<table> <tr><td> <a href="https://www.reddit.com/r/FastAPI/comments/1r3ofpf/help_i_dont_understanding_any_of_the_db/"> <img src="https://preview.redd.it/qcg2almoe9jg1.png?width=140&amp;height=113&amp;auto=webp&amp;s=48c8a3692f06263d626d353336463cf3f24294fe" alt="Help, i dont understanding any of the db connections variables, like db_dependency, engine or sessionlocal and base" title="Help, i dont understanding any of the db connections variables, like db_dependency, engine or sessionlocal and base" /> </a> </td><td> <div class="md">i was following a tutorial and he started to connect the db part to the endpoints of the api, and the moment he did this, alot of variables were introduced without being much explained, what does each part of those do, why we need all this for? also why did we do the try, yield and finally instead of ust return db? execuse my idnorance i am still new to this </div> &#32; submitted by &#32; <a href="https://www.reddit.com/user/Beyond_Birthday_13"> /u/Beyond_Birthday_13 </a> <a href="https://www.reddit.com/gallery/1r3ofpf">[link]</a> &#32; <a href="https://www.reddit.com/r/FastAPI/comments/1r3ofpf/help_i_dont_understanding_any_of_the_db/">[comments]</a> </td></tr></table>

i was following a tutorial and he started to connect the db part to the endpoints of the api, and the moment he did this, alot of variables were introduced without being much explained, what does each part of those do, why we need all this for?
 also why did we do the try, yield and finally instead of ust return db?
 execuse my idnorance i am still new to this
    submitted by    /u/Beyond_Birthday_13  
 [link]   [comments]

Help, i dont understanding any of the db connections variables, like db_dependency, engine or sessionlocal and base

<div class="md">Hey folks I’ve been using FastAPI for ~5 years now and I probably spend an unhealthy amount of time staring at Swagger every single day. I actually like the default theme. It’s clean and familiar. But after a few hours… especially at night… it starts feeling like I’m getting flashbanged by my own API docs :D So I thought, instead of replacing Swagger with a completely different theme, why not just add a proper Dark / Light toggle? I’ve seen dark-mode versions before ( <a href="/u/BlueFriends">u/BlueFriends</a> and <a href="/u/Fit_Tell_8592">u/Fit_Tell_8592</a> did some cool stuff), but I wanted something that keeps the original Swagger vibe and just enhances it a bit. My goal was to: • Keep the original Swagger feel • Add a smooth Dark / Light toggle • Not break FastAPI defaults • Implement smth that is easy to plug into existing projects(actually 1 line) You can enable it with literally one line of code. Your eyesight is worth more than 1 line of code :D So I built this: Repo: <a href="https://github.com/akutayural/fastapi-swagger-ui-theme">https://github.com/akutayural/fastapi-swagger-ui-theme</a> Pypi: <a href="https://pypi.org/project/fastapi-swagger-ui-theme/">https://pypi.org/project/fastapi-swagger-ui-theme/</a> Contributions, ideas, improvements, or even nitpicks are very welcome. </div> &#32; submitted by &#32; <a href="https://www.reddit.com/user/SpecialistCamera5601"> /u/SpecialistCamera5601 </a> <a href="https://www.reddit.com/r/FastAPI/comments/1r33cxm/i_added_a_dark_light_mode_toggle_to_fastapi/">[link]</a> &#32; <a href="https://www.reddit.com/r/FastAPI/comments/1r33cxm/i_added_a_dark_light_mode_toggle_to_fastapi/">[comments]</a>

Hey folks 
 I’ve been using FastAPI for ~5 years now and I probably spend an unhealthy amount of time staring at Swagger every single day.
 I actually like the default theme. It’s clean and familiar. But after a few hours… especially at night… it starts feeling like I’m getting flashbanged by my own API docs :D 
 So I thought, instead of replacing Swagger with a completely different theme, why not just add a proper Dark / Light toggle?
 I’ve seen dark-mode versions before ( u/BlueFriends and u/Fit_Tell_8592 did some cool stuff), but I wanted something that keeps the original Swagger vibe and just enhances it a bit.
 My goal was to:
 • Keep the original Swagger feel
 • Add a smooth Dark / Light toggle
 • Not break FastAPI defaults
 • Implement smth that is easy to plug into existing projects(actually 1 line)
 You can enable it with literally one line of code. Your eyesight is worth more than 1 line of code :D 
 So I built this:
 Repo:
 https://github.com/akutayural/fastapi-swagger-ui-theme
 Pypi:
 https://pypi.org/project/fastapi-swagger-ui-theme/
 Contributions, ideas, improvements, or even nitpicks are very welcome.
    submitted by    /u/SpecialistCamera5601  
 [link]   [comments]

I added a Dark / Light mode toggle to FastAPI Swagger UI

<div class="md">Hi All, I spent the weekend tweaking a strict .cursorrules file for FastAPI + Pydantic v2 projects because I got tired of fixing: <ul> <li><code>class Config:</code> instead of <code>model_config = ConfigDict(...)</code></li> <li>Sync DB calls inside async routes</li> <li>Missing type hints</li> </ul> It forces the AI to use: <ul> <li>Python 3.11+ syntax (<code>|</code> types)</li> <li>Async SQLAlchemy 2.0 patterns</li> <li>Google-style docstrings</li> </ul> If anyone wants the config file, let me know in the comments and I&#39;ll DM it / post the link (it&#39;s free).&quot; </div> &#32; submitted by &#32; <a href="https://www.reddit.com/user/zupiterss"> /u/zupiterss </a> <a href="https://www.reddit.com/r/FastAPI/comments/1r40lcf/finally_got_cursor_ai_to_stop_writing_deprecated/">[link]</a> &#32; <a href="https://www.reddit.com/r/FastAPI/comments/1r40lcf/finally_got_cursor_ai_to_stop_writing_deprecated/">[comments]</a>

Hi All,
 I spent the weekend tweaking a strict 
 .cursorrules file for FastAPI + Pydantic v2 projects because I got tired of fixing:
  
class Config: instead of model_config = ConfigDict(...)
 Sync DB calls inside async routes
 Missing type hints
  
It forces the AI to use:
  
Python 3.11+ syntax (| types)
 Async SQLAlchemy 2.0 patterns
 Google-style docstrings
  
If anyone wants the config file, let me know in the comments and I'll DM it / post the link (it's free)."
    submitted by    /u/zupiterss  
 [link]   [comments]

Finally got Cursor AI to stop writing deprecated Pydantic v1 code (My strict .cursorrules config)

<div class="md">Are you usually satisfied with the built-in dependency injection or are you using an additional DI-Library. If using an additional one, which is the best one? </div> &#32; submitted by &#32; <a href="https://www.reddit.com/user/CartoonistWhole3172"> /u/CartoonistWhole3172 </a> <a href="https://www.reddit.com/r/FastAPI/comments/1r8iqzi/dependency_injection_in_fastapi/">[link]</a> &#32; <a href="https://www.reddit.com/r/FastAPI/comments/1r8iqzi/dependency_injection_in_fastapi/">[comments]</a>

Are you usually satisfied with the built-in dependency injection or are you using an additional DI-Library. If using an additional one, which is the best one?
    submitted by    /u/CartoonistWhole3172  
 [link]   [comments]

Dependency Injection in FastAPI

<table> <tr><td> <a href="https://www.reddit.com/r/FastAPI/comments/1r3su01/built_a_lightweight_actuatorstyle_extension_for/"> <img src="https://external-preview.redd.it/FjOFbv64aVKnr7NEMFedYi2VMtR2xC9T9vZs0b7ix3U.png?width=640&amp;crop=smart&amp;auto=webp&amp;s=c7cffa487cfa1248b78190fd39641fe191cffa77" alt="Built a lightweight Actuator-style extension for FastAPI – looking for feedback" title="Built a lightweight Actuator-style extension for FastAPI – looking for feedback" /> </a> </td><td> <div class="md">Hi everyone, While building APIs with FastAPI, one thing I kept missing from my earlier experience with Spring Boot was Actuator. I liked being able to quickly check: is the app alive is it ready to serve traffic what version is deployed runtime metrics which endpoints exist So I started building a small, lightweight actuator-style extension for FastAPI. Current features /actuator/health/live /actuator/health/ready /actuator/info /actuator/metrics /actuator/platform /actuator/mappings It also supports pluggable readiness checks, so applications can register something like a DB check and readiness will depend on it. The goal is to keep it simple, fast, and easy to plug into any service without bringing heavy dependencies. I haven’t published it to PyPI yet — it’s currently just on GitHub. I would really appreciate feedback on: API design missing essentials naming things that would make this useful in real projects If you’ve worked on production systems, I’d love to know what you typically expect from an actuator endpoint. Thanks 🙏 </div> &#32; submitted by &#32; <a href="https://www.reddit.com/user/DSpy01"> /u/DSpy01 </a> <a href="https://github.com/Abhijit0303/fastapi-actuator">[link]</a> &#32; <a href="https://www.reddit.com/r/FastAPI/comments/1r3su01/built_a_lightweight_actuatorstyle_extension_for/">[comments]</a> </td></tr></table>

Hi everyone, While building APIs with FastAPI, one thing I kept missing from my earlier experience with Spring Boot was Actuator.
 I liked being able to quickly check: is the app alive is it ready to serve traffic what version is deployed runtime metrics which endpoints exist
 So I started building a small, lightweight actuator-style extension for FastAPI.
 Current features /actuator/health/live /actuator/health/ready /actuator/info /actuator/metrics /actuator/platform /actuator/mappings
 It also supports pluggable readiness checks, so applications can register something like a DB check and readiness will depend on it. The goal is to keep it simple, fast, and easy to plug into any service without bringing heavy dependencies. I haven’t published it to PyPI yet — it’s currently just on GitHub.
 I would really appreciate feedback on: API design missing essentials naming things that would make this useful in real projects
 If you’ve worked on production systems, I’d love to know what you typically expect from an actuator endpoint. Thanks 🙏
    submitted by    /u/DSpy01  
 [link]   [comments]

