def load_from_yaml(date: Union[str, pd.Timestamp],
ports: set = None) -> Portfolio:
"""Загружает информацию о портфеле из yaml-файлов."""
usd = indexes.usd(pd.Timestamp(date))
usd = usd.iloc[-1]
cash = 0
value = 0
positions = collections.Counter()
name = list()
for path in sorted(config.PORT_PATH.glob("*.yaml")):
if ports is None or path.name in ports:
name.append(path.stem)
with path.open() as port:
port = yaml.safe_load(port)
positions.update(port.pop("positions"))
cash += port.get("USD", 0) * usd + port.get("RUR", 0)
value += port.get("value", 0)
if value:
LOGGER.info(f"Проверка стоимости: {path}")
try:
Portfolio([path.stem], date, cash, positions, value)
except config.POptimizerError as err:
LOGGER.error(err)
continue
LOGGER.info("OK")
if not value:
value = None
return Portfolio(name, date, cash, positions, value)
def test_usd(date, usd):
"""Проверка, что первые данные обрезаны, а последние соответствуют аргументу."""
date = pd.Timestamp(date)
df = indexes.usd(date)
assert isinstance(df, pd.Series)
assert df.index.is_monotonic_increasing and df.name == col.CLOSE
assert df.index[0] >= bootstrap.START_DATE
assert df.index[-1] == pd.Timestamp(date)
assert df.loc[date] == pytest.approx(usd)
def __init__(self, ticker: str, params: DataParams):
"""Сохраняет данные о курсе."""
super().__init__(ticker, params)
usd = indexes.usd(params.end)
price = params.price(ticker)
usd = usd.reindex(
price.index,
method="ffill",
axis=0,
)
self.usd = torch.tensor(usd.values, dtype=torch.float, device=DEVICE)
self.history_days = params.history_days