Papers › Safe-DS: A Domain Specific Language to Make Data Science Safe
Safe-DS: A Domain Specific Language to Make Data Science Safe
Lars Reimann, Günter Kniesel-Wünsche
Due to the long runtime of Data Science (DS) pipelines, even small programming mistakes can be very costly, if they are not detected statically. However, even basic static type checking of DS pipelines is difficult because most are written in Python. Static typing is available in Python only via external linters. These require static type annotations for parameters or results of functions, which many DS libraries do not provide. In this paper, we show how the wealth of Python DS libraries can be used in a statically safe way via Safe-DS, a domain specific language (DSL) for DS. Safe-DS catches conventional type errors plus errors related to range restrictions, data manipulation, and call order of functions, going well beyond the abilities of current Python linters. Python libraries are integrated into Safe-DS via a stub language for specifying the interface of its declarations, and an API-Editor that is able to extract type information from the code and documentation of Python libraries, and automatically generate suitable stubs. Moreover, Safe-DS complements textual DS pipelines with a graphical representation that eases safe development by preventing syntax errors. The seamless synchronization of textual and graphic view lets developers always choose the one best suited for their skills and current task. We think that Safe-DS can make DS development easier, faster, and more reliable, significantly reducing development costs.
Code
Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.
Code Syntology ran Syntology
Not run by Syntology. Nothing on this page verifies that the listed code works.
Tasks
Results from the paper archive 2025-07-28
No leaderboard rows for this paper in the archive.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections