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karmanaut's Introduction

This project has been superseded by Whitman and is unlikely to see any more improvements or bugfixes.


Karmanaut

Karmanaut is a simple service for sampling link and comment reputation from Reddit. It takes a list of users from a MongoDB collection, collects those users' reputation scores, and saves them back into a MongoDB collection.

Prerequisites

  1. Leiningen
  2. MongoDB, running on your local machine.

Usage

  1. Build the Jar:

     $ lein uberjar
    
  2. Create a MongoDB database called karmanaut.

  3. In the karmanaut database, create a collection called users.

  4. Populate the users collection with users whose karma you would like to record, in the following format:

     {_id: <reddit username>}
    
  5. Run the Jar file:

     $ java -jar target/uberjar/karmanaut-standalone.jar
    

You will probably want to run the program as a cron task, to sample reputation periodically.


FAQ

Do you have any affiliation with karmanaut?

No. I was loosely inspired by the username, but karmanaut—literally, "karma sailor" or "karma explorer"—just made sense for this project name, since that's what it's doing: exploring karma.

Where does this project come from?

It's a fork of a similar crawler I wrote for Stack Overflow reputation called Chameleon. One day I hope to factor out a common base for both these projects; for now, though, Karmanaut remains but a (very divergent) fork.

What's the goal?

To build charts of karma growth over time, and calculate all sorts of fun statistics, as well as other data points like the derivative of one's karma.

Is this project actually used in production?

Yes. It is running on pacific.monkey-robot.com. I haven't exposed the data publicly yet, not because I don't want to, but because I haven't had time to build a web frontend for it.

karmanaut's People

Contributors

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Watchers

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karmanaut's Issues

Improve database design

Re-consider how the data is stored in MongoDB. Perhaps karmanaut should create one document per day, with multiple readings per day stored in the document, as outlined here.

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