def test_cache_subset(mocker):
set_session()
ir_swap = IRSwap('Pay', '10y', 'DKK')
values = [
{'date': '2019-10-07', 'value': 0.01},
{'date': '2019-10-08', 'value': 0.01}
]
mocker.return_value = [[values]]
dates = (dt.date(2019, 10, 7), dt.date(2019, 10, 8))
with HistoricalPricingContext(dates=dates, use_cache=True) as hpc:
pricing_key = hpc.pricing_key
price_f = ir_swap.price()
price_f.result()
cached = PricingCache.get(ir_swap, risk.Price, pricing_key)
assert len(cached) == len(dates)
cached_scalar = PricingCache.get(ir_swap, risk.Price, PricingContext(pricing_date=dates[0]).pricing_key)
assert isinstance(cached_scalar, float)
dates = dates + (dt.date(2019, 10, 9),)
pricing_key = HistoricalPricingContext(dates=dates).pricing_key
cached2 = PricingCache.get(ir_swap, risk.Price, pricing_key)
assert cached2 is None
cached3 = PricingCache.get(ir_swap, risk.Price, pricing_key, return_partial=True)
assert len(cached3) < len(dates)
values = [
{'date': '2019-10-07', 'marketDataType': 'IR', 'assetId': 'USD', 'pointClass': 'Swap',
'point': '1y', 'value': 0.01},
{'date': '2019-10-07', 'marketDataType': 'IR', 'assetId': 'USD', 'pointClass': 'Swap',
'point': '2y', 'value': 0.015},
{'date': '2019-10-08', 'marketDataType': 'IR', 'assetId': 'USD', 'pointClass': 'Swap',
'point': '1y', 'value': 0.01},
{'date': '2019-10-08', 'marketDataType': 'IR', 'assetId': 'USD', 'pointClass': 'Swap',
'point': '2y', 'value': 0.015},
{'date': '2019-10-09', 'marketDataType': 'IR', 'assetId': 'USD', 'pointClass': 'Swap',
'point': '1y', 'value': 0.01},
{'date': '2019-10-09', 'marketDataType': 'IR', 'assetId': 'USD', 'pointClass': 'Swap',
'point': '2y', 'value': 0.015}
]
mocker.return_value = [[values]]
with HistoricalPricingContext(dates=dates, use_cache=True) as hpc:
pricing_key = hpc.pricing_key
risk_f = ir_swap.calc(risk.IRDelta)
risk_frame = risk_f.result()
assert isinstance(risk_frame, pd.DataFrame)
assert len(risk_frame.index.unique()) == len(dates)
cached4 = PricingCache.get(ir_swap, risk.IRDelta, pricing_key)
assert len(cached4.index.unique()) == len(dates)
cached5 = PricingCache.get(ir_swap, risk.IRDelta, PricingContext(pricing_date=dates[0]).pricing_key)
assert len(cached5.index.unique()) == len(cached5)
def test_pricing_context(mocker):
swap1 = IRSwap('Pay', '1y', 'EUR', name='EUR1y')
future_date = business_day_offset(dt.date.today(), 10, roll='forward')
with MockCalc(mocker):
with RollFwd(date='10b', realise_fwd=True):
market = swap1.market()
with pytest.raises(ValueError):
# cannot pass in future date into pricing context, use RollFwd instead
with PricingContext(pricing_date=future_date):
_ = swap1.calc(risk.Price)
# cannot pass in market dated in the future into pricing context, use RollFwd instead
with PricingContext(market=CloseMarket(date=future_date)):
_ = swap1.calc(risk.Price)
with PricingContext(market=OverlayMarket(base_market=CloseMarket(date=future_date, location='NYC'),
market_data=market.result())):
_ = swap1.calc(risk.Price)
def test_cache_subset(mocker):
set_session()
ir_swap = IRSwap('Pay', '10y', 'DKK')
values = [{'$type': 'Risk', 'val': 0.01}]
mocker.return_value = [[[values]], [[values]]]
dates = (dt.date(2019, 10, 7), dt.date(2019, 10, 8))
with HistoricalPricingContext(dates=dates, use_cache=True):
