<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.

<div class="md">Sometimes in my work codebase I found some old templates I haven&#39;t seen in a while and even though I skim the code, it does not always gives me the right picture of what the rendered template looks like. After all, my brain haven&#39;t got that update to render html properly in my mind. So my question is, do you guys know some lib that can parse the template and mock its data? Would it be hard to implement myself? That way I could just do something like <code>django-mock-render &lt;template&gt;</code> </div> &#32; submitted by &#32; <a href="https://www.reddit.com/user/windanrain"> /u/windanrain </a> <a href="https://www.reddit.com/r/djangolearning/comments/1raa719/is_there_a_lib_to_parse_a_template_and_mock_its/">[link]</a> &#32; <a href="https://www.reddit.com/r/djangolearning/comments/1raa719/is_there_a_lib_to_parse_a_template_and_mock_its/">[comments]</a>

Sometimes in my work codebase I found some old templates I haven't seen in a while and even though I skim the code, it does not always gives me the right picture of what the rendered template looks like.
 After all, my brain haven't got that update to render html properly in my mind.
 So my question is, do you guys know some lib that can parse the template and mock its data? Would it be hard to implement myself?
 That way I could just do something like django-mock-render <template>
 submitted by /u/windanrain 
 [link] [comments]

Is there a lib to parse a template and mock its data?

&#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/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.

<div class="md">My question is: - what is the selling point of django templates and why do people use them - are they slower to load than just calling a drf api from an SPA? - do clients want django templates? Because i had a client that paid me to migrate his django templates to React SPA with DRF... but didn&#39;t encounter the other way around.... - do devs with experience in both SPA+DRF and templates actively choose templates either due to superiority or the use case? </div> &#32; submitted by &#32; <a href="https://www.reddit.com/user/natanasrat"> /u/natanasrat </a> <a href="/r/django/comments/1r9r06l/for_the_devs_who_use_django_templates/">[link]</a> &#32; <a href="https://www.reddit.com/r/djangolearning/comments/1r9r274/for_the_devs_who_use_django_templates/">[comments]</a>

My question is: - what is the selling point of django templates and why do people use them - are they slower to load than just calling a drf api from an SPA? - do clients want django templates? Because i had a client that paid me to migrate his django templates to React SPA with DRF... but didn't encounter the other way around.... - do devs with experience in both SPA+DRF and templates actively choose templates either due to superiority or the use case?
    submitted by    /u/natanasrat  
 [link]   [comments]

For the devs who use django templates....

