class TestShareDefault(object):
def setup_class(self):
self.cshare = Stock("aapl")
self.cshare2 = Stock("aapl", output_format='pandas')
self.cshare3 = Stock("svxy")
self.cshare4 = Stock("aapl",
json_parse_int=Decimal,
json_parse_float=Decimal)
self.cshare5 = Stock("gig^")
def test_invalid_symbol(self):
data = Stock("BAD SYMBOL")
with pytest.raises(IEXSymbolError):
data.get_price()
def test_get_all_format(self):
data = self.cshare.get_all()
assert isinstance(data, dict)
def test_get_all(self):
data = self.cshare.get_all()
assert len(data) == 20
def test_get_endpoints(self):
data = self.cshare.get_endpoints(["price"])
assert list(data) == ["price"]
def test_get_endpoints_bad_endpoint(self):
with pytest.raises(IEXEndpointError):
self.cshare.get_endpoints(["BAD ENDPOINT", "quote"])
with pytest.raises(IEXEndpointError):
self.cshare.get_endpoints("BAD ENDPOINT")
def test_get_book_format(self):
data = self.cshare.get_book()
assert isinstance(data, dict)
data2 = self.cshare2.get_book()
assert isinstance(data2, pd.DataFrame)
def test_get_chart_format(self):
data = self.cshare.get_chart()
assert isinstance(data, list)
data2 = self.cshare2.get_chart()
assert isinstance(data2, list)
def test_get_chart_params(self):
data = self.cshare.get_chart()
# Test chart ranges
data2 = self.cshare.get_chart(range_='1y')
assert 15 < len(data) < 35
assert 240 < len(data2) < 260
# Test chartSimplify
data4 = self.cshare.get_chart(chartSimplify=True)[0]
assert "simplifyFactor" in list(data4)
data5 = self.cshare.get_chart(range_='1y', chartInterval=5)
assert 45 < len(data5) < 55
@pytest.mark.xfail(reason="This test only runs correctly between 00:00 and"
"09:30 EST")
def test_get_chart_reset(self):
# Test chartReset
data3 = self.cshare.get_chart(range_='1d', chartReset=True)
assert data3 == []
def test_get_company_format(self):
data = self.cshare.get_company()
assert isinstance(data, dict)
data2 = self.cshare2.get_company()
assert isinstance(data2, pd.DataFrame)
def test_get_delayed_quote_format(self):
data = self.cshare.get_delayed_quote()
assert isinstance(data, dict)
data2 = self.cshare2.get_delayed_quote()
assert isinstance(data2, pd.DataFrame)
def test_get_dividends_format(self):
data = self.cshare.get_dividends()
assert isinstance(data, list)
data2 = self.cshare2.get_dividends()
assert isinstance(data2, list)
def test_get_dividends_params(self):
data = self.cshare.get_dividends()
data2 = self.cshare.get_dividends(range_='2y')
data3 = self.cshare.get_dividends(range_='5y')
assert len(data) < len(data2) < len(data3)
def test_get_earnings_format(self):
data = self.cshare.get_earnings()
assert isinstance(data, list)
data2 = self.cshare2.get_earnings()
assert isinstance(data2, pd.DataFrame)
# Ensure empty list is returned for symbol with no earnings
data3 = self.cshare5.get_earnings()
assert isinstance(data3, list)
def test_get_effective_spread_format(self):
data = self.cshare.get_effective_spread()
assert isinstance(data, list)
data2 = self.cshare2.get_effective_spread()
assert isinstance(data2, pd.DataFrame)
def test_get_financials_format(self):
data = self.cshare.get_financials()
assert isinstance(data, list)
data2 = self.cshare2.get_financials()
assert isinstance(data2, pd.DataFrame)
# Ensure empty list is returned even when ticker has no financials
data3 = self.cshare5.get_financials()
assert isinstance(data3, list)
def test_get_key_stats_format(self):
data = self.cshare.get_key_stats()
assert isinstance(data, dict)
data2 = self.cshare2.get_key_stats()
assert isinstance(data2, pd.DataFrame)
def test_get_largest_trades(self):
data = self.cshare.get_largest_trades()
assert isinstance(data, list)
data2 = self.cshare2.get_largest_trades()
assert isinstance(data2, pd.DataFrame)
def test_get_logo_format(self):
data = self.cshare.get_logo()
assert isinstance(data, dict)
data2 = self.cshare2.get_logo()
assert isinstance(data2, pd.DataFrame)
def test_get_news_format(self):
data = self.cshare.get_news()
assert isinstance(data, list)
@pytest.mark.xfail(reason="Provider error. Awaiting patch.")
