There is Distribution.cdf abstract method, but it is not implemented for most distributions. scipy.stats is generally better, if you’re doing interactive work and don’t need gradients (see also: torch.from_numpy(), Tensor.numpy()).
As for density, Binomial(total_count=n,probs=p).log_prob(x).exp() would correspond to dbinom(x,n,p), I think.