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869cfed125
* merge branch develop with main * bump desktop version * fix the merge * sync Cargo.lock to desktop 2.0.0 * fix cli conftest.py --------- Co-authored-by: deeleeramone <>
161 lines
4.8 KiB
Python
161 lines
4.8 KiB
Python
import pytest
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from openbb_core.app.model.obbject import OBBject
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@pytest.fixture(scope="session")
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def obb(pytestconfig):
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if pytestconfig.getoption("markexpr") != "not integration":
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import openbb
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return openbb.obb
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return None
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@pytest.mark.integration
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def test_quantitative_normality(obb, prices_data):
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result = obb.quantitative.normality(data=prices_data, target="close")
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assert isinstance(result, OBBject)
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assert result.results
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@pytest.mark.integration
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def test_quantitative_capm(obb, prices_data):
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result = obb.quantitative.capm(data=prices_data, target="close")
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assert isinstance(result, OBBject)
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assert result.results
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@pytest.mark.integration
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def test_quantitative_unitroot_test(obb, prices_data):
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result = obb.quantitative.unitroot_test(data=prices_data, target="close")
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assert isinstance(result, OBBject)
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assert result.results
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@pytest.mark.integration
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def test_quantitative_summary(obb, prices_data):
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result = obb.quantitative.summary(data=prices_data, target="close")
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assert isinstance(result, OBBject)
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assert result.results
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@pytest.mark.integration
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def test_quantitative_rolling_skew(obb, prices_data):
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result = obb.quantitative.rolling.skew(data=prices_data, target="close", window=20)
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assert isinstance(result, OBBject)
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assert result.results
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@pytest.mark.integration
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def test_quantitative_rolling_variance(obb, prices_data):
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result = obb.quantitative.rolling.variance(
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data=prices_data, target="close", window=20
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)
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assert isinstance(result, OBBject)
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assert result.results
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@pytest.mark.integration
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def test_quantitative_rolling_stdev(obb, prices_data):
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result = obb.quantitative.rolling.stdev(data=prices_data, target="close", window=20)
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assert isinstance(result, OBBject)
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assert result.results
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@pytest.mark.integration
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def test_quantitative_rolling_kurtosis(obb, prices_data):
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result = obb.quantitative.rolling.kurtosis(
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data=prices_data, target="close", window=20
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)
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assert isinstance(result, OBBject)
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assert result.results
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@pytest.mark.integration
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def test_quantitative_rolling_mean(obb, prices_data):
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result = obb.quantitative.rolling.mean(data=prices_data, target="close", window=20)
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assert isinstance(result, OBBject)
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assert result.results
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@pytest.mark.integration
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def test_quantitative_rolling_quantile(obb, prices_data):
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result = obb.quantitative.rolling.quantile(
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data=prices_data, target="close", window=20, quantile_pct=0.75
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)
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assert isinstance(result, OBBject)
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assert result.results
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@pytest.mark.integration
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def test_quantitative_stats_skew(obb, prices_data):
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result = obb.quantitative.stats.skew(data=prices_data, target="close")
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assert isinstance(result, OBBject)
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assert result.results
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@pytest.mark.integration
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def test_quantitative_stats_variance(obb, prices_data):
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result = obb.quantitative.stats.variance(data=prices_data, target="close")
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assert isinstance(result, OBBject)
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assert result.results
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@pytest.mark.integration
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def test_quantitative_stats_stdev(obb, prices_data):
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result = obb.quantitative.stats.stdev(data=prices_data, target="close")
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assert isinstance(result, OBBject)
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assert result.results
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@pytest.mark.integration
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def test_quantitative_stats_kurtosis(obb, prices_data):
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result = obb.quantitative.stats.kurtosis(data=prices_data, target="close")
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assert isinstance(result, OBBject)
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assert result.results
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@pytest.mark.integration
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def test_quantitative_stats_mean(obb, prices_data):
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result = obb.quantitative.stats.mean(data=prices_data, target="close")
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assert isinstance(result, OBBject)
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assert result.results
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@pytest.mark.integration
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def test_quantitative_stats_quantile(obb, prices_data):
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result = obb.quantitative.stats.quantile(
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data=prices_data, target="close", quantile_pct=0.75
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)
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assert isinstance(result, OBBject)
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assert result.results
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@pytest.mark.integration
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def test_quantitative_performance_omega_ratio(obb, prices_data):
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returns = [
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{"date": current["date"], "return": current["close"] / previous["close"] - 1}
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for previous, current in zip(prices_data, prices_data[1:])
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]
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result = obb.quantitative.performance.omega_ratio(data=returns, target="return")
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assert isinstance(result, OBBject)
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assert result.results
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@pytest.mark.integration
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def test_quantitative_performance_sharpe_ratio(obb, prices_data):
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result = obb.quantitative.performance.sharpe_ratio(
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data=prices_data, target="close", window=20
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)
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assert isinstance(result, OBBject)
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assert result.results
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@pytest.mark.integration
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def test_quantitative_performance_sortino_ratio(obb, prices_data):
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result = obb.quantitative.performance.sortino_ratio(
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data=prices_data, target="close", window=20
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)
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assert isinstance(result, OBBject)
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assert result.results
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