PyEMILI automates the identification of spectral lines, especially for emission-line objects such as planetary nebulae (PNe), H II regions, and Herbig–Haro (HH) objects. The package identifies emission lines in various astronomical objects and absorption lines in stellar spectra. PyEMILI can also automatically fit the continuum of the 1D spectrum and finds lines in the spectrum; it also offers an interactive interface for manually reviewing, adding, or revising spectral lines.

Deep-Transit detects transits using a deep learning based 2D object detection algorithm. The code determines the light curve and outputs the transiting candidates' bounding boxes and confidence scores. It has been trained for Kepler and TESS data, and can be extended to other photometric surveys and even ground-based observations. Deep-Transit also provides an interface for training new datasets.