Getting down and dirty with Haskell

August 11, 2013

I’ve started using c2hs recently, for a Haskell NetCDF library I’m writing (which might see the light of day in a couple of months). I like c2hs, so I volunteered to help out with maintenance. The first thing we did was transfer the source code repository from Darcs to GitHub, which was easy, using Steve Purcell’s darcs-to-git utility. Once that was done, the next task was to transfer all the tickets on the c2hs Trac site to GitHub’s issue tracking. That’s what I want to talk about here.

I didn’t have access to the Trac database, so this was going to be a nasty hacky web-scraping kind of job. Trac makes this easier by having some nice semantic markup in its HTML pages for each issue, but it was still going to be kind of ugly. There was a time when this kind of job would have made me reach for Perl, but these days, I’m trying to do as much as possible in Haskell. It ended up being fun and I learnt some things (as well as getting the job done!).

The code is here. I want to talk about three different aspects of what I had to do: CSV file parsing, HTML scraping, and communicating with the GitHub web API, all of which are “bread and butter” activities that we’d hope might be supported by libraries (they are).

CSV files

Trac provides basic information about each issue as a CSV file that you can pull from the Trac site with an HTTP request. CSV is pretty easy to parse, but why reinvent the wheel? There are a number of different options in Haskell, but I’ve become quite fond of csv-conduit. It interfaces with conduits if you need that, but it also has convenience functions for simple uses: here, I just needed to use the parseCSV function from Data.CSV.Conduit.Parser.Text. No muss, no fuss.

HTML scraping

Parsing HTML isn’t as easy as parsing CSV data, and I’d have avoided it if I could, but I wanted to convert the comment history from each Trac issue to comments on GitHub and I couldn’t figure out a way to get Trac comments in any other form than as fields on an HTML page. I also wanted to carry over information about attachments for Trac issues to the GitHub issues, just providing a link back to the Trac site so that people would still be able to see the attachments.

The go-to solution for HTML and XML parsing in Haskell is HXT, but this is what I would definitely categorise as a scarey package. The list of modules on the contents page of the Haddock documentation starts with 14 modules called Control.Arrow.SomethingFrightening, which is never a good sign. Fortunately, there is good documentation available if you look around a bit: the “gentle introduction” is about as gentle as Haskell “gentle introductions” ever get, but even better is the page Working With HTML In Haskell, written by the author of the HandsomeSoup package. (HandsomeSoup adds a number of features convenient for working with HTML to HXT. In particular, it allows you to use full CSS selector syntax for locating elements in your document, which is a real boon.)

Once you get over the initial barrier to entry, HXT and HandsomeSoup are really easy to use for the kind of page scraping I needed. Here’s a little example: given the contents of a Trac HTML page for an issue as a Text value (called html in the code below), let’s get a list of the URLs of attachments on the page – these are held in a definition list of class attachments in hyperlinks with the word “View” in their title:

This code (which runs in the IO monad here) parses the HTML into a tree of XML elements, then uses HandsomeSoup’s css combinator to pull out the relevant elements we want (note the full CSS3 selector syntax!), then extracts the href attribute from each of those elements, giving us a list of URLs for the attachments. HXT and HandsomeSoup combinators use arrows for plumbing, hence the >>> combinator, and the runX function is used to execute a chain of HXT combinators to get a result.

This was about the simplest kind of thing I needed to do: I also had to extract comments and convert the HTML markup to GitHub Markdown so that I could insert the comments into GitHub. This was a bit more complicated, but the arrow pipeline processing model of HXT makes this sort of thing as straightforward as it’s ever going to be. Here’s how I got the comments out:

Here, pres, ps and tts are arrows to convert various kinds of HTML elements to equivalents or near equivalents in GitHub Markdown:

HXT’s processTopDown function allows you to recursively transform the elements of an XML document tree, and the when combinator allows you to do this transformation selectively, depending on the kind of element you’re looking at.

There’s a huge amount of stuff you can do with HXT, and I can see that it’s going to take a long time to learn even a fraction of it. However, despite the initially forbidding facade, once you’ve played with it a little, it’s a lot less intimidating.

GitHub API

Once I’d scrabbled and scraped my way to some data that looked reasonable, I wanted to create issues on the c2hs GitHub repository. GitHub has a nice and well-documented web API for doing most administrative actions for a repository, so this ought to be easy. What makes it even easier is that there is already a Haskell package for talking to GitHub, called, logically enough, github. When I originally looked at this, it didn’t have functions for creating and editing issues and comments, but all the infrastructure was there, and it was easy to add the new functionality. It all worked fine and the new functions are now incorporated in the latest version of the package.

It’s really easy to use. Here’s a function that creates a new GitHub issue from a Trac ticket (represented as a value of type TracTicket). You create a value of type NewIssue (which has fields corresponding exactly to the fields in the JSON payload passed to the GitHub API endpoint) and pass it to createIssue along with some authentication information and the user name and repository name for the repository you want to add the issue to. You get back either an error, or an Issue value constructed from GitHub’s reply. (Here, I also edit the issue right after creating it if it needs it – adding labels or changing the issue state, for example).

Conclusion

I always find it kind of funny when people mention Haskell as being an “academic” language or “too difficult to use for everyday things”. The Haskell ecosystem is now at a point where you really can do a lot of those “everyday things” with very little effort, and the Haskell solutions to problems like XML manipulation and other nasty but necessary tasks often feel much more powerful (and safer) than the untyped alternatives. And, perhaps contrary to expectations, doing these “scripting” tasks in a strongly-typed language feels really natural.