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Reddit Archiving Tool

Hacker News

Reddit Archiving Tool

Inspired by the ongoing call-to-action by the Internet Archive team over at /r/DataHoarder [1], I've decided I want to try to preserve all cybersecurity related subreddits. [2] For people that don't know what's going on: There's a likelihood that the try to monetize the Reddit API will lead to a lot of moderators quitting the platform, and it could be that a lot of subreddits are going to be set on private and/or their threads are going to be deleted. At least that's kind of the fear from the ongoing moderator strike. In my case I learned a LOT from reddits' discussions about malware, exploits and how they work, and without those I certainly wouldn't be where I am today ... so I'm trying to preserve them. As the Archive Warrior only scrapes the HTML directly to the Web Archive, I'm trying to preserve the data itself directly as JSON files; with intent to store it later on IPFS (having been inspired a couple days ago by the-eye-team's effort to archive RARBG on IPFS). I just wanted to let people know here about the tool, and in case you want to archive your favorite subreddits, feel free to modify it. There are some limitations though, because listings (new/hot/top/search) are all limited to 1000 entries, which means that the discovery of old threads is quite limited. Keyword search increases the discovery of old threads. In my case I'm searching for a lot of keywords (like CVE, RCE, vulnerability etc) in order to discover more threads. Would love to hear feedback, currently it's just a prototypical quick n' dirty tool because the threat of my favorite subreddits going dark is quite immediate. I tried to reduce as much noise from the schema as possible, and the tool is only archiving the subreddit threads and comments, with the idea to be able to scrape the websites/blog articles at a later point in time. [1] https://old.reddit.com/r/DataHoarder/comments/142l1i0/archiveteam_has_saved_over_108_billion_reddit/ [2] https://github.com/cookiengineer/reddit-archivar

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
83%83% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Hacker NewsStrong engagement from HN community · Strong signals: ide, 000, io · Missing: https docs, excited, just released
71%71% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntOn track for Day 1 leaderboard · Strong signals: new · Missing: mac, agents, macos
60%60% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews
43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
24%24% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: arr · Missing: mrr, revenue, profit
12%12% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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