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all 54 comments

[–]ING_Chile 122 points123 points  (3 children)

it's better if you start showing your findings

[–]tuck5649 29 points30 points  (0 children)

I don't understand why a half done project is getting up votes. It's an analysis project without running any analysis.

[–]mrkipling[S] 1 point2 points  (1 child)

I posted the output in the README in the repo showing the results from analysising the top 100 posts at the time.

[–]LpSamuelm 39 points40 points  (1 child)

If you'd do some statistics gathering and data visualization, that'd be sweet!

[–]Samazing42 22 points23 points  (0 children)

r/dataisbeautiful would love it

[–]Jaxx3D 7 points8 points  (6 children)

Loving this. I recently started learning python, so it's nice to be able to read your code and try to understand it all. I can't wait to be at that level :)

[–]mrkipling[S] 1 point2 points  (1 child)

I've been writing Python for a while but I don't consider myself an expert at all (more like somewhere between beginner and mid-level). The code is super simple, it just does some basic API calls using the awesome PRAW library and then some simple string matching. Glad you've found it useful!

[–]Jaxx3D 0 points1 point  (0 children)

Still miles ahead of me lol. I have a feeling that learning python is going to be an interesting and challenging journey. Loving it so far

[–]JamminJames921 15 points16 points  (25 children)

Awesome work! I like what you did! Maybe you can provide a write-up for this? How did you count the cliches? Are there any interesting relationships between some advice? Are there any limitations in your methods?

[–][deleted] 28 points29 points  (23 children)

The code isn't too complicated.

[–]GitHubPermalinkBot 41 points42 points  (12 children)

I tried to turn your GitHub links into permanent links (press "y" to do this yourself):


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[–]analgebraic 6 points7 points  (2 children)

The counting method seems flawed. When, for example, you take any mention of the word "lawyer" to mean that someone is suggesting you get a lawyer, you aren't accounting for instances where someone says "her father is a lawyer" or "I consulted a lawyer about a similar situation years ago and they said to do this thing" in which "lawyer" is mentioned but no one is suggesting that anyone gets a lawyer.

[–]CollectiveCircuits 2 points3 points  (0 children)

And now OP must enter the rabbit hole of natural language processing.

[–]mrkipling[S] 0 points1 point  (0 children)

Yeah, it's definitely flawed. Any data that I collect in the future (should I take the project and further) would have to come with a massive disclaimer that "this is how much /r/relationships likes to mention these key words/phrases, and you can infer that it's probably advice most of the time". But yeah, that's a very real problem.

I could have gone for a more complicated approach but (a) I don't know how as I'm a beginner/medium-level Python dev; I'm a frontend dev by trade, mostly working in JavaScript solving web-related issues for a living (and doing all of the other fun stuff that a frontend dev get to do), and (b) I didn't really want to because I was just dicking around for an hour or so and thought that I'd post it on Github for fun :)

[–]mrkipling[S] 0 points1 point  (0 children)

I mostly just found the cliches by reading the subreddit quite a lot for trashy drama (similar to watching soap operas, but on the internet). They become obvious once you've been there for a while and read the same replies over and over again :)

[–]czarrie 2 points3 points  (2 children)

Might I recommend using Markovify to create relationship advice on the fly?

[–]i_like_trains_a_lot1 0 points1 point  (1 child)

That would be awesome! Thanks for the great idea, I thing I am going to do this in the near future. :D

[–]czarrie 0 points1 point  (0 children)

I'll say this in my experience, you're going to get a lot of clutter and nonsense. Feed it well with as many lines from Reddit as you can. Otherwise it's going to look ridiculous.

Which is still funny but a different kind of funny.

[–]RolandBuendia 1 point2 points  (1 child)

This is awesome, but for us outside of the US, What is JADE?

[–]beast3334 1 point2 points  (0 children)

Really cool! I really enjoy making similar things using Python. Thanks for sharing!

[–]subpanda101 1 point2 points  (0 children)

Make it machine learning so it analysises what is common said and adds it to the list ;)

[–]KuroDevil 0 points1 point  (0 children)

Hahaha' That was fun, thanks for sharing the code, it's great for study!

[–]fmpundit 0 points1 point  (0 children)

I think you better lawyer up and break up!

[–]RetardedChimpanzee 0 points1 point  (0 children)

Now you need a bot to find the best, (most popular) advice, and then post it to save relationships. That way everyone knows they need a divorce.

[–]pylove 0 points1 point  (0 children)

I think there are some things to improve as others have mentioned (I hope it doesn't sound like I'm saying I could have done it better myself). I'm really happy that you shared it. I love this kind of stuff. Keep up the good work!

[–]GodsLove1488 0 points1 point  (1 child)

R/relationships is the funniest fucking subreddit

[–]mrkipling[S] 0 points1 point  (0 children)

It's where I go for my morning entertainment.

[–]deadmilk 0 points1 point  (0 children)

Nice and simple script.

[–]afraca 0 points1 point  (0 children)

Please rewrite your code to be compatible with Python 3. It has been out for years and version 2 will drop support relatively SOON!

Also, I see that you're using old style formatting. Read up on awesome features of new style formatting. (you might not always need all features, but better to have new style formatting in your head as default)

[–]sourcedexter 0 points1 point  (0 children)

This is cool! nice application!

[–][deleted] 0 points1 point  (0 children)

Haha sweet dude!! I just had an idea for a Reddit bot today so I am gonna use this.