{"categories":[{"label":"Python Modules","url":"https://skillfed.io/packages/category/software-development-libraries-python-modules/9"}],"enrichment":{"capability":"Koheesio is a Python framework for building modular, reusable data pipelines using step-based components with strong typing via Pydantic, supporting multiple data processing libraries and frameworks.","skillfed_tags":["data-engineering","etl","pydantic-based"],"use_cases":["Build reusable ETL components that can be tested independently and composed into larger data workflows.","Write data transformation and validation logic with strong typing and structured configuration using Pydantic.","Create modular data tasks for use within orchestration frameworks like Apache Airflow or Databricks Workflows.","Develop data quality checks and data processing steps with built-in logging and error handling.","Implement step-based data pipelines where each task is a manageable, testable unit of work."],"what_it_does":"Koheesio is a Python framework for constructing data pipelines from reusable, step-based components. It emphasizes modularity, testability, and strong typing through Pydantic, enabling developers to build robust data tasks that can be composed into larger workflows. The framework is designed to work with multiple data processing libraries and frameworks, making it adaptable to various data scales and technologies.\n\nUnlike workflow orchestration tools (Airflow, Luigi, Databricks), Koheesio focuses on making individual data tasks resilient, observable, and maintainable. It provides built-in logging, flexible context customization, and a foundation for data validation, transformation, and ETL work. The framework is positioned as a complement to orchestration tools rather than a replacement, allowing teams to write well-engineered data tasks that can be orchestrated separately.","worth_installing":"Yes. Koheesio is actively maintained, has low install friction, carries no known vulnerabilities, and is licensed permissively. It fills a clear niche for developers building modular, testable data tasks\u2014particularly those who plan to integrate with orchestration tools. The framework's reliance on well-established dependencies (Pydantic, cryptography, PyYAML) and its production-stable classifier make it a sound choice for data engineering work."},"id":"koheesio","links":{"html":"https://skillfed.io/packages/koheesio","md":"https://skillfed.io/packages/koheesio.md","pypi":"https://pypi.org/project/koheesio/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-07-27","license_spdx":"Apache-2.0","license_treatment":"permissive","name":"koheesio","python_support":"capped_below_current","summary":"The steps-based Koheesio framework"},"popularity":{"monthly_downloads":665001,"position":5430,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.11.0"}