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eyekit
Advanced tools
Eyekit is a Python package for analyzing reading behavior using eyetracking data. Eyekit aims to be entirely independent of any particular eyetracker hardware, experiment software, or data formats. It has an object-oriented style that defines three core objects – the TextBlock, InterestArea, and FixationSequence – that you bring into contact with a bit of coding.
You want to analyze which parts of a text someone is looking at and for how long.
You need convenient tools for extracting areas of interest from texts, such as specific words, phrases, or letter combinations.
You want to calculate common reading measures, such as gaze duration or initial landing position.
You need support for arbitrary fonts, multiline passages, right-to-left text, or non-alphabetical scripts.
You want the flexibility to define custom reading measures and to build your own reproducible processing pipeline.
You would like tools for dealing with noise and calibration issues, and for discarding fixations according to your own criteria.
You want to share your data in an open format and produce publication-ready vector graphics.
Eyekit may be installed using pip:
$ pip install eyekit
Eyekit is compatible with Python 3.8+. Its main dependency is the graphics library Cairo, which you might also need to install if it's not already on your system. Many Linux distributions have Cairo built in. On a Mac, it can be installed using Homebrew: brew install cairo. On Windows, it can be installed using Anaconda: conda install -c anaconda cairo.
Full documentation and a usage guide is available here
This project is in the stable/maintenance phase and is not under active development. I am only aiming to fix bugs and keep it compatible with current versions of Python so that it remains useful to the community. With that in mind, contributions are very welcome, but please read the CONTRIBUTING file before submitting a pull request.
FAQs
A Python package for analyzing reading behavior using eyetracking data
We found that eyekit demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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