Differences-in-differences evaluates the effect of a treatment. In its basic version, a “control group” is untreated at two dates, whereas a “treatment group” becomes fully treated at the second date. However, in many applications of this method, the treatment rate increases more only in the treatment group. In such fuzzy designs, de Chaisemartin and D’Haultfoeuille (2018b, Review of Economic Studies 85: 999–1028) propose various estimands that identify local average and quantile treatment effects under different assumptions. They also propose estimands that can be used in applications with a nonbinary treatment, multi- ple periods, and groups and covariates. In this article, we present the command fuzzydid, which computes the various corresponding estimators. We illustrate the use of the command by revisiting Gentzkow, Shapiro, and Sinkinson (2011, American Economic Review 101: 2980–3018).