<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

&#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&#39;ve been building a discovery engine for solo-built software — think of it as intent-based search where users type a problem (&quot;I need to send invoices&quot;) and get matched to tools, instead of browsing by product name or upvotes. The stack is FastAPI + SQLite. No Postgres. No Redis. No managed database service. Just a single <code>.db</code> file. I wanted to share what I&#39;ve learned after a few weeks in case it helps anyone evaluating the same choice. Why SQLite <ul> <li>Zero operational overhead. No connection pooling, no database server to monitor, no Docker Compose dependency. The app and the data live together.</li> <li>Reads are absurdly fast. My use case is read-heavy (search queries) with infrequent writes (new tool submissions, maybe 10-20/day). SQLite handles this without breaking a sweat.</li> <li>Backups are <code>cp</code>. I rsync the <code>.db</code> file nightly. That&#39;s the entire backup strategy. It works.</li> <li>Deployment is simple. One process, one file, one VPS. I deploy with a git pull and a systemd restart. The calm tech dream.</li> </ul> The tradeoffs I&#39;ve hit <ul> <li>Write concurrency. SQLite uses a file-level lock for writes. With WAL mode enabled, concurrent reads are fine, but if you have multiple processes writing simultaneously, you&#39;ll hit <code>SQLITE_BUSY</code>. My solution: a single FastAPI worker handles all writes via a background task queue. If you&#39;re running Gunicorn with multiple workers, this is something you have to think about.</li> <li>Full-text search. SQLite&#39;s built-in FTS5 is surprisingly capable. I&#39;m using it for intent-based search with custom tokenizers. It&#39;s not Elasticsearch, but for a catalog of a few thousand items, it&#39;s more than enough. The main limitation: no fuzzy matching out of the box. I handle typo tolerance at the application layer.</li> <li>No native JSON operators (sort of). SQLite has <code>json_extract()</code> and friends, but they&#39;re not as ergonomic as Postgres&#39;s <code>-&gt;</code> and <code>-&gt;&gt;</code> operators. I store structured metadata as JSON blobs and parse in Python when needed. Minor annoyance, not a blocker.</li> <li>Schema migrations. There&#39;s no <code>ALTER COLUMN</code> in SQLite. If you need to change a column type, you&#39;re rebuilding the table. I use <code>alembic</code> with the <code>batch</code> mode for this, which wraps the create-copy-drop-rename dance. Works fine, just feels clunky.</li> </ul> Where the line is I think SQLite stops being the right choice when: - You need concurrent writes from multiple services (microservices, multiple API servers) - Your dataset exceeds ~50GB and you need complex analytical queries - You need real-time replication to a read replica For a solo-built SaaS serving hundreds or even low thousands of users with a read-heavy workload? SQLite is underrated. The operational simplicity alone is worth it. Happy to answer questions about the setup. I&#39;m using Python 3.12, FastAPI with async endpoints, and SQLAlchemy 2.0 with the synchronous SQLite driver (async SQLite drivers exist but add complexity I don&#39;t need). </div> &#32; submitted by &#32; <a href="https://www.reddit.com/user/edmillss"> /u/edmillss </a> <a href="https://www.reddit.com/r/FastAPI/comments/1ra1xlg/why_im_using_sqlite_as_the_only_database_for_a/">[link]</a> &#32; <a href="https://www.reddit.com/r/FastAPI/comments/1ra1xlg/why_im_using_sqlite_as_the_only_database_for_a/">[comments]</a>

I've been building a discovery engine for solo-built software — think of it as intent-based search where users type a problem ("I need to send invoices") and get matched to tools, instead of browsing by product name or upvotes.
 The stack is FastAPI + SQLite. No Postgres. No Redis. No managed database service. Just a single .db file.
 I wanted to share what I've learned after a few weeks in case it helps anyone evaluating the same choice.
 Why SQLite
  
Zero operational overhead. No connection pooling, no database server to monitor, no Docker Compose dependency. The app and the data live together.
 Reads are absurdly fast. My use case is read-heavy (search queries) with infrequent writes (new tool submissions, maybe 10-20/day). SQLite handles this without breaking a sweat.
 Backups are cp. I rsync the .db file nightly. That's the entire backup strategy. It works.
 Deployment is simple. One process, one file, one VPS. I deploy with a git pull and a systemd restart. The calm tech dream.
  
The tradeoffs I've hit
  
Write concurrency. SQLite uses a file-level lock for writes. With WAL mode enabled, concurrent reads are fine, but if you have multiple processes writing simultaneously, you'll hit SQLITE_BUSY. My solution: a single FastAPI worker handles all writes via a background task queue. If you're running Gunicorn with multiple workers, this is something you have to think about.
 Full-text search. SQLite's built-in FTS5 is surprisingly capable. I'm using it for intent-based search with custom tokenizers. It's not Elasticsearch, but for a catalog of a few thousand items, it's more than enough. The main limitation: no fuzzy matching out of the box. I handle typo tolerance at the application layer.
 No native JSON operators (sort of). SQLite has json_extract() and friends, but they're not as ergonomic as Postgres's -> and ->> operators. I store structured metadata as JSON blobs and parse in Python when needed. Minor annoyance, not a blocker.
 Schema migrations. There's no ALTER COLUMN in SQLite. If you need to change a column type, you're rebuilding the table. I use alembic with the batch mode for this, which wraps the create-copy-drop-rename dance. Works fine, just feels clunky.
  
