def test_batch_historical_pandas(self):
f = get_historical_data(["AMZN", "TSLA"], self.good_start,
self.good_end, output_format="pandas")
assert isinstance(f, dict)
assert len(f) == 2
assert sorted(list(f)) == ["AMZN", "TSLA"]
a = f["AMZN"]
t = f["TSLA"]
assert len(a) == 73
assert len(t) == 73
expected1 = a.loc["2017-02-09"]
assert expected1["close"] == pytest.approx(821.36, 3)
assert expected1["high"] == pytest.approx(825.0, 3)
expected2 = a.loc["2017-05-24"]
assert expected2["close"] == pytest.approx(980.35, 3)
assert expected2["high"] == pytest.approx(981.0, 3)
expected1 = t.loc["2017-02-09"]
assert expected1["close"] == pytest.approx(269.20, 3)
assert expected1["high"] == pytest.approx(271.18, 3)
expected2 = t.loc["2017-05-24"]
assert expected2["close"] == pytest.approx(310.22, 3)
assert expected2["high"] == pytest.approx(311.0, 3)
def import_chart():
apple = Company.objects.filter(symbol='AAPL')[0]
chart = iex.get_historical_data(symbols='AAPL')
data = chart['AAPL']
try:
iex_provider = Provider.objects.filter(name="iex")[0]
except IndexError:
iex_provider = Provider.objects.create(name="iex")
iex_provider.save()
for date_tick in data.keys():
date = string_to_date(date_tick)
try:
tick_db = Tick.objects.filter(company=apple,
provider=iex_provider,
date=date)[0]
except IndexError:
tick_db = Tick.objects.create(company=apple,
provider=iex_provider,
date=date,
open=data[date_tick]['open'],
high=data[date_tick]['high'],
low=data[date_tick]['low'],
close=data[date_tick]['close'],
volume=data[date_tick]['volume'])
tick_db.save()
ticks = serializers.json.Deserializer(chart)
print("ticks", ticks)
def test_single_historical_json(self):
f = get_historical_data("AMZN", self.good_start, self.good_end)
assert isinstance(f, dict)
assert len(f["AMZN"]) == 73
expected1 = f["AMZN"]["2017-02-09"]
assert expected1["close"] == pytest.approx(821.36, 3)
assert expected1["high"] == pytest.approx(825.0, 3)
expected2 = f["AMZN"]["2017-05-24"]
assert expected2["close"] == pytest.approx(980.35, 3)
assert expected2["high"] == pytest.approx(981.0, 3)
def test_single_historical_pandas(self):
f = get_historical_data("AMZN", self.good_start, self.good_end,
output_format="pandas")
assert isinstance(f, pd.DataFrame)
assert len(f) == 73
expected1 = f.loc["2017-02-09"]
assert expected1["close"] == pytest.approx(821.36, 3)
assert expected1["high"] == pytest.approx(825.0, 3)
expected2 = f.loc["2017-05-24"]
assert expected2["close"] == pytest.approx(980.35, 3)
assert expected2["high"] == pytest.approx(981.0, 3)
def test_invalid_dates_batch(self):
start = datetime(2010, 5, 9)
end = datetime(2017, 5, 9)
with pytest.raises(ValueError):
get_historical_data(["AAPL", "TSLA"], start, end)
def test_invalid_symbol_batch(self):
start = datetime(2017, 2, 9)
end = datetime(2017, 5, 24)
with pytest.raises(IEXSymbolError):
get_historical_data(["BADSYMBOL", "TSLA"], start, end)