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scyseq is a Python package for generating, defining, manipulating, characterizing and plotting symbolic sequences which are defined as successive occurrences of symbols (or states) taken from a finite-length alphabet (set of states).

Tools used in this package:

Sphinx pytest Hatch doctest

For development, hatch is used to manage the virtual environment and dependencies.

Make sure you have hatch installed in your default Python environment:

hatch --version

If it is not installed, you can install it using pip:

pip install hatch

Development installation / activation

hatch shell

Virtual Environment Setup

Hatch manages virtual environments for this project. Virtual environments can be stored in a centralized location by adding the following to ~/.config/hatch/config.toml:

[envs]
storage.path = "~/_virtualenvs/hatch_envs"

This configuration centralizes all environments in one directory for easier management across projects.

To deactivate the environment, run:

exit

Building Documentation

To generate HTML documentation from the repository root, run:

hatch run docs:build

The generated HTML documentation will be available in docs/build/html/. Open docs/build/html/index.html in your browser to view the documentation.

You can also build the documentation manually by first activating the Hatch environment:

hatch shell

Then navigate to the docs folder and build the HTML files:

On Windows:

cd docs
./make.bat html

On Linux/Mac:

cd docs
make html

The generated HTML documentation will be available in docs/build/html/. Open docs/build/html/index.html in your browser to view the documentation.

Tutorials

Tutorials are available in the docs/source/notebooks directory. To run a tutorial, activate the Hatch environment and execute the desired tutorial script:

hatch shell

Make sure you have Jupyter installed in the environment:

pip install jupyter

Then you can open the Jupyter Notebook interface by running:

jupyter notebook 

This will open a web interface where you can navigate to the docs/source/notebooks directory and open the tutorial notebooks to run them interactively.

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A Python package for symbolic sequences analysis

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