How