Update juliacall_unfold.jl

docs/literate/HowTo/juliacall_unfold.jl

@@ -38,3 +38,13 @@
 
 # ## Example: Unfold model fitting from Python
 # In this [notebook](https://github.com/unfoldtoolbox/Unfold.jl/blob/main/docs/src/HowTo/juliacall_unfold.ipynb), you can find a more detailed example of how to use Unfold from Python to load data, fit an Unfold model and visualise the results in Python.
+
+# ## Important limitations
+# Python doesnt not offer the full expressions that are available in Julia. So there are some things you need to give special attention:
+#
+# `@formula` - we havent found a way to call macros yet, even though we think it should be possible. For now please use `f = jl.seval("@formula(0~1+my+cool+design)")`. Later versions might support something like f = `@formula("0~1+my+cool+design)"` directly
+#
+# specifying the design: Since Unfold 0.7 we officially switched to the `["eventtypeA"=>(formula,basisfunction),"eventtypeB"=>(otherformula,otherbasisfunction)]` syntax from a Dict-based syntax. Unfortunately, `=>` (a pair) is not supported in Python and one needs to do some rewriting:
+# `jl.convert(jl.Pair,(formula,basisfunction))` which makes the code less readable. We are thinking of ways to remedy this - but right now there is now way around. For now, it is also possible to use the old syntax {"eventtypeA"=>(formula,basisfunction),"eventtypeB"=>(otherformula,otherbasisfunction)} which is clearly easier to read :)
+#
+# `UnfoldSim.design` special case in UnfoldSim design, we need a `Dict` with a `Symbol` , one has to do something like `condition_dict_jl = {convert(jl.Symbol,"condA"):["car", "face"]}` to do so. We will try to allow strings here as well, removing this constraint.