Built a lightweight Actuator-style extension for FastAPI – looking for feedback

<div class="md">If you&#39;re diving into the new Microsoft Foundry (2026), the initial setup can be a bit of a maze. I see a lot of people getting stuck just trying to figure out how Resource Groups link to Projects, and why they can&#39;t see their models in the code. I’ve put together a step-by-step guide that focuses on the Connectivity Flow and getting that first successful Chat response. What I covered: <ul> <li>The Blueprint: A simple breakdown of the Resource Group &gt; AI Hub &gt; AI Project hierarchy.</li> <li>The Setup: How to deploy a model (like GPT-4o-mini) and test it directly in the Foundry portal.</li> <li>The Handshake: Connecting your Python script using Client ID &amp; Client Secret so you don&#39;t have to deal with manual logins.</li> <li>The Result: Testing the &quot;Responses API&quot; to get your first successful chat output.</li> </ul> This is the &quot;Day 1&quot; guide for anyone moving their AI projects into a professional Azure environment. Full Walkthrough: <a href="https://youtu.be/KE8h5kOuOrI">https://youtu.be/KE8h5kOuOrI</a> </div> &#32; submitted by &#32; <a href="https://www.reddit.com/user/Worldly_Mammoth_7868"> /u/Worldly_Mammoth_7868 </a> <a href="https://www.reddit.com/r/FastAPI/comments/1r7ed9m/from_zero_to_ai_chat_a_clean_guide_to_microsoft/">[link]</a> &#32; <a href="https://www.reddit.com/r/FastAPI/comments/1r7ed9m/from_zero_to_ai_chat_a_clean_guide_to_microsoft/">[comments]</a>

If you're diving into the new Microsoft Foundry (2026), the initial setup can be a bit of a maze. I see a lot of people getting stuck just trying to figure out how Resource Groups link to Projects, and why they can't see their models in the code.
 I’ve put together a step-by-step guide that focuses on the Connectivity Flow and getting that first successful Chat response.
 What I covered:
  
The Blueprint: A simple breakdown of the Resource Group > AI Hub > AI Project hierarchy.
 The Setup: How to deploy a model (like GPT-4o-mini) and test it directly in the Foundry portal.
 The Handshake: Connecting your Python script using Client ID & Client Secret so you don't have to deal with manual logins.
 The Result: Testing the "Responses API" to get your first successful chat output.
  
This is the "Day 1" guide for anyone moving their AI projects into a professional Azure environment.
 Full Walkthrough: https://youtu.be/KE8h5kOuOrI
    submitted by    /u/Worldly_Mammoth_7868  
 [link]   [comments]

From Zero to AI Chat: A Clean Guide to Microsoft Foundry Setup (Hierarchy & Connectivity)

<table> <tr><td> <a href="https://www.reddit.com/r/FastAPI/comments/1r4iiw4/persistent_hybrid_rag_adding_postgresql_faiss/"> <img src="https://external-preview.redd.it/feNel6zrGZ_gSL2Fznnyf7w6qoIvNNIuuAsChu02sH8.jpeg?width=320&amp;crop=smart&amp;auto=webp&amp;s=6fe741ab81376cc7c6a7a1a36f06b201926a389a" alt="Persistent Hybrid RAG: Adding PostgreSQL &amp; FAISS Storage (Part 2)" title="Persistent Hybrid RAG: Adding PostgreSQL &amp; FAISS Storage (Part 2)" /> </a> </td><td> &#32; submitted by &#32; <a href="https://www.reddit.com/user/Worldly_Mammoth_7868"> /u/Worldly_Mammoth_7868 </a> <a href="https://youtube.com/watch?v=VJW_vCFeoBc&amp;si=QfJjubwL15ju2gm2">[link]</a> &#32; <a href="https://www.reddit.com/r/FastAPI/comments/1r4iiw4/persistent_hybrid_rag_adding_postgresql_faiss/">[comments]</a> </td></tr></table>

submitted by    /u/Worldly_Mammoth_7868  
 [link]   [comments]

Persistent Hybrid RAG: Adding PostgreSQL & FAISS Storage (Part 2)

<div class="md">I was searching for a SaaS template for FastAPI and there have been a few posted here, and I am looking at each of them, but my search outside of Reddit led me to <a href="https://www.fast-saas.com/">https://www.fast-saas.com/</a>. - has anyone here used it? If so, any good or bad feedback would be appreciated. I emailed them earlier today but I have not gotten a response. Could be that it&#39;s Friday and maybe they are already on their weekend. - does anyone have a production site built with fast-saas that they would be willing to post a link to so I can evaluate it in the wild? Thanks in advance </div> &#32; submitted by &#32; <a href="https://www.reddit.com/user/Natural-Ad-9678"> /u/Natural-Ad-9678 </a> <a href="https://www.reddit.com/r/FastAPI/comments/1r42j1c/does_anyone_have_realworld_experience_with/">[link]</a> &#32; <a href="https://www.reddit.com/r/FastAPI/comments/1r42j1c/does_anyone_have_realworld_experience_with/">[comments]</a>

I was searching for a SaaS template for FastAPI and there have been a few posted here, and I am looking at each of them, but my search outside of Reddit led me to https://www.fast-saas.com/.
 - has anyone here used it? If so, any good or bad feedback would be appreciated. I emailed them earlier today but I have not gotten a response. Could be that it's Friday and maybe they are already on their weekend.
 - does anyone have a production site built with fast-saas that they would be willing to post a link to so I can evaluate it in the wild?
 Thanks in advance
    submitted by    /u/Natural-Ad-9678  
 [link]   [comments]

Does anyone have real-world experience with fast-saas

<div class="md">Olá, pessoal. Durante a implementação manual de autenticação baseada em JWT, desenvolvendo toda a lógica diretamente no código, identifiquei a biblioteca <a href="https://authx.yezz.me">AuthX</a> como uma possível alternativa para simplificar esse processo. Ela aparenta abstrair boa parte da complexidade envolvida na geração, validação e gerenciamento de tokens, o que pode aumentar a produtividade e reduzir riscos de implementação incorreta. No entanto, gostaria de compreender melhor qual biblioteca ela utiliza como base para manipulação de JWT — se é <a href="https://github.com/mpdavis/python-jose">python-jose</a> ou <a href="https://pyjwt.readthedocs.io/en/stable/">PyJWT</a> — considerando que o projeto python-jose aparenta estar com manutenção reduzida há algum tempo. Diante disso, qual abordagem vocês recomendam: continuar com uma implementação mais controlada utilizando diretamente uma biblioteca consolidada, ou adotar uma camada de abstração como o AuthX? </div> &#32; submitted by &#32; <a href="https://www.reddit.com/user/llMakarov"> /u/llMakarov </a> <a href="https://www.reddit.com/r/FastAPI/comments/1r7fcqv/avaliação_da_biblioteca_authx_para_autenticação/">[link]</a> &#32; <a href="https://www.reddit.com/r/FastAPI/comments/1r7fcqv/avaliação_da_biblioteca_authx_para_autenticação/">[comments]</a>

Olá, pessoal.
 Durante a implementação manual de autenticação baseada em JWT, desenvolvendo toda a lógica diretamente no código, identifiquei a biblioteca AuthX como uma possível alternativa para simplificar esse processo.
 Ela aparenta abstrair boa parte da complexidade envolvida na geração, validação e gerenciamento de tokens, o que pode aumentar a produtividade e reduzir riscos de implementação incorreta. No entanto, gostaria de compreender melhor qual biblioteca ela utiliza como base para manipulação de JWT — se é python-jose ou PyJWT — considerando que o projeto python-jose aparenta estar com manutenção reduzida há algum tempo.
 Diante disso, qual abordagem vocês recomendam: continuar com uma implementação mais controlada utilizando diretamente uma biblioteca consolidada, ou adotar uma camada de abstração como o AuthX?
    submitted by    /u/llMakarov  
 [link]   [comments]

Avaliação da biblioteca AuthX para autenticação JWT em Python

<table> <tr><td> <a href="https://www.reddit.com/r/FastAPI/comments/1r6zowj/microsoft_foundry_2026_ultimate_guide_to_the_new/"> <img src="https://external-preview.redd.it/DE1ZoTnWwM0EHYvDKr3xUVMwiZ9Jmkq3BmnnNSZXTtc.jpeg?width=320&amp;crop=smart&amp;auto=webp&amp;s=f8e52b4c88bb734c3f53ae9d70fe0a1e921f5046" alt="Microsoft Foundry 2026: Ultimate Guide to the New Agent Service in Hindi..." title="Microsoft Foundry 2026: Ultimate Guide to the New Agent Service in Hindi..." /> </a> </td><td> &#32; submitted by &#32; <a href="https://www.reddit.com/user/Worldly_Mammoth_7868"> /u/Worldly_Mammoth_7868 </a> <a href="https://youtube.com/watch?v=xudPOxSnIRI&amp;si=eh8R2bD9m5Dy2CgF">[link]</a> &#32; <a href="https://www.reddit.com/r/FastAPI/comments/1r6zowj/microsoft_foundry_2026_ultimate_guide_to_the_new/">[comments]</a> </td></tr></table>

Microsoft Foundry 2026: Ultimate Guide to the New Agent Service in Hindi...

