2023ApJS..269...40Y

The progenitors for many types of supernovae (SNe) are still unknown, and an approach to diagnose their physical origins is to investigate the light-curve brightness and shape of a large set of SNe. However, it is often difficult to compare and contrast the existing sample studies due to differences in their approaches and assumptions, for example, in how to eliminate host galaxy extinction, and this might lead to systematic errors when comparing the results. We therefore introduce the Hybrid Analytic Flux FittEr for Transients (HAFFET), a Python-based software package that can be applied to download photometric and spectroscopic data for transients from open online sources, derive bolometric light curves, and fit them to semianalytical models for estimation of their physical parameters. In a companion study, we have investigated a large collection of SNe Ib and Ic observed with the Zwicky Transient Facility (ZTF) with HAFFET, and here we detail the methodology and the software package to encourage more users. As large-scale surveys such as ZTF and LSST continue to discover increasing numbers of transients, tools such as HAFFET will be critical for enabling rapid comparison of models against data in statistically consistent, comparable, and reproducible ways. Additionally, HAFFET is created with a graphical user interface mode, which we hope will boost the efficiency and make the usage much easier (https://github.com/saberyoung/HAFFET).