In order to solve the problem of setting cut-off distance and selecting clustering center in Density Peak Clustering algorithm (DPC), a new self-adjusting step-size fruit fly optimization algorithm is used to calculate the cut-off distance and the important parameters in density peak clustering, an adaptive method for selecting clustering centers is designed. In the cut-off distance calculation process, the search step-size is dynamically adjusted according to the rate of change of the difference between the optimal concentration and the worst concentration in each step of the iterative process, and its optimization efficiency and accuracy are better than the existing improved fruit fly algorithm. In the selection process of clustering center, the clustering center is selected adaptively according to the distribution of the product of local density and distance. The computational accuracy and efficiency of the proposed algorithm are both better than the existing improved DPC algorithm, and it can realize data clustering completely adaptively.