<div class="md">Paying good if someone knows how to make webhook urls so it looks like something is intergreted to a site so it looks real If first goes good there’s good opportunityti make money if you got the skills </div> &#32; submitted by &#32; <a href="https://www.reddit.com/user/Best_Improvement2042"> /u/Best_Improvement2042 </a> <a href="https://www.reddit.com/r/FastAPI/comments/1r77y91/webhook_url/">[link]</a> &#32; <a href="https://www.reddit.com/r/FastAPI/comments/1r77y91/webhook_url/">[comments]</a>

Paying good if someone knows how to make webhook urls so it looks like something is intergreted to a site so it looks real 
 If first goes good there’s good opportunityti make money if you got the skills 
    submitted by    /u/Best_Improvement2042  
 [link]   [comments]

Webhook url

<div class="md">Hey all. I&#39;ve been building <a href="https://github.com/definableai/definable.ai">Definable</a> - a Python framework for AI agents. I got frustrated with existing options being either too bloated or too toy-like, so I built what I actually wanted to use in production. Here&#39;s what it looks like: ```python from definable.agents import Agent from definable.models.openai import OpenAIChat from definable.tools.decorator import tool from definable.interfaces.telegram import TelegramInterface, TelegramConfig @tool def search_docs(query: str) -&gt; str: &quot;&quot;&quot;Search internal documentation.&quot;&quot;&quot; return db.search(query) agent = Agent( model=OpenAIChat(id=&quot;gpt-5.2&quot;), tools=[search_docs], instructions=&quot;You are a docs assistant.&quot;, ) <h1>Use it directly</h1> response = agent.run(&quot;Steps for configuring auth?&quot;) <h1>Or deploy it — HTTP API + Telegram bot in one line</h1> agent.add_interface(TelegramInterface( config=TelegramConfig(bot_token=os.environ[&quot;TELEGRAM_BOT_TOKEN&quot;]), )) agent.serve(port=8000) ``` <h2>What My Project Does</h2> Python framework for AI agents with built-in cognitive memory, run replay, file parsing (14+ formats), streaming, HITL workflows, and one-line deployment to HTTP + Telegram/Discord/Signal. Async-first, fully typed, non-fatal error handling by design. <h2>Target Audience</h2> Developers building production AI agents who&#39;ve outgrown raw API calls but don&#39;t want LangChain-level complexity. v0.2.6, running in production. <h2>Comparison</h2> <ul> <li>vs LangChain - No chain/runnable abstraction. Normal Python. Memory is multi-tier with distillation, not just a chat buffer. Deployment is built-in, not a separate project.</li> <li>vs CrewAI/AutoGen - Those focus on multi-agent orchestration. Definable focuses on making a single agent production-ready: memory, replay, file parsing, streaming, HITL.</li> <li>vs raw OpenAI SDK - Adds tool management, RAG, cognitive memory, tracing, middleware, deployment, and file parsing out of the box.</li> </ul> <code>pip install definable</code> Would love feedback. Still early but it&#39;s been running in production for a few weeks now. <a href="https://github.com/definableai/definable.ai">GitHub</a> </div> &#32; submitted by &#32; <a href="https://www.reddit.com/user/anandesh-sharma"> /u/anandesh-sharma </a> <a href="https://www.reddit.com/r/FastAPI/comments/1r4k4qa/i_built_an_python_ai_agent_framework_that_doesnt/">[link]</a> &#32; <a href="https://www.reddit.com/r/FastAPI/comments/1r4k4qa/i_built_an_python_ai_agent_framework_that_doesnt/">[comments]</a>

