Ah, I had completely misunderstood! I had in mind something much more complicated (infer from the function body what fields are needed), but I agree that’s much harder if at all possible.
If you need to rely on the names the user is passing, I would tend to agree with @Tamas_Papp that this could be done by a macro using symbols, say @λ :SepalLength > 2*:SepalWidth (or denoted in another way, say @λ $SepalLength > 2*$SepalWidth or @λ &SepalLength > 2 * &SepalWidth) would return a SelectingClosure object. Such a basic macro could live in a very low-dependency package (say a TablesMeta that only requires Tables and maybe MacroTools) and DataFrames could even reexport it. In this case, from my proposal above, one would add the dispatch:
filter(f::SelectingClosure, df::DataFrame) = filter(f.f, df, select = f.select)
Otherwise, if I’m working on a table with a 1000 columns and I filter on x -> x.mycol > 3 but :x is one of the columns, I would get Error: type ... has no field mycol