Fixing the Piping/Chaining Issue

Internals & Design
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187

Okay so since working through that example I basically did all the work needed to figure out how to it anyway, I threw together a quick and simple script that does what I described for a simple autocomplete (you knew I would, didn’t you :triumph:)

Code here 

function propose_method_autocompletions(obj, func_name_fragment::String=""; 
    type_depth = 1:typemax(Int), only_same_module = false, 
    prioritize_firstlast = false, github_inference = false, personalized_inference = false)::Vector{Method}

    @assert first(type_depth) ≥ 1 && last(type_depth ≥ 1)
    recs = Vector{Method}[]
    get_type_at_depth(type, depth=1) = depth == 1 ? type : type == Any ? nothing : get_type_at_depth(supertype(type), depth-1)

    for i ∈ type_depth
        stype = get_type_at_depth(typeof(obj), i)
        isnothing(stype) && break

        meths = filter(only_same_module ? methodswith(stype, parentmodule(typeof(obj))) : methodswith(stype)) do m
            length(func_name_fragment) > length(string(m.name)) && return false
            string(m.name)[1:length(func_name_fragment)] == func_name_fragment
        end

        prioritize_firstlast || true # do cool sorting stuff, add later
        github_inference || true # do cool sorting stuff, add later
        personalized_inference || true # do cool sorting stuff, add later

        recs = [recs; meths]
    end

    recs
end

To invoke:

using DataFrames
df = DataFrame(a=1, b=2)

propose_method_autocompletions(df)

By default, it returns all available methods that can act on object df. As you start to type in a function name, the list gets narrowed down quickly:

propose_method_autocompletions(df, "p")
propose_method_autocompletions(df, "pu")
propose_method_autocompletions(df, "pushfirst!")

You can also change the search depth. By default, it searches specializations on typeof(df), as well as supertype(typeof(df)), supertype(supertype(typeof(df))), and so on. This can be changed like so:

propose_method_autocompletions(df, "p"; type_depth=1:2)

This gives methods of DataFrame as well as AbstractDataFrame, but not Any. The iterator can also be reversed 2:-1:1 to show the abstract type’s methods first.

You can also restrict the search to only methods that are defined in the same module as DataFrame:

propose_method_autocompletions(df, "p"; only_same_module = true)

And, one day, it’ll work with the arg_order_inference, github_inference and personalized_inference options too. :wink:

Someday it could be interesting to make it feed its results into a Channel, so that it can offer results with greater immediacy.

Unfortunately it doesn’t solve *my* problem, because the module didn’t export its methods so they don’t appear in methodswith :sweat_smile:

Oddly, when calling methodswith(DataFrame, DataFrames) (trying this to see if it improves speed over filtering *after* the methodswith call), it simply doesn’t return a bunch of methods of DataFrame that are indeed declared by the DataFrames module. For example, pushfirst! is missing. Strange.

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