The Astropy Project: sustaining and growing a community-oriented open-source project and the latest major release (v5. 0) of the core package
AM Price-Whelan, PL Lim, N Earl… - The Astrophysical …, 2022 - iopscience.iop.org
The Astrophysical Journal, 2022•iopscience.iop.org
The Python programming language is a high-level, interpreted (as opposed to compiled)
programming language that has become an industry standard across many computational
domains, technological sectors, and fields of research. This recent and rapid adoption of
Python stems from the fact that it enables scalable, time-and energy-efficient code execution
(eg, Augier et al. 2021) with a focus on code readability, ease of use, and interoperability
with other languages. Over the last decade, Python has grown enormously in popularity to …
programming language that has become an industry standard across many computational
domains, technological sectors, and fields of research. This recent and rapid adoption of
Python stems from the fact that it enables scalable, time-and energy-efficient code execution
(eg, Augier et al. 2021) with a focus on code readability, ease of use, and interoperability
with other languages. Over the last decade, Python has grown enormously in popularity to …
The Python programming language is a high-level, interpreted (as opposed to compiled) programming language that has become an industry standard across many computational domains, technological sectors, and fields of research. This recent and rapid adoption of Python stems from the fact that it enables scalable, time-and energy-efficient code execution (eg, Augier et al. 2021) with a focus on code readability, ease of use, and interoperability with other languages. Over the last decade, Python has grown enormously in popularity to become a dominant programming language, especially in the astronomical and broader scientific communities. For example, Figure 1 shows the number of yearly full-text mentions of Python as compared to a selection of other programming languages in refereed articles in the astronomical literature, demonstrating its nearly exponential growth in popularity. The adoption of Python by astronomy researchers, students, observatories, and technical staff combined with an associated increase in awareness and interest in opensource software tools is contributing to a paradigm shift in the way research is done, data is analyzed, and results are shared in astronomy and beyond.
One of the factors that has led to its rapid ascent in popularity in scientific contexts is the combination of volunteer-driven and professionally supported effort behind developing communityoriented open-source software tools and fostering communities of users and developers that have grown around these efforts. Today, a broad and feature-diverse ecosystem of packages exists in the Python scientific computing landscape: roughly ordered from general use to domain specific, this landscape now includes packages that provide core numerical analysis functionality like numpy Harris et al.(2020) and scipy Virtanen et al.(2020), visualization frameworks like matplotlib (Hunter 2007), machine-learning and data analysis packages like tensorflow (Abadi et al. 2015), pymc3 (Salvatier et al. 2016), and emcee (Foreman-Mackey et al. 2013), domain-specific libraries like yt (Turk et al. 2011), plasmpy (PlasmaPy Community et al. 2021),
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