Hey all. I've been building Definable - a Python framework for AI agents. I got frustrated with existing options being either too bloated or too toy-like, so I built what I actually wanted to use in production.
 Here's what it looks like:
 ```python from definable.agents import Agent from definable.models.openai import OpenAIChat from definable.tools.decorator import tool from definable.interfaces.telegram import TelegramInterface, TelegramConfig
 @tool def search_docs(query: str) -> str: """Search internal documentation.""" return db.search(query)
 agent = Agent( model=OpenAIChat(id="gpt-5.2"), tools=[search_docs], instructions="You are a docs assistant.", )
 Use it directly
 response = agent.run("Steps for configuring auth?")
 Or deploy it — HTTP API + Telegram bot in one line
 agent.add_interface(TelegramInterface( config=TelegramConfig(bot_token=os.environ["TELEGRAM_BOT_TOKEN"]), )) agent.serve(port=8000) ```
 What My Project Does
 Python framework for AI agents with built-in cognitive memory, run replay, file parsing (14+ formats), streaming, HITL workflows, and one-line deployment to HTTP + Telegram/Discord/Signal. Async-first, fully typed, non-fatal error handling by design.
 Target Audience
 Developers building production AI agents who've outgrown raw API calls but don't want LangChain-level complexity. v0.2.6, running in production.
 Comparison
  
vs LangChain - No chain/runnable abstraction. Normal Python. Memory is multi-tier with distillation, not just a chat buffer. Deployment is built-in, not a separate project.
 vs CrewAI/AutoGen - Those focus on multi-agent orchestration. Definable focuses on making a single agent production-ready: memory, replay, file parsing, streaming, HITL.
 vs raw OpenAI SDK - Adds tool management, RAG, cognitive memory, tracing, middleware, deployment, and file parsing out of the box.
  
pip install definable
 Would love feedback. Still early but it's been running in production for a few weeks now.
 GitHub
    submitted by    /u/anandesh-sharma  
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I built an python AI agent framework that doesn't make me want to mass-delete my venv

<div class="md">I just finished Django for APIs, and started with Django for Beginners. These books are clearing concepts in ways no other Paid Course or YouTube Playlist has ever done, for me. I do accept most parts may feel surface level (Django for APIs), but still it was a solid introduction nonetheless. What other books worked for you? What books would you recommend I get printed? Also just a personal recommendation: <blockquote> Experiment what learning style suits you best. Videos, Books etc. Go with Certified Quality Resources first. </blockquote> </div> &#32; submitted by &#32; <a href="https://www.reddit.com/user/jadd_logs"> /u/jadd_logs </a> <a href="https://www.reddit.com/r/djangolearning/comments/1r6aml2/need_book_recommendation_for_learning_python/">[link]</a> &#32; <a href="https://www.reddit.com/r/djangolearning/comments/1r6aml2/need_book_recommendation_for_learning_python/">[comments]</a>

I just finished Django for APIs, and started with Django for Beginners. These books are clearing concepts in ways no other Paid Course or YouTube Playlist has ever done, for me. I do accept most parts may feel surface level (Django for APIs), but still it was a solid introduction nonetheless. 
 What other books worked for you? What books would you recommend I get printed? 
 Also just a personal recommendation: 
  
Experiment what learning style suits you best. Videos, Books etc. Go with Certified Quality Resources first. 
  
   submitted by    /u/jadd_logs  
 [link]   [comments]

Need book recommendation for learning Python, Django & DRF.

&#32; submitted by &#32; <a href="https://www.reddit.com/user/jadd_logs"> /u/jadd_logs </a> <a href="/r/learnprogramming/comments/1r4elw1/need_help_with_standardizingsimplifying_logic/">[link]</a> &#32; <a href="https://www.reddit.com/r/djangolearning/comments/1r4em6u/need_help_with_standardizingsimplifying_logic/">[comments]</a>

submitted by    /u/jadd_logs  
 [link]   [comments]

Need Help with Standardizing/Simplifying Logic Placement in DRF Projects.

&#32; submitted by &#32; <a href="https://www.reddit.com/user/heyMan__07"> /u/heyMan__07 </a> <a href="https://www.reddit.com/r/djangolearning/comments/1r69jek/can_anyone_provide_me_a_good_resource_to_learn/">[link]</a> &#32; <a href="https://www.reddit.com/r/djangolearning/comments/1r69jek/can_anyone_provide_me_a_good_resource_to_learn/">[comments]</a>

submitted by    /u/heyMan__07  
 [link]   [comments]

Can anyone provide me a good resource to learn django?

&#32; submitted by &#32; <a href="https://www.reddit.com/user/jadd_logs"> /u/jadd_logs </a> <a href="/r/learnprogramming/comments/1r57fuc/had_an_epiphany_what_does_it_take_to_reach_50lpa/">[link]</a> &#32; <a href="https://www.reddit.com/r/djangolearning/comments/1r57glg/had_an_epiphany_what_does_it_take_to_reach_50lpa/">[comments]</a>

Had an epiphany && What does it take to reach 50LPA?

<div class="md">I have already ready created ecommerce app so don&#39;t suggest it. </div> &#32; submitted by &#32; <a href="https://www.reddit.com/user/ganeshchavan_gc"> /u/ganeshchavan_gc </a> <a href="https://www.reddit.com/r/djangolearning/comments/1r7e1zr/i_need_idea_for_a_project_to_make_my_portfolio/">[link]</a> &#32; <a href="https://www.reddit.com/r/djangolearning/comments/1r7e1zr/i_need_idea_for_a_project_to_make_my_portfolio/">[comments]</a>

I have already ready created ecommerce app so don't suggest it.
    submitted by    /u/ganeshchavan_gc  
 [link]   [comments]

I need Idea for a project to make my portfolio strong

<div class="md">Hey everyone 👋 I just published my first PyPI package 🎉<a href="https://pypi.org/project/sqlite-opus/">sqlite-opus</a> sqlite-opus is a simple tool to work with SQLite in a web UI. It’s built for simplicity and easy integration — just install it in your Flask project and start querying your database from the browser. Git repo here: <a href="https://github.com/hungle00/sqlite-opus">https://github.com/hungle00/sqlite-opus</a> Current features: <ul> <li>Connect to DB and view tables, columns, indexes, etc.</li> <li>Execute SQL queries</li> <li>Export query results to CSV</li> </ul> More features coming soon. Hope you find it useful! 🚀 </div> &#32; submitted by &#32; <a href="https://www.reddit.com/user/lmh-cadenza-093"> /u/lmh-cadenza-093 </a> <a href="https://www.reddit.com/r/flask/comments/1r55ut9/sqliteopus_the_web_ui_for_sqlite_query_on_flask/">[link]</a> &#32; <a href="https://www.reddit.com/r/flask/comments/1r55ut9/sqliteopus_the_web_ui_for_sqlite_query_on_flask/">[comments]</a>

Hey everyone 👋
 I just published my first PyPI package 🎉sqlite-opus
 sqlite-opus is a simple tool to work with SQLite in a web UI. It’s built for simplicity and easy integration — just install it in your Flask project and start querying your database from the browser.
 Git repo here: https://github.com/hungle00/sqlite-opus
 Current features:
  
Connect to DB and view tables, columns, indexes, etc.
 Execute SQL queries
 Export query results to CSV
  
More features coming soon. Hope you find it useful! 🚀
    submitted by    /u/lmh-cadenza-093  
 [link]   [comments]

sqlite-opus - The web UI for SQLite query on Flask

<table> <tr><td> <a href="https://www.reddit.com/r/flask/comments/1r6b92x/semantic_search_app_in_flask_using_qdrant/"> <img src="https://external-preview.redd.it/pM4Ir9fuDMttG2-Aea2V28aackogc2JR9nkKehENQxw.jpeg?width=320&amp;crop=smart&amp;auto=webp&amp;s=f685af86b99d3b023d5ab0b1a2aa6d5d2b148c7e" alt="Semantic Search App in Flask using Qdrant" title="Semantic Search App in Flask using Qdrant" /> </a> </td><td> &#32; submitted by &#32; <a href="https://www.reddit.com/user/Remarkable_Nothing65"> /u/Remarkable_Nothing65 </a> <a href="https://youtu.be/aVWDAwQzcSA">[link]</a> &#32; <a href="https://www.reddit.com/r/flask/comments/1r6b92x/semantic_search_app_in_flask_using_qdrant/">[comments]</a> </td></tr></table>

submitted by    /u/Remarkable_Nothing65  
 [link]   [comments]

Semantic Search App in Flask using Qdrant

<div class="md">Hi everyone, in my project I use flask as my rest api, with a layered architecture with controller, service, and repository. Now, since the repository doesn&#39;t perform commits, but adds, removes or modifies entities through the sqlalchemy session, I want to understand how to handle the commit. Specifically, I would like to create something like spring boot&#39;s Transactional decorator, where with the default settings (propagation required) if decorated service A calls decorated service B, service B uses service A&#39;s session, only committing at the end of all operations. Has anyone done something like this before? Or is there a better way to handle these situations? Thanks in advance. Example of base repository (it is extended by other repositories): <code>class BaseRepository(Generic[T]):</code> <code>model: type[T]</code> <code>def __init__(self, db: SQLAlchemy) -&gt; None:</code> <code>self.db = db</code> <code>def get_all(self) -&gt; Sequence[T]:</code> <code>stmt = select(self.model)</code> <code>res = self.db.session.execute(stmt).scalars().all()</code> <code>return res</code> <code>def save(self, obj: T) -&gt; T:</code> <code>if object_session(obj) is None: # If is new the session associated with the object will be None</code> <code>self.db.session.add(obj)</code> <code>self.db.session.flush()</code> <code>return obj</code> <code>def get_by_id(self, id: int) -&gt; T | None:</code> <code>stmt = select(self.model).where(self.model.id == id)</code> <code>obj = self.db.session.execute(stmt).scalar_one_or_none()</code> <code>return obj</code> <code>def delete_by_id(self, id: int) -&gt; T | None:</code> <code>stmt = select(self.model).where(self.model.id == id)</code> <code>obj = self.db.session.execute(stmt).scalar_one_or_none()</code> <code>if obj:</code> <code>self.db.session.delete(obj)</code> <code>return obj</code> </div> &#32; submitted by &#32; <a href="https://www.reddit.com/user/Substantial_Waltz951"> /u/Substantial_Waltz951 </a> <a href="https://www.reddit.com/r/flask/comments/1r352j6/attempt_to_create_a_transactional_spring_boot/">[link]</a> &#32; <a href="https://www.reddit.com/r/flask/comments/1r352j6/attempt_to_create_a_transactional_spring_boot/">[comments]</a>

Hi everyone, in my project I use flask as my rest api, with a layered architecture with controller, service, and repository. Now, since the repository doesn't perform commits, but adds, removes or modifies entities through the sqlalchemy session, I want to understand how to handle the commit. Specifically, I would like to create something like spring boot's Transactional decorator, where with the default settings (propagation required) if decorated service A calls decorated service B, service B uses service A's session, only committing at the end of all operations. Has anyone done something like this before? Or is there a better way to handle these situations? Thanks in advance.
 Example of base repository (it is extended by other repositories):
 class BaseRepository(Generic[T]):
 model: type[T]
 def __init__(self, db: SQLAlchemy) -> None:
 self.db = db
 def get_all(self) -> Sequence[T]:
 stmt = select(self.model)
 res = self.db.session.execute(stmt).scalars().all()
 return res
 def save(self, obj: T) -> T:
 if object_session(obj) is None: # If is new the session associated with the object will be None
 self.db.session.add(obj)
 self.db.session.flush()
 return obj
 def get_by_id(self, id: int) -> T | None:
 stmt = select(self.model).where(self.model.id == id)
 obj = self.db.session.execute(stmt).scalar_one_or_none()
 return obj
 def delete_by_id(self, id: int) -> T | None:
 stmt = select(self.model).where(self.model.id == id)
 obj = self.db.session.execute(stmt).scalar_one_or_none()
 if obj:
 self.db.session.delete(obj)
 return obj
    submitted by    /u/Substantial_Waltz951  
 [link]   [comments]

Attempt to create a @Transactional spring boot like decorator in python

