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README.md

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vprof

vprof is a Python package providing rich and interactive visualizations for various Python program characteristics such as running time and memory usage. It supports Python 2.7, Python 3.4, Python 3.5 and distributed under BSD license.

The project is in active development and some of its features might not work as expected.

Screenshots

vprof-gif

Contributing

All contributions are highly encouraged! You can add new features, report and fix existing bugs and write docs and tutorials. Feel free to open issue or send pull request!

Prerequisites

The required dependencies to build vprof from source code:

  • Python 2.7, Python 3.4 or Python 3.5
  • pip
  • npm >= 3.3.12

npm is required to build vprof from sources only.

Dependencies

All Python and npm module dependencies are listed in package.json and requirements.txt.

Installation

vprof can be installed from PyPI

pip install vprof

To build vprof from sources, clone this repository and execute

python setup.py deps_install && python setup.py build_ui && python setup.py install

To install just vprof dependencies, run

python setup.py deps_install

Usage

vprof -c <config> <src>

<config> is a combination of supported modes:

  • c - CPU flame graph

Shows CPU flame graph for <src>.

  • p - profiler

Runs Python profiler on <src> and displays results.

  • m - memory graph

Shows objects that are tracked by CPython GC and left in memory after code execution. Also shows process memory usage after execution of each line of <src>.

  • h - code heatmap

Displays all executed code of <src> with line execution count.

<src> can be Python source file (e.g. testscript.py) or path to package (e.g. myproject/test_package).

To run scripts with arguments use double quotes

vprof -c cmh "testscript.py --foo --bar"

Modes can be combined

vprof -c cm testscript.py

vprof can also profile functions. In order to do this, launch vprof in remote mode:

vprof -r

vprof will open new tab in default web browser and then wait for stats.

To profile a function run

from vprof import runner

def foo(arg1, arg2):
    ...

runner.run(foo, 'cmhp', args=(arg1, arg2), host='localhost', port=8000)

where cmhp is profiling mode, host and port are hostname and port of vprof server launched in remote mode. Obtained stats will be rendered in new tab of default web browser, opened by vprof -r command.

vprof is able to save profile stats to file and render visualizations from previously saved file.

vprof -c cmh src.py --output-file profile.json

writes profile to file and

vprof --input-file profile.json

renders visualizations from previously saved file.

Check vprof -h for full list of supported parameters.

To show UI help, press h when visualizations are displayed.

Also you can check examples directory for more profiling examples.

Testing

Just run:

python setup.py test && python setup.py e2e_test

License

BSD