<jupyter_start><jupyter_text>To verify that the server is **actually** running, go to [http://127.0.0.1:5678/ping](http://127.0.0.1:5678/ping).This is just a ping test  Very first run<jupyter_code>N = 10
N
s = 5
s
l = 0<jupyter_output><empty_output><jupyter_text>Update the value of a variable, asynchronously<jupyter_code>%%async_run 
N = 10**s
print(N)<jupyter_output><empty_output><jupyter_text>The following cell has no output, just computation<jupyter_code>%%async_run
s += 1
l += 1
s, l
l += 1
l<jupyter_output><empty_output><jupyter_text>1. Output History is correctly updated<jupyter_code>_oh<jupyter_output><empty_output><jupyter_text>2. Exception Output HandlingIn this particular example, the `L` variable has been never defined, thus leading to a `NameError` exception<jupyter_code>%async_run L += 1<jupyter_output><empty_output><jupyter_text>3. Let's do an heavy computation example<jupyter_code>%%async_run 
N = 10**7
s = sum([i**2 for i in range(N)])
print(s)
s<jupyter_output><empty_output><jupyter_text>4. Module Import in `async_run` cells<jupyter_code>from sklearn.datasets import load_iris

iris = load_iris()
X = iris.data
%%async_run
import numpy as np
s = np.sum(X)
print(s)<jupyter_output><empty_output><jupyter_text>Now the `numpy` module is available in the notebook namespace to be used<jupyter_code>a = np.array(range(10))
a
%%async_run
s = np.sum(a)
s
np.sum(range(10))
%async_stop_server<jupyter_output><empty_output>
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