The TESS space telescope captures incredible amounts of data as it hunts for exoplanets across the entire sky, but accessing specific regions from its massive Full Frame Image (FFI) cubes has traditionally required downloading gigabytes of data. Whether you’re studying stellar variability, searching for asteroids, or characterizing exoplanet host stars, you shouldn’t need to wrestle with bulk data downloads just to analyze a small patch of sky.
Tesscube elegantly solves this by letting you slice directly into MAST’s AWS-hosted TESS data cubes. Simply specify a sector, camera, and CCD, then extract individual FFIs by time index or create Target Pixel Files (TPFs) around any coordinate—whether you provide pixel positions or just say ‘AU Mic’ and let astropy handle the rest. The tool returns familiar astropy objects that integrate seamlessly with lightkurve, making it feel like native TESS mission products. No authentication required, no massive downloads, just pure astronomical data at your fingertips.
This cloud-native approach transforms how researchers interact with TESS data, enabling rapid prototyping and analysis directly in Jupyter notebooks or cloud computing environments. From graduate students exploring their first variable stars to seasoned astronomers conducting large-scale surveys, tesscube democratizes access to one of astronomy’s most valuable datasets.
⭐ Stars: 6
💻 Language: Python
🔗 Repository: tessgi/tesscube