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SHARPpy-Reimagined, published by Shian Michael, is a modernized, standalone fork of the SHARPpy sounding analysis package, with the current release at version 1.2.0 across a history of eleven versions. Its purpose is to provide meteorologists and atmospheric scientists with reproducible point-sounding analysis tools that fit cleanly into packageable Python 3.11+ workflows, replacing legacy dependencies with contemporary Qt6/PySide6 rendering for interactive and scriptable visualization. The software retains the familiar SPC-style skew-T diagrams, hodographs, hazard displays, and derived-parameter views that users of the original SHARPpy and the Storm Prediction Center's SHARP applications expect, making it directly relevant to the scientific visualization and atmospheric analysis software category. Use cases include examining upper-air soundings from UWyo observations, working with ERA5 reanalysis data, and processing output from WRF model simulations, all within unified analysis workflows that support both graphical exploration and automated processing. Clean command-line entry points make the tool practical for scripted pipelines and repeatable research tasks, while bundled resources simplify installation and distribution as a self-contained package. A test-backed decoder and extractor layer underpins the data handling, providing confidence that sounding data ingested from the supported sources is parsed reliably and consistently. By combining the established SHARPpy analysis paradigm with modern Python packaging, updated graphical rendering, and a focus on reproducibility, SHARPpy-Reimagined serves operational forecasters, severe-weather researchers, and students who need dependable skew-T and hodograph analysis without maintaining aging software stacks.
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