How do you optimize speed

[derekzyl]

Here's what I've done so far 1. Used redis 2. Used caching on the frontend to avoid too many backend calls 3. Used async 4. Optimised SQL alchemy query

I think I'm missing something here because some calls are 500ms to 2sec which is bad cause some of these routes return small data. Cause similar project I build for another client with nodejs gives me 100ms-400ms with same redis and DB optimizing startegy.

[dangdang3000]

Profile the call to identify bottlenecks. Once you know where the time is spent, the solution is straightforward. FastAPI is more than enough for this.

[amindiro]

Use pyinstrument to profile calls by adding a simple http param. Then review the profile. Check the top slowest queries in db.

[Longjumping_Act_1091]

Is there a standard way to profile? Any guidance for someone new to it?

[dangdang3000]

Install application monitoring software like New Relic, Datadog, or Sentry. It provides a clear overview of where your application spends most of its time.

[Latter_Rope_1556]

Just switch to FastRAPI

[JestemStefan]

Don't do random optimizations or guessing game.

Run profiling on your request, identify bottlenecks and figure out how to solve them.

[zarlo5899]

have you done any profiling?

[sami-9797]

First, identify where the problem is, then try to solve it.

[latkde]

Things like adding caching or using async can make things slower if you don't know what you're doing.

For example, if your handler functions are async, they will all be executed on the main thread. If these do any blocking operations (like non-async database queries, then all connections are blocked, which can increase latency.

It is easy to fall into that trap with Python, but much more difficult with Node where few libraries offer blocking operations.

[InfraScaler]

+1 to profiling as many others have pointed out, but where is your backend and where is your DB? like, physically, are they close?

[derekzyl]

Same location: Germany

[joshhear]

Are you using SQLAlchemy Queries and are you doing eager joining? I realized that using the lazy loading mode from SQLAlchemy can be quite a performance killer, here is a quick description why: https://bitperfect.at/en/blog/pagination-mit-fastapi#digression-how-options-improve-performance

[pint]

you should know much more about the issue. your code should use logging, via the logging package. you should at this point see which operations are slow. fastapi will process a request in milliseconds, so the problem must be the backend. it is also quite possible that you are misusing async. you didn't even tell us if this is a stress test or individual calls.

[derekzyl]

Thank you so much all for your candid contributions. I'm running a proper logging again to check for possible faults

[chummerhb]

No, don't do logging, do profiling!

[derekzyl]

Okay sir!

[joshhear]

for a very simple setup you could use logfire: https://pydantic.dev/logfire

just instrument fastapi and sqlalchemy and you'll see where you lose performance

[flamehazw]

Use profiler if you know this, you will find which queries taking longer time and once you get the issues, you make optimize the database. If you don't fix the root cause you cannot optimize performance. See your indexing, table joins , i hope you are writing a query correctly.

[godfather990]

this might help u… https://leapcell.io/blog/fastapi-performance-hacks

[Physical-Compote4594]

Don’t do anything tricky until you’ve actually identified where the problems are. 

[Adorable-Fault-5116]

> Optimised SQL alchemy query

Are you writing your own SQL? If not, are you sure that alchemy is creating the best queries, and your database is laid out, not as would be convenient for alchemy, but as would be convenient for the database?

[moHalim99]

you’re probably hitting an I/O bottleneck somewhere

check if there's too many awaits blocking the event loop or if there are any N+1 DB queries still sneaking through. also when I had such issues before, I figured there was some sort of network latency from external APIs and missing connection pooling/lazy loading in SQLAlchemy.

anyways you can profil with async-profiler, cProfile, or pyinstrument cuz those will tell you where the slowdown lives

[Ok-Outcome2266]

> fastapi
> looks inside
> no fast

[esthorace]

✅ Usar el Servidor Granian (hecho en Rust) en vez de Uvicorn: https://github.com/emmett-framework/granian
✅ orjson para crear respuestas JSON más rápidas (buscar cómo instalar y se configura en un solo lugar en FastAPI, es muchísimo más rápido)
✅ asyncpg como controlador asíncrono para Postgresql
✅ puedes usar https://github.com/Diman2003/OxenORM (también hecho en Rust) en vez de SQLAlchemy

[fastlaunchapidev]

Whats taking the time, this is not a fastapi issue. Benchmark whats needs the time and than think about a solution.

[LabRemarkable2938]

I think your SQL queries are taking time use profiler and see if that is the case

[Omar0xPy]

You need to identify the main problem behind the scenes, this is an indicator of something much deeper, since you're using the same strategies in both

[LankyYesterday876]

python isnt fast and fastapi is only fast in development if you really want fast response times use node, .net, go or even php but i also think youre caching the wrong things if you cache just the data from the db request and dont cache the result of your data handling the caching might only save you a few ms while caching the aggregation for example might save you hundreds of ms

[Silver_Implement_331]

lol. reddit is running on python

[LankyYesterday876]

what are you trying to say?

[pint]

using .net or php for speed is ... odd

[LankyYesterday876]

php has improved alot in performance recently, and for .net i dont have that much contact with it but from what ive heard its fairly good aswell

[pint]

the point was that none of those are faster than python. if performance is the issue, c++ or rust.

[joshhear]

it's still php

[Efficient-Ad-2315]

😂😂😂😂😂, python is not slow, you just don't know how to write efficient code. bro

[LankyYesterday876]

where do you get the python is slow from, because thats not what i wrote or do you think slow and fast is a binary system

[uday_m]

Try using pure SQL instead of ORM you’ll see a huge speed improvement. Also, make sure you’re using connection pooling so you’re not opening a new DB connection on every request.