Process profiler

A simple process profiler. propro can be used in many different ways. Conviniently in can be used on the command line:

$ propro --fmt=png <command>

for more options call:

$ propro --help

Another option is to call the profiling programatically

import propro
x = propro.profile_cmd("ufig --background-type=chunked_map ufig.config.random")

The returned profiling result can than for instance be used for custom plotting.

propro offers the option to profile a single Python function using a decorator

import propro
import numpy as np


@propro.profile(sample_rate=0.1, fmt="txt")
def mem_hungry(size):
    a = []
    for i in range(size):
        a.append(np.random.random())

    b = []
    for i in range(size):
        t = []
        for j in range(size):
            t.append(i * a[j])
        b.append(t)

    b = np.array(b)

The profiling output is stored in the folder where the Python code was launched.

Finally, propro can be embedded in your IPython notebooks. Load the extentsion with

import propro

%load_ext propro

The profiling can be done on line level

%propro -r 0.1 load_pixels(path, PIXEL_COUNT)

or on cell level

%%propro -r 0.1
X = np.random.normal(size=(200,200,1000))
P, D, Q = np.linalg.svd(X, full_matrices=False)
X_a = np.dot(np.dot(P, np.diag(D)), Q)
print(np.std(X), np.std(X_a), np.std(X - X_a))

The output will look something like this if rendered into an image:

Contents:

• Installation
• propro Package
  • propro Package
  • cli Module
  • magic Module
  • plotting Module
  • propro Module
• Contributing
  • Types of Contributions
  • Pull Request Guidelines
  • Tips
• Credits
  • Development Lead
  • Contributors
• History
  • 0.1.0 (2016-01-01)

Feedback

If you have any suggestions or questions about Process profiler feel free to email me at jakeret@phys.ethz.ch.

If you encounter any errors or problems with Process profiler, please let me know!