s['symbol'] + ', ' + s['name'])
# Apple
apple = Stock('AAPL')
apple.get_key_stats()
apple.get_volume()
apple.get_earnings()
apple.get_quote()
apple.get_quote()['peRatio']
apple.get_quote()['close']
