In data science packages, a single function will often implement several conceptually distinct models or methods by dispatching on the value of an argument, as in R's glm or scikit-learn's LogisticRegression (which supports multiple forms of regularization). Function annotations should support dispatching on such arguments as well.
In this package, it is enough to describe a schema that makes sense and start writing the annotations. The language-specific flow graph packages should then be updated accordingly.
In data science packages, a single function will often implement several conceptually distinct models or methods by dispatching on the value of an argument, as in R's
glmor scikit-learn'sLogisticRegression(which supports multiple forms of regularization). Function annotations should support dispatching on such arguments as well.In this package, it is enough to describe a schema that makes sense and start writing the annotations. The language-specific flow graph packages should then be updated accordingly.