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#fastapi

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🌟 Beginner Tutorial Alert at #EuroSciPy2025:

Deploy your Machine Learning model with FastAPI
📣 With Cheuk Ting Ho

Learn to:
🔹 Build an API for your pre-trained ML model
🔄 Design retraining workflows
🪄 Move from prototype to production-ready service
🛠️ Package in Docker & deploy to the cloud

Perfect for data scientists new to FastAPI or ML deployment.

📍 Kraków | 🗓️ August 18–22
🗓️ euroscipy.org/schedule

euroscipy.orgEuroSciPy 2025 ScheduleThe EuroSciPy meeting is a cross-disciplinary gathering focused on the use and development of the Python language in scientific research.

One of the joys of my current role has been getting to code Python at enterprise level, rather than ‘enthusiastic hobbyist’, and learning current industry best practices from my colleagues.

Case in point, I just migrated a project from Flask to FastAPI and swapped out aiohttp for httpx.

✅ FastAPI: Async-first, type hints, Pydantic integration = dev happiness
✅ httpx: Cleaner API, connection pooling, great with async/await

It feels like I’m finally stepping into 2025 with both feet! (Albeit halfway through the year)

#Python#FastAPI#httpx

Choosing a hash function for 2030 and beyond: SHA-2 vs SHA-3 vs BLAKE3

As everyone knows, "temporary fixes" are nothing but temporary.
Unfortunately, the same is true for cryptography: unless security is your core value-proposition, crypto algorithms are almost never updated, and that's how we end up with SHA1-hashed password in 2024 🤦‍♂️

# kerkour.com/fast-secure-hash-f

#hash#hashfunctions#coding

looking for an #OSS #APIgateway

* API keys (API users) + Oauth (website) for auth
* rate limiting + protection against content crawling
* queuing requests to prevent overloading our self-hosted AI models
* ability to track usage so that we can charge expensive API calls to users/orgs
* basic monitoring

API will most likely be written in #NestJS, another likely using #FastAPI (or something else in #Python). I like #GitOps. Doesn’t need to handle insane traffic just make the above things easier.

Antwortete im Thread

@djangonews @_chrismay @carlton @wsvincent I built/support a few #FastAPI applications in prod, my $0.02:

1. Focus on one explicit use case. No templates, no ORM, etc. so the surface area/ramp up much smaller than Django.
2. Defined happy paths, less analysis paralysis.
3. I personally feel that all-async is a little overblown, but others obviously don't. Plus, “the fastest x” is always good marketing.
4. Ride the AI boom.

TBH, I think #Django can learn from some of this. 😅

I need to learn more about how databases work and the best way to setup relationships in SQLModel. I was working on Rack Root tonight and am still running into an issue with some circular dependencies I'm having between various tables. I need these relationships to enhance the data/utility of the app, but might need to rethink how I'm actually putting them together.

The other fun part of this is that I'm learning that the way I test the app and the way I run the app isn't always the same. The tests will run fine the first time against my test Postgres container, but subsequent runs don't work because of how I tell the test DB to drop all data before running the tests. It's complaining about the relationships, but really I think I need to tell it to either cascade delete or just ignore something.