def METHOD_NAME(
    item_id_to_length: Dict[str, int],
    static_features: Optional[pd.DataFrame] = None,
    covariates_names: Optional[List[str]] = None,
    freq: str = "D",
):
    tuples = []
    for item_id, length in item_id_to_length.items():
        for ts in pd.date_range(pd.Timestamp("2022-01-01"), periods=length, freq=freq):
            tuples.append((item_id, ts))
    index = pd.MultiIndex.from_tuples(tuples, names=[ITEMID, TIMESTAMP])
    df = TimeSeriesDataFrame(
        pd.DataFrame(
            index=index,
            data=[random.random() for _ in index],
            columns=["target"],
        )
    )
    df.freq  # compute _cached_freq
    df.static_features = static_features
    if covariates_names is not None:
        for name in covariates_names:
            df[name] = np.random.normal(size=len(df))
    return df