Interesting! I thought this would use the ideas in your classic blog post. This is a very elegant alternative.

The running median in the blog post needed an indexable skiplist (or sorted collections or a blist) because it was the median over a window instead of all values seen so far. Windowing requires the ability to delete old elements as well as add new ones, and the heap version can't do that (it is add only).

If you're open to going beyond what is in the CPython docs, it would be nice to add an option for a running median over a sliding window:

def running_median(iterable, *, window=None):
    """Cumulative median of values seen so far or values in a sliding window.

    For example:

        >>> list(running_median([5.0, 9.0, 4.0, 12.0, 8.0, 9.0]))
        [5.0, 7.0, 5.0, 7.0, 8.0, 8.5]
        >>> list(running_median([5.0, 9.0, 4.0, 12.0, 8.0, 9.0], window=3))
        [5.0, 9.0, 8.0, 7.0, 8.0, 9.0]

    Supports numeric types such as int, float, Decimal, and Fraction,
    but not complex numbers which are unorderable.
    """

Yeah, let's do the windowed version - would be nice to be able to do a very long running median.