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reddhead

Reddhead provides a Scala abstraction over Reddit web services. Reddhead makes it simple to write programs that consume data from the Reddit front page and subreddits, including article comments and other metadata. The intent is to provide an abstraction that is type safe and conforms to idiomatic functional programing style.

Reddhead uses Spray and Akka. Akka provides asynchronous messaging, and Spray provides a REST client built on top of Akka. TimerBasedThrottler is used to throttle web service calls in accordance with Reddit's rules.

Model classes provide typed abstractions over Reddit JSON objects. See model.scala.

APIs provide abstractions over Reddit queries and use cases. See api.scala.

The Console class demonstrates how to create the environment and use the API.

getting started

Clone this git repo.

Examine Console.scala. Uncomment the use case you want to test. Run with sbt run.

I have been having memory issues. I am experimenting with export SBT_OPTS='-XX:MaxPermSize=512m -Xms512m -Xmx512m'.

use cases

print front page image links

links(frontpage) {
	case link if link.domain == "i.imgur.com" => println("""<img href="%s"/>""".format(link))
}

The frontpage parameter to links specifies which feed to consume. The block that follows is called for each link in the feed. Reddhead scrolls through the entire feed (until the program is killed, or Reddit returns no data).

Output:

<img href="http://i.imgur.com/oIJMk.jpg"/>
<img href="http://i.imgur.com/dFMeh.png"/>
<img href="http://i.imgur.com/oyAET.jpg"/>
<img href="http://i.imgur.com/nrl9w.jpg"/>
<img href="http://i.imgur.com/bgrDM.jpg"/>
<img href="http://i.imgur.com/T4dlD.jpg"/>
<img href="http://i.imgur.com/1iL6G.jpg"/>
<img href="http://i.imgur.com/yNsQt.png"/>
<img href="http://i.imgur.com/Fls4C.jpg"/>
<img href="http://i.imgur.com/wqtMD.jpg"/>
<img href="http://i.imgur.com/XqBS7.png"/>
<img href="http://i.imgur.com/3tmgi.jpeg"/>
<img href="http://i.imgur.com/Qy0ol.jpg"/>
<img href="http://i.imgur.com/cFLfy.jpg"/>
<img href="http://i.imgur.com/SCEMx.jpg"/>
<img href="http://i.imgur.com/FZf1J.jpg"/>
<img href="http://i.imgur.com/ERCVX.gif"/>
<img href="http://i.imgur.com/ExhfA.jpeg"/>
<img href="http://i.imgur.com/7nKNO.png?3"/>
<img href="http://i.imgur.com/Fc4tg.jpg"/>
<img href="http://i.imgur.com/Jj1jH.jpg"/>
<img href="http://i.imgur.com/lN7Ln.jpg"/>
<img href="http://i.imgur.com/aAEwP.gif"/>

print all submissions and comments by user

scroll(user("masta")) {
	case l:Link => println("link: %s".format(l))
	case c:Comment => println("comment: " + c)
}

This user is a mod on /r/pics, so I assume he or she has a lively feed.

The callback block is executed for each Thing in the feed. The parameter is a PartialFunction[Thing, Unit], allowing this abbreviated match syntax.

monitor the front page for new posts

monitor_links(frontpage) {
	case l => println(l)
}

The callback is called for each Link from the main feed. Note that these functions consume all pages of the feed, not just what is visible on the first page of the UI. Reddhead will make multiple API requests to Reddit in order to get the data. Requests happen lazily (as needed) and follow Reddit's throttling rules.

monitor the top post for new comments

first_link(frontpage) {
	case l: Link => monitor_comments(l) {
		case (_, c) => println(c)
	}
}

This example prints new comments as they appear in a story. The story used is the top link from the front page feed.

concurrently read 2 feeds

links(frontpage_top) {
	case t => println("top: " + t)
}
links(frontpage_new) {
	case t => println("new: " + t)
}

Thanks to Akka and Spray all web service calls happens in background threads, and are non-blocking. This allows us to run concurrent behaviors. This example crawls links from two different feeds. Each link is printed to stdout, which will result in interleaved output. An improvement might be to write the output to files.

download images from r/pics

import sys.process._
import akka.actor._
val execute = system.actorOf(Props(new Actor {
	def receive = {
		case cmd:String => cmd.run
	}
}))
links(subreddit("pics")) {
	case link => execute ! "wget -o /tmp/wget.log -P /tmp %s".format(link)
}

An actor is created to handle spawning the wget process. Crawling Reddit and downloading images happen concurrently!

crawl link comments

comments("16716l") {
	case (ancestors, c) => println("-" * ancestors.size + c.body)
}

ancestors contains this comment's parent comment, listing back to the root comment. Here I am using its size to format the output.

build a social graph by reading comments

var connections = Map[Set[String], Int]().withDefaultValue(0)
links(frontpage_top) {
	case link => comments(link) {
		case (ancestors, comment) => {
			val user1 = ancestors match {
				case parent :: _ => parent.author
				case Nil => link.author
			}
			val user2 = comment.author
			val key = Set(user1, user2)
			connections = connections + (key -> (connections(key) + 1))
			println("%s / %s = %d".format(user1, user2, connections(key)))
		}
	}
}

Here we build a simple social graph by reading Reddit comments. This code reads all the comments on all the posts on the front page. Each comment counts as a connection between the author and the parent comment. Top level comments count as a connection between the commentor and the OP. The connection count is incremented and printed along the way, creating a simple report.

output:

goleks / OddDude55 = 1
troshinsky / CharlesFoxtrot = 1
troshinsky / nittywame = 1
nittywame / AlexHeyNa = 1
AlexHeyNa / troshinsky = 1
troshinsky / eobet = 1
troshinsky / tembies = 1
troshinsky / Not_A_Hipster_ = 1
Not_A_Hipster_ / troshinsky = 2
troshinsky / whatsthematter = 1
whatsthematter / troshinsky = 2
troshinsky / Melton_John = 1
troshinsky / onebighoopla = 1
onebighoopla / troshinsky = 2
troshinsky / onebighoopla = 3
onebighoopla / troshinsky = 4
troshinsky / guydudeman = 1
troshinsky / fer_ril = 1
fer_ril / troshinsky = 2
troshinsky / eyecite = 1
troshinsky / fer_ril = 3
fer_ril / troshinsky = 4
troshinsky / anonysera = 1
troshinsky / FatalLozenge = 1
FatalLozenge / troshinsky = 2
troshinsky / FatalLozenge = 3

TODO

  • package as a library
  • authenticated write requests (voting, link submission, commenting, etc.)
  • traversal into more comments

references