<div class="md">I’m focusing on React (frontend) and Django + DRF (backend), with PostgreSQL and AWS for deployment. I’m also planning to go deeper into backend fundamentals — things like Docker, CI/CD basics, caching (Redis), system design, and improving API design (auth, permissions, performance, etc.). I keep seeing a lot more noise around MERN/Node stacks lately, so I’m wondering — is this stack still competitive in the current job market? Are companies actively hiring for React + Django developers? And how does it look long-term compared to Node-based stacks? Would love honest opinions from people already working in industry. </div> &#32; submitted by &#32; <a href="https://www.reddit.com/user/alokbind"> /u/alokbind </a> <a href="https://www.reddit.com/r/django/comments/1r4nkut/is_react_djangodrf_still_a_solid_stack_in_ai_era/">[link]</a> &#32; <a href="https://www.reddit.com/r/django/comments/1r4nkut/is_react_djangodrf_still_a_solid_stack_in_ai_era/">[comments]</a>

I’m focusing on React (frontend) and Django + DRF (backend), with PostgreSQL and AWS for deployment.
 I’m also planning to go deeper into backend fundamentals — things like Docker, CI/CD basics, caching (Redis), system design, and improving API design (auth, permissions, performance, etc.).
 I keep seeing a lot more noise around MERN/Node stacks lately, so I’m wondering — is this stack still competitive in the current job market?
 Are companies actively hiring for React + Django developers? And how does it look long-term compared to Node-based stacks?
 Would love honest opinions from people already working in industry.
    submitted by    /u/alokbind  
 [link]   [comments]

Is React + Django/DRF still a solid stack in AI era of 2026?

<div class="md">Hey everyone 👋 I’ve been working on an open-source project called Cratos, a self-hosted task scheduling system built with Django. You register a URL, define a schedule, and Cratos handles: <ul> <li>Scheduled HTTP calls</li> <li>Retries with backoff</li> <li>Execution history &amp; logs</li> <li>Real-time updates</li> <li>Web dashboard </li> </ul> I built it because I kept needing reliable scheduled webhooks across projects but didn’t want to depend on SaaS cron services or rebuild scheduling logic every time. It’s split into three repos: <ul> <li>Backend (Django)</li> <li>Web dashboard</li> <li>Python SDK</li> </ul> I’d love feedback from Django devs: <ul> <li>Architecture-wise, what would you change?</li> <li>Would you separate the scheduler into a dedicated worker process?</li> <li>Anything you’d consider essential before using it in production?</li> </ul> GitHub: <ul> <li><a href="https://github.com/Ghiles1010/Cratos">https://github.com/Ghiles1010/Cratos</a></li> <li><a href="https://github.com/Ghiles1010/Cratos-UI">https://github.com/Ghiles1010/Cratos-UI</a></li> <li><a href="https://github.com/Ghiles1010/Cratos-SDK">https://github.com/Ghiles1010/Cratos-SDK</a></li> </ul> Appreciate any thoughts or critique 🙏 </div> &#32; submitted by &#32; <a href="https://www.reddit.com/user/One-Meeting-921"> /u/One-Meeting-921 </a> <a href="https://www.reddit.com/gallery/1r85z4d">[link]</a> &#32; <a href="https://www.reddit.com/r/django/comments/1r85z4d/built_a_selfhosted_task_scheduler_in_django/">[comments]</a>

Hey everyone 👋
 I’ve been working on an open-source project called Cratos, a self-hosted task scheduling system built with Django.
 You register a URL, define a schedule, and Cratos handles:
  
Scheduled HTTP calls
 Retries with backoff
 Execution history & logs
 Real-time updates
 Web dashboard 
  
I built it because I kept needing reliable scheduled webhooks across projects but didn’t want to depend on SaaS cron services or rebuild scheduling logic every time.
 It’s split into three repos:
  
Backend (Django)
 Web dashboard
 Python SDK
  
I’d love feedback from Django devs:
  
Architecture-wise, what would you change?
 Would you separate the scheduler into a dedicated worker process?
 Anything you’d consider essential before using it in production?
  
GitHub:
  
https://github.com/Ghiles1010/Cratos
 https://github.com/Ghiles1010/Cratos-UI
 https://github.com/Ghiles1010/Cratos-SDK
  
Appreciate any thoughts or critique 🙏
    submitted by    /u/One-Meeting-921  
 [link]   [comments]

Built a self-hosted task scheduler in Django (Cratos) - feedback welcome

<div class="md">Hey team, I’ve just released dj-urls-panel It’s another panel in my series of django admin based tooling (dj-celery-panel, dj-redis-panel, etc) This project is aimed at creating better visibility of your project’s urlpatterns; URLs can grow unwieldy for large projects and it can be hard to understand exactly what is being surfaced by your project (whether by you or a third party app). Additionally, this project also includes a testing interface that can help replace other similar dependencies (Swagger UI) if they are being used solely for testing. Hope some of you can find some use out of this. Repo: <a href="https://github.com/yassi/dj-urls-panel">https://github.com/yassi/dj-urls-panel</a> pypi: <a href="https://pypi.org/project/dj-urls-panel/">https://pypi.org/project/dj-urls-panel/</a> docs: <a href="https://yassi.github.io/dj-urls-panel/">https://yassi.github.io/dj-urls-panel/</a> </div> &#32; submitted by &#32; <a href="https://www.reddit.com/user/yassi_dev"> /u/yassi_dev </a> <a href="https://www.reddit.com/r/django/comments/1r30x1j/djurlspanel_visualize_and_test_django_url_routing/">[link]</a> &#32; <a href="https://www.reddit.com/r/django/comments/1r30x1j/djurlspanel_visualize_and_test_django_url_routing/">[comments]</a>

Hey team,
 I’ve just released dj-urls-panel
 It’s another panel in my series of django admin based tooling (dj-celery-panel, dj-redis-panel, etc)
 This project is aimed at creating better visibility of your project’s urlpatterns; URLs can grow unwieldy for large projects and it can be hard to understand exactly what is being surfaced by your project (whether by you or a third party app).
 Additionally, this project also includes a testing interface that can help replace other similar dependencies (Swagger UI) if they are being used solely for testing.
 Hope some of you can find some use out of this.
 Repo: https://github.com/yassi/dj-urls-panel
 pypi: https://pypi.org/project/dj-urls-panel/
 docs: https://yassi.github.io/dj-urls-panel/
    submitted by    /u/yassi_dev  
 [link]   [comments]

dj-urls-panel: Visualize and test Django URL routing inside the Django Admin

<div class="md">Hi everyone, after 11 years of developing Django apps and finding myself copy-pasting the same devops code over and over, I finally took the time to open source it. <a href="https://github.com/mherrmann/djevops">Djevops </a>is a command-line tool for deploying Django apps to Linux VPSs. Unlike other solutions, it does not use Docker. This makes it faster and easier to work with. Take your Django app, add a $5 per month Linux VPS and you&#39;re good to go. Feedback would be appreciated :) Here&#39;s the full link again: <a href="https://github.com/mherrmann/djevops">https://github.com/mherrmann/djevops</a> </div> &#32; submitted by &#32; <a href="https://www.reddit.com/user/mherrmann"> /u/mherrmann </a> <a href="https://www.reddit.com/r/django/comments/1r5l8p5/djevops_host_django_on_bare_metal/">[link]</a> &#32; <a href="https://www.reddit.com/r/django/comments/1r5l8p5/djevops_host_django_on_bare_metal/">[comments]</a>

Hi everyone,
 after 11 years of developing Django apps and finding myself copy-pasting the same devops code over and over, I finally took the time to open source it. Djevops is a command-line tool for deploying Django apps to Linux VPSs. Unlike other solutions, it does not use Docker. This makes it faster and easier to work with. Take your Django app, add a $5 per month Linux VPS and you're good to go.
 Feedback would be appreciated :) Here's the full link again: https://github.com/mherrmann/djevops
    submitted by    /u/mherrmann  
 [link]   [comments]

Djevops: Host Django on bare metal

<div class="md">Hi all, I&#39;m a solo dev that just finished a Django based project. Being a solo dev, I&#39;ve noticed that it&#39;s hard to get advice from other experienced devs on my projects and codebase in general. I&#39;m just starting out with my software career and would really appreciate getting some advice from more experienced devs. Things like preventing bad habits, anti-patterns and other stuff. Even the small nitpicks are fine with me. If you find yourself with time to spare and nothing else to do, please feel free to rip into my codebase here. <a href="https://github.com/JBK2116/collaboard-inc">Codebase</a> and <a href="http://collaboard.site">Live App</a> </div> &#32; submitted by &#32; <a href="https://www.reddit.com/user/VermicelliFearless22"> /u/VermicelliFearless22 </a> <a href="https://www.reddit.com/r/django/comments/1r47u55/advice_from_experienced_django_devs/">[link]</a> &#32; <a href="https://www.reddit.com/r/django/comments/1r47u55/advice_from_experienced_django_devs/">[comments]</a>

Hi all, I'm a solo dev that just finished a Django based project. Being a solo dev, I've noticed that it's hard to get advice from other experienced devs on my projects and codebase in general. I'm just starting out with my software career and would really appreciate getting some advice from more experienced devs. Things like preventing bad habits, anti-patterns and other stuff. Even the small nitpicks are fine with me. If you find yourself with time to spare and nothing else to do, please feel free to rip into my codebase here.
 Codebase and Live App
    submitted by    /u/VermicelliFearless22  
 [link]   [comments]

Advice From Experienced Django Devs

<div class="md">What My Project Does The Python command-line interface tool dotenvguard enables users to compare their .env files with .env.example files and it determines which environment variables they lack or which variables they possess without value or which variables they possess that were not in the example file. The system creates a terminal output which shows a color-coded table and it produces an exit code of 1 when any required element is absent thus enabling users to implement it directly into their CI pipelines or pre-commit hooks or their deployment verification process. pip install dotenvguard Target Audience Any developer working on projects that use .env files — which is most web/backend projects. The software arrives as production-ready which functions correctly within CI pipelines through GitHub Actions and GitLab CI together with pre-commit hooks. The solution provides maximum value to teams which maintain environment configuration through shared responsibilities. Comparison python-dotenv The library loads .env files into os.environ but it does not perform validation against a specified template. The system will still trigger a KeyError during runtime if a variable remains absent from the environment. pydantic-settings The library establishes validation procedures through Python models at application startup yet demands users to create a Settings class. Users can operate dotenvguard without modifying their application code because it requires only one command to execute. envguard (PyPI): The project implements an identical concept to its v0.1 version but it lacks advanced output features and shows signs of being abandoned by its developers. Manual diffing (diff .env .env.example) The process reveals line-by-line differences yet it fails to show how variables between both files relate to each other. The system cannot process comments together with ordering and quoted values. The system operates as a zero-config solution that presents you with an accurate table of all existing problems while its exit code facilitates simple integration into any pipeline. GitHub: <a href="https://github.com/hamzaplojovic/dotenvguard">https://github.com/hamzaplojovic/dotenvguard</a> PyPI: <a href="https://pypi.org/project/dotenvguard/">https://pypi.org/project/dotenvguard/</a> </div> &#32; submitted by &#32; <a href="https://www.reddit.com/user/StudioQuiet7064"> /u/StudioQuiet7064 </a> <a href="https://www.reddit.com/r/django/comments/1r6bvzw/cli_that_validates_your_env_files_against/">[link]</a> &#32; <a href="https://www.reddit.com/r/django/comments/1r6bvzw/cli_that_validates_your_env_files_against/">[comments]</a>

What My Project Does
 The Python command-line interface tool dotenvguard enables users to compare their .env files with .env.example files and it determines which environment variables they lack or which variables they possess without value or which variables they possess that were not in the example file. The system creates a terminal output which shows a color-coded table and it produces an exit code of 1 when any required element is absent thus enabling users to implement it directly into their CI pipelines or pre-commit hooks or their deployment verification process.
