Since its launch, TESS has provided high cadence observations for objects across the sky. Although high cadence TESS observations provide a unique possibility to study the rapid time evolution of numerous objects, artifacts in the data make it particularly challenging to use in studying transients. Furthermore, the broadband red filter of TESS, makes calibrating it to physical flux units, or magnitudes, challenging. Here we present TESSreduce an open-source, and user-friendly Python package which is built to lower the barrier to entry for transient science with TESS. In a few commands users can produce a reliable TESS light curve, accounting for systematic biases that are present in other models (such as instrument drift and the varied TESS background) and calculate a zeropoint to percent level precision. With this package anyone can use TESS for science, such as studying rapid transients and constraining progenitors of supernovae.