def test_processing_plot():
from distributed.bokeh.worker_monitor import processing_plot
source, fig = processing_plot()
def f(_, old, new):
host = worker_source.data['host']
hosts = [host[i] for i in new['1d']['indices']]
@gen.coroutine
def _():
results = yield scheduler.broadcast(hosts=hosts, msg={'op': 'health'})
text = json.dumps(results, indent=2)
paragraph.text = text
doc.add_next_tick_callback(_)
worker_source.on_change('selected', f)
"""
processing_source, processing_plot = processing_plot(width=WIDTH, height=150)
def processing_plot_update():
with log_errors():
msg = messages['processing']
if not msg['ncores']:
return
data = processing_update(msg)
x_range = processing_plot.x_range
max_right = max(data['right'])
min_left = min(data['left'][:-1])
cores = max(data['ncores'])
if min_left < x_range.start: # not out there enough, jump ahead
x_range.start = min_left - 2
elif x_range.start < 2 * min_left - cores: # way out there, walk back
x_range.start = x_range.start * 0.95 + min_left * 0.05
if x_range.end < max_right:
def test_processing_plot():
from distributed.bokeh.worker_monitor import processing_plot
source, fig = processing_plot()
