Dj

Django Ninja CRUD – Rethinking CRUD Operations in Django

Hacker News

Django Ninja CRUD – Rethinking CRUD Operations in Django

I've developed Django Ninja CRUD, a tool to simplify CRUD operations in Django by leveraging Django Ninja's strengths. It aims to make CRUD operations more intuitive, modular, and efficient, especially for large-scale projects. Key aspects: - Declarative, intuitive CRUD operations. - Modular approach with composition-over-inheritance. - Enhanced testing capabilities for robust applications. The tool is designed to transform Django development workflows, improving efficiency and maintainability. Read more about the development, features and roadmap here: https://medium.com/@hbakri/introducing-django-ninja-crud-ee9... GitHub Repository: https://github.com/hbakri/django-ninja-crud I'm eager to hear your feedback and hope it adds value to your Django projects!

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Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
54%54% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
45%45% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos
44%44% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: intuitive, efficient · Missing: plus, platform, 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
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
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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