Dockerfile defines a set of instructions for building container images, which instruct how the containerized applications should be built. Recent studies have shown that there are quite a lot of quality problems in Dockerfile. This study proposes a new tool, namely Dockerfile Miner (DMiner) to extract implicit rules from high-quality Dockerfile, and these rules will help to improve the quality of Dockerfile. DMiner is mainly divided into three modules, which are responsible for the collection and filtering of Dockerfile, parsing of Dockerfile, and mining and extraction of Dockerfile rules. DMiner parses Dockerfile into a unified sequential representation and uses a sequential rule mining algorithm to extract rules. This tool expands the existing Dockerfile dataset and extracts nine new rules that have not appeared in other work. A large number of experiments on real datasets show that the tool is effective and efficient.