 pip install dotenvguard
 Target Audience
 Any developer working on projects that use .env files — which is most web/backend projects. The software arrives as production-ready which functions correctly within CI pipelines through GitHub Actions and GitLab CI together with pre-commit hooks. The solution provides maximum value to teams which maintain environment configuration through shared responsibilities.
 Comparison
 python-dotenv The library loads .env files into os.environ but it does not perform validation against a specified template. The system will still trigger a KeyError during runtime if a variable remains absent from the environment.
 pydantic-settings The library establishes validation procedures through Python models at application startup yet demands users to create a Settings class. Users can operate dotenvguard without modifying their application code because it requires only one command to execute.
 envguard (PyPI): The project implements an identical concept to its v0.1 version but it lacks advanced output features and shows signs of being abandoned by its developers.
 Manual diffing (diff .env .env.example) The process reveals line-by-line differences yet it fails to show how variables between both files relate to each other. The system cannot process comments together with ordering and quoted values.
 The system operates as a zero-config solution that presents you with an accurate table of all existing problems while its exit code facilitates simple integration into any pipeline.
 GitHub: https://github.com/hamzaplojovic/dotenvguard
 PyPI: https://pypi.org/project/dotenvguard/
    submitted by    /u/StudioQuiet7064  
 [link]   [comments]

CLI that validates your .env files against .env.example so you stop getting KeyErrors in production

<div class="md">Hi everyone! 👋 I’m exploring Django development and wanted to get a sense of the community’s experiences. A couple of things I’m curious about: <ol> <li>What are the biggest challenges or pain points you face when building projects with Django?</li> <li>When it comes to caching, do you typically stick with Django’s built-in caching framework (like <code>cache_page</code>, <code>Low-Level Cache API</code>, etc.), or do you implement a custom caching layer tailored to your app’s needs?</li> </ol> I’d love to hear your experiences, tips, or lessons learned. Thanks in advance! 🙏 </div> &#32; submitted by &#32; <a href="https://www.reddit.com/user/confessto"> /u/confessto </a> <a href="https://www.reddit.com/r/django/comments/1r5cscz/curious_about_challenges_and_caching_strategies/">[link]</a> &#32; <a href="https://www.reddit.com/r/django/comments/1r5cscz/curious_about_challenges_and_caching_strategies/">[comments]</a>

Hi everyone! 👋
 I’m exploring Django development and wanted to get a sense of the community’s experiences. A couple of things I’m curious about:
  
What are the biggest challenges or pain points you face when building projects with Django?
 When it comes to caching, do you typically stick with Django’s built-in caching framework (like cache_page, Low-Level Cache API, etc.), or do you implement a custom caching layer tailored to your app’s needs?
  
I’d love to hear your experiences, tips, or lessons learned. Thanks in advance! 🙏
    submitted by    /u/confessto  
 [link]   [comments]

Curious about challenges and caching strategies in Django

<div class="md">Hey everyone 👋 I’ve been working on a small Django tool called django-migration-audit. The idea is simple: Django assumes that if a migration is recorded as applied, the database schema matches. But in reality, that’s not always true. Things like: <ul> <li>modified migration files after they were applied</li> <li>fake-applied migrations (<code>--fake</code>)</li> <li>manual schema changes</li> <li>squashed migration mismatches</li> <li>restored databases from backups</li> </ul> can cause the database to drift away from what Django thinks happened. This tool performs two checks: <ol> <li>Trust Verification – Can we trust the migration history?</li> <li>Reality Check – Does the live schema actually match what migrations imply?</li> </ol> It’s read-only and currently meant for development, staging, CI, or forensic debugging. Example usage: <pre><code>python manage.py audit_migrations </code></pre> It’s still early, but I’m working toward making it stable and CI-friendly. Would love feedback on: <ul> <li>edge cases I should consider</li> <li>whether this is useful in real-world Django setups</li> <li>things you’ve seen break migrations in production</li> <li>have folks test it out and give feedback</li> </ul> Repo: <a href="https://github.com/JohananOppongAmoateng/django-migration-audit">https://github.com/JohananOppongAmoateng/django-migration-audit</a> Appreciate any thoughts 🙏 </div> &#32; submitted by &#32; <a href="https://www.reddit.com/user/Dependent_Dig_7009"> /u/Dependent_Dig_7009 </a> <a href="https://www.reddit.com/r/django/comments/1r3ayxa/built_a_tool_to_audit_django_migration_drift/">[link]</a> &#32; <a href="https://www.reddit.com/r/django/comments/1r3ayxa/built_a_tool_to_audit_django_migration_drift/">[comments]</a>

Hey everyone 👋
 I’ve been working on a small Django tool called django-migration-audit.
 The idea is simple: Django assumes that if a migration is recorded as applied, the database schema matches. But in reality, that’s not always true.
 Things like:
  
modified migration files after they were applied
 fake-applied migrations (--fake)
 manual schema changes
 squashed migration mismatches
 restored databases from backups
  
can cause the database to drift away from what Django thinks happened.
 This tool performs two checks:
  
Trust Verification – Can we trust the migration history?
 Reality Check – Does the live schema actually match what migrations imply?
  
It’s read-only and currently meant for development, staging, CI, or forensic debugging.
 Example usage:
 python manage.py audit_migrations 
 It’s still early, but I’m working toward making it stable and CI-friendly.
 Would love feedback on:
  
edge cases I should consider
 whether this is useful in real-world Django setups
 things you’ve seen break migrations in production
 have folks test it out and give feedback
  
Repo: https://github.com/JohananOppongAmoateng/django-migration-audit
 Appreciate any thoughts 🙏
    submitted by    /u/Dependent_Dig_7009  
 [link]   [comments]

Built a tool to audit Django migration drift — looking for feedback

<div class="md">Hi, So because of management preference I will have to use AWS only. I can&#39;t go anywhere else, until I am ready to pay from my own pocket. Current Setup. <ol> <li>One AWS RDS Postgres micro instance db.t4.micro</li> <li>Two EC2 instance t2x.large</li> <li>Then there are other things in bill that I never got to understand. </li> </ol> Everything is on demand. I have heard that one can save at least 40-50% money, if he just understands AWS. I have like 10-14 apps running in total, and one single DB server for all the apps. And my apps very slow. I use coolify to deploy my apps, which to be very honest has made the deployment process a piece of cake. Now, I have heard that AWS has services to run containers and some special services for the deploying apps (maybe app runner). Also, then there is something like serverless. I have no idea about these. If anyone has any experience with these situations then please help me, suggest me services on which I should focus. My management doesn&#39;t gives me sufficient time to read about all the possible services and then experiment on them all. So, if you could suggest me some service, then I will specifically read about it and experiment on it. Reserved instances also saves money? I had also read somewhere that there is something in which amazon gives you it&#39;s machines which is idle for low rates, but then once someone buys it, then your application will be turned off immediately. </div> &#32; submitted by &#32; <a href="https://www.reddit.com/user/virtualshivam"> /u/virtualshivam </a> <a href="https://www.reddit.com/r/django/comments/1r7cyce/cost_saving_deployment_of_dockerized_django/">[link]</a> &#32; <a href="https://www.reddit.com/r/django/comments/1r7cyce/cost_saving_deployment_of_dockerized_django/">[comments]</a>

Hi, 
 So because of management preference I will have to use AWS only. I can't go anywhere else, until I am ready to pay from my own pocket. 
 Current Setup. 
  
One AWS RDS Postgres micro instance db.t4.micro
 
Two EC2 instance t2x.large
 
Then there are other things in bill that I never got to understand. 
 
 Everything is on demand. 
 I have heard that one can save at least 40-50% money, if he just understands AWS. 
 I have like 10-14 apps running in total, and one single DB server for all the apps. And my apps very slow. 
 I use coolify to deploy my apps, which to be very honest has made the deployment process a piece of cake. 
 Now, I have heard that AWS has services to run containers and some special services for the deploying apps (maybe app runner). 
 Also, then there is something like serverless. 
 I have no idea about these. 
 If anyone has any experience with these situations then please help me, suggest me services on which I should focus. 
 My management doesn't gives me sufficient time to read about all the possible services and then experiment on them all. So, if you could suggest me some service, then I will specifically read about it and experiment on it. 
 Reserved instances also saves money? I had also read somewhere that there is something in which amazon gives you it's machines which is idle for low rates, but then once someone buys it, then your application will be turned off immediately. 
    submitted by    /u/virtualshivam  
 [link]   [comments]

Cost Saving Deployment of Dockerized django projects with AWS

<div class="md">I&#39;m build pure Django app for sports event registration, and RSVPs. The site is <a href="https://registerfor.events">https://registerfor.events</a> It&#39;s simple right now and I&#39;m going a Craigslist model. I like the direction that it&#39;s going but it seems bland. I&#39;ve build with Django before, but it&#39;s been about 4 years since I&#39;ve used it without any JS anywhere. I like how fast/predictable it is to develop, but I worry about getting users interested with the retro design and feel. For example, I have direct messaging that works and feels like it&#39;s from 2005. I could rebuild it as a service to be much nicer with something else, but I&#39;m not sure that focusing on that rather then core features that would actually get used is really the way to go. So, does anyone build with pure Django? Just templates and form and view? </div> &#32; submitted by &#32; <a href="https://www.reddit.com/user/ExtensionBreath1262"> /u/ExtensionBreath1262 </a> <a href="https://www.reddit.com/r/django/comments/1r5yj51/do_you_build_with_progressive_enhancements_in_mind/">[link]</a> &#32; <a href="https://www.reddit.com/r/django/comments/1r5yj51/do_you_build_with_progressive_enhancements_in_mind/">[comments]</a>

I'm build pure Django app for sports event registration, and RSVPs. The site is https://registerfor.events 
 It's simple right now and I'm going a Craigslist model. I like the direction that it's going but it seems bland. I've build with Django before, but it's been about 4 years since I've used it without any JS anywhere.
 I like how fast/predictable it is to develop, but I worry about getting users interested with the retro design and feel. For example, I have direct messaging that works and feels like it's from 2005. I could rebuild it as a service to be much nicer with something else, but I'm not sure that focusing on that rather then core features that would actually get used is really the way to go.
 So, does anyone build with pure Django? Just templates and form and view?
    submitted by    /u/ExtensionBreath1262  
 [link]   [comments]

Do you build with progressive enhancements in mind?

