django-ninja
simonwillisonblog
django-ninja | simonwillisonblog | |
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70 | 28 | |
6,235 | 163 | |
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9.0 | 8.1 | |
4 days ago | 2 days ago | |
Python | JavaScript | |
MIT License | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
django-ninja
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Ask HN: What Underrated Open Source Project Deserves More Recognition?
Django Ninja [1], it forever changed how I write Django project, in a way so elegant and productive.
[1]: https://django-ninja.dev/
- Django Ninja is a web framework for building APIs with Django
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UtilMeta Python Framework VS django-ninja - a user suggested alternative
2 projects | 3 Feb 2024
Django Ninja is a RESTful wrapper for Django, while UtilMeta Python Framework uses a more concise declarative ORM Schema for Django and other future-supporting ORMs like sqlachemy and Peewee to build RESTful APIs more efficiently, and supports not only Django but all Python mainstream frameworks like Django, Flask, Starlette, FastAPI, Sanic, Tornado, etc.
- Django Ninja
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Ask HN: What Python libraries do you wish more people knew about?
I can't recommend [django-ninja](https://github.com/vitalik/django-ninja) enough. It's an easy to use, extremely fast, typed API for django. I've found it to be better in almost all aspects when compared to djangorestframework.
It's gaining popularity but is still widely unknown.
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Building a Blog in Django
> The only place I really see Django at large companies is as an api using DRF or something.
This is not a bad thing. Using Django as an API backend is amazingly fast in terms of development time, especially with modern frameworks such as django-ninja [1].
Just use the built-in ORM to create models, write your endpoints, and use the built-in admin interface to play with the database if you don't have endpoints for everything.
There is also a less known feature of Django called admindocs [2], which automatically generates a human readable, hyperlinked documentation for your models and relations between them.
[1] https://django-ninja.rest-framework.com/
[2] https://docs.djangoproject.com/en/4.2/ref/contrib/admin/admi...
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Learning Django
Personally, I also prefer django-ninja to DRF.
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Why I chose django-ninja instead of django-rest-framework to build my project
Actually that's not fully true. If you mix async and sync codes in django-ninja there will be some errors. Where's the proof ? django-ninja doesn't support async auth
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Built This GPT-Powered Document Search and Question Answering App with Django
Subscribe to this issue :D
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Django 4.2 released
Also recommend Django-Ninja. It basically reimplements fastapi's type and decorator-based API construction, but embedded directly in django so you have access to django's ORM and middleware library.
simonwillisonblog
- Sandboxing Python with Win32 App Isolation
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AI for Web Devs: Addressing Bugs, Security, & Reliability
Simon Willison has pointed out several examples of prompt injection attacks and why it may never be a solved problem:
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Where Have All the Websites Gone?
I want more people to have link blogs.
I have one in the sidebar of https://simonwillison.net/ which I've been running since November 2003. You can search through all 6,836 links here: https://simonwillison.net/search/?type=blogmark
I can post things to it with a bookmarklet. It has an Atom feed.
It's such a low-friction way of publishing. A lot of https://daringfireball.net works like this too. I also like https://waxy.org/ and https://kottke.org/ for this.
I'd love to see more of these.
- Ask HN: Is it feasible to train my own LLM?
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Moving Away from Substack
My approach is to publish to my own blog at https://simonwillison.net and then copy and paste content from that into a Substack newsletter at https://simonw.substack.com a few times a month.
It's been working really well.
Substack don't have an API, but they do support copy and paste - so I built myself a tool that assembles my blog content into rich text I can copy and paste straight into the Substack editor.
I wrote about how that works here: https://simonwillison.net/2023/Apr/4/substack-observable/
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Building a Blog in Django
Hah, yeah securing something like WordPress can be a challenge, especially if you're running a bunch of plugins.
My blog is a pretty straight-forward Django setup without many other dependencies, so it's a lot less of an attack surface: https://github.com/simonw/simonwillisonblog
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Show HN: Superfunctions – AI prompt templates as an API
That specific prompt is just an example and it's pretty bad, it was the shortest and simplest prompt I could come up with that would be easily understood.
You can set response content-types (text, html, json, etc...). If you use json it will get pretty good results because I have some is some logic to attempt to pick out json or json5 objects from the text output. I dont yet have logic to support json arrays, but I'm hoping to add that soon.
But still client side validation is needed for applications with untrusted input. I dont attempt to solve prompt injection. I saw a lot of interesting posts on this topic from this blog https://simonwillison.net/. I need to find sometime to read more about it.
Try this one instead, it should be better
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Stopping at 90%
I've started to consider "commit to writing about it" as the price I have to pay for giving into the lure of another project. It's one of the main reasons I publish so much content on https://simonwillison.net/ and https://til.simonwillison.net
A project with a published write-up unlocks so much more value than one which you complete without giving others a chance of understanding what you built.
I've maintained internal blogs (sometimes just a Slack channel or Confluence area) at previous employers for this purpose too.
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Stanford A.I. Courses
I think you are asking specifically about practical LLM engineering and not the underlying science.
Honestly this is all moving so fast you can do well by reading the news, following a few reddits/substacks, and skimming the prompt engineering papers as they come out every week (!).
https://www.latent.space/p/ai-engineer provides an early manifesto for this nascent layer of the stack.
Zvi writes a good roundup (though he is concerned mostly with alignment so skip if you don’t like that angle): https://thezvi.substack.com/p/ai-18-the-great-debate-debates
Simon W has some good writeups too: https://simonwillison.net/
I strongly recommend playing with the OpenAI APIs and working with langchain in a Colab notebook to get a feel for how these all fit together. Also, the tools here are incredibly simple and easy to understand (very new) so looking at, say, https://github.com/minimaxir/simpleaichat/tree/main/simpleai... or https://github.com/smol-ai/developer and digging in to the prompts, what goes in system vs assistant roles, how you gourde the LLM, etc.
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Seeking Your Top Recommendations for Resources on ChatGPT and Generative AI
Simon Willison's Weblog
What are some alternatives?
fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production
pg_cjk_parser - Postgres CJK Parser pg_cjk_parser is a fts (full text search) parser derived from the default parser in PostgreSQL 11. When a postgres database uses utf-8 encoding, this parser supports all the features of the default parser while splitting CJK (Chinese, Japanese, Korean) characters into 2-gram tokens. If the database's encoding is not utf-8, the parser behaves just like the default parser.
django-rest-framework - Web APIs for Django. 🎸
pgvector - Open-source vector similarity search for Postgres
fastapi-admin - A fast admin dashboard based on FastAPI and TortoiseORM with tabler ui, inspired by Django admin
awesome-personal-blogs - A delightful list of personal tech blogs
drf-spectacular - Sane and flexible OpenAPI 3 schema generation for Django REST framework.
tsv-utils - eBay's TSV Utilities: Command line tools for large, tabular data files. Filtering, statistics, sampling, joins and more.
openapi-generator - OpenAPI Generator allows generation of API client libraries (SDK generation), server stubs, documentation and configuration automatically given an OpenAPI Spec (v2, v3)
awesome-ml - Curated list of useful LLM / Analytics / Datascience resources
cookiecutter-django - Cookiecutter Django is a framework for jumpstarting production-ready Django projects quickly.
knowledge - Everything I know