Where the line is
 I think SQLite stops being the right choice when: - You need concurrent writes from multiple services (microservices, multiple API servers) - Your dataset exceeds ~50GB and you need complex analytical queries - You need real-time replication to a read replica
 For a solo-built SaaS serving hundreds or even low thousands of users with a read-heavy workload? SQLite is underrated. The operational simplicity alone is worth it.
 Happy to answer questions about the setup. I'm using Python 3.12, FastAPI with async endpoints, and SQLAlchemy 2.0 with the synchronous SQLite driver (async SQLite drivers exist but add complexity I don't need).
    submitted by    /u/edmillss  
 [link]   [comments]

Why I'm using SQLite as the only database for a production SaaS (and the tradeoffs I've hit so far)

<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

<div class="md">Hi everyone, I just released v1.0.0 of <a href="https://github.com/d3vyce/fastapi-toolsets">fastapi-toolsets</a>, a modular set of tools to accelerate and simplify the creation of FastAPI projects. After a year of working on different FastAPI projects, I kept writing the same boilerplate over and over. So I extracted everything into a reusable, modular library. A few things to know about this project: - Async only: built entirely around async/await - PostgreSQL + SQLAlchemy only: no plans to support other databases for now - Modular: install only what you need, the base package stays lean and optional extras (`cli`, `metrics`, `pytest`) add features on top <h1>Features</h1> <a href="https://fastapi-toolsets.d3vyce.fr/module/crud/">CRUD</a> - Generic async CRUD operations (`get`, `first`, `list`, `create`, `update`, `delete`, `upsert`) - Pagination with metadata - Full-text search with relationship traversal - Many-to-many relationship handling <a href="https://fastapi-toolsets.d3vyce.fr/module/db/">Database</a> - Session dependency factory for FastAPI routes - Context managers for standalone usage (CLI, background tasks) - Nested transactions with savepoints - Table lock - Row-change polling for event-driven flows <a href="https://fastapi-toolsets.d3vyce.fr/module/dependencies/">Dependencies</a> - `PathDependency`: auto-fetch a model from a URL path parameter - `BodyDependency`: auto-fetch a model from a request body field <a href="https://fastapi-toolsets.d3vyce.fr/module/schemas/">Schemas</a> &amp; <a href="https://fastapi-toolsets.d3vyce.fr/module/exceptions/">Exceptions</a> - Generic API responses and errors - Unified error response handler - Auto-generated OpenAPI error documentation <a href="https://fastapi-toolsets.d3vyce.fr/module/fixtures/">Fixtures</a> - Decorator-based fixture registration - Dependency-aware DB seeding with topological resolution - Context-based loading and multiple load strategies <a href="https://fastapi-toolsets.d3vyce.fr/module/cli/">CLI</a> (optional) - Django-style `manager` command - Built-in `fixtures list/load` subcommands + extensible with custom commands <a href="https://fastapi-toolsets.d3vyce.fr/module/metrics/">Metrics</a> (optional) - Decorator-based metric registration - Provider mode (registered once at startup) and collector mode (called on each scrape) - Auto-mounted `/metrics` endpoint - Multi-process compatible <a href="https://fastapi-toolsets.d3vyce.fr/module/pytest/">Pytest helpers</a> (optional) - Pre-configured async HTTP client - Isolated DB sessions for tests - Per-worker test database (pytest-xdist compatible) <h1>Links</h1> - GitHub: <a href="https://github.com/d3vyce/fastapi-toolsets">https://github.com/d3vyce/fastapi-toolsets</a> - Docs: <a href="https://fastapi-toolsets.d3vyce.fr">https://fastapi-toolsets.d3vyce.fr</a> - PyPI: <code>uv add fastapi-toolsets</code> Feedback welcome! </div> &#32; submitted by &#32; <a href="https://www.reddit.com/user/d3vyce"> /u/d3vyce </a> <a href="https://www.reddit.com/r/FastAPI/comments/1r9xqu4/i_published_fastapitoolsets_v100_a_set_of_tools/">[link]</a> &#32; <a href="https://www.reddit.com/r/FastAPI/comments/1r9xqu4/i_published_fastapitoolsets_v100_a_set_of_tools/">[comments]</a>

