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']