FastAPI Reviews

1. Kurslog team

   · Working at Kurslog · 4 months ago

   When our backend team needs to build services for data parsing, aggregators, or high-load APIs, FastAPI is our absolute go-to choice. It completely lives up to its name-development speed is outstanding.

   The combination of Pydantic for data validation and built-in async support keeps our shared codebase clean, strictly typed, and reliable. But the biggest highlight for our cross-functional team is the automatic generation of interactive OpenAPI (Swagger) documentation. Our frontend and mobile developers no longer have to wait for backend engineers to manually update API docs; everything stays perfectly in sync automatically. It has drastically improved our team's communication and delivery speed.

   🏁 Competitors: Django, Flask, ExpressJS, Nest.js, Spring Boot

   👍 Pros:    Blazing fast performance (on par with nodejs and go)|Native asynchronous support out of the box|Automatic, interactive documentation generation (swagger/redoc)|Strict typing and data validation with pydantic

   👎 Cons:    Smaller plug-and-play ecosystem compared to older frameworks like django|Requires our architects to design the project structure and directory layout from scratch

Modal Reviews

FastAPI mentions (311)

• Shipping Sovereign SDK: Cryptographic Forensic Receipts and the End of the AI "Prose Tax"

  The Sovereign SDK is a Python-native framework designed to minimize prose overhead while generating ironclad, cryptographic execution receipts for AI agents, complete with drop-in FastAPI/Starlette ASGI middleware. - Source: dev.to / about 2 months ago

• 5-Minute AI Jobs and Closed Tabs — Why We Built Replay-Then-Tail SSE

  We had a feature in production where a single user request could run for five-plus minutes — fetch documents, chunk them, hit an LLM per chunk, synthesize a final answer. We did the obvious thing first: a FastAPI handler that ran the pipeline and streamed progress back to the browser over Server-Sent Events. - Source: dev.to / 3 months ago

• FastAPI With LangChain and MongoDB

  FastAPI is a Python framework for building APIs quickly, efficiently, and with very little code. - Source: dev.to / 3 months ago

• I Built A " CrowdSense AI " : A Scalable, Context-Aware Platform for Smart Stadiums

  Backend: Python-based FastAPI for its asynchronous I/O capabilities and rapid JSON serialization. - Source: dev.to / 3 months ago

• Async PyMongo in FastAPI

  FastAPI is a high-performance web framework that is production-ready and designed for building APIs in python, with roots embedded in asynchronous programming. It embraces Python’s asyncio model as its core principle rather than treating it as optional. This design choice gives FastAPI leverage for I/O bound workloads such as db access, external API calls and real-time data streaming. - Source: dev.to / 3 months ago

Modal mentions (45)

• EU managed sandboxes for AI agents, in private beta

  If you've used E2B, Daytona, Modal sandboxes, or Cloudflare Sandboxes, the shape is familiar: REST API, Python and JS SDKs, exec / files / snapshot primitives. Here's what the Python SDK looks like:. - Source: dev.to / 2 months ago

• Hermes Agent: The AI That Actually Gets Smarter Every Time You Use It

  The supported environments include your local machine, Docker containers, remote SSH servers, and two serverless options called Daytona and Modal. Daytona and Modal are the interesting ones for beginners as they handle all the infrastructure for you, and you only pay for compute when Hermes is actively doing something. - Source: dev.to / 3 months ago

• Top 5 Code Sandboxes for AI Agents in 2026

  TL;DR: If you just need to ship fast, E2B has the best SDK experience. If you need the fastest cold starts, Blaxel wins at 25ms. For GPU workloads, Modal is unmatched. For self-hosted control, Daytona is open-source with a managed option. For persistent long-running sessions, Fly.io Sprites gives you 100GB NVMe per sandbox. - Source: dev.to / 4 months ago

• Show HN

  * dramatically increasing inference throughput on [modal.com](http://modal.com) meant I could generate 10s of thousands of tiles in a few hours at very little cost, allowing me to experiment much more rapidly This project continues to be a lot of fun, but I’m now mostly focusing on the agentic workflows that power this kind of ambitious generation at scale. Can’t wait to share more soon. - Source: Hacker News / 5 months ago

• Show HN: Skill that lets Claude Code/Codex spin up VMs and GPUs

  Thanks for sharing this interesting project and approach! One suggestion for improvement: Add some more info to your website/GitHub about the need for a provider and which providers are compatible. It took me a bit to figure that out because there was no prominent info about it. Additionally, none of the demos showed a login or authentication part. To me, it seemed like the VMs just came out of nowhere. So at... - Source: Hacker News / 5 months ago