Why does the Qlib use 238 instead of 252 as the number of trading days per year in the \contrib\evaluate.py?

In the risk_analysis of \contrib\evaluate.py, the function comments say

    Parameters
    ----------
    r : pandas.Series
        daily return series.
    N: int
        scaler for annualizing information_ratio (day: 252, week: 50, month: 12), at least one of `N` and `freq` should exist
    freq: str
        analysis frequency used for calculating the scaler, at least one of `N` and `freq` should exist

But inside the function, it uses 238 instead of 252 to calculate the annualized_return.

    def cal_risk_analysis_scaler(freq):
        _count, _freq = Freq.parse(freq)
        # len(D.calendar(start_time='2010-01-01', end_time='2019-12-31', freq='day')) = 2384
        _freq_scaler = {
            Freq.NORM_FREQ_MINUTE: 240 * 238,
            Freq.NORM_FREQ_DAY: 238,
            Freq.NORM_FREQ_WEEK: 50,
            Freq.NORM_FREQ_MONTH: 12,
        }
        return _freq_scaler[_freq] / _count

    if N is None and freq is None:
        raise ValueError("at least one of `N` and `freq` should exist")
    if N is not None and freq is not None:
        warnings.warn("risk_analysis freq will be ignored")
    if N is None:
        N = cal_risk_analysis_scaler(freq)

    mean = r.mean()
    std = r.std(ddof=1)
    annualized_return = mean * N

Can I ask why the _freq_scaler uses 238 instead of 252?

Start in contrib/evaluate.py at risk_analysis and cal_risk_analysis_scaler, then inspect Freq.parse and the surrounding annualization logic. Determine whether the 238-day scaler is intentional for the available calendar or conflicts with the documented 252-day value; done means the code and comments consistently explain the chosen behavior, with relevant tests updated if they exist.