<div class="md">While learning web development, I kept organizing my notes and practice examples so things made more sense. Over time, this turned into a beginner-friendly roadmap covering: • HTML fundamentals • CSS layouts &amp; responsive design • JavaScript basics • Practice project ideas I’m sharing a few sample chapters here in case they help someone getting started: HTML sample: [<a href="https://drive.google.com/file/d/1fobDAb9GlLvE-cz3sR3zpu8dWLnGxc4Z/view?usp=drive_link%5D">https://drive.google.com/file/d/1fobDAb9GlLvE-cz3sR3zpu8dWLnGxc4Z/view?usp=drive_link]</a> CSS sample: [<a href="https://drive.google.com/file/d/1NpZN8Ign68JojqC-9NdjW8edRbGImRbQ/view?usp=drive_link%5D">https://drive.google.com/file/d/1NpZN8Ign68JojqC-9NdjW8edRbGImRbQ/view?usp=drive_link]</a> JavaScript sample: [<a href="https://drive.google.com/file/d/1Q_iNeH9yt2E5-siABltwrJtBCbBL3SBC/view?usp=drive_link%5D">https://drive.google.com/file/d/1Q_iNeH9yt2E5-siABltwrJtBCbBL3SBC/view?usp=drive_link]</a> Hope this helps anyone starting their web dev journey. Happy to hear feedback or suggestions. </div> &#32; submitted by &#32; <a href="https://www.reddit.com/user/Far-Rich-9149"> /u/Far-Rich-9149 </a> <a href="https://www.reddit.com/r/django/comments/1r7959h/resources_that_helped_me_learn_web_development/">[link]</a> &#32; <a href="https://www.reddit.com/r/django/comments/1r7959h/resources_that_helped_me_learn_web_development/">[comments]</a>

While learning web development, I kept organizing my notes and practice examples so things made more sense.
 Over time, this turned into a beginner-friendly roadmap covering:
 • HTML fundamentals
 • CSS layouts & responsive design
 • JavaScript basics
 • Practice project ideas
 I’m sharing a few sample chapters here in case they help someone getting started:
 HTML sample:
 [https://drive.google.com/file/d/1fobDAb9GlLvE-cz3sR3zpu8dWLnGxc4Z/view?usp=drive_link]
 CSS sample:
 [https://drive.google.com/file/d/1NpZN8Ign68JojqC-9NdjW8edRbGImRbQ/view?usp=drive_link]
 JavaScript sample:
 [https://drive.google.com/file/d/1Q_iNeH9yt2E5-siABltwrJtBCbBL3SBC/view?usp=drive_link]
 Hope this helps anyone starting their web dev journey.
 Happy to hear feedback or suggestions.
    submitted by    /u/Far-Rich-9149  
 [link]   [comments]

Resources that helped me learn web development — sharing my compiled notes

<div class="md">I’ve been rethinking how I model certain data in Django. By default, it’s natural to just update a model instance: - change the address - update the status - overwrite the salary - save() But some of these fields feel more like facts that were true at a point in time rather than just mutable state. For example: - Order status transitions - User role changes - Pricing updates - Subscription changes Overwriting them works — until you need: - audit history - debugging context - “how did we get here?” answers I’m curious how people approach this in real Django systems. Do you: - Use history tables? - django-simple-history? - Explicit versioned models? - Separate “events” tables? - Just accept mutation unless compliance requires otherwise? Not looking for a specific pattern — more interested in how you draw the line in practice. </div> &#32; submitted by &#32; <a href="https://www.reddit.com/user/disizrj"> /u/disizrj </a> <a href="https://www.reddit.com/r/django/comments/1r8bann/how_do_you_model_historical_facts_in_django/">[link]</a> &#32; <a href="https://www.reddit.com/r/django/comments/1r8bann/how_do_you_model_historical_facts_in_django/">[comments]</a>

I’ve been rethinking how I model certain data in Django.
 By default, it’s natural to just update a model instance: - change the address - update the status - overwrite the salary - save()
 But some of these fields feel more like facts that were true at a point in time rather than just mutable state.
 For example: - Order status transitions - User role changes - Pricing updates - Subscription changes
 Overwriting them works — until you need: - audit history - debugging context - “how did we get here?” answers
 I’m curious how people approach this in real Django systems.
 Do you: - Use history tables? - django-simple-history? - Explicit versioned models? - Separate “events” tables? - Just accept mutation unless compliance requires otherwise?
 Not looking for a specific pattern — more interested in how you draw the line in practice.
    submitted by    /u/disizrj  
 [link]   [comments]

How do you model historical facts in Django without making everything event-sourced?

<div class="md">&#x200B; I’ve just released django-ml-audit, a reusable Django app to keep a per-prediction audit trail for ML models running inside Django/DRF APIs. I’m looking for feedback on whether this solves a real pain for you and how the API should evolve. The problem Once a model is in production, questions like these show up: “A user complained about a decision last month – can we replay exactly what the model did for that request?” “Which model version made this prediction, with which inputs and confidence?” “We compute SHAP/LIME offline, but where do we store explanations for real production predictions?” “How do we keep enough context to debug while not dumping raw PII into logs?” Most teams end up with ad-hoc logging or custom tables per project, which makes audits and incident reviews painful. What django-ml-audit does It’s a Django app that gives you: A standard schema for prediction events: model + version, environment, redacted features, outputs, confidence, status, latency, trace ID, etc. A separate RequestingActor model to track who/what called the model (user, service, tenant, IP, user agent). An Explanation model to attach JSON payloads (e.g. SHAP) plus a human-readable summary to each prediction. A field-based redaction layer for feature payloads: Configurable allowlist/denylist. Conservative defaults for keys like email, password, token, credit_card, etc. Built-in Django admin and read-only DRF endpoints to browse and filter predictions: List predictions with filters for model, time range, environment, actor, confidence range, and “has explanation”. Retrieve a single prediction with its model, actor, and explanation attached. The idea is: months later, for any given prediction, you can answer “what happened here and why?” without reverse-engineering logs. Example use case (high level) A typical use case is a fraud detection API in Django: Every time the API scores a transaction, it records: The model version that made the decision. Redacted features (e.g. amount, country, but masked email/ID). Outputs, confidence, and decision outcome (flagged / clean). The user or service that requested it, plus optional tenant. A separate background job (or the same view) can compute an explanation (SHAP, reason codes, etc.) and attach it. Later, if a regulator or internal reviewer asks about a specific transaction, you can pull a single prediction record with full context and explanation instead of scraping logs. How to try it PyPI: django-ml-audit Add ml_audit and rest_framework to INSTALLED_APPS, run migrations, mount /api/ml-audit/ in urls.py. Start logging predictions via a small service function (record_prediction_event) and optionally attach explanations. Repo &amp; docs: GitHub: <a href="https://github.com/RJ-Gamer/ml-audit">https://github.com/RJ-Gamer/ml-audit</a> PyPI: <a href="https://pypi.org/project/django-ml-audit/">https://pypi.org/project/django-ml-audit/</a> Feedback I’m looking for Does per-prediction auditability solve a real problem in your Django/ML projects? What extra fields or behaviors would you want in a production-ready audit trail? Would you prioritize: Multiple explanations per prediction, Better export/reporting for audits, or A minimal web UI to browse and compare predictions? Any thoughts, criticism, or “this would be useful if it also did X” are very welcome. </div> &#32; submitted by &#32; <a href="https://www.reddit.com/user/disizrj"> /u/disizrj </a> <a href="https://www.reddit.com/r/django/comments/1r3t89p/i_built_djangomlaudit_a_django_app_for_auditing/">[link]</a> &#32; <a href="https://www.reddit.com/r/django/comments/1r3t89p/i_built_djangomlaudit_a_django_app_for_auditing/">[comments]</a>

​
 I’ve just released django-ml-audit, a reusable Django app to keep a per-prediction audit trail for ML models running inside Django/DRF APIs.
 I’m looking for feedback on whether this solves a real pain for you and how the API should evolve.
 The problem
 Once a model is in production, questions like these show up:
 “A user complained about a decision last month – can we replay exactly what the model did for that request?”
 “Which model version made this prediction, with which inputs and confidence?”
 “We compute SHAP/LIME offline, but where do we store explanations for real production predictions?”
 “How do we keep enough context to debug while not dumping raw PII into logs?”
 Most teams end up with ad-hoc logging or custom tables per project, which makes audits and incident reviews painful.
 What django-ml-audit does
 It’s a Django app that gives you:
 A standard schema for prediction events: model + version, environment, redacted features, outputs, confidence, status, latency, trace ID, etc.
 A separate RequestingActor model to track who/what called the model (user, service, tenant, IP, user agent).
 An Explanation model to attach JSON payloads (e.g. SHAP) plus a human-readable summary to each prediction.
 A field-based redaction layer for feature payloads:
 Configurable allowlist/denylist.
 Conservative defaults for keys like email, password, token, credit_card, etc.
 Built-in Django admin and read-only DRF endpoints to browse and filter predictions:
 List predictions with filters for model, time range, environment, actor, confidence range, and “has explanation”.
 Retrieve a single prediction with its model, actor, and explanation attached.
 The idea is: months later, for any given prediction, you can answer “what happened here and why?” without reverse-engineering logs.
 Example use case (high level)
 A typical use case is a fraud detection API in Django:
 Every time the API scores a transaction, it records:
 The model version that made the decision.
 Redacted features (e.g. amount, country, but masked email/ID).
 Outputs, confidence, and decision outcome (flagged / clean).
 The user or service that requested it, plus optional tenant.
 A separate background job (or the same view) can compute an explanation (SHAP, reason codes, etc.) and attach it.
 Later, if a regulator or internal reviewer asks about a specific transaction, you can pull a single prediction record with full context and explanation instead of scraping logs.
 How to try it
 PyPI: django-ml-audit
 Add ml_audit and rest_framework to INSTALLED_APPS, run migrations, mount /api/ml-audit/ in urls.py.
 Start logging predictions via a small service function (record_prediction_event) and optionally attach explanations.
 Repo & docs:
 GitHub: https://github.com/RJ-Gamer/ml-audit
 PyPI: https://pypi.org/project/django-ml-audit/
 Feedback I’m looking for
 Does per-prediction auditability solve a real problem in your Django/ML projects?
 What extra fields or behaviors would you want in a production-ready audit trail?
 Would you prioritize:
 Multiple explanations per prediction,
 Better export/reporting for audits, or
 A minimal web UI to browse and compare predictions?
 Any thoughts, criticism, or “this would be useful if it also did X” are very welcome.
    submitted by    /u/disizrj  
 [link]   [comments]

I built django-ml-audit: a Django app for auditing ML predictions (feedback welcome)

<div class="md">hello guys, I&#39;m a new intern , so while making a django project, the entire thing is completed. So what i want to do is start my queue_process when I start the server. so what i have done is in manage.py ,in main i just call the function(start_queue) , but I don&#39;t think this is how you should do it, now the entire thing has been merged to beta, and the entire process works only once after working once the entire thing restarts(killing the queue_process background thread) </div> &#32; submitted by &#32; <a href="https://www.reddit.com/user/unmployd_dropper"> /u/unmployd_dropper </a> <a href="https://www.reddit.com/r/django/comments/1r610no/trying_to_run_another_process_in_managepy/">[link]</a> &#32; <a href="https://www.reddit.com/r/django/comments/1r610no/trying_to_run_another_process_in_managepy/">[comments]</a>

hello guys,
 I'm a new intern , so while making a django project, the entire thing is completed. So what i want to do is start my queue_process when I start the server.