def test_get_news_params(self):
data = self.cshare.get_news(last=15)
assert len(data) == 15
def test_ohlc(self):
data = self.cshare.get_ohlc()
assert isinstance(data, dict)
data2 = self.cshare2.get_ohlc()
assert isinstance(data2, pd.DataFrame)
def test_get_open_close_format(self):
data = self.cshare.get_open_close()
assert isinstance(data, dict)
data2 = self.cshare2.get_open_close()
assert isinstance(data2, pd.DataFrame)
def test_get_peers_format(self):
data = self.cshare.get_peers()
assert isinstance(data, list)
data2 = self.cshare2.get_peers()
assert isinstance(data2, list)
def test_get_previous_format(self):
data = self.cshare.get_previous()
assert isinstance(data, dict)
data2 = self.cshare2.get_previous()
assert isinstance(data2, pd.DataFrame)
def test_get_price_format(self):
data = self.cshare.get_price()
assert isinstance(data, float)
data2 = self.cshare2.get_price()
assert isinstance(data2, pd.DataFrame)
data4 = self.cshare4.get_price()
assert isinstance(data4, Decimal)
def test_get_quote_format(self):
data = self.cshare.get_quote()
assert isinstance(data, dict)
data2 = self.cshare2.get_quote()
assert isinstance(data2, pd.DataFrame)
def test_get_quote_params(self):
data = self.cshare.get_quote()
data2 = self.cshare.get_quote(displayPercent=True)
assert (abs(data2["ytdChange"]) > abs(data["ytdChange"]))
def test_get_relevant_format(self):
data = self.cshare.get_relevant()
assert isinstance(data, dict)
data2 = self.cshare2.get_relevant()
assert isinstance(data2, pd.DataFrame)
def test_get_splits_format(self):
data = self.cshare3.get_splits()
assert isinstance(data, list)
data2 = self.cshare3.get_splits(range_="1y")
assert isinstance(data2, list)
def test_get_splits_params(self):
data = self.cshare3.get_splits(range_="2y")
data2 = self.cshare3.get_splits(range_="5y")
assert len(data2) > len(data)
def test_get_time_series(self):
data = self.cshare.get_time_series()
data2 = self.cshare.get_chart()
assert data == data2
def test_get_volume_by_venue_format(self):
data = self.cshare.get_volume_by_venue()
assert isinstance(data, list)
data2 = self.cshare2.get_volume_by_venue()
assert isinstance(data2, pd.DataFrame)
def test_filter(self):
data = self.cshare.get_quote(filter_='ytdChange')
assert isinstance(data, dict)
assert isinstance(data["ytdChange"], float)
data4 = self.cshare4.get_quote(filter_='ytdChange')
assert isinstance(data4, dict)
assert isinstance(data4["ytdChange"], Decimal)
class TestBatchDefault(object):
def setup_class(self):
self.cbatch = Stock(["aapl", "tsla"])
self.cbatch2 = Stock(["aapl", "tsla"], output_format='pandas')
self.cbatch3 = Stock(["uvxy", "svxy"])
def test_invalid_symbol_or_symbols(self):
with pytest.raises(IEXSymbolError):
a = Stock(["TSLA", "BAD SYMBOL", "BAD SYMBOL"])
a.get_price()
def test_get_endpoints(self):
data = self.cbatch.get_endpoints(["price"])["AAPL"]
assert list(data) == ["price"]
def test_get_endpoints_bad_endpoint(self):
with pytest.raises(IEXEndpointError):
self.cbatch.get_endpoints(["BAD ENDPOINT", "quote"])
with pytest.raises(IEXEndpointError):
self.cbatch.get_endpoints("BAD ENDPOINT")
def test_get_all(self):
data = self.cbatch.get_all()
assert len(data) == 2
assert len(data["AAPL"]) == 20
def test_get_all_format(self):
data = self.cbatch.get_all()
assert isinstance(data, dict)