Hi everyone,
 I just released v1.0.0 of fastapi-toolsets, a modular set of tools to accelerate and simplify the creation of FastAPI projects.
 After a year of working on different FastAPI projects, I kept writing the same boilerplate over and over. So I extracted everything into a reusable, modular library.
 A few things to know about this project:
 - Async only: built entirely around async/await
 - PostgreSQL + SQLAlchemy only: no plans to support other databases for now
 - Modular: install only what you need, the base package stays lean and optional extras (`cli`, `metrics`, `pytest`) add features on top
 Features
 CRUD
 - Generic async CRUD operations (`get`, `first`, `list`, `create`, `update`, `delete`, `upsert`)
 - Pagination with metadata
 - Full-text search with relationship traversal
 - Many-to-many relationship handling
 Database
 - Session dependency factory for FastAPI routes
 - Context managers for standalone usage (CLI, background tasks)
 - Nested transactions with savepoints
 - Table lock
 - Row-change polling for event-driven flows
 Dependencies
 - `PathDependency`: auto-fetch a model from a URL path parameter
 - `BodyDependency`: auto-fetch a model from a request body field
 Schemas & Exceptions
 - Generic API responses and errors
 - Unified error response handler
 - Auto-generated OpenAPI error documentation
 Fixtures
 - Decorator-based fixture registration
 - Dependency-aware DB seeding with topological resolution
 - Context-based loading and multiple load strategies
 CLI (optional)
 - Django-style `manager` command
 - Built-in `fixtures list/load` subcommands + extensible with custom commands
 Metrics (optional)
 - Decorator-based metric registration
 - Provider mode (registered once at startup) and collector mode (called on each scrape)
 - Auto-mounted `/metrics` endpoint
 - Multi-process compatible
 Pytest helpers (optional)
 - Pre-configured async HTTP client
 - Isolated DB sessions for tests
 - Per-worker test database (pytest-xdist compatible)
 Links
 - GitHub: https://github.com/d3vyce/fastapi-toolsets
 - Docs: https://fastapi-toolsets.d3vyce.fr
 - PyPI: uv add fastapi-toolsets
 Feedback welcome!
    submitted by    /u/d3vyce  
 [link]   [comments]

I published FastAPI-Toolsets v1.0.0 — A set of tools to simplify and accelerate the creation of FastAPI projects

<div class="md">What is the best use case for background tasks? I am wondering when to use them because once the service restarts, the tasks could be lost without finishing execution, which leads to inconsistent behavior, after successfully returning the response to the client </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/1rabwtb/when_to_use_background_tasks_considering_their/">[link]</a> &#32; <a href="https://www.reddit.com/r/FastAPI/comments/1rabwtb/when_to_use_background_tasks_considering_their/">[comments]</a>

What is the best use case for background tasks? 
 I am wondering when to use them because once the service restarts, the tasks could be lost without finishing execution, which leads to inconsistent behavior, after successfully returning the response to the client
    submitted by    /u/CartoonistWhole3172  
 [link]   [comments]

When to use background tasks considering their non-persistence?

