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The SunPy Project is a community of scientists and software developers creating an ecosystem of Python packages for solar physics. The project includes the sunpy core package as well as a set of affiliated packages. The sunpy core package provides general purpose tools to access data from different providers, read image and time series data, and transform between commonly used coordinate systems. Affiliated packages perform more specialized tasks that do not fall within the more general scope of the sunpy core package. In this article, we give a high-level overview of the SunPy Project, how it is broader than the sunpy core package, and how the project curates and fosters the affiliated package system. We demonstrate how components of the SunPy ecosystem, including sunpy and several affiliated packages, work together to enable multi-instrument data analysis workflows. We also describe members of the SunPy Project and how the project interacts with the wider solar physics and scientific Python communities. Finally, we discuss the future direction and priorities of the SunPy Project.

We report on observations of highly-varying Si IV 1402.77 Å line profiles observed with the Interface Region Imaging Spectrograph (IRIS) during the M-class flare from 18 January 2022 at an unprecedented 0.8 s cadence. Moment analysis of this line observed in flare ribbon kernels showed that the intensity, Doppler velocity, and non-thermal broadening exhibited variations with periods below 10 s. These variations were found to be correlated with properties of the Gaussian fit to a well-resolved secondary component of the line redshifted by up to 70 km s−1, while the primary component was consistently observed near the rest wavelength of the line. A particularly high correlation was found between the non-thermal broadening of the line resulting from the moment analysis and the redshift of the secondary component. This means that the oscillatory enhancements in the line broadening were due to plasma flows (away from the observer) with varying properties. A simple de-projection of the Doppler velocities of the secondary component based on a three-dimensional reconstruction of flare loops rooted in the kernel suggests that the observed flows were caused by downflows and compatible with strong condensation flows recently predicted by numerical simulations. Furthermore, peaks of the intensity and the trends of Doppler velocity of the Gaussian fit to the secondary component (averaged in the ribbon) were found to correspond to one of the quasi-periodic pulsations (QPPs) detected during the event in the soft X-ray flux (as measured by the Geostationary Operational Environmental Satellite, GOES) and the microwave radio flux (as measured by the Expanded Owens Valley Solar Array, EOVSA). This result supports a scenario in which the QPPs were driven by repeated magnetic reconnection.

The NDCube 2 API is a Python application programming interface (API) for storing and manipulating N-dimensional coordinate-aware astronomical data. While there are Python packages for handling astronomical data and coordinate transformations separately and for handling specific combinations of dimensions and transformations, none provide a unified and agnostic way of handling them simultaneously. This leads to a proliferation of different APIs for conducting the same analysis tasks on similar types of observations and introduces technical barriers between multi-instrument studies and cross-community collaboration. In this paper, we outline how the NDCube 2 API and its implementation in the open-source, community-developed ndcube package, together with the AstroPy WCS API, help to solve this problem. We discuss the guiding principles underpinning the API design and provide examples of how it is already being used to serve broad sections of the astronomy community, including agency-funded missions. The aim of this paper is to help users better understand the purpose and potential of the NDCube 2 API and ndcube package and hence how to more effectively deploy them in scientific analyses and software development.

The goal of the SunPy project is to facilitate and promote the use and development of community-led, free, and open source data analysis software for solar physics based on the scientific Python environment. The project achieves this goal by developing and maintaining the sunpy core package and supporting an ecosystem of affiliated packages. This paper describes the first official stable release (version 1.0) of the core package, as well as the project organization and infrastructure. This paper concludes with a discussion of the future of the SunPy project. [ABSTRACT FROM AUTHOR]