downloader.entsoe.load_interim

downloader.entsoe.load_interim(mode='combined', *, data_home=None)

Read the ENTSO-E interim CSV(s) written by the downloader.

This is the library-level counterpart of the inline load_interim() helpers that every submission script defines identically. The two modes reproduce the exact CSV-reading logic from those scripts so callers can replace their local copies with a single import.

Parameters

Name	Type	Description	Default
mode	str	Which interim layout to read. `"combined"` (default) — reads `<data_home>/interim/energy_load.csv` (written by `download_new_data`). This is the single DE-total series path used by chronos, optuna, and spotoptim submission scripts. `"four_zone"` — assembles the per-zone QC frame via `build_zone_qc_frame` and also writes the zones-only modelling CSV (`interim/energy_load_zones.csv`). This is the normal four-zone path used by team4_4zones_submit.	`'combined'`
data_home		Root data directory. If `None`, resolved via `get_data_home()`.	`None`

Returns

Name	Type	Description
	pd.DataFrame	pd.DataFrame: A UTC-indexed interim frame ready for `assert_submission_coverage`,
	pd.DataFrame	`select_key_lags`, and `entsoe_predictions`. In `"combined"` mode the
	pd.DataFrame	frame contains at least `Actual Load` and `Forecasted Load`. In
	pd.DataFrame	`"four_zone"` mode the frame additionally contains the per-zone columns
	pd.DataFrame	(`load_amprion`, `load_tennet`, `load_transnetbw`, `load_50hertz`).

Raises

Name	Type	Description
	FileNotFoundError	When the required interim file(s) are missing.
	ValueError	When `mode` is not `"combined"` or `"four_zone"`.

Examples

import os, shutil, tempfile
import pandas as pd
from spotforecast2_safe.downloader.entsoe import get_data_home, load_interim

tmp = tempfile.mkdtemp()
os.environ["SPOTFORECAST2_DATA"] = tmp
interim_dir = os.path.join(tmp, "interim")
os.makedirs(interim_dir, exist_ok=True)

idx = pd.date_range("2026-06-01", periods=48, freq="h", tz="UTC")
df = pd.DataFrame(
    {"Actual Load": 40000.0, "Forecasted Load": 41000.0}, index=idx
)
df.index.name = "Time (UTC)"
df.to_csv(os.path.join(interim_dir, "energy_load.csv"))

frame = load_interim(mode="combined")
print(frame.index.tz, len(frame))

shutil.rmtree(tmp)
del os.environ["SPOTFORECAST2_DATA"]

UTC 48