docuscospacy: Support for spaCy models trained on DocuScope and the CLAWS7 tagset
The docuscospacy package contains a set of functions to facilitate the processing of tagged corpora using:
en_docusco_spacy – a spaCy model trained on the CLAWS7 tagset and DocuScope
The current version of the package runs in polars
The package can also convert a corpus to and from:
tmtoolkit – a set of tools for text mining and topic modeling
The documentation for docuscospacy is available on docuscospacy.readthedocs.org and the GitHub code repository is on github.com/browndw/docuscospacy.
Requirements and installation
docuscospacy works with Python 3.10 or newer (tested up to Python 3.12). It also requires spacy >= 3.8.
The recommended way of installing docuscospacy is to:
create and activate a Python Virtual Environment (“venv”)
install spacy
install docuscospacy
download the en_docusco_spacy model
pip install docuscospacyThe optional dtm_to_coo helper returns a SciPy sparse matrix for interoperability with tools such as tmtoolkit. Install the sparse extra if you need that conversion:
pip install "docuscospacy[sparse]"Note that installing the model depends on your spaCy version. Some versions allow:
pip install https://huggingface.co/browndw/en_docusco_spacy/resolve/main/en_docusco_spacy-1.5-py3-none-any.whlBut new ones may require:
pip install "en_docusco_spacy @ https://huggingface.co/browndw/en_docusco_spacy/resolve/main/en_docusco_spacy-1.5-py3-none-any.whl"Features
Corpus analysis
The docuscospacy package supports the post-tagging generation of:
Outputs can be controlled either by part-of-speech or by DocuScope tag. Thus, can as noun and can as verb, for example, can be disambiguated.
Additionally, tagged multi-token sequences are aggregated for analysis. So, for example, where in spite of is tagged as a token sequence, it is combined into a single token.
Other features
KWIC tables that locate a node word in a center column with context columns on either side
Limits
the model that this package is designed for has only been trained on English
all data must reside in memory, i.e. no streaming of large data from the hard disk (which for example Gensim supports)
License
Code licensed under Apache License 2.0. See LICENSE file.
1 maintainer
Release files for docuscospacy 0.3.7
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Source distribution (sdist)
| File | Size | Uploaded | |
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| docuscospacy-0.3.7.tar.gz | 1.1 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| docuscospacy-0.3.7-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 2.2 MB
Release files / docuscospacy-0.3.7.tar.gz
| Download URL | docuscospacy-0.3.7.tar.gz |
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| Size | 1.1 MB |
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