def run(self):
ticker_min_order_dates = self.order_logic.get_all_order_tickers_min_date(
)
for ticker_date in ticker_min_order_dates:
self.process_ticker_order_date(ticker_date)
min_date = min(t.date for t in ticker_min_order_dates)
for ticker in constants.BENCHMARK_TICKERS:
self.process_ticker_order_date(TickerDate(ticker, min_date))
def test_run(self):
batch = AlphavantagePriceHistoryFetcher()
ticker_date = TickerDate('AAPL', datetime.date(2017, 6, 19))
with mock.patch.object(
batch.order_logic,
'get_all_order_tickers_min_date',
return_value=[ticker_date]
), mock.patch.object(
batch,
'process_ticker_order_date'
) as patch_process:
batch.run()
benchmark_ticker_dates = [TickerDate(t, ticker_date.date) for t in constants.BENCHMARK_TICKERS]
assert patch_process.call_args_list == [mock.call(ticker_date)] + \
[mock.call(td) for td in benchmark_ticker_dates]
def get_ticker_price_history_map(self, tickers, dates):
ticker_dates = [
TickerDate(x[0], x[1]) for x in itertools.product(tickers, dates)
]
prices = self.get_ticker_dates_prices(ticker_dates)
price_info = defaultdict(dict)
for price in prices:
price_info[price.ticker][price.date] = price.price
return price_info
def process_ticker_order_date(self, ticker_date):
self.log.info("Processing ticker %s" % ticker_date.ticker)
fetch_date = self.get_fetch_date(ticker_date)
if self.should_fetch_data_for_date(fetch_date):
self.log.info("Fetch history for ticker %s to %s" %
(ticker_date.ticker, fetch_date.isoformat()))
history = self.fetch_ticker_history(
TickerDate(ticker_date.ticker, fetch_date))
self.price_logic.add_prices(history)
def test_fetch_ticker_history(self):
batch = AlphavantagePriceHistoryFetcher()
ticker_date = TickerDate('YELP', datetime.date(2017, 6, 12))
ticker_date_price = TickerDatePrice('YELP', datetime.date(2017, 6, 12), 31.2)
with mock.patch(
'batch.advantagealpha_price_history_fetcher.time'
), mock.patch(
'batch.advantagealpha_price_history_fetcher.requests'
) as mock_requests, mock.patch.object(
batch,
'_parse_historical',
return_value=[ticker_date_price]
) as mock_parse:
mock_requests.get = mock.Mock()
data = batch.fetch_ticker_history(ticker_date)
assert mock_requests.get.called
assert mock_parse.called
assert data == [ticker_date_price]
def test_process_ticker_order_date(self):
batch = AlphavantagePriceHistoryFetcher()
ticker_date = TickerDate('AAPL', datetime.date(2017, 6, 19))
mock_history = mock.Mock()
with mock.patch.object(
batch,
'get_fetch_date',
return_value=ticker_date.date
), mock.patch.object(
batch,
'should_fetch_data_for_date',
return_value=True
), mock.patch.object(
batch,
'fetch_ticker_history',
return_value=mock_history
), mock.patch.object(
batch.price_logic,
'add_prices'
) as mock_price_logic:
batch.process_ticker_order_date(ticker_date)
assert mock_price_logic.call_args_list == [mock.call(mock_history)]
def test_get_all_order_tickers_min_date(self):
logic = OrderHistoryLogic()
user_id_1 = 1
user_id_2 = 2
order1 = Order(
user_id=user_id_1,
order_type=order_history.BUY_ORDER_TYPE,
date=datetime.date(2015, 8, 9),
ticker='AAPL',
num_shares=20,
price=150.001,
)
order2 = Order(
user_id=user_id_2,
order_type=order_history.BUY_ORDER_TYPE,
date=datetime.date(2017, 1, 1),
ticker='AAPL',
num_shares=20,
price=152.333,
)
logic.add_orders([order1, order2])
ticker_dates = logic.get_all_order_tickers_min_date()
assert ticker_dates == [TickerDate(order1.ticker, order1.date)]
class TestAlphavantagePriceHistoryFetcher(object):
def test_parse_historical_data(self):
batch = AlphavantagePriceHistoryFetcher()
content = '{ "Meta Data": { "2. Symbol": "MOMO"},"Time Series (Daily)": {' + \
'"2017-12-20": { "4. close": "1.0" }, ' + \
'"2017-12-19": { "4. close": "2.0" }}}'
content = content.encode()
price_history = batch._parse_historical(content)
assert price_history == [
TickerDatePrice(ticker='MOMO', date=datetime.date(2017, 12, 19), price=2.0),
