Our developer wants to use Python for our API — is it a solid choice, or just personal comfort?

With modern asynchronous frameworks in Python, I/O-bound data transfers won't run into bottlenecks. Even if a B2B platform's traffic scales to tens of thousands of requests per minute, as long as your database indexes are solid, the bottleneck will be your database, not the language. You have nothing to worry about.

We handle 1.5 million API calls daily on our e-commerce logistics platform using Python microservices. Our monthly cloud server bill barely hits $65. Don't buy into the 'Python is too slow' myth; bad architecture is what actually drains your budget.

Dev preference matters of course, but what happens if that dev leaves tomorrow? Python's talent pool is huge, but writing clean async architecture properly is another story. Definitely verify they're using a clean layered structure and strict typing, otherwise handoffs will turn into an absolute nightmare.

Make sure to add these 3 technical requirements to the contract: 1) Documenting all endpoints with a standard OpenAPI schema. 2) Full use of type hints. 3) At least 70 percent unit test coverage for core scenarios. As long as these three conditions are met, Python won't leave any risks behind.

python is a great choice when it comes to code readability. later on when you hire a new dev for the team it takes a couple of days at most for them to understand the project. in more complex languages that takes weeks.

Regardless of the choice of software architecture, I recommend clarifying the intellectual property and code ownership clauses. Keeping the codebase source code in a private repository owned by your company and checking the licenses of third-party dependencies are essential for your legal security.

Just ask your developer one question: 'Which architecture and asynchronous framework will you use, and how will you manage the database connection pooling?' If they can answer this without hesitation and with clear technical justification, you can move forward with confidence.

Three years ago on the platform I founded, we picked a very niche system on the team's recommendation because 'it would run super fast.' Six months later the lead developer quit and we couldn't find anyone else who knew that language. In the end, we had everything rewritten from scratch in Python and finally breathed a sigh of relief.

Let me share what happened to me; it might be useful. Everyone rushing into api development gets stuck at the same point.

I'm writing this so you don't make the same mistake. Trying to do this alone is the most expensive way.

When making a decision, first look at what data you have on hand. Hope this helps.

I'm a small business let me explain from my side. People defend habits not processes. Resistance comes from there.

Good luck with that.

Timely topic.

I don't think this advice fits everyone. The cheapest quote is usually the least thought-out one.

Hope this helps.

The discussion got scattered, let me summarize. If it's your first time, start small; scaling comes later.

If you post the result here, it will help others too.

i disagree with you on this point. if it's your first time, start small; scaling comes later.

of course it varies if your situation is different.

Let me write how it's done in practice. In legacy systems, the most expensive thing is unknown dependencies.

That's all, sorry if I went on too long.

Let me summarize the topic, since several different answers were given. In legacy systems, the most expensive thing is unknown dependencies.

If you don't write this down from the start, it leads to arguments later. Just leaving this note, it might be useful.

Great work.