Code Refactoring Using Metaprogramming

It’s been nearly a year since I wrote Twitter.jl, back when I seemingly had MUCH more free time. In these past 10 months, I’ve used Julia quite a bit to develop other packages, and I try to use it at work when I know I’m not going to be collaborating with others (since my colleagues don’t know Julia, not because it’s bad for collaboration!).

One of the things that’s obvious from my earlier Julia code is that I didn’t understand how powerful metaprogramming can be, so here’s a simple example where I can replace 50 lines of Julia code with 10.


Admittedly, when I started on the Twitter package, I fully meant to go back and clean up the codebase, but moved onto something more fun instead. The Twitter package started out as a means of learning how to use the Requests.jl library to make API calls, figure out the OAuth syntax I needed (which itself should be factored out of Twitter.jl), then copied-and-pasted the same basic function structure over and over. While fast, what I was left with was this (currently, the help.jl file in the Twitter package):

# Help section Functions for Twitter API

function get_help_configuration(; options=Dict{String, String}())

    r = get_oauth("", options)

    return r.status == 200 ? JSON.parse( : r


function get_help_languages(; options=Dict{String, String}())

    r = get_oauth("", options)

    return r.status == 200 ? JSON.parse( : r


function get_help_privacy(; options=Dict{String, String}())

    r = get_oauth("", options)

    return r.status == 200 ? JSON.parse( : r


function get_help_tos(; options=Dict{String, String}())

    r = get_oauth("", options)

    return r.status == 200 ? JSON.parse( : r


function get_application_rate_limit_status(; options=Dict{String, String}())

    r = get_oauth("", options)

    return r.status == 200 ? JSON.parse( : r


It’s pretty clear that this is the same exact code pattern, right down to the spacing! The way to interpret this code is that for these five Twitter API methods, there are no required inputs. Optionally, there is the ‘options’ keyword that allows for specifying a Dict() of options. For these five functions, there are no options you can pass to the Twitter API, so even this keyword is redundant. These are simple functions so I don’t gain a lot by way of maintainability by using metaprogramming, but at the same time, one of the core tenets of programming is ‘Don’t Repeat Yourself’, so let’s clean this up.

For :symbol in symbolslist…

In order to clean this up, we need to take out the unique parts of the function, then pass them as arguments to the @eval macro as follows:

funcname = (:get_help_configuration, :get_help_languages, :get_help_privacy, :get_help_tos, :get_application_rate_limit_status)
endpoint = ("help/configuration.json", "help/languages.json", "help/privacy.json",  "help/tos.json", "application/rate_limit_status.json")

for (func, endp) in zip(funcname, endpoint)
	@eval function ($func)(; options=Dict{String, String}())

	        r = get_oauth($"$endp", options)

	        return r.status == 200 ? JSON.parse( : r


What’s happening in this code is that I define two tuples: one of function names (as symbols, denoted by :) and one of the API endpoints. We can then iterate over the two tuples, substituting the function names and endpoints into the code. When the package is loaded, this code evaluates, defining the five functions for use in the Twitter package.


Yeah, so metaprogramming can be simple, but it can also be mind-bending. It’s one thing to not repeat yourself, it’s another to write something so complex that even YOU can’t remember how the code works. But somewhere in between lies a sweet spot where you can re-factor whole swaths of code and streamline your codebase. Metaprogramming is used throughout the Julia codebase, so if you’re interested in seeing more examples of metaprogramming, check out the Julia source code, the Requests.jl package (where I first saw this) or really anyone who actually knows what they are doing. I’m just a metaprogramming pretender at this point 🙂  

To read additional discussion around this specific example, see the Julia-Users discussion at:!topic/julia-users/zvJmqB2N0GQ

Edit, 11/22/2014: DarthToaster on Reddit provided another fantastic way to approach refactoring, using macros:

macro endpoint(name, path)
        function $(esc(name))(; options=Dict{String, String}())
            r = get_oauth($"$path", options)
            return r.status == 200 ? JSON.parse( : r

