The request asks for a MapReduce-style tool. None of the candidate sources describes a MapReduce framework directly; the closest matches are parallel data-processing libraries such as Dask 1, which parallelizes Python code across machines and offers DataFrames that run on pandas, plus distributed task systems like Celery 6 and Volcano 5 for batch workloads. Dask is the closest fit for map-then-reduce style parallel computation.

1. 1

   Daskdask.orgverified and signed

   Open-source Python library for parallel computing that runs ordinary Python code across machines and offers parallel DataFrames built on pandas 111.

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   +2 community tools built for it

   for agents: parallel · pandas · task-scheduling

2. 2

   Volcanovolcano.shwebsite read, tools not yet checked

   Cloud native batch scheduling system for compute-intensive workloads, including big data frameworks such as Apache Spark 5.

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3. 3

   Celeryceleryq.devverified and signed

   Distributed task queue for processing large numbers of messages and jobs across workers, supporting task scheduling 616.

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   for agents: distributed · job · task