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reddit

historical code from reddit.com

148Distinct people
170Mentions
3Explicit recommenders
16.9KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

historical code from reddit.com

GitHub

Where it is used

No documented product use was verified in the last source check.

What people are saying

If you use Python for anything remotely performance sensitive, I highly recommend giving Cython a shot. The trick is to find your computation-intensive inner loop stuff, move…

ketralnis used a recommendation phrase. 3 indexed comments match. This is a phrase match, not a verdict.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

Mentioned in the same Hacker News threads. That is not proof they are substitutes.

This week on Hacker News

Nov 8–Nov 15 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/15/2026, 5:58:02 AM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year170 dated mentions

Observed mentions: 2010-07-01 14:04:07 UTC to 2024-01-01 19:05:34 UTC.

05101520252010-01-01 00:00:00 UTC to 2011-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments20102011-01-01 00:00:00 UTC to 2012-01-01 00:00:00 UTC (exclusive): 8 mentions; 0 submissions, 8 comments2012-01-01 00:00:00 UTC to 2013-01-01 00:00:00 UTC (exclusive): 21 mentions; 2 submissions, 19 comments2013-01-01 00:00:00 UTC to 2014-01-01 00:00:00 UTC (exclusive): 18 mentions; 3 submissions, 15 comments2014-01-01 00:00:00 UTC to 2015-01-01 00:00:00 UTC (exclusive): 25 mentions; 6 submissions, 19 comments2015-01-01 00:00:00 UTC to 2016-01-01 00:00:00 UTC (exclusive): 13 mentions; 1 submissions, 12 comments2016-01-01 00:00:00 UTC to 2017-01-01 00:00:00 UTC (exclusive): 13 mentions; 1 submissions, 12 comments2017-01-01 00:00:00 UTC to 2018-01-01 00:00:00 UTC (exclusive): 19 mentions; 0 submissions, 19 comments20172018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 10 mentions; 1 submissions, 9 comments2019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 4 mentions; 0 submissions, 4 comments2021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 8 mentions; 0 submissions, 8 comments2022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 24 mentions; 1 submissions, 23 comments2024-01-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2024

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20102010-01-01 00:00:00 UTC2011-01-01 00:00:00 UTC202
20112011-01-01 00:00:00 UTC2012-01-01 00:00:00 UTC808
20122012-01-01 00:00:00 UTC2013-01-01 00:00:00 UTC21219
20132013-01-01 00:00:00 UTC2014-01-01 00:00:00 UTC18315
20142014-01-01 00:00:00 UTC2015-01-01 00:00:00 UTC25619
20152015-01-01 00:00:00 UTC2016-01-01 00:00:00 UTC13112
20162016-01-01 00:00:00 UTC2017-01-01 00:00:00 UTC13112
20172017-01-01 00:00:00 UTC2018-01-01 00:00:00 UTC19019
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC1019
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC202
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC404
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC808
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC202
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC24123
20242024-01-01 00:00:00 UTC2025-01-01 00:00:00 UTC101

