{"categories":[{"label":"Python Modules","url":"https://skillfed.io/packages/category/software-development-libraries-python-modules/21"},{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/11"}],"enrichment":{"capability":"Reads and writes ARFF (Attribute-Relation File Format) files, a standard format for machine learning datasets, converting them to and from Python dictionaries and lists.","skillfed_tags":["data-format","machine-learning","abandoned"],"use_cases":["Loading ARFF datasets from Weka experiments into Python for analysis or preprocessing.","Converting machine learning datasets between ARFF and Python native structures for interoperability.","Serializing experimental data to ARFF format for use in Weka or other ML tools.","Batch processing of ARFF files in data pipelines that do not require active maintenance.","Reading historical datasets stored in ARFF format in academic or research archives."],"what_it_does":"liac-arff is a lightweight parser for ARFF files, the standard dataset format used by Weka and other machine learning tools. It provides a json-like interface to read ARFF files into Python dictionaries and lists, and to serialize Python data structures back to ARFF format. The module handles NUMERIC, REAL, INTEGER, STRING, and NOMINAL attribute types, supports missing values and unicode, and can work with scipy sparse matrices and SVMLight-style dictionary lists.\n\nThe package has no external runtime dependencies and works across Python 2.7 and Python 3.5+. However, it has been abandoned since 2020 with no recent maintenance, which means it may face compatibility issues with future Python releases or ecosystem changes. It remains in production-stable status and is still downloaded regularly, but users should be aware of the maintenance gap when considering it for new projects.","worth_installing":"Yes, but with caution. The package is stable and dependency-free for reading/writing ARFF files, and it has no known vulnerabilities. However, its abandoned status since 2020 makes it risky for new projects\u2014install only if you need ARFF support for legacy datasets or existing workflows, and consider monitoring for compatibility issues as Python evolves. For new machine learning projects, evaluate whether a maintained alternative or direct pandas/numpy workflows would be more sustainable."},"id":"liac-arff","links":{"html":"https://skillfed.io/packages/liac-arff","md":"https://skillfed.io/packages/liac-arff.md","pypi":"https://pypi.org/project/liac-arff/"},"maintenance":{"status":"abandoned"},"meta":{"latest_release":"2020-08-31","license_spdx":null,"license_treatment":"permissive","name":"liac-arff","python_support":"supports_current","summary":"A module for read and write ARFF files in Python."},"popularity":{"monthly_downloads":80895,"position":14264,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"2.5.0"}