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bartzbeielstein merged 5 commits into from
Jun 13, 2026
Merged

docs(tasks): promote develop to main — clear stale task_safe links #374

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4dc24c6
chore: sync main into develop [skip ci]
github-actions[bot] Jun 12, 2026
00e9dab
docs(tasks): drop stale n-to-1 task wrapper references from task_multi
bartzbeielstein Jun 13, 2026
26d3d90
Merge pull request #373 from sequential-parameter-optimization/docs/f…
bartzbeielstein Jun 13, 2026
f8b7dd2
test(preprocessing,data): fix CodeQL alerts in tests
bartzbeielstein Jun 13, 2026
05ad147
Merge pull request #375 from sequential-parameter-optimization/test/f…
bartzbeielstein Jun 13, 2026
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4 changes: 2 additions & 2 deletions _freeze/docs/tasks/task_multi/execute-results/html.json
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6 changes: 3 additions & 3 deletions _freeze/docs/tutorials/n2n_predict_with_covariates_demo10/execute-results/html.json
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24 changes: 0 additions & 24 deletions docs/tasks/task_multi.qmd
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Original file line number Diff line number Diff line change
Expand Up @@ -206,29 +206,6 @@ instead of silent dropping) and to plotting:
`MultiTask.plot_with_outliers()` raises `NotImplementedError` because no
plotting library is permitted in this package.

## The n-to-1 task entry point

[`run_pipeline`](../reference/tasks.task_safe_n_to_1_with_covariates_and_dataframe.qmd) from
`task_safe_n_to_1_with_covariates_and_dataframe`
wraps exactly this pipeline with `task="lazy"` — one call from config and
DataFrame to combined forecast:

```{python}
from spotforecast2_safe.tasks.task_safe_n_to_1_with_covariates_and_dataframe import (
run_pipeline,
)

forecast = run_pipeline(config=cfg, dataframe=df, cache_home=cache)
forecast.head(3)
```

The matching console script accepts the same knobs as flags:

```bash
uv run spotforecast-safe-n2o1-cov-df --forecast_horizon 24 --lags 24 \
--include_holiday_features true
```

## Scaling up from the toy example

For a real run, switch the feature machinery on instead of off:
Expand Down Expand Up @@ -263,5 +240,4 @@ design, absent.

## Where to go next

- API reference: [`run_pipeline`](../reference/tasks.task_safe_n_to_1_with_covariates_and_dataframe.qmd) — the CLI-facing wrapper around this pipeline.
- API reference: [`MultiTask`](../reference/multitask.multi.MultiTask.qmd), [`BaseTask`](../reference/multitask.base.BaseTask.qmd), [`ConfigMulti`](../reference/configurator.config_multi.ConfigMulti.qmd), [`runner.run`](../reference/multitask.runner.run.qmd).
26 changes: 10 additions & 16 deletions tests/preprocessing/test_target_corruption.py
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Expand Up @@ -650,14 +650,11 @@ def test_fall_back_no_raise(self):
)
vals = [BASE_MW] * len(idx)
df = pd.DataFrame({"load": vals}, index=idx)
try:
mask = detect_target_corruption(
df, targets=["load"], range_mw=5_000, step_mw=8_000, window_days=7
)
except Exception as exc:
pytest.fail(
f"detect_target_corruption raised on fall-back DST index: {exc}"
)
# A raise here fails the test (with a full traceback); that is exactly
# the "must not raise" guarantee this case is asserting.
mask = detect_target_corruption(
df, targets=["load"], range_mw=5_000, step_mw=8_000, window_days=7
)
assert not mask.any(), "Clean DST week must produce no flags."

def test_fall_back_dropout_is_flagged(self):
Expand Down Expand Up @@ -694,14 +691,11 @@ def test_spring_forward_no_raise(self):
)
vals = [BASE_MW] * len(idx)
df = pd.DataFrame({"load": vals}, index=idx)
try:
mask = detect_target_corruption(
df, targets=["load"], range_mw=5_000, step_mw=8_000, window_days=7
)
except Exception as exc:
pytest.fail(
f"detect_target_corruption raised on spring-forward DST index: {exc}"
)
# A raise here fails the test (with a full traceback); that is exactly
# the "must not raise" guarantee this case is asserting.
mask = detect_target_corruption(
df, targets=["load"], range_mw=5_000, step_mw=8_000, window_days=7
)
assert not mask.any(), "Clean spring-forward DST week must produce no flags."


