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I wrote a book teaching web app development for non-programmers

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I wrote a book teaching web app development for non-programmers

Hey HN, I wrote a book teaching beginner web app development using Django, launching on May 4th (successfully Kickstarted last year.) Website: http://hellowebapp.com Highlights: - Aimed at people who have previous HTML/building websites experience. - Template-first development: see the web app as a website first, before setting up databases and models. - Generic “collection of things” tutorial. Readers are encouraged to create something using this rubric that means something to them (a blog, a directory of people, etc.) Adding creativity will make the material stick better. - Includes Heroku deployment, which was honestly the hardest chapter to write (I ended up creating my own Python package to make it partially easier: https://github.com/hellowebapp/hellowebapp-deploy) - Additional resources are being added to https://github.com/hellowebapp/hellowebapp If anyone has ideas of how to reach people who are getting into webapp stuff (HTML/CSS) but haven't been able to cross the threshold to programming a backend, would love to hear them!

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Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting
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Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
73%73% 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: model, models, using · Missing: mac, agents, macos
52%52% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive
51%51% 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
29%29% 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
17%17% 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
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