Using Parallel Magics¶

IPython has a few magics for working with your engines.

This assumes you have started an IPython cluster, either with the notebook interface, or the ipcluster/controller/engine commands.

In [ ]:
from IPython import parallel
rc = parallel.Client()
dv = rc[:]
rc.ids


Creating a Client registers the parallel magics %px, %%px, %pxresult, pxconfig, and %autopx.
These magics are initially associated with a DirectView always associated with all currently registered engines.

Now we can execute code remotely with %px:

In [ ]:
%px a=5

In [ ]:
%px print(a)

In [ ]:
%px a

In [ ]:
with dv.sync_imports():
import sys

In [ ]:
%px from __future__ import print_function
%px print("ERROR", file=sys.stderr)


You don't have to wait for results. The %pxconfig magic lets you change the default blocking/targets for the %px magics:

In [ ]:
%pxconfig --noblock

In [ ]:
%px import time
%px time.sleep(5)
%px time.time()


But you will notice that this didn't output the result of the last command. For this, we have %pxresult, which displays the output of the latest request:

In [ ]:
%pxresult


Remember, an IPython engine is IPython, so you can do magics remotely as well!

In [ ]:
%pxconfig --block
%px %matplotlib inline

In [ ]:
%%px
import numpy as np
import matplotlib.pyplot as plt


%%px can also be used as a cell magic, for submitting whole blocks. This one acceps --block and --noblock flags to specify the blocking behavior, though the default is unchanged.

In [ ]:
dv.scatter('id', dv.targets, flatten=True)
dv['stride'] = len(dv)

In [ ]:
%%px --noblock
x = np.linspace(0,np.pi,1000)
for n in range(id,12, stride):
print(n)
plt.plot(x,np.sin(n*x))
plt.title("Plot %i" % id)

In [ ]:
%pxresult


It also lets you choose some amount of the grouping of the outputs with --group-outputs:

The choices are:

• engine - all of an engine's output is collected together
• type - where stdout of each engine is grouped, etc. (the default)
• order - same as type, but individual displaypub outputs are interleaved. That is, it will output the first plot from each engine, then the second from each, etc.
In [ ]:
%%px --group-outputs=engine
x = np.linspace(0,np.pi,1000)
for n in range(id+1,12, stride):
print(n)
plt.figure()
plt.plot(x,np.sin(n*x))
plt.title("Plot %i" % n)


When you specify 'order', then individual display outputs (e.g. plots) will be interleaved.

%pxresult takes the same output-ordering arguments as %%px, so you can view the previous result in a variety of different ways with a few sequential calls to %pxresult:

In [ ]:
%pxresult --group-outputs=order


Single-engine views¶

When a DirectView has a single target, the output is a bit simpler (no prefixes on stdout/err, etc.):

In [ ]:
from __future__ import print_function

def generate_output():
"""function for testing output

publishes two outputs of each type, and returns something
"""

import sys,os
from IPython.display import display, HTML, Math

print("stdout")
print("stderr", file=sys.stderr)

display(HTML("<b>HTML</b>"))

print("stdout2")
print("stderr2", file=sys.stderr)

display(Math(r"\alpha=\beta"))

return os.getpid()

dv['generate_output'] = generate_output


You can also have more than one set of parallel magics registered at a time.

The View.activate() method takes a suffix argument, which is added to 'px'.

In [ ]:
e0 = rc[-1]
e0.block = True
e0.activate('0')

In [ ]:
%px0 generate_output()

In [ ]:
%px generate_output()


As mentioned above, we can redisplay those same results with various grouping:

In [ ]:
%pxresult --group-outputs order

In [ ]:
%pxresult --group-outputs engine


Parallel Exceptions¶

When you raise exceptions with the parallel exception, the CompositeError raised locally will display your remote traceback.

In [ ]:
%%px
from numpy.random import random
A = random((100,100,'invalid shape'))


Remote Cell Magics¶

Remember, Engines are IPython too, so the cell that is run remotely by %%px can in turn use a cell magic.

In [ ]:
%%px
%%timeit
from numpy.random import random
from numpy.linalg import norm
A = random((100,100))
norm(A, 2)


Local Execution¶

As of IPython 1.0, you can instruct %%px to also execute the cell locally. This is useful for interactive definitions, or if you want to load a data source everywhere, not just on the engines.

In [ ]:
%%px --local
import os
thispid = os.getpid()
print(thispid)