{"categories":[{"label":"Application Frameworks","url":"https://skillfed.io/packages/category/software-development-libraries-application-frameworks/5"}],"enrichment":{"capability":"Adds a data asset pattern to Prefect workflows, enabling functions to persist, cache, and query data using DuckDB with minimal boilerplate.","skillfed_tags":["prefect-integration","data-pipeline","caching"],"use_cases":["Build ETL pipelines where each transformation step is a queryable data asset that can be executed and cached independently.","Cache intermediate machine learning datasets and query them for model training without recomputing or loading full data into memory.","Enable data analysts to query preprocessed assets via SQL without understanding the underlying retrieval logic.","Maintain historical snapshots of data assets for auditing and rollback in incremental data processing workflows.","Reduce redundant computations in multi-step workflows by reusing cached artifacts within configurable expiration windows."],"what_it_does":"mad_prefect wraps Prefect workflow functions with a `@asset` decorator that automatically handles data persistence, caching, and querying. When you decorate a function, it becomes a data asset that can materialize its output to disk (in JSON, Parquet, or CSV), reuse cached results within a configurable expiration window, and query the stored data using DuckDB without loading it entirely into memory.\n\nThe library is built on seven runtime dependencies: prefect (the orchestration framework), duckdb (for SQL querying), pandas and pyarrow (for data handling), fsspec and sshfs (for filesystem abstraction), and jsonlines (for line-delimited JSON support). It targets Python 3.11 and 3.12, and is actively maintained. Use it to build modular ETL pipelines where each step is independently executable and queryable, or to cache intermediate results in machine learning workflows.","worth_installing":"Yes, with conditions. The package solves a real problem\u2014adding lightweight data asset management to Prefect\u2014and has low install friction with active maintenance. However, the unclear license status is a blocker for any project with strict licensing requirements; resolve that first. Once licensed, it's a solid choice for Prefect users building data pipelines that benefit from caching, querying, and artifact management."},"id":"mad-prefect","links":{"html":"https://skillfed.io/packages/mad-prefect","md":"https://skillfed.io/packages/mad-prefect.md","pypi":"https://pypi.org/project/mad-prefect/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-04-10","license_spdx":null,"license_treatment":"unclear","name":"mad-prefect","python_support":"capped_below_current","summary":null},"popularity":{"monthly_downloads":104076,"position":12770,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"2.3.0"}