nbresuse reports total Jupyter server memory

It looks like nbresuse is reporting the memory use for the entire server process, including all notebooks.

class MetricsHandler(IPythonHandler):
    def get(self):
        """
        Calculate and return current resource usage metrics
        """
        config = self.settings['nbresuse_display_config']
        cur_process = psutil.Process()
        all_processes = [cur_process] + cur_process.children(recursive=True)
        rss = sum([p.memory_info().rss for p in all_processes])

Is it possible to report memory use for each notebook individually? I don’t know anything about jupyter architecture, but maybe there’s a way to get a pointer to the calling notebook or PID?

[mathematicalmichael]

I mean, isn’t the total memory usage what you really care about, since bumping up against your system’s limits is what the concern is? I think one solution to get what you would like to see is to run dockerspawner through jupyterhub so that each notebook instance is in an isolated container. That way this extension should report the usage as a proportion of the total memory allocated to the container.

[jtpio]

@jkleint yes per notebook metrics would roughly correspond to per kernel metrics (although there can be multiple notebooks sharing the same kernel).

This is great feedback. Would you like to continue the conversation in https://github.com/yuvipanda/nbresuse/issues/31? (and maybe link to you comment or copy the content over there)