Skip to content
master
Switch branches/tags
Go to file
Code

Latest commit

 

Git stats

Files

Permalink
Failed to load latest commit information.
Type
Name
Latest commit message
Commit time
 
 
 
 
 
 
 
 
 
 

README.md

getRedditDataset

This repository uses PRAW to create custom datasets from reddit.

PRAW/Reddit API Basics

This isn't intended as a tutorial for PRAW. If you want that, I recommend visiting their docs. This section will only go through the fundamentals of PRAW necessary to create a data set from reddit.

First, let's import praw and the redditDataset module

import praw
import redditDataset

Next, let's initialize a connection with PRAW as follows:

redditObject = praw.Reddit(user_agent='get_reddit_dataset')

We can grab subreddits using getSubreddits. Here, we'll grab /r/funny and /r/gaming

subreddits = redditDataset.getSubreddits(redditObject, ['funny', 'gaming'])

PRAW also has a variety of functions to grab subreddits. One of the most useful is the method get_popular_subreddits.

popularSubreddits = redditObject.get_popular_subreddits(limit=200)

This will return a generator containing the 200 most popular subreddits. PRAW has many other methods to grab specific submissions, comments, users, etc., but these are the only ones you'll need to know to use the module.

Now that we have a reddit object and the subreddits to query, let's make a data set.

Grabbing a data set from a set of subreddits

Once you have a generator or list of subreddit objects and your praw object, call createDataset to start downloading comments and posts into a sqlite3 database. The database will be saved in ~\Databases\<dbName>db.

Let's grab all the posts from the funny subreddit from March 1, 2015:

funnySubreddit = redditDataset.getSubreddits(redditObject, ['funny'])
redditDataset.createDataset(redditObject, funnySubreddit, startDate='150301000000'
							endDate='150301235959', dbName='March_01_2015_funny_posts'
							fineScale=4)

Basically, you give createDataset the reddit object, the subreddits (in list or generator form), a start and end date, a base name for the database, and a fine scale (which I'll get to in a moment).

For the start and end date, provide a string in the format 'yymmddHHMMSS'. So, in the above example, we're pulling posts between March 1, 2015 at 12:00:00 AM and March 1, 2015 at 11:59:59 PM.

Unfortunately, the reddit API will only provide a list of 1000 posts for any query. What does this mean for us? Well, say we want to get all the posts from 2014. If we request all those posts, we'll only get the 1000 with whatever sort is specified (createDataset uses a 'top' sort). To get around this, createDataset will make many requests in increments of 'fineScale' hours. So, in the example, above, we'll actually make six separate queries for a theoretical maximum of 6,000 posts. Because of the overhead associated with getting posts, we want to set this parameter to be as large as possible while still getting all the data we want. I've found that 8 works well for all but the most frequented subreddits.

And that's it! It'll work to retrieve all the posts within the desired range and the top comments from each post (by default, this is set to 100). One thing to note: because of the reddit API limits, this process is slow. We can only make 30 requests per minute. Currently, we only get the data for one post per request. I think this can be improved (potentially up to 25 posts per request), but I haven't gotten around to it yet.

Database structure

The sql database is pretty simple. It has two tables: submissions and comments.

Each row in submissions represents a single post. The columns contain the postID, postTitle, postBody (text if a self-post, url if a link), postScore (as of when it was downloaded), subredditName, and subredditID.

Each row in comments represents a single comment in a post. The columns contain the commentDate, user, body, comScore (as of when it was downloaded), and the postID.

About

Allows user to grab datasets from reddit

Resources

License

Releases

No releases published

Packages

No packages published

Languages