MediaCMS – An open source, self hosted video and media CMS

Hacker News

Dear HN community, we are happy to announce the release of MediaCMS on Github! It is a modern CMS built in Django/PostgreSQL/React and a REST API, released under AGPL license. MediaCMS handles the life cycle of media files and is deal for those who want to build online communities around media file sharing, for informational, educational or entertainment purposes. As stated on our page on Github, we have three goals for MediaCMS: a) deliver all functionality one would expect from a modern system, b) allow for easy installation and maintenance, c) allow easy customization and addition of features. Check out more on the following links: Home page: https://mediacms.io Github: https://github.com/mediacms-io/mediacms

Visit product View on Hacker NewsDec 22, 2020

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

69%69% 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, ide, io · Missing: https docs, excited, just released

59%59% 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: open · Missing: mac, agents, macos

58%58% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: host · 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 · Strong signals: video, education · Missing: mobile apps, ios, personal

39%39% 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

19%19% 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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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