What Hacker News says

19 sources
Marketing. Marketing is what MongoDB got right, along with a small helping of being early to market. It's not even the best or most convenient document store, doesn't have the most features, isn't the most secure, doesn't handle high availability the best, they basically got everything just "good enough" (and sometimes not), along with stellar marketing. They marketed their asses off while they iterated to build a document store that was worth the praise they got people to heap on to it. IIRC the acquisition of the wired tiger engine was basically a rewrite, because the previous implementation was just bad. So if the database engine wasn't good, and distribution wasn't good (until later), and schema management wasn't good, and the query language wasn't all that great, what did mongo really get right? Marketing and being early to market/ne
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w and shiny at the right time (when everyone was deciding that writing the frontend and the backend in the same language, javascript, was an awesome thing -- which I don't necessarily disagree with). If someone needs a database these days, I always just suggest postgres. if it's good enoguh for reddit (https://github.com/reddit/reddit/wiki/Architecture-Overview#...), it's good enough for the next facebook for dogs (unless your problem is completely different then of course you should explore whatever database paradigm fits your problem the best).
In What MongoDB got right (2015)
Oh, it will certainly come up, but it's not going to break Reddit if you get an old version of a comment as long as it's eventually consistent. Nobody is going to die, and nobody is going to lose any money. Data stores like Cassandra and MongoDB don't lose revisions. That's not the kind of consistency we're talking about. CAP consistency is just getting the most recent version. You won't lose data -- data loss is a bug, not expected behavior, just like any other data store -- you just won't always get the most recent version of it. And, keep in mind, when we talk about eventual consistency here we generally mean "consistent on all nodes within a few minutes, but we're not blocking reads to write this data." It's not going to take hours. That said, if you find you get an old version of your own comment, I'd be more willing to believe
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it's the fact that your request failed with a 503 error or otherwise timed out as much as it was a data store problem. Next time it happens, wait 5 minutes and try again. > is there really no other way to cluster their data except "one big table"? Maybe like shard subreddits to specific servers ala Hyperdex? The whole point of MongoDB or Cassandra is that you can get shards without all the headache that RDBMSs usually put you through. You configure your sharding function and let the system do the rest. You don't have to connect to the right shard or anything of the sort, which some RDBMSs do (or did, it's been awhile since I've looked) require with sharding. Reddit has their code and architecture posted, though it's out-of-date now, it makes it clear that it's basically just two big tables: https://github.com/reddit/reddit/wiki/Architecture-Overview It's PostgreSQL, ThingDB, Cassandra, memcached, and RabbitMQ.
In MongoDB shares jump more than 30% in $192M IPO
Hey bold_panda, I'm the Group PM for Monetization and Growth @ Reddit. I'm really sorry to hear you're experiencing worse CPMs from this targeting change. We definitely did not make this change to intentionally deceive you. You, the advertiser, are our the customer of our ads product. We certainly don't intend to reduce advertiser ROI, because at the end of the day if you are unhappy with your ad performance and leave that doesn't boost our ad revenue at all. To clarify what happened here, around the time we released our new ads platform - 6 months ago - we made some changes to targeting. Specifically, we modified subreddit targeting so that recent visitors to a subreddit or a post from a subreddit could also qualify to see ads targeted to that subreddit. We did not make any changes to how users who subscribe to a subreddit see ads (subre
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ddit subscribers have been eligible to see ads targeted to a subreddit as long as they are visiting safe for work content since this commit ~2 years ago: https://github.com/reddit/reddit/commit/f6a37b64c17579b82e22...) The release of our new ads platform also coincided with a re-release of our help center docs, which detail how subreddit targeting works. You can see the specific page here: https://www.reddithelp.com/en/categories/advertising/targeti... As noted there: "Targeting a subreddit means you are targeting the subscribers and recent visitors of that subreddit. Subscribers can see your ad while visiting the targeted subreddit and on other subreddits if they recently visited that targeted subreddit." We made this change in response to advertiser feedback that they would like to see an increase in targeted inventory, the idea being that if you're interested in jerky when you're on /r/jerky you're also interested in jerky when you're not on /r/jerky. This change has helped a good number of our advertisers successfully expand budgets while still meeting their return on ad spend goals, specifically for advertisers that target smaller subreddits regularly. We of course also limit the subreddits your ads can show on outside of the targeted subreddit to ones that are similarly "brand safe" to the ones you are targeting. (e.g. if you are explicitly targeting only NSFW subs your ad will show up on other NSFW subs, but if you're not targeting NSFW subs your ad will never show up on a NSFW sub) While we haven't done any sort of official analysis of CPM changes here, the expected effect of this change was that advertisers would be able to spend significantly more budget (a specific request of many of our advertisers). An expected side effect is that CPMs might possibly increase due to more bids on a per-impression basis, but since you're bidding on a wider range of inventory I would expect that you would be able to reduce your CPMs and still spend the same budget you were spending before, with similar performance. If there's something I can do to help please don't hesitate to email me directly (jamie@reddit.com). In the future for ads problems we also hang out on https://www.reddit.com/r/redditads
In Reddit's Ad Changes Reduce Your ROI
I think there are a few disadvantages Reddit has here. The first that comes to mind is that website administrators, especially for large and politically-charged sites, might like Reddit's software, but not its ... um, culture. "Just embed Reddit" sounds approximately like "just embed 4chan". While smaller sites are happy to give up some control for the sake of easily adding a major feature to their site, larger businesses are probably going to want to own their own content and self-host their code as much as possible. Reddit has a non-trivial set of dependencies (https://github.com/reddit/reddit/wiki/Dependencies), so it's not very attractive as far as that goes. My from-my-ass guess is that once Reddit ended up in the mainstream news a few times for some drama or another, it lost the opportunity to be taken seriously as an embeddable fea
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ture by other major sites.
In Washington Post integrates Talk – Mozilla’s open-source commenting platform
I never was huge on Python but always preferred it to Ruby. One web framework that always fascinated me was CherryPy[0]. On my first (and current) real programming job I was asked to work on a RESTful type of project, and was given free reign to research a language and stack. I initially was asked if I liked Python, once I spotted interest towards Python I suggested CherryPy. I stuck with CherryPy and 4 months later, my RESTful service had a front-end using the Mako[1] templating library alongside it's RESTful back-end. All the code is done in an Object Oriented fashion. I can't imagine doing the same work without any external libraries. [0]: http://cherrypy.org/ [1]: http://www.makotemplates.org/ Note: Mako is used by Reddit for their template library. https://github.com/reddit/reddit/blob/master/r2/setup.py#L62
In Learning Python Without Library Overload

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