price_f = ir_swap.price()
price_f.result()
for date in dates:
risk_key = PricingContext(pricing_date=date)._PricingContext__risk_key(
risk.Price, ir_swap.provider)
cached_scalar = PricingCache.get(risk_key, ir_swap)
assert cached_scalar
assert isinstance(cached_scalar, float)
risk_key = PricingContext(
pricing_date=dt.date(2019, 10, 9))._PricingContext__risk_key(
risk.Price, ir_swap.provider)
cached2 = PricingCache.get(risk_key, ir_swap)
assert cached2 is None
values = [{
'$type':
'RiskVector',
'asset': [0.01, 0.015],
'points': [{
'type': 'IR',
'asset': 'USD',
'class_': 'Swap',
'point': '1y'
}, {
'type': 'IR',
'asset': 'USD',
'class_': 'Swap',
'point': '2y'
}]
}]
# Check that we can return the same values from the cache, after calculating once (with return values set to None)
for return_values in ([[[values]], [[values]], [[values]]], None):
mocker.return_value = return_values
with HistoricalPricingContext(dates=dates, use_cache=True):
risk_f = ir_swap.calc(risk.IRDelta)
risk_frame = risk_f.result()
assert isinstance(risk_frame, pd.DataFrame)
assert len(risk_frame.index.unique()) == len(dates)
def test_cache_subset(mocker):
set_session()
ir_swap = IRSwap('Pay', '10y', 'DKK')
values = [{
'date': '2019-10-07',
'value': 0.01
}, {
'date': '2019-10-08',
'value': 0.01
}]
mocker.return_value = [[values]]
dates = (dt.date(2019, 10, 7), dt.date(2019, 10, 8))
with HistoricalPricingContext(dates=dates, use_cache=True):
market_data_location = PricingContext.current.market_data_location
price_f = ir_swap.price()
price_f.result()
cached = PricingCache.get(ir_swap, market_data_location, risk.Price, dates)
assert len(cached) == len(dates)
cached_scalar = PricingCache.get(ir_swap, market_data_location, risk.Price,
dates[0])
assert isinstance(cached_scalar, float)
dates = dates + (dt.date(2019, 10, 9), )
cached2 = PricingCache.get(ir_swap, market_data_location, risk.Price,
dates)
assert len(cached2)
assert len(cached2) < len(dates)
values = [{
'date': '2019-10-07',
'marketDataType': 'IR',
'assetId': 'USD',
'pointClass': 'Swap',
'point': '1y',
'value': 0.01
}, {
'date': '2019-10-07',
'marketDataType': 'IR',
'assetId': 'USD',
'pointClass': 'Swap',
'point': '2y',
'value': 0.015
}, {
'date': '2019-10-08',
'marketDataType': 'IR',
'assetId': 'USD',
'pointClass': 'Swap',
'point': '1y',
'value': 0.01
}, {
'date': '2019-10-08',
'marketDataType': 'IR',
'assetId': 'USD',
'pointClass': 'Swap',
'point': '2y',
'value': 0.015
}, {
'date': '2019-10-09',
'marketDataType': 'IR',
'assetId': 'USD',
'pointClass': 'Swap',
'point': '1y',
'value': 0.01
}, {
'date': '2019-10-09',
'marketDataType': 'IR',
'assetId': 'USD',
'pointClass': 'Swap',
'point': '2y',
'value': 0.015
}]
mocker.return_value = [[values]]
with HistoricalPricingContext(dates=dates, use_cache=True):
market_data_location = PricingContext.current.market_data_location
risk_f = ir_swap.calc(risk.IRDelta)
risk_frame = risk_f.result()
assert isinstance(risk_frame, pd.DataFrame)
assert len(risk_frame.index.unique()) == len(dates)
cached3 = PricingCache.get(ir_swap, market_data_location, risk.IRDelta,
dates)
assert len(cached3.index.unique()) == len(dates)
cached4 = PricingCache.get(ir_swap, market_data_location, risk.IRDelta,
dates[0])
assert len(cached4.index.unique()) == len(cached4)