TickerDatePrice(ticker='MOMO', date=datetime.date(2017, 12, 20), price=1.0),
]
@pytest.mark.parametrize(
'fetch_date,now,should_fetch', [
# Have data for Thursday but not Friday and it's Sunday
(datetime.date(2017, 6, 16), datetime.datetime(2017, 6, 18), True),
# Have data for Friday and it's Sunday
(datetime.date(2017, 6, 17), datetime.datetime(2017, 6, 18), False),
# Have data for Friday and it's Monday before close
(datetime.date(2017, 6, 17), datetime.datetime(2017, 6, 19, 15, tzinfo=pytz.timezone('US/Eastern')), False),
# Have data for Friday and it's Monday after close
(datetime.date(2017, 6, 17), datetime.datetime(2017, 6, 19, 17, tzinfo=pytz.timezone('US/Eastern')), True),
# Have data for day before and it's before close
(datetime.date(2017, 6, 13), datetime.datetime(2017, 6, 13, 15, tzinfo=pytz.timezone('US/Eastern')), False),
# Have data for day before and it's after close
(datetime.date(2017, 6, 13), datetime.datetime(2017, 6, 13, 17, tzinfo=pytz.timezone('US/Eastern')), True),
]
)
def test_should_fetch_data_for_date(self, fetch_date, now, should_fetch):
batch = AlphavantagePriceHistoryFetcher()
with mock.patch(
'batch.advantagealpha_price_history_fetcher.datetime.datetime'
) as mock_datetime:
mock_datetime.now.return_value = now
assert batch.should_fetch_data_for_date(fetch_date) is should_fetch
def test_fetch_ticker_history(self):
batch = AlphavantagePriceHistoryFetcher()
ticker_date = TickerDate('YELP', datetime.date(2017, 6, 12))
ticker_date_price = TickerDatePrice('YELP', datetime.date(2017, 6, 12), 31.2)
with mock.patch(
'batch.advantagealpha_price_history_fetcher.time'
), mock.patch(
'batch.advantagealpha_price_history_fetcher.requests'
) as mock_requests, mock.patch.object(
batch,
'_parse_historical',
return_value=[ticker_date_price]
) as mock_parse:
mock_requests.get = mock.Mock()
data = batch.fetch_ticker_history(ticker_date)
assert mock_requests.get.called
assert mock_parse.called
assert data == [ticker_date_price]
@pytest.mark.parametrize(
'ticker_date,min_date_history_exists,max_history_date,result', [
(
TickerDate('AAPL', datetime.date(2017, 6, 16)),
False,
None,
datetime.date(2017, 6, 16)
),
(
TickerDate('AAPL', datetime.date(2017, 6, 16)),
True,
datetime.date(2017, 6, 26),
datetime.date(2017, 6, 27)
),
]
)
def test_get_fetch_date(self, ticker_date, min_date_history_exists, max_history_date, result):
batch = AlphavantagePriceHistoryFetcher()
with mock.patch.object(
batch.price_logic,
'does_ticker_date_history_exists',
return_value=min_date_history_exists
), mock.patch.object(
batch.price_logic,
'get_max_date_history_for_ticker',
return_value=max_history_date
):
assert batch.get_fetch_date(ticker_date) == result
def test_run(self):
batch = AlphavantagePriceHistoryFetcher()
ticker_date = TickerDate('AAPL', datetime.date(2017, 6, 19))
with mock.patch.object(
batch.order_logic,
'get_all_order_tickers_min_date',
return_value=[ticker_date]
), mock.patch.object(
batch,
'process_ticker_order_date'
) as patch_process:
batch.run()
benchmark_ticker_dates = [TickerDate(t, ticker_date.date) for t in constants.BENCHMARK_TICKERS]
assert patch_process.call_args_list == [mock.call(ticker_date)] + \
[mock.call(td) for td in benchmark_ticker_dates]
def test_process_ticker_order_date(self):
batch = AlphavantagePriceHistoryFetcher()
ticker_date = TickerDate('AAPL', datetime.date(2017, 6, 19))
mock_history = mock.Mock()
with mock.patch.object(
batch,
'get_fetch_date',
return_value=ticker_date.date
), mock.patch.object(
batch,
'should_fetch_data_for_date',
return_value=True
), mock.patch.object(
batch,
'fetch_ticker_history',
return_value=mock_history
), mock.patch.object(
batch.price_logic,
'add_prices'
) as mock_price_logic:
batch.process_ticker_order_date(ticker_date)
assert mock_price_logic.call_args_list == [mock.call(mock_history)]