<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">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  
 [link]   [comments]

I built an python AI agent framework that doesn't make me want to mass-delete my venv

<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">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">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  
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Djevops: Host Django on bare metal

<div class="md">Giving another go to this topic now that I’ve managed to retrieve enough data from GitHub, and correlate enough PyPI packages with their repo. If this proves popular, I think this way to assess package popularity has the potential to be turned into an always-available &quot;package ecosystem dashboard&quot;! </div> &#32; submitted by &#32; <a href="https://www.reddit.com/user/thibaudcolas"> /u/thibaudcolas </a> <a href="https://wagtail.org/blog/the-1000-most-popular-django-packages/">[link]</a> &#32; <a href="https://www.reddit.com/r/django/comments/1r96ioi/the_1000_most_popular_django_packages/">[comments]</a>

Giving another go to this topic now that I’ve managed to retrieve enough data from GitHub, and correlate enough PyPI packages with their repo. If this proves popular, I think this way to assess package popularity has the potential to be turned into an always-available "package ecosystem dashboard"!
    submitted by    /u/thibaudcolas  
 [link]   [comments]

The 1000 most popular* Django packages

<div class="md"><ol> <li>Django template + JS/JQuery sprinkles</li> <li>HTMX + Alpine.js</li> <li>React/Vue/Svelte SPA</li> <li>React/Vue/Angular/Svelte + Inertia.js</li> <li>Next/Nuxt/Sveltekit</li> </ol> </div> &#32; submitted by &#32; <a href="https://www.reddit.com/user/Best_Recover3367"> /u/Best_Recover3367 </a> <a href="https://www.reddit.com/r/django/comments/1r9gocg/if_you_guys_were_to_start_a_greenfield_django/">[link]</a> &#32; <a href="https://www.reddit.com/r/django/comments/1r9gocg/if_you_guys_were_to_start_a_greenfield_django/">[comments]</a>

Django template + JS/JQuery sprinkles
 
HTMX + Alpine.js
 
React/Vue/Svelte SPA
 
React/Vue/Angular/Svelte + Inertia.js
 
Next/Nuxt/Sveltekit
 
    submitted by    /u/Best_Recover3367  
 [link]   [comments]

If you guys were to start a greenfield Django project in 2026, what FE stack would you be more inclined go with?

<div class="md">I wrote this article to document a practical way to use Django’s ORM in standalone mode to connect to and explore an existing database without creating a full Django project. </div> &#32; submitted by &#32; <a href="https://www.reddit.com/user/pauloxnet"> /u/pauloxnet </a> <a href="https://www.paulox.net/2026/02/20/django-orm-standalone-database-inspectdb-query/">[link]</a> &#32; <a href="https://www.reddit.com/r/django/comments/1r9toyy/django_orm_standalone¹_querying_an_existing/">[comments]</a>

I wrote this article to document a practical way to use Django’s ORM in standalone mode to connect to and explore an existing database without creating a full Django project.
    submitted by    /u/pauloxnet  
 [link]   [comments]

Django ORM Standalone⁽¹⁾: Querying an existing database

<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  
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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  
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Curious about challenges and caching strategies in Django

<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">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">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&#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?

&#32; submitted by &#32; <a href="https://www.reddit.com/user/dwaxe"> /u/dwaxe </a> <a href="https://www.djangoproject.com/weblog/2026/feb/19/2026-coc-update-phase-2/">[link]</a> &#32; <a href="https://www.reddit.com/r/django/comments/1r932fm/plan_to_adopt_contributor_covenant_3_as_djangos/">[comments]</a>

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

Plan to Adopt Contributor Covenant 3 as Django’s New Code of Conduct

<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

<div class="md">One client, eight businesses, 200M+ shillings portfolio — all visible in one app. CCTV streaming, M-Pesa float monitoring, KRA auto-filing, carwash payroll splits, law firm case management. All built here, hosted here. Full write-up: <a href="https://medium.com/@updatedennismwangi/we-built-the-operating-system-for-african-business-and-it-goes-all-the-way-down-to-the-kernel-2ad9b2871aa9">https://medium.com/@updatedennismwangi/we-built-the-operating-system-for-african-business-and-it-goes-all-the-way-down-to-the-kernel-2ad9b2871aa9</a> </div> &#32; submitted by &#32; <a href="https://www.reddit.com/user/updatedennis"> /u/updatedennis </a> <a href="https://www.reddit.com/r/django/comments/1r9pyew/we_built_a_full_business_os_in_kenya_kernel_to_ui/">[link]</a> &#32; <a href="https://www.reddit.com/r/django/comments/1r9pyew/we_built_a_full_business_os_in_kenya_kernel_to_ui/">[comments]</a>

