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Abstract Tidal disruption events (TDEs) are a class of transients that occur when a star is destroyed by the tides of a massive black hole (MBH). Their rates encode valuable MBH demographic information, but this can only be extracted if accurate TDE rate predictions are available for comparisons with observed rates. In this work, we present a new, observer-friendly Python package called REPTiDE, which implements a standard loss-cone model for computing TDE rates given a stellar density distribution and an MBH mass. We apply this software to a representative sample of 91 nearby galaxies over a wide range of stellar masses with high-resolution nuclear density measurements from C. H. Hannah et al. We measure per-galaxy TDE rates ranging between 10^−7.7and 10^−2.9yr^–1and find that the sample-averaged rates agree well with observations. We find a turnover in the TDE rate as a function of both galaxy stellar mass and black hole mass, with the peak rates being observed in galaxies at a galaxy mass of 10^9.5M_⊙and a black hole mass of 10^6.5M_⊙. Despite the lower TDE rates inferred for intermediate-mass black holes, we find that they have gained a higher fraction of their mass through TDEs when compared to higher-mass black holes. This growth of lower-mass black holes through TDEs can enable us to place interesting constraints on their spins; we find maximum spins ofa_• ≈ 0.9 for black holes with masses below ∼10^5.5M_⊙.