{"categories":[{"label":"Scientific/Engineering","url":"https://skillfed.io/packages/category/scientific-engineering/7"}],"enrichment":{"capability":"Distributed generalized linear model fitting using Dask for parallel computation across clusters or multi-core systems.","skillfed_tags":["distributed-computing","generalized-linear-models","dormant"],"use_cases":["Training logistic regression or other GLMs on datasets too large to fit in a single machine's memory using Dask clusters.","Prototyping distributed statistical models in research or exploratory analysis where the library's experimental status is acceptable.","Learning how to structure distributed machine-learning code using Dask's primitives and task graphs.","Benchmarking or comparing distributed GLM implementations across different parallelization frameworks."],"what_it_does":"Dask-glm is a library for fitting generalized linear models in a distributed setting using Dask, the parallel computing framework. It integrates with Dask's task scheduler to enable model training across multiple machines or cores, leveraging dependencies like scikit-learn for model definitions, numpy and scipy for numerical computation, and numba for JIT-compiled performance. The package targets scientific and machine-learning workflows where dataset size or computational cost makes single-machine fitting impractical.\n\nHowever, the package's own documentation explicitly warns that it is not ready for use, and it has not received recent updates. The Beta development status and aging maintenance signal suggest the project is dormant or abandoned. Installation is straightforward (low friction, pure-Python wheel), but adopting it for production work carries substantial risk given the explicit non-readiness statement and lack of recent activity.","worth_installing":"No. The package explicitly states it is not ready for use, has not been updated recently, and carries Beta status with an aging maintenance signal. While the install friction is low and the license is permissive, the lack of readiness and dormant development make it unsuitable for production or even reliable experimental work. Consider alternatives with active maintenance."},"id":"dask-glm","links":{"html":"https://skillfed.io/packages/dask-glm","md":"https://skillfed.io/packages/dask-glm.md","pypi":"https://pypi.org/project/dask-glm/"},"maintenance":{"status":"aging"},"meta":{"latest_release":"2026-01-23","license_spdx":"BSD-3-Clause","license_treatment":"permissive","name":"dask-glm","python_support":"supports_current","summary":"Generalized Linear Models with Dask"},"popularity":{"monthly_downloads":110399,"position":12464,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.4.0"}