lift-linguistic-features-py 0.1.0

Linguistic feature extraction and annotation utilities for text.

PyLift is the Python branch of the LiFT library.

Installation

Core package:

pip install py_lift

Optional tooling dependencies (examples/workbench):

poetry install --with examples

spaCy language models are optional and must be installed separately when using Spacy_Preprocessor with the default model names:

python -m py_lift.model_setup --languages en de fr sl tr

For Turkish (tr_core_news_md) and for SE_AbstractnessAnnotator (lift-resources-lists), install the required internal packages from your organization's package source.

py_lift.model_setup supports language-specific wheel URLs via built-in defaults and overrides. Turkish currently uses this built-in URL by default:

https://pypi.cats.fernuni-hagen.de/packages/tr_core_news_md-1.0-py3-none-any.whl

You can override sources for any language via environment variables:

export PY_LIFT_MODEL_URL_TR="https://your-internal-source/tr_core_news_md-1.0-py3-none-any.whl"
python -m py_lift.model_setup --languages tr

Or via CLI:

python -m py_lift.model_setup --languages tr --model-url tr=https://your-internal-source/tr_core_news_md-1.0-py3-none-any.whl

You can also let the preprocessor auto-install missing models at runtime:

from py_lift.preprocessing import Spacy_Preprocessor

prep = Spacy_Preprocessor("en", auto_install_models=True)

Standalone Python example

Run a non-visual end-to-end pipeline example:

python examples/pure_python_pipeline.py

The script is located at examples/pure_python_pipeline.py and demonstrates:

• language detection
• spaCy preprocessing
• spelling anomaly annotation
• readability + count feature extraction
• plain stdout output (no visualization)

Other examples (now also in top-level examples/):

• examples/visualization_streamlit.py
• examples/visualization_notebook.ipynb

Release (PyPI)

Short release checklist:

1. Update the version in pyproject.toml.

2. Run tests:

   poetry install --with dev
   poetry run pytest
   

Model-dependent tests (for example py_lift/tests/test_preprocessing.py) are marked as requires_models and skipped by default. Run them explicitly with:

poetry run pytest --run-model-tests

3. Build distribution artifacts:

   poetry build
   

4. Publish:

   export POETRY_PYPI_TOKEN_PYPI="pypi-XXXXXXXXXXXXXXXXXXXX"
   poetry publish