One client, eight businesses, 200M+ shillings portfolio — all visible in one app. CCTV streaming, M-Pesa float monitoring, KRA auto-filing, carwash payroll splits, law firm case management. All built here, hosted here.
 Full write-up: https://medium.com/@updatedennismwangi/we-built-the-operating-system-for-african-business-and-it-goes-all-the-way-down-to-the-kernel-2ad9b2871aa9
    submitted by    /u/updatedennis  
 [link]   [comments]

We built a full business OS in Kenya — kernel to UI, servers in-country, no foreign cloud. Here's the story.

&#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?

<div class="md">Hi everyone I finished a Backend Bootcamp 2 years ago. Since then I&#39;ve been building small projects, but also I was busy managing and closing my previous business. For the last 2 months, I&#39;ve been focused full-time in coding and looking for job opportunities. This is the &#39;big&#39; project where I really tried to use best practices. I&#39;ve been looking for a role for 2 months now but I only get rejections or ghosting. I even tried to volunteer for 4 NGOs listed in idealist dot org but none of them replied. The Project: -Fkapi: REST API and scraper that extracts data from footballkitarchive. Using Django Ninja, Celery and Redis -FootyCollect: Django fullstack project to manage football collections. Similar technologies as above (Connected to Fkapi) I need to now if my project is good enough to get a Junior role. Please feel free to check the project and give some feedback about it. Github: <a href="https://github.com/sunr4y/FootyCollect">https://github.com/sunr4y/FootyCollect</a> Live demo: <a href="https://footycollect-demo.sunr4y.dev/">footycollect-demo.sunr4y.dev/</a> PS: If anyone its in similar situation and want to collaborate in a project I would be happy to start something together </div> &#32; submitted by &#32; <a href="https://www.reddit.com/user/sunr4ydev"> /u/sunr4ydev </a> <a href="https://www.reddit.com/r/django/comments/1r9ts3r/seeking_feedback_on_my_django_project/">[link]</a> &#32; <a href="https://www.reddit.com/r/django/comments/1r9ts3r/seeking_feedback_on_my_django_project/">[comments]</a>

Hi everyone
 I finished a Backend Bootcamp 2 years ago. Since then I've been building small projects, but also I was busy managing and closing my previous business. For the last 2 months, I've been focused full-time in coding and looking for job opportunities. This is the 'big' project where I really tried to use best practices.
 I've been looking for a role for 2 months now but I only get rejections or ghosting. I even tried to volunteer for 4 NGOs listed in idealist dot org but none of them replied.
 The Project:
 -Fkapi: REST API and scraper that extracts data from footballkitarchive. Using Django Ninja, Celery and Redis
 -FootyCollect: Django fullstack project to manage football collections. Similar technologies as above (Connected to Fkapi)
 I need to now if my project is good enough to get a Junior role. Please feel free to check the project and give some feedback about it.
 Github: https://github.com/sunr4y/FootyCollect
 Live demo: footycollect-demo.sunr4y.dev/
 PS: If anyone its in similar situation and want to collaborate in a project I would be happy to start something together
    submitted by    /u/sunr4ydev  
 [link]   [comments]

