Metadata-Version: 2.4
Name: eyekit
Version: 0.7.1
Summary: A Python package for analyzing reading behavior using eyetracking data
Author-email: Jon Carr <jon.carr@rhul.ac.uk>
License-Expression: GPL-3.0-only
Project-URL: Homepage, https://github.com/jwcarr/eyekit
Project-URL: Documentation, https://jwcarr.github.io/eyekit/
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Human Machine Interfaces
Classifier: Topic :: Scientific/Engineering :: Visualization
Classifier: Topic :: Text Processing :: Fonts
Classifier: Topic :: Text Processing :: Linguistic
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: cairocffi>=1.1
Dynamic: license-file

<img src='https://jwcarr.github.io/eyekit/images/logo.png' width='300'>

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.


Is Eyekit the Right Tool for Me?
--------------------------------

- 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.


Installation
------------

Eyekit may be installed using `pip`:

```shell
$ pip install eyekit
```

Eyekit is compatible with Python 3.8+. Its main dependency is the graphics library [Cairo](https://cairographics.org), 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](https://brew.sh): `brew install cairo`. On Windows, it can be installed using [Anaconda](https://anaconda.org/anaconda/cairo): `conda install -c anaconda cairo`.


**[Full documentation and a usage guide is available here](https://jwcarr.github.io/eyekit/)**


Contributing
------------

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.