 so what i have done is in manage.py ,in main i just call the function(start_queue) ,
 but I don't think this is how you should do it, now the entire thing has been merged to beta, and the entire process works only once after working once the entire thing restarts(killing the queue_process background thread)
    submitted by    /u/unmployd_dropper  
 [link]   [comments]

Trying to run another process in manage.py

&#32; submitted by &#32; <a href="https://www.reddit.com/user/jadd_logs"> /u/jadd_logs </a> <a href="/r/djangolearning/comments/1r6aml2/need_book_recommendation_for_learning_python/">[link]</a> &#32; <a href="https://www.reddit.com/r/django/comments/1r6amy6/need_book_recommendation_for_learning_python/">[comments]</a>

<div class="md">Quick follow-up: I just shipped <a href="https://github.com/gettranslatebot/translatebot-django">TranslateBot v0.6.0</a>. In v0.4.0, I added <code>TRANSLATING.md</code>, a file in your project root that gives the LLM context about your terminology, tone, and domain. That works great when your whole project shares the same vocabulary. But what if different apps in your project have very different domains? A medical records app and a legal documents app need completely different translation guidance. &quot;record&quot; means something different in each, and &quot;brief&quot; definitely shouldn&#39;t be translated the same way. The new feature: per-app <code>TRANSLATING.md</code> You can now drop a <code>TRANSLATING.md</code> inside any Django app directory, and TranslateBot will pick it up automatically: <pre><code>myproject/ ├── TRANSLATING.md # project-wide context ├── medical_records/ │ ├── locale/de/LC_MESSAGES/django.po │ └── TRANSLATING.md # &quot;record&quot; = medical record, not DB record ├── legal_docs/ │ ├── locale/de/LC_MESSAGES/django.po │ └── TRANSLATING.md # &quot;brief&quot; = legal document, not underwear └── common/ └── locale/de/LC_MESSAGES/django.po # uses project-level context only </code></pre> App-level context gets combined with the project-level context automatically. Apps without their own file just use the project-level one. And apps sharing the same context get batched together, so you are not making redundant API calls. Project links: <ul> <li>Docs: <a href="https://translatebot.dev/docs/usage/translation-context/">https://translatebot.dev/docs/usage/translation-context/</a> </li> <li>GitHub: <a href="https://github.com/gettranslatebot/translatebot-django">https://github.com/gettranslatebot/translatebot-django</a></li> </ul> Feedback / feature ideas are welcome, just as patches :)! </div> &#32; submitted by &#32; <a href="https://www.reddit.com/user/leipegokker"> /u/leipegokker </a> <a href="https://www.reddit.com/r/django/comments/1r63jnj/translatebot_v060_perapp_translatingmd_for/">[link]</a> &#32; <a href="https://www.reddit.com/r/django/comments/1r63jnj/translatebot_v060_perapp_translatingmd_for/">[comments]</a>

Quick follow-up: I just shipped TranslateBot v0.6.0.
 In v0.4.0, I added TRANSLATING.md, a file in your project root that gives the LLM context about your terminology, tone, and domain.
 That works great when your whole project shares the same vocabulary.
 But what if different apps in your project have very different domains? A medical records app and a legal documents app need completely different translation guidance. "record" means something different in each, and "brief" definitely shouldn't be translated the same way.
 The new feature: per-app TRANSLATING.md
 You can now drop a TRANSLATING.md inside any Django app directory, and TranslateBot will pick it up automatically:
 myproject/ ├── TRANSLATING.md # project-wide context ├── medical_records/ │ ├── locale/de/LC_MESSAGES/django.po │ └── TRANSLATING.md # "record" = medical record, not DB record ├── legal_docs/ │ ├── locale/de/LC_MESSAGES/django.po │ └── TRANSLATING.md # "brief" = legal document, not underwear └── common/ └── locale/de/LC_MESSAGES/django.po # uses project-level context only 
 App-level context gets combined with the project-level context automatically. Apps without their own file just use the project-level one. And apps sharing the same context get batched together, so you are not making redundant API calls.
 Project links:
  
Docs: https://translatebot.dev/docs/usage/translation-context/ 
 GitHub: https://github.com/gettranslatebot/translatebot-django
  
Feedback / feature ideas are welcome, just as patches :)!
    submitted by    /u/leipegokker  
 [link]   [comments]

TranslateBot v0.6.0: Per-app TRANSLATING.md for domain-specific translations

&#32; submitted by &#32; <a href="https://www.reddit.com/user/Ill_Leading9202"> /u/Ill_Leading9202 </a> <a href="/r/webdev/comments/1r0z6g9/pwas_in_real_projects_worth_it/">[link]</a> &#32; <a href="https://www.reddit.com/r/django/comments/1r4jrkn/has_anyone_here_used_pwas_with_django_in_real/">[comments]</a>

submitted by    /u/Ill_Leading9202  
 [link]   [comments]

Has anyone here used PWAs with Django in real projects? How did it go?

&#32; submitted by &#32; <a href="https://www.reddit.com/user/bllenny"> /u/bllenny </a> <a href="/r/SideProject/comments/1r7jhf8/i_built_a_django_app_that_finds_profitable_video/">[link]</a> &#32; <a href="https://www.reddit.com/r/django/comments/1r7kjzn/i_built_a_django_app_that_finds_profitable_video/">[comments]</a>

submitted by    /u/bllenny  
 [link]   [comments]

I built a Django app that finds profitable video game deals on eBay

&#32; submitted by &#32; <a href="https://www.reddit.com/user/BuffHaloBill"> /u/BuffHaloBill </a> <a href="/r/webdev/comments/1r6mygb/migrating_a_large_django_bootstrap_5_saas_to_a/">[link]</a> &#32; <a href="https://www.reddit.com/r/django/comments/1r6myy7/migrating_a_large_django_bootstrap_5_saas_to_a/">[comments]</a>

submitted by    /u/BuffHaloBill  
 [link]   [comments]

Migrating a Large Django + Bootstrap 5 SaaS to a More Modern UI - Rewrite or Incremental?

<div class="md">In a Django + DRF app serving ML models, we ran into a recurring problem: Months later someone asks: “Why was this transaction flagged?” “Which model version made this decision?” “What inputs were used?” “Who triggered it?” Standard logs and metrics weren’t enough. So we built a small append-only audit layer around a few invariants: Each prediction becomes a structured PredictionEvent Stable external prediction_id (idempotent on retries) Redacted feature snapshot (allowlist/denylist + conservative defaults) Linked ModelVersion Optional RequestingActor (user/service/tenant/IP) At most one explanation artifact per prediction (v1 simplification) Read-only DRF API for querying (no write endpoints) We’re intentionally treating it as a decision ledger, not monitoring or experiment tracking. A few design questions I’d love critique on: Is app-level “append-only” good enough, or would you enforce DB-level immutability? Would you store redacted feature payloads, only hashes, or push raw inputs to object storage? Is “one explanation per prediction” too restrictive early on? Would you keep this as a pluggable Django app, or split it into a separate audit service? For context, I packaged this approach into a reusable Django app here: <a href="https://github.com/RJ-Gamer/ml-audit%EF%BF%BD">https://github.com/RJ-Gamer/ml-audit�</a> Genuinely interested in how others are solving this in production (especially fintech/healthcare contexts). </div> &#32; submitted by &#32; <a href="https://www.reddit.com/user/disizrj"> /u/disizrj </a> <a href="https://www.reddit.com/r/django/comments/1r6gzxe/how_are_you_handling_perrequest_ml_audit_trails/">[link]</a> &#32; <a href="https://www.reddit.com/r/django/comments/1r6gzxe/how_are_you_handling_perrequest_ml_audit_trails/">[comments]</a>

In a Django + DRF app serving ML models, we ran into a recurring problem:
 Months later someone asks:
 “Why was this transaction flagged?”
 “Which model version made this decision?”
 “What inputs were used?”
 “Who triggered it?”
 Standard logs and metrics weren’t enough. So we built a small append-only audit layer around a few invariants:
 Each prediction becomes a structured PredictionEvent
 Stable external prediction_id (idempotent on retries)
 Redacted feature snapshot (allowlist/denylist + conservative defaults)
 Linked ModelVersion
 Optional RequestingActor (user/service/tenant/IP)
 At most one explanation artifact per prediction (v1 simplification)
 Read-only DRF API for querying (no write endpoints)
 We’re intentionally treating it as a decision ledger, not monitoring or experiment tracking.
 A few design questions I’d love critique on:
 Is app-level “append-only” good enough, or would you enforce DB-level immutability?
 Would you store redacted feature payloads, only hashes, or push raw inputs to object storage?
 Is “one explanation per prediction” too restrictive early on?
 Would you keep this as a pluggable Django app, or split it into a separate audit service?
 For context, I packaged this approach into a reusable Django app here:
 https://github.com/RJ-Gamer/ml-audit�
 Genuinely interested in how others are solving this in production (especially fintech/healthcare contexts).
    submitted by    /u/disizrj  
 [link]   [comments]

How are you handling per-request ML audit trails in Django?

&#32; submitted by &#32; <a href="https://www.reddit.com/user/jadd_logs"> /u/jadd_logs </a> <a href="/r/learnprogramming/comments/1r4elw1/need_help_with_standardizingsimplifying_logic/">[link]</a> &#32; <a href="https://www.reddit.com/r/django/comments/1r4emgc/need_help_with_standardizingsimplifying_logic/">[comments]</a>

<div class="md">Hi, is there anywhere where I can get all of django allauth settings with default settings? I feel like it&#39;s better if I have all the settings in one file in my repo. Bonus if every variable has a comment explaining it&#39;s purpose, just like in the docs. </div> &#32; submitted by &#32; <a href="https://www.reddit.com/user/BaseKodu"> /u/BaseKodu </a> <a href="https://www.reddit.com/r/django/comments/1r39ojz/django_allauth_settings/">[link]</a> &#32; <a href="https://www.reddit.com/r/django/comments/1r39ojz/django_allauth_settings/">[comments]</a>

Hi, is there anywhere where I can get all of django allauth settings with default settings? I feel like it's better if I have all the settings in one file in my repo. Bonus if every variable has a comment explaining it's purpose, just like in the docs.
    submitted by    /u/BaseKodu  
 [link]   [comments]

Django allauth settings

<div class="md">Do Django Devs Use Proxy Models? Did you know you can create a &quot;Ghost Model&quot; called a Proxy Model that lets you add Python methods or custom managers without creating a new DB table? It’s the perfect way to extend behavior without touching the schema or doing expensive joins. </div> &#32; submitted by &#32; <a href="https://www.reddit.com/user/natanasrat"> /u/natanasrat </a> <a href="https://youtu.be/LxrfvtUpXBE">[link]</a> &#32; <a href="https://www.reddit.com/r/django/comments/1r84mmz/dont_overlook_proxy_models/">[comments]</a>

Do Django Devs Use Proxy Models? 
 Did you know you can create a "Ghost Model" called a Proxy Model that lets you add Python methods or custom managers without creating a new DB table? 
 It’s the perfect way to extend behavior without touching the schema or doing expensive joins.
    submitted by    /u/natanasrat  
 [link]   [comments]

Don't overlook proxy models...

&#32; submitted by &#32; <a href="https://www.reddit.com/user/jadd_logs"> /u/jadd_logs </a> <a href="/r/learnprogramming/comments/1r4d62u/need_experienced_opinion_this/">[link]</a> &#32; <a href="https://www.reddit.com/r/django/comments/1r4d6dp/need_experienced_opinion_this/">[comments]</a>

Need Experienced Opinion This!

&#32; submitted by &#32; <a href="https://www.reddit.com/user/kankyo"> /u/kankyo </a> <a href="https://kodare.net/2026/02/15/using-claude-for-spell-checking.html">[link]</a> &#32; <a href="https://www.reddit.com/r/django/comments/1r5m5x5/using_claude_for_spellchecking_and_grammar/">[comments]</a>

submitted by    /u/kankyo  
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Hello, Python

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Django allauth settings

Don't overlook proxy models...

Need Experienced Opinion This!

Using Claude for spellchecking and grammar