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pyheat

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Profilers are extremely helpful tools. They help us dig deep into code, find and understand performance bottlenecks. But sometimes we just want to lay back, relax and still get a gist of the hot zones in our code.

A picture is worth a thousand words.

So, instead of presenting the data in tabular form, if presented as a heatmap visualization, it makes comprehending the time distribution in the given program much easier and quicker. That is exactly what is being done here !

Demo

Demo

Scroll Demo

ScrollDemo

Features

Setup

Using pip

pip install py-heat

Directly from the repository

git clone https://github.com/csurfer/pyheat.git
python pyheat/setup.py install

Usage

As a command

# To view the heatmap.
pyheat <path_to_python_file>
# To output the heatmap as a file.
pyheat <path_to_python_file> --out image_file.png
pyheat --help

As a module

from pyheat import PyHeat
ph = PyHeat(<file_path>)
ph.create_heatmap()
# To view the heatmap.
ph.show_heatmap()
# To output the heatmap as a file.
ph.show_heatmap('image_file.png')

Contributing

Bug Reports and Feature Requests

Please use issue tracker for reporting bugs or feature requests.

Development

Pull requests are most welcome.

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