data2 = self.cbatch2.get_all()
assert isinstance(data2["AAPL"], dict)
def test_get_book_format(self):
data = self.cbatch.get_book()
assert isinstance(data, dict)
data2 = self.cbatch2.get_book()
assert isinstance(data2, pd.DataFrame)
def test_get_chart_format(self):
data = self.cbatch.get_chart()
assert isinstance(data, dict)
data2 = self.cbatch2.get_chart()
assert isinstance(data2["AAPL"], list)
def test_get_chart_params(self):
data = self.cbatch.get_chart()["AAPL"]
# Test chart range_s
data2 = self.cbatch.get_chart(range_='1y')["AAPL"]
assert 15 < len(data) < 35
assert 240 < len(data2) < 260
# Test chartSimplify
data4 = self.cbatch.get_chart(chartSimplify=True)["AAPL"][0]
assert "simplifyFactor" in list(data4)
data5 = self.cbatch.get_chart(range_='1y', chartInterval=5)["AAPL"]
assert 45 < len(data5) < 55
@pytest.mark.xfail(reason="This test only works overnight")
def test_get_chart_reset(self):
# Test chartReset
data = self.cbatch.get_chart(range_='1d', chartReset=True)
assert data == []
def test_get_company_format(self):
data = self.cbatch.get_company()
assert isinstance(data, dict)
data2 = self.cbatch2.get_company()
assert isinstance(data2, pd.DataFrame)
def test_get_delayed_quote_format(self):
data = self.cbatch.get_delayed_quote()
assert isinstance(data, dict)
data2 = self.cbatch2.get_delayed_quote()
assert isinstance(data2, pd.DataFrame)
def test_get_dividends_format(self):
data = self.cbatch.get_dividends()
assert isinstance(data, dict)
data2 = self.cbatch2.get_dividends()
assert isinstance(data2, dict)
def test_get_dividends_params(self):
data = self.cbatch.get_dividends()["AAPL"]
data2 = self.cbatch.get_dividends(range_='2y')["AAPL"]
data3 = self.cbatch.get_dividends(range_='5y')["AAPL"]
assert len(data) < len(data2) < len(data3)
def test_get_earnings_format(self):
data = self.cbatch.get_earnings()
assert isinstance(data, dict)
data2 = self.cbatch2.get_earnings()
assert isinstance(data2, pd.DataFrame)
def test_get_effective_spread_format(self):
data = self.cbatch.get_effective_spread()
assert isinstance(data, dict)
data2 = self.cbatch2.get_effective_spread()
assert isinstance(data2, pd.DataFrame)
def test_get_financials_format(self):
data = self.cbatch.get_financials()
assert isinstance(data, dict)
data2 = self.cbatch2.get_financials()
assert isinstance(data2, pd.DataFrame)
def test_get_key_stats_format(self):
data = self.cbatch.get_key_stats()
assert isinstance(data, dict)
data2 = self.cbatch2.get_key_stats()
assert isinstance(data2, pd.DataFrame)
def test_get_logo_format(self):
data = self.cbatch.get_logo()
assert isinstance(data, dict)
data2 = self.cbatch2.get_logo()
assert isinstance(data2, pd.DataFrame)
def test_get_news_format(self):
data = self.cbatch.get_news()
assert isinstance(data, dict)
def test_ohlc(self):
data = self.cbatch.get_ohlc()
assert isinstance(data, dict)
def test_get_open_close_format(self):
data = self.cbatch.get_open_close()
assert isinstance(data, dict)
data2 = self.cbatch2.get_open_close()
assert isinstance(data2, pd.DataFrame)
def test_get_peers_format(self):
data = self.cbatch.get_peers()
assert isinstance(data, dict)
data2 = self.cbatch2.get_peers()
assert isinstance(data2, dict)
def test_get_previous_format(self):
data = self.cbatch.get_previous()
assert isinstance(data, dict)
data2 = self.cbatch2.get_previous()