@endpoint get_help_configuration "help/configuration.json"
@endpoint get_help_languages "help/languages.json"

RSiteCatalyst Version 1.4.1 Release Notes


Version 1.4.1 of RSiteCatalyst is now available on CRAN. There were a handful of bug fixes and new features added, including:

  • Fixed bug in QueueRanked function where only 10 results were returned when requesting multiple element reports. Function now returns up to 50,000 per breakdown (API limit)
  • Created better error message to inform user to login with credentials instead of making function call without proper API credentials
  • Added support for using SAINT classifications in QueueRanked/QueueTrended functions
  • Added more error checking to make functions fail more elegantly
  • Added remaining GET methods from Reporting/Administration API

Additional GET methods

This version of RSiteCatalyst has roughly 20 new GET methods, mostly providing additional report suite information for those who might desire to generate their documentation programmatically rather than manually. New API methods include (but are not limited to):

  • GetMarketingChannelRules: Get a list of all criteria used to build the Marketing Channels report
  • GetReportDescription: For a given bookmark_id, get the report definition
  • GetListVariables: Get a list of the List Variables defined for a report suite
  • GetLogins: Get all logins for a given Company

If you were the type of person who enjoyed this blog post showing how to auto-generate Adobe Analytics documentation, I encourage you to take a look at these newly incorporated functions and use them to improve your documentation even further.

Feature Requests/Bugs

If you come across any bugs, or have any feature requests, please continue to use the RSiteCatalyst GitHub Issues page to make tickets. While I’ve responded to many of you via the maintainer email provided in the R package itself, it’s much more efficient (and you’re much more likely to get a response) if you use the GitHub Issues page. Don’t worry about cluttering up the page with tickets, please fill out a new issue for anything you encounter, unless you are SURE that it is the same problem someone else is facing.

And finally, like I end every blog post about RSiteCatalyst, please note that I’m not an Adobe employee. Please don’t send me your API credentials, expect immediate replies or ask to set up phone calls to troubleshoot your problems. This is open-source software…Willem Paling and I did the hard part writing it, you’re expected to support yourself as best as possible unless you believe you’re encountering a bug. Then use GitHub 🙂

Declaring Twitter Bankruptcy

Maybe I don’t have enough to do today, or a long day of vendor calls has made me re-evaluate what I’m doing with my life, but I had a thought:

I started on Twitter in December 2009. Quite ironically from where I sit now, I think I joined Twitter because I was an Omniture/Adobe Analytics newcomer, and probably searched Google for some term I didn’t understand. I eventually realized that people were talking about digital analytics on Twitter, so I created an account. Now, of course, I would imagine many would consider me an Adobe Analytics expert, at least in the case of the API and data feeds. And I now use Twitter way differently than I used to.

Since 2009, I’ve gone from banking and a beginner at digital analytics, to a working at an agency on helping them with Omniture, to being a digital analytics consultant at a specialty firm, to a start-up that didn’t work out, to a gigantic media company. I also pretty much never think about ‘web’ analytics, except for the fact that I created and maintain a very specialized R package that maybe a few hundred people in the world use (if I’m lucky).

When we graduate from high school, then college, get married, the natural progression is that people come into your life and some fall out. But Twitter has a sort of hoarder quality to it. Some people cull their follower list, because they don’t like what the person tweets about or they get in stupid Twitter feuds, but for the most part the list just builds and builds. Others stop using Twitter and you never hear from them again, but you still follow them (their silence?). But it occurs to me, this seems at least tangentially like the Abilene Paradox: at some point, you arrive at a place and you don’t know how you got there. What have I done over the past five years that has lead me to this place where I’m reading about what I do on Twitter?

So I’m going to conduct an experiment. I’m unfollowing all of you without prejudice. Just as if I had a hard drive crash. And I’m going to re-follow all the people I can remember, then re-discover what I’m really interested in getting from Twitter as a platform by re-following friends of friends, people saying interesting things on hashtags, etc. Hope none of you are hurt by my unfollows, but then again, if you are then maybe that says something about what kind of relationship we currently have.

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