Access curated or locally stored data with curated data functions?

Question

Say I have a toy package, something like:

BeginPackage["myPackage`"]
plotSomeData::usage = "plotFinancialData[symbol]... some usage language";
Begin["`Private`"]
plotSomeData[symbol_]:= DateListPlot[FinancialData[symbol, All]]
End[]
EndPackage[]

This should work fine, nothing particularly complicated here.

So now, I'd like to extend the FinancialData[] function embedded in the package to enable it to seamlessly access non-Wolfram curated data stored locally on my computer.

I could rewrite the package and set up some conditional code that would replace FinancialData[] with Import[], something like:

plotSomeData[symbol_] := DateListPlot[
  Which[
   symbol == "xyz", Import[pathAndFileName],
   symbol != "xyz", FinancialData[symbol, All]
   ]]

But, in my case, that would mean rewriting a bunch of perfectly good packges, so I'd like another solution. Some of the questions and answers such as:

What is a paclet?

UpValues TagSet and UpSet

have me wondering if another more elegant way exists to do this.

Could, for instance, one extend the paclet information for a set of curated data?

I've used TagSet before to do things like define how to calculate the CDF of a custom distribution, but I don't see a clear way to use it to enable a curated data function to recognize the location of a data symbol it doesn't already know.

SetOptions doesn't seem like the thing either.

UpVales and UpSet might do it, but I don't see it yet.

Ideally, I'd simply like to extend a curated data function to recognize the location of a data symbol it doesn't already know and thereby enable it to get the newly identified data.

Best if I can do this outside of the packages I already have.

Any ideas?

(The tags I have on this question could use some improvement, if anyone has some better ideas.)

Answer 1

As @Mr.Wizard asked, "...it's time for an answer, don't you think?".

I forgot about this question, but after year it occurred to me to formulate an answer following @LeonidShifin suggestions:

First get some test data:

testData = FinancialData["GE", "Jan. 1, 2000"][[1 ;; 10]];
dataFile = "/Users/jagra/Data.test.csv";
Export[dataFile, testData, "CSV"];

Apply UpValues

sym /: FinancialData[sym] := Last[Import[dataFile]][[2]]
sym /: FinancialData[sym, All] := Import[dataFile]
sym /: FinancialData[sym, date_String] := Module[{data, pos},
  data = Import[dataFile];
  pos = Position[data, date];
  data[[Flatten[pos][[1]]]]]

FinancialData[sym]
FinancialData[sym, All]
FinancialData[sym, "{2000, 1, 4}"]


32.45

{{{2000, 1, 3},32.24},{{2000, 1, 4},30.95},{{2000, 1, 5},30.89},{{2000, 1, 6},31.31},{{2000, 1, 7},32.52},{{2000, 1, 10},32.5},{{2000, 1, 11},32.56},{{2000, 1, 12},32.67},{{2000, 1, 13},33.04},{{2000, 1, 14},32.45}}

{{2000, 1, 4},30.95}

This doesn't show all possible configurations for getting data (and even has a shortcut in using "{2000, 1, 4}") , but I think it demonstrates the flexibility of the approach.