assert isinstance(data2, pd.DataFrame)
def test_get_price_format(self):
data = self.cbatch.get_price()
assert isinstance(data, dict)
data2 = self.cbatch2.get_price()
assert isinstance(data2, pd.DataFrame)
def test_get_quote_format(self):
data = self.cbatch.get_quote()
assert isinstance(data, dict)
data2 = self.cbatch2.get_quote()
assert isinstance(data2, pd.DataFrame)
data3 = self.cbatch.get_quote(displayPercent=True)
assert (abs(data3["AAPL"]["ytdChange"]) > abs(
data["AAPL"]["ytdChange"]))
def test_get_relevant_format(self):
data = self.cbatch.get_relevant()
assert isinstance(data, dict)
data2 = self.cbatch2.get_relevant()
assert isinstance(data2, pd.DataFrame)
def test_get_splits(self):
data = self.cbatch.get_splits()
assert isinstance(data, dict)
data2 = self.cbatch2.get_splits()
assert isinstance(data2, pd.DataFrame)
def test_get_splits_params(self):
data = self.cbatch3.get_splits(range_="2y")["SVXY"]
data2 = self.cbatch3.get_splits(range_="5y")["SVXY"]
assert len(data2) > len(data)
def test_time_series(self):
data = self.cbatch.get_time_series()
data2 = self.cbatch.get_chart()
assert data == data2
def test_get_volume_by_venue_format(self):
data = self.cbatch.get_volume_by_venue()
assert isinstance(data, dict)
data2 = self.cbatch2.get_volume_by_venue()
assert isinstance(data2, pd.DataFrame)
def test_get_select_ep_bad_params(self):
with pytest.raises(ValueError):
self.cbatch.get_endpoints()
with pytest.raises(IEXEndpointError):
self.cbatch.get_endpoints("BADENDPOINT")
class TestBatch(object):
def setup_class(self):
self.cbatch = Stock(["aapl", "tsla"])
def test_invalid_symbol_or_symbols(self):
with pytest.raises(IEXSymbolError):
Stock(["TSLA", "AAAPLPL", "fwoeiwf"])
def test_get_all_format(self):
data = self.cbatch.get_all()
assert isinstance(data, dict)
def test_get_chart_format(self):
data = self.cbatch.get_chart()
assert isinstance(data, dict)
def test_get_book_format(self):
data = self.cbatch.get_book()
assert isinstance(data, dict)
def test_get_open_close_format(self):
data = self.cbatch.get_open_close()
assert isinstance(data, dict)
def test_get_previous_format(self):
data = self.cbatch.get_previous()
assert isinstance(data, dict)
def test_get_company_format(self):
data = self.cbatch.get_company()
assert isinstance(data, dict)
def test_get_key_stats_format(self):
data = self.cbatch.get_key_stats()
assert isinstance(data, dict)
def test_get_relevant_format(self):
data = self.cbatch.get_relevant()
assert isinstance(data, dict)
def test_get_news_format(self):
data = self.cbatch.get_news()
assert isinstance(data, dict)
def test_get_financials_format(self):
data = self.cbatch.get_financials()
assert isinstance(data, dict)
def test_get_earnings_format(self):
data = self.cbatch.get_earnings()
assert isinstance(data, dict)
def test_get_logo_format(self):
data = self.cbatch.get_logo()
assert isinstance(data, dict)
def test_get_price_format(self):
data = self.cbatch.get_price()
assert isinstance(data, dict)
def test_get_delayed_quote_format(self):
data = self.cbatch.get_delayed_quote()
assert isinstance(data, dict)
def test_get_effective_spread_format(self):
data = self.cbatch.get_effective_spread()
assert isinstance(data, dict)
def test_get_volume_by_venue_format(self):
data = self.cbatch.get_volume_by_venue()
assert isinstance(data, dict)
