Skip to main content

IPython magic for parallel profiling

Project description

A tool for measuring serial and parallel execution, and comparing the results. Provides an IPython magic %ptime. This can be useful for measuring the benefits of parallelizing code, including measuring the effect of the Global Interpreter Lock (GIL).


In [1]: %load_ext ptime

In [2]: import numpy as np

In [3]: x = np.ones((5000, 10000))

In [4]: %ptime x + x
Total serial time:   0.42 s
Total parallel time: 0.25 s
For a 1.67X speedup across 2 threads

In [5]: %ptime -n4 x + x  # use 4 threads
Total serial time:   0.82 s
Total parallel time: 0.31 s
For a 2.60X speedup across 4 threads

In [6]: res = %ptime -o x + x  # Get the result
Total serial time:   0.41 s
Total parallel time: 0.25 s
For a 1.66X speedup across 2 threads

In [7]: res.speedup
Out[7]: 1.6610825669011922

In [8]: %%ptime  # Use as a cell magic
...: x = np.ones((5000, 10000))
...: y = x + x
Total serial time:   0.72 s
Total parallel time: 0.47 s
For a 1.54X speedup across 2 threads


This package is available via pip:

pip install ptime

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

ptime-0.0.1.tar.gz (2.8 kB view hashes)

Uploaded source

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page