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Other literature type . 2024
License: CC BY
Data sources: ZENODO
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Presentation . 2024
License: CC BY
Data sources: Datacite
ZENODO
Presentation . 2024
License: CC BY
Data sources: Datacite
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hostess: Lightweight Distributed Resource Management and Data Processing in Python

Authors: Million, Chase;

hostess: Lightweight Distributed Resource Management and Data Processing in Python

Abstract

`hostess` is an open-source library that provides lightweight, Pythonic interfaces for managing and working with distributed resources, system processes, and Python internals. It offers high-level modules for interacting with EC2 instances, S3 buckets, and SSH servers, along with a workflow coordination framework called `station`. It also includes public APIs for these modules' lower-level building blocks, permitting users to manipulate resources in preferred contexts (including locally) and levels of abstraction. `hostess` is designed to fit especially smoothly into data analysis workflows. It provides support for cloud-based data science, including one-line launch of EC2-based Jupyter Notebooks to permit use of S3-based datasets without incurring massive egress fees. It also supports massive cloud-based data processing: a single line of code can launch a distributed workflow across an arbitrary number of EC2 instances (or other servers, local or remote). It has been used to develop tactical processing pipelines for the VIS instrument suite on the VIPER mission, and to process massive NASA data sets from the GALEX and Clementine missions. It is stable, well-documented, and under continuous development. It is available on conda-forge, PyPi, and GitHub (github.com/MillionConcepts/hostess).

In-depth materials for the 2024 Software for the NASA SMD Workshop.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green