def test_get_select_ep_bad_params(self):
with pytest.raises(ValueError):
self.cbatch.get_select_endpoints()
with pytest.raises(IEXEndpointError):
self.cbatch.get_select_endpoints("BADENDPOINT")
def test_ohlc(self):
data = self.cbatch.get_ohlc()
assert isinstance(data, dict)
def test_time_series(self):
data = self.cbatch.get_time_series()
data2 = self.cbatch.get_chart()
assert data == data2
def test_nondefault_params_1(self):
data = Stock(["AAPL", "TSLA"], _range='5y')
data2 = Stock(["AAPL", "TSLA"])
assert len(data.get_chart()["AAPL"]) > len(data2.get_chart()["AAPL"])
assert len(data.get_chart()["TSLA"]) > len(data2.get_chart()["TSLA"])
def test_nondefault_params_2(self):
data = Stock(["AAPL", "TSLA"], last=37)
assert len(data.get_news()["AAPL"]) == 37
assert len(data.get_news()["TSLA"]) == 37
class TestShare(object):
def setup_class(self):
self.cshare = Stock("aapl")
def test_get_all_format(self):
data = self.cshare.get_all()
assert isinstance(data, dict,)
def test_get_chart_format(self):
data = self.cshare.get_chart()
assert isinstance(data, list)
def test_get_book_format(self):
data = self.cshare.get_book()
assert isinstance(data, dict)
def test_get_open_close_format(self):
data = self.cshare.get_open_close()
assert isinstance(data, dict)
def test_get_previous_format(self):
data = self.cshare.get_previous()
assert isinstance(data, dict)
def test_get_company_format(self):
data = self.cshare.get_company()
assert isinstance(data, dict)
def test_get_key_stats_format(self):
data = self.cshare.get_key_stats()
assert isinstance(data, dict)
def test_get_relevant_format(self):
data = self.cshare.get_relevant()
assert isinstance(data, dict)
def test_get_news_format(self):
data = self.cshare.get_news()
assert isinstance(data, list)
def test_get_financials_format(self):
data = self.cshare.get_financials()
assert isinstance(data, dict)
def test_get_earnings_format(self):
data = self.cshare.get_earnings()
assert isinstance(data, dict)
def test_get_logo_format(self):
data = self.cshare.get_logo()
assert isinstance(data, dict)
def test_get_price_format(self):
data = self.cshare.get_price()
assert isinstance(data, float)
def test_get_delayed_quote_format(self):
data = self.cshare.get_delayed_quote()
assert isinstance(data, dict)
def test_get_effective_spread_format(self):
data = self.cshare.get_effective_spread()
assert isinstance(data, list)
def test_get_volume_by_venue_format(self):
data = self.cshare.get_volume_by_venue()
assert isinstance(data, list)
def test_ohlc(self):
data = self.cshare.get_ohlc()
assert isinstance(data, dict)
def test_time_series(self):
data = self.cshare.get_time_series()
data2 = self.cshare.get_chart()
assert data == data2
def test_nondefault_params_1(self):
aapl = Stock("AAPL", _range='5y')
aapl2 = Stock("AAPL")
assert len(aapl.get_chart()) > len(aapl2.get_chart())
def test_nondefault_params_2(self):
aapl = Stock("AAPL", last=37)
assert len(aapl.get_news()) == 37
def import_data(self):
self.download()
stock_list = pd.read_csv("stock_list.csv")
os.remove("stock_list.csv")
stocks = pd.DataFrame(get_available_symbols(output_format='pandas'))
stocks = stocks.loc[stocks['type'] == 'cs']
stocks = stocks.merge(stock_list,
how='inner',
left_on='symbol',
right_on='Symbol')
#Plainly filter list to reduce further analysis load