Seeking feedback on my Django project

<div class="md">Another update on <a href="https://github.com/gettranslatebot/translatebot-django">TranslateBot</a>, my open source tool for translating Django <code>.po</code> files with LLMs. For those who haven&#39;t seen the previous posts: TranslateBot scans your <code>.po</code> files, translates untranslated entries using whatever LLM you want (OpenAI, Claude, Gemini, etc.), and preserves all your placeholders. You put a <code>TRANSLATING.md</code> in your project to control terminology and tone across languages. The new feature in <code>v0.7.0</code>: <code>check_translations</code> management command I kept running into a problem where someone would add new translatable strings, run <code>makemessages</code>, but forget to actually translate them. Everything works fine in development (English fallback), and then you deploy and your German users see blank strings or English mixed in. <code>check_translations</code> catches this. It scans all your <code>.po</code> files for untranslated or fuzzy entries and exits with code 1 if anything is missing. Meant to be dropped into CI so you never ship incomplete translations again. <pre><code># simple check ./manage.py check_translations # or run makemessages first, then check ./manage.py check_translations --makemessages </code></pre> The <code>--makemessages</code> flag runs <code>makemessages -a --no-obsolete</code> before checking, so you can do it all in one step. Handy if you want CI to verify that no one forgot to update the <code>.po</code> files after adding new strings. Output looks like: <pre><code>locale/nl/LC_MESSAGES/django.po: OK (120 translated) locale/de/LC_MESSAGES/django.po: 3 untranslated, 1 fuzzy </code></pre> If anything is off, it fails the build. If everything is complete, exit code 0. Project links: - Docs: <a href="https://translatebot.dev/docs/">https://translatebot.dev/docs/</a> - GitHub: <a href="https://github.com/gettranslatebot/translatebot-django">https://github.com/gettranslatebot/translatebot-django</a> 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/1r9o5gp/translatebot_v070_catch_missing_translations_in/">[link]</a> &#32; <a href="https://www.reddit.com/r/django/comments/1r9o5gp/translatebot_v070_catch_missing_translations_in/">[comments]</a>

Another update on TranslateBot, my open source tool for translating Django .po files with LLMs.
 For those who haven't seen the previous posts: TranslateBot scans your .po files, translates untranslated entries using whatever LLM you want (OpenAI, Claude, Gemini, etc.), and preserves all your placeholders. You put a TRANSLATING.md in your project to control terminology and tone across languages.
 The new feature in v0.7.0: check_translations management command
 I kept running into a problem where someone would add new translatable strings, run makemessages, but forget to actually translate them. Everything works fine in development (English fallback), and then you deploy and your German users see blank strings or English mixed in.
 check_translations catches this. It scans all your .po files for untranslated or fuzzy entries and exits with code 1 if anything is missing. Meant to be dropped into CI so you never ship incomplete translations again.
 # simple check ./manage.py check_translations # or run makemessages first, then check ./manage.py check_translations --makemessages 
 The --makemessages flag runs makemessages -a --no-obsolete before checking, so you can do it all in one step. Handy if you want CI to verify that no one forgot to update the .po files after adding new strings.
 Output looks like:
 locale/nl/LC_MESSAGES/django.po: OK (120 translated) locale/de/LC_MESSAGES/django.po: 3 untranslated, 1 fuzzy 
 If anything is off, it fails the build. If everything is complete, exit code 0.
 Project links:
 - Docs: https://translatebot.dev/docs/
 - GitHub: https://github.com/gettranslatebot/translatebot-django
 Feedback / feature ideas are welcome, just as patches :)!
    submitted by    /u/leipegokker  
 [link]   [comments]

