Skip to main content

Visualize Python performance profiles

Project description

tuna

Performance analysis for Python.

CircleCI Code style: black PyPI pyversions PyPi Version GitHub stars PyPi downloads

tuna is a modern, lightweight Python profile viewer inspired by SnakeViz. It handles runtime and import profiles, has no Python dependencies, uses d3 and bootstrap, and avoids certain errors present in SnakeViz (see below).

Create a runtime profile with

python -mcProfile -o program.prof yourfile.py

or an import profile with

python -X importtime yourfile.py 2> import.log

and show it with

tuna program.prof

Why tuna doesn't show the whole call tree

The whole timed call tree cannot be retrieved from profile data. Python developers made the decision to only store parent data in profiles because it can be computed with little overhead. To illustrate, consider the following program.

import time


def a(t0, t1):
    c(t0)
    d(t1)


def b():
    a(1, 4)


def c(t):
    time.sleep(t)


def d(t):
    time.sleep(t)


if __name__ == "__main__":
    a(4, 1)
    b()

The root process (__main__) calls a() which spends 4 seconds in c() and 1 second in d(). __main__ also calls b() which calls a(), this time spending 1 second in c() and 4 seconds in d(). The profile, however, will only store that c() spent a total of 5 seconds when called from a(), and likewise d(). The information that the program spent more time in c() when called in root -> a() -> c() than when called in root -> b() -> a() -> c() is not present in the profile.

tuna only displays the part of the timed call tree that can be deduced from the profile. SnakeViz, on the other hand, tries to construct the entire call tree, but ends up providing lots of wrong timings.

SnakeViz output. Wrong. tuna output. Only shows what can be retrieved from the profile.

Installation

tuna is available from the Python Package Index, so simply do

pip install tuna

to install.

Testing

To run the tuna unit tests, check out this repository and type

pytest

IPython magics

tuna includes a tuna line / cell magic which can be used as a drop-in replacement for the prun magic. Simply run %load_ext tuna to load the magic and then call it like %tuna sleep(3) or

%%tuna
sleep(3)

prun is still used to do the actual profiling and then the results are displayed in the notebook.

Development

After forking and cloning the repository, make sure to run make dep to install additional dependencies (bootstrap and d3) which aren't stored in the repo.

License

This software is published under the GPLv3 license.

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

tuna-0.4.7.tar.gz (140.1 kB view details)

Uploaded Source

Built Distribution

tuna-0.4.7-py3-none-any.whl (138.5 kB view details)

Uploaded Python 3

File details

Details for the file tuna-0.4.7.tar.gz.

File metadata

  • Download URL: tuna-0.4.7.tar.gz
  • Upload date:
  • Size: 140.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/49.2.1 requests-toolbelt/0.9.1 tqdm/4.48.2 CPython/3.9.0b5

File hashes

Hashes for tuna-0.4.7.tar.gz
Algorithm Hash digest
SHA256 7a4eb545bde7eb5cd43a7d1233e55c15bfe3101a0fff3da5cde1ff68b2191bcb
MD5 aa8277680eb5ebd8b097379e45dcb124
BLAKE2b-256 4db35eac2edb7daaed48b9cd7c06200ae273c75458a5baee2b1d61420aad447a

See more details on using hashes here.

File details

Details for the file tuna-0.4.7-py3-none-any.whl.

File metadata

  • Download URL: tuna-0.4.7-py3-none-any.whl
  • Upload date:
  • Size: 138.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/49.2.1 requests-toolbelt/0.9.1 tqdm/4.48.2 CPython/3.9.0b5

File hashes

Hashes for tuna-0.4.7-py3-none-any.whl
Algorithm Hash digest
SHA256 61101a82a6191fac5e6823c8d8fe4c67a642ba610666e0da8d900cee259c2d23
MD5 65ca68d14340ac0114aba9aa7bf5abfb
BLAKE2b-256 ec66916703dc27abba2d0ed8cf297151c7646a4b2e6bf2044dd264a007d0e32e

See more details on using hashes here.

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