stocks = stocks.loc[(stocks['MarketCap'] > 0)
& stocks['MarketCap'].notnull()]
stocks = stocks.loc[stocks['Industry'].notnull()]
stocks = stocks.loc[(stocks['LastSale'] > .25)
& (stocks['LastSale'] <= 5.0)]
#add columns to df that we will go through and fill for analysis
stocks['profitMargin'] = Series([])
stocks['day50MovingAvg'] = Series([])
stocks['beta'] = Series([])
stocks['avg_daily_change_30'] = Series([])
stocks['avg_change_over_time_30'] = Series([])
stocks['avg_daily_change_5'] = Series([])
stocks['avg_change_over_time_5'] = Series([])
stocks['last_change_percent'] = Series([])
stocks['avg_close_30'] = Series([])
stocks['std_close_30'] = Series([])
stocks['avg_close_5'] = Series([])
stocks['std_close_5'] = Series([])
stocks['avg_volume_30'] = Series([])
stocks['avg_volume_5'] = Series([])
stocks['last_volume'] = Series([])
stocks['shortRatio'] = Series([])
stocks.reset_index(inplace=True, drop=True)
print(stocks.head(), stocks.info())
for index, row in stocks.iterrows():
#print (index, row)
#Pause so api doesn't kick us out
if index % 7 == 0 and index != 0:
print("Waiting 3 seconds")
time.sleep(3)
stock = Stock(str(row['symbol']))
stock_stats = pd.DataFrame(stock.get_key_stats(), index=[0])
#Five day timeseries avg for values
stock_book = pd.DataFrame(
stock.get_time_series(output_format='pandas'))
stock_book_3 = stock_book.tail(3)
#Close to real time
#stock_quote = pd.DataFrame(stock.get_quote(), index=[0])
#print (stock_move.head(), stock_move.info())
#print (stock_stats)
print(index)
#print (stock_stats)
stock_stats = stock_stats[[
'profitMargin', 'day50MovingAvg', 'beta', 'shortRatio'
]]
stocks.loc[index,
'profitMargin'] = stock_stats.iloc[0]['profitMargin']
stocks.loc[
index,
'day50MovingAvg'] = stock_stats.iloc[0]['day50MovingAvg']
stocks.loc[index, 'beta'] = stock_stats.iloc[0]['beta']
stocks.loc[index, 'shortRatio'] = stock_stats.iloc[0]['shortRatio']
stocks.loc[
index,
'avg_daily_change_30'] = stock_book['changePercent'].mean()
stocks.loc[index, 'avg_change_over_time_30'] = stock_book[
'changeOverTime'].mean()
stocks.loc[
index,
'avg_daily_change_5'] = stock_book_3['changePercent'].mean()
stocks.loc[index, 'avg_change_over_time_5'] = stock_book_3[
'changeOverTime'].mean()
stocks.loc[index, 'last_change_percent'] = stock_book.loc[
len(stock_book) - 1, 'changePercent']
stocks.loc[index, 'avg_close_30'] = stock_book['close'].mean()
stocks.loc[index, 'std_close_30'] = stock_book['close'].std()
stocks.loc[index, 'avg_close_5'] = stock_book_3['close'].mean()
stocks.loc[index, 'std_close_5'] = stock_book_3['close'].std()
stocks.loc[index, 'avg_volume_30'] = stock_book['volume'].mean()
stocks.loc[index, 'avg_volume_5'] = stock_book_3['volume'].mean()
stocks.loc[index,
'last_volume'] = stock_book.loc[len(stock_book) - 1,
'volume']
#if index > 50:
#break
stocks.to_csv('stocks_before_filter.csv')
stocks = stocks.loc[
(stocks['LastSale'] < (stocks['avg_close_30'] -
(1.40 * stocks['std_close_30'])))
& (stocks['LastSale'] >= (stocks['avg_close_30'] -
(2.00 * stocks['std_close_30'])))]
stocks = stocks.loc[((stocks['avg_volume_5'] / stocks['avg_volume_30'])
> 1.02)]
stocks.sort_values('shortRatio', inplace=True)
stocks.reset_index(inplace=True, drop=True)
#print (stocks.head(20),stocks.info())
stocks.to_csv('stocklist.csv')
return (stocks)