Expand Down
18 changes: 7 additions & 11 deletions tests/test_entsoe_loader.py
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Expand Up @@ -8,10 +8,6 @@

import spotforecast2_safe.data.entsoe_loader as entsoe_loader
from spotforecast2_safe.configurator import ConfigEntsoe
from spotforecast2_safe.data.entsoe_loader import (
entsoe_data_loader,
entsoe_test_data_loader,
)


def _write_interim_csv(path, start: str, periods: int, tz: str | None = "UTC"):
Expand All @@ -29,7 +25,7 @@ def test_absolute_path_loads_full_frame(self, tmp_path):

config = ConfigEntsoe()
config.data_filename = str(csv_path)
df = entsoe_data_loader(config)
df = entsoe_loader.entsoe_data_loader(config)

assert df.shape == (48, 1)
assert df.index.name == "Time (UTC)"
Expand All @@ -41,7 +37,7 @@ def test_relative_path_resolves_against_data_home(self, tmp_path, monkeypatch):

config = ConfigEntsoe()
config.data_filename = "energy_load.csv"
df = entsoe_data_loader(config)
df = entsoe_loader.entsoe_data_loader(config)

assert df.shape == (24, 1)

Expand All @@ -50,7 +46,7 @@ def test_missing_file_raises_with_cli_hint(self, tmp_path):
config.data_filename = str(tmp_path / "does_not_exist.csv")

with pytest.raises(FileNotFoundError, match="spotforecast2-entsoe"):
entsoe_data_loader(config)
entsoe_loader.entsoe_data_loader(config)


class TestEntsoeTestDataLoader:
Expand All @@ -66,7 +62,7 @@ def test_slices_predict_size_steps_after_end_train(self, tmp_path):
_write_interim_csv(csv_path, "2025-12-29 00:00", 120)
config = self._config(csv_path, "2025-12-31 00:00+00:00")

test_df = entsoe_test_data_loader(config)
test_df = entsoe_loader.entsoe_test_data_loader(config)

assert test_df.shape == (24, 1)
assert test_df.index[0] == pd.Timestamp("2025-12-31 01:00", tz="UTC")
Expand All @@ -77,7 +73,7 @@ def test_naive_end_train_is_localized_to_utc(self, tmp_path):
_write_interim_csv(csv_path, "2025-12-29 00:00", 120)
config = self._config(csv_path, "2025-12-31 00:00") # no tz marker

test_df = entsoe_test_data_loader(config)
test_df = entsoe_loader.entsoe_test_data_loader(config)

assert test_df.shape == (24, 1)
assert test_df.index[0] == pd.Timestamp("2025-12-31 01:00", tz="UTC")
Expand All @@ -87,7 +83,7 @@ def test_naive_csv_index_is_supported(self, tmp_path):
_write_interim_csv(csv_path, "2025-12-29 00:00", 120, tz=None)
config = self._config(csv_path, "2025-12-31 00:00+00:00")

test_df = entsoe_test_data_loader(config)
test_df = entsoe_loader.entsoe_test_data_loader(config)

assert test_df.shape == (24, 1)
assert test_df.index[0] == pd.Timestamp("2025-12-31 01:00")
Expand All @@ -98,6 +94,6 @@ def test_window_shorter_when_data_runs_out(self, tmp_path):
_write_interim_csv(csv_path, "2025-12-29 00:00", 60) # ends 12-31 11:00
config = self._config(csv_path, "2025-12-31 00:00+00:00")

test_df = entsoe_test_data_loader(config)
test_df = entsoe_loader.entsoe_test_data_loader(config)

assert len(test_df) == 11 # only the rows that exist after the cutoff
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