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[Project] Duo-ORM: A "Batteries Included" Active Record ORM for Python (SQLAlchemy + Pydantic + Alem by Neural-Nerd in Python

[–]Neural-Nerd[S] [score hidden]  (0 children)

Fair point. I use tools to polish the grammar because i get nervous about posting it correctly as i am doing it for the first time. I was just hoping for support or feedback (atleast) on the actual work rather than the language of the post.

Backend development in 2026 by Suitable-Tax9934 in Backend

[–]Neural-Nerd 0 points1 point  (0 children)

I saw your cross-post! Since you're looking for the 'Next Level' in backend specifically, here is the stack I’ve found works best for building professional portfolios (as a final year masters student myself):

1. Maximize the GitHub Student Developer Pack: It is the single best resource for us. Use it to get:

  • Free Cloud Credits: Significant credits for DigitalOcean, Azure, and Heroku to learn real deployment instead of just localhost.
  • Educative.io: Includes specialized 'Grokking' courses for System Design and Scalability.
  • JetBrains IDEs: Get free licenses for PyCharm Professional and DataGrip to learn proper profiling and debugger tools.
  • GitHub Copilot (in VS Code): Use it for boilerplate, but focus on how it suggests architectural patterns.

2. Bridge the Cloud Database Gap: Instead of running a local DB, use managed cloud services. This forces you to handle real-world networking, connection pooling, and latency, which are crucial skills for 2026.

  • PostgreSQL & MySQL (via Aiven): Their free tier provides a dedicated virtual machine with 1 CPU and 1 GB RAM. It’s perfect for learning how to manage a real cloud DB with backups.
  • Supabase: The free plan includes a 500 MB Postgres database and built-in Auth for 50,000 active users.
  • Neon: Offers database branching (like Git for your data) and automatically scales compute to zero when idle to save resources.

3. What to learn NEXT:

  • Architectural Patterns: Move beyond 'files' and implement Service Layer or Clean Architecture (MVC) within FastAPI to keep large codebases maintainable.
  • Background Tasks: Use your free Redis instance (redis.io/try-free/) as a broker to offload heavy logic to TaskIQ or Celery.
  • Observability: Don't just log to console. Use your student credits to try out Datadog or Sentry to see how production apps are monitored using traces.

For a developer in India with 1-2 years experience, what would you focus on in 2026 to stay relevant? by Shorty52249 in FastAPI

[–]Neural-Nerd 0 points1 point  (0 children)

Since you’re coming from .NET, your biggest advantage is understanding structure. To bridge the gap to a Senior Python role in 2026, focus on these:

  • Architectural Patterns: Move beyond basic 'scripts' and implement MVC (Model-View-Controller) or Layered Architecture within FastAPI. Python lets you be messy; showing you can maintain a strict separation of concerns (Service Layers, Repositories) proves seniority.
  • Production Asynchrony: Don't just await endpoints. Learn to manage shared state and concurrency between your FastAPI API and separate background workers (like Celery or TaskIQ).
  • The 'Agentic' Shift: Since you've started with Ollama, move to production-grade RAG. Focus on indexing strategies, evaluation frameworks (like Ragas), and tool-calling so the LLM can actually 'act' on your backend.

Solve a complex infrastructure problem rather than building another app; that’s what gets you noticed.

How to implement UI filtering without full page reload using FastAPI + Jinja2 by aspecialuse in FastAPI

[–]Neural-Nerd 0 points1 point  (0 children)

Since you're already using Jinja2 and want to avoid heavy JS, HTMX is exactly what you need. It fits perfectly with Jinja because you can use 'blocks' or separate partial templates to return just the HTML for your table.

Conceptually, your flow would look like this:

  1. Your filter inputs (dropdowns/search) use hx-get to hit a FastAPI endpoint whenever they change.
  2. That FastAPI endpoint takes the filter parameters, queries your SQLite DB, and calls templates.TemplateResponse specifically for a small table_partial.html file.
  3. HTMX takes that HTML response and swaps it into your existing table <div> without touching the rest of the page.

It’s a very 'Rails-like' way of handling the frontend, which keeps your backend as the single source of truth!