async def test_ticker_traded(mocker):
"""Для торгуемого тикера должны обновляться котировки и дивиденды."""
dispatcher = handlers.EventHandlersDispatcher()
event = events.TickerTraded(
"ticker",
"ISIN",
"M1",
date(2020, 12, 22),
pd.DataFrame([1]),
)
fake_repo = mocker.Mock()
fake_load_by_id_and_handle_event = mocker.patch.object(
handlers,
"_load_by_id_and_handle_event",
side_effect=[["aa"], ["bb", "cc"]],
)
assert await dispatcher.handle_event(event,
fake_repo) == ["aa", "bb", "cc"]
fake_load_by_id_and_handle_event.assert_has_calls([
mocker.call(fake_repo, base.create_id(ports.QUOTES, "ticker"), event),
mocker.call(fake_repo, base.create_id(ports.DIVIDENDS, "ticker"),
event),
], )
def test_new_events(table, mocker):
"""Создание событий для всех торгуемых тикеров."""
table._df = pd.DataFrame(
[["YY", 10, "m2"], ["UU", 100, "m1"]],
columns=[col.ISIN, col.LOT_SIZE, col.MARKET],
index=["GAZP", "AKRN"],
)
trading_date = date(2020, 12, 15)
fake_usd = mocker.Mock()
event = events.USDUpdated(trading_date, fake_usd)
assert table._new_events(event) == [
events.TickerTraded("GAZP", "YY", "m2", trading_date,
fake_usd.copy.return_value),
events.TickerTraded("AKRN", "UU", "m1", trading_date,
fake_usd.copy.return_value),
]
async def test_prepare_df(div_table, mocker):
"""Корректно рассчитываются значения.
Курс сдвигается вперед для отсутствующих дат.
Рублевые значения не пересчитываются.
Для задвоенных дат данные группируются и суммируются.
"""
div_table._gateway = mocker.AsyncMock()
div_table._gateway.return_value = pd.DataFrame(
[
[20, col.RUR],
[30, col.USD],
[40, col.USD],
[10, col.RUR],
],
index=[
date(2020, 12, 16),
date(2020, 12, 16),
date(2021, 1, 11),
date(2021, 2, 5),
],
columns=["TICKER", col.CURRENCY],
)
usd = pd.DataFrame(
[2, 3, 4],
index=[
date(2020, 12, 15),
date(2021, 1, 10),
date(2021, 2, 5),
],
columns=[col.CLOSE],
)
event = events.TickerTraded("TICKER", "ISIN", "M1", date(2020, 12, 16),
usd)
pd.testing.assert_frame_equal(
await div_table._prepare_df(event),
pd.DataFrame(
[80, 120, 10],
index=[
date(2020, 12, 16),
date(2021, 1, 11),
date(2021, 2, 5),
],
columns=["TICKER"],
),
check_dtype=False,
)
def _new_events(self,
event: events.USDUpdated) -> List[domain.AbstractEvent]:
"""События факта торговли конкретных бумаг."""
df: pd.DataFrame = self._df
trading_date = event.date
return [
events.TickerTraded(
ticker,
df.at[ticker, col.ISIN],
df.at[ticker, col.MARKET],
trading_date,
event.usd.copy(deep=True),
) for ticker in df.index
]
async def test_load_after_empty(table, mocker):
"""Загрузка данных для пустых старых."""
table._df = pd.DataFrame()
table._aliases = mocker.AsyncMock()
table._quotes = mocker.AsyncMock()
mocker.patch.object(quotes.pd, "concat")
event = events.TickerTraded(
"TICKER",
"ISIN",
"M1",
date(2020, 12, 16),
mocker.Mock(),
)
assert await table._load_df(event) is quotes.pd.concat.return_value
assert table._aliases.call_count == 0
table._quotes.assert_called_once_with("TICKER", "M1", None, "2020-12-16")
async def test_load_first(table, mocker):
"""Загрузка данных в первый раз."""
fake_aliases = mocker.AsyncMock()
fake_aliases.return_value = ["ALIAS"]
table._aliases = fake_aliases
table._quotes = mocker.AsyncMock()
mocker.patch.object(quotes.pd, "concat")
event = events.TickerTraded(
"TICKER",
"ISIN",
"M1",
date(2020, 12, 16),
mocker.Mock(),
)
assert await table._load_df(event) is quotes.pd.concat.return_value
fake_aliases.assert_called_once_with("ISIN")
table._quotes.assert_called_once_with("ALIAS", "M1", None, "2020-12-16")
from poptimizer.data.domain import events
from poptimizer.data.domain.tables import base, dividends
from poptimizer.shared import col
@pytest.fixture(scope="function", name="div_table")
def create_div_table():
"""Создает пустую таблицу дивидендов для тестов."""
id_ = base.create_id(ports.DIVIDENDS)
return dividends.Dividends(id_)
DIV_UPDATE_CASES = (
(
None,
events.TickerTraded("TICKER", "ISIN", "M1", date(2020, 12, 17),
pd.DataFrame()),
True,
),
(
pd.DataFrame(),
events.UpdateDivCommand("TICKER"),
True,
),
(
pd.DataFrame(),
events.TickerTraded("TICKER", "ISIN", "M1", date(2020, 12, 17),
pd.DataFrame()),
False,
),
)