TranslateBot v0.7.0: catch missing translations in CI before they hit production

<div class="md"><h2>Building recurring meeting slots in Django feels simple… until it’s not.</h2> I’ve built booking systems a few times now — the typical “doctor availability / meeting slots / interview scheduling” kind of thing. Every single time I started with the same confidence: <blockquote> start_time + end_time + recurrence rule. Done. </blockquote> And every single time it exploded in complexity. The real problems start when users do normal human things: <ul> <li>“Change timing, but only for future slots.”</li> <li>“Cancel just this one date.”</li> <li>“Reschedule one occurrence.”</li> <li>“Don’t let two people book the same slot.”</li> <li>“Oh, and we support timezones.”</li> </ul> Now you’re not storing slots. You’re managing: <ul> <li>A recurring definition </li> <li>Concrete generated instances </li> <li>Per-instance exceptions </li> <li>Booking constraints </li> <li>Concurrency </li> </ul> And if you regenerate slots after an edit, you better not accidentally recreate something that was cancelled. If two processes try generating future slots at the same time, you better not duplicate rows. If DST shifts, you better not drift the entire series. At some point I realized this isn’t CRUD. It’s a state machine with invariants. The invariant that kept biting me: <blockquote> A cancelled or modified instance must never reappear when the series regenerates. </blockquote> That sounds obvious. It’s not trivial. After rebuilding this logic multiple times, I extracted it into a reusable Django package called <code>timeblocks</code> because I was tired of rewriting the same edge-case handling. Curious how others here are solving recurring meeting slot systems in Django. Are you: - Pre-generating? - Calculating dynamically? - Using RRULE directly? - Rolling everything custom? What broke first in your implementation? </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/1r97q3y/building_recurring_meeting_slots_in_django_is_way/">[link]</a> &#32; <a href="https://www.reddit.com/r/django/comments/1r97q3y/building_recurring_meeting_slots_in_django_is_way/">[comments]</a>

Building recurring meeting slots in Django feels simple… until it’s not.
 I’ve built booking systems a few times now — the typical “doctor availability / meeting slots / interview scheduling” kind of thing.
 Every single time I started with the same confidence:
  
start_time + end_time + recurrence rule. Done.
  
And every single time it exploded in complexity.
 The real problems start when users do normal human things:
  
“Change timing, but only for future slots.”
 “Cancel just this one date.”
 “Reschedule one occurrence.”
 “Don’t let two people book the same slot.”
 “Oh, and we support timezones.”
  
Now you’re not storing slots.
 You’re managing:
  
A recurring definition
 
Concrete generated instances
 
Per-instance exceptions
 
Booking constraints
 
Concurrency
 
 And if you regenerate slots after an edit, you better not accidentally recreate something that was cancelled.
 If two processes try generating future slots at the same time, you better not duplicate rows.
 If DST shifts, you better not drift the entire series.
 At some point I realized this isn’t CRUD.
 It’s a state machine with invariants.
 The invariant that kept biting me:
  
A cancelled or modified instance must never reappear when the series regenerates.
  
That sounds obvious. It’s not trivial.
 After rebuilding this logic multiple times, I extracted it into a reusable Django package called timeblocks because I was tired of rewriting the same edge-case handling.
 Curious how others here are solving recurring meeting slot systems in Django.
 Are you: - Pre-generating? - Calculating dynamically? - Using RRULE directly? - Rolling everything custom?
 What broke first in your implementation?
    submitted by    /u/disizrj  
 [link]   [comments]

Building recurring meeting slots in Django is way more complex than it looks. How are you handling it?

&#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  
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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">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">That&#39;s why I have just launched Flask Vibe: 👉 <a href="https://www.flaskvibe.com/">https://www.flaskvibe.com/</a> I&#39;ve also released a lightweight Flask-based analytics solution. One-click deploy to Railway or Render, MCP ready + Telegram and Discord bot: <a href="https://github.com/callmefredcom/NanoAnalytics">https://github.com/callmefredcom/NanoAnalytics</a> </div> &#32; submitted by &#32; <a href="https://www.reddit.com/user/astonfred"> /u/astonfred </a> <a href="https://www.reddit.com/r/flask/comments/1r9rjj2/i_am_a_huge_python_flask_fan_its_my_favourite/">[link]</a> &#32; <a href="https://www.reddit.com/r/flask/comments/1r9rjj2/i_am_a_huge_python_flask_fan_its_my_favourite/">[comments]</a>

That's why I have just launched Flask Vibe:
 👉 https://www.flaskvibe.com/
 I've also released a lightweight Flask-based analytics solution.
 One-click deploy to Railway or Render, MCP ready + Telegram and Discord bot:
 https://github.com/callmefredcom/NanoAnalytics
    submitted by    /u/astonfred  
 [link]   [comments]

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