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I open sourced my image sharing application

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I open sourced my image sharing application

I made an image sharing application to compete with Imgur. Chances are it's not going to take over Imgur any time soon, so I figured I'd open source it. Stack: * Symfony w/ PHP 5.5 * Postgres 9.2 * Redis 2.8 * Ruby 2.0 (Capistrano) * Vagrant It's a fairly basic Symfony application but also makes use of a lot of Symfony components. It's sufficiently complex enough that you can probably learn a decent amount from it if you want to start playing around with Symfony. It has a few tests, uses Resque, uses the Symfony service container, and integrates with Amazon S3. Check it out, would love your thoughts. Thanks! https://github.com/brightmarch/picto

Visit productView on Hacker NewsDec 21, 2013
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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
76%76% 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: open source, io · Missing: https docs, excited, just released
68%68% 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: apis, open · Missing: mac, agents, macos
50%50% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: soon · Missing: plus, platform, intuitive
41%41% 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
37%37% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
13%13% 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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