{"categories":[{"label":"Python Modules","url":"https://skillfed.io/packages/category/software-development-libraries-python-modules/6"},{"label":"Internet","url":"https://skillfed.io/packages/category/internet/2"},{"label":"Chat","url":"https://skillfed.io/packages/category/communications-chat"}],"enrichment":{"capability":"Serializes and deserializes machine learning pipelines to a portable Bundle.ML format for cross-platform deployment and execution.","skillfed_tags":["ml-serialization","model-deployment","pipeline-interchange"],"use_cases":["Export a fitted scikit-learn pipeline to Bundle.ML for deployment in a lightweight runtime environment.","Serialize a gensim Word2Vec model to Bundle.ML for consistent text vectorization across environments.","Share trained ML pipelines between teams via a standardized interchange format.","Build reproducible ML workflows where serialized models execute consistently across different contexts.","Integrate scikit-learn models with systems that consume Bundle.ML format."],"what_it_does":"MLeap is a Python library that provides serialization and deserialization of machine learning pipelines to a portable Bundle.ML format. It integrates with scikit-learn and enables pipelines built with numpy, scipy, pandas, and scikit-learn to be exported to a common interchange format. The library maintains mathematical parity across implementations, allowing models to produce consistent results when moved between different execution environments.\n\nThe package depends on numpy, six, scipy, pandas, and scikit-learn, with optional gensim integration for Word2Vec serialization. It is actively maintained, supports Python 3.10 through 3.13, and carries no known security vulnerabilities. Scikit-Learn deserialization is noted as in development.","worth_installing":"Yes. MLeap is actively maintained, carries no vulnerabilities, and solves a real portability problem for machine learning pipelines. The low install friction and permissive license make it a straightforward addition. Install if you need to serialize scikit-learn pipelines or integrate with Bundle.ML-based systems; skip if you have no need for model interchange or deployment outside your current framework."},"id":"mleap","links":{"html":"https://skillfed.io/packages/mleap","md":"https://skillfed.io/packages/mleap.md","pypi":"https://pypi.org/project/mleap/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-07-21","license_spdx":null,"license_treatment":"permissive","name":"mleap","python_support":"supports_current","summary":"MLeap Python API"},"popularity":{"monthly_downloads":2313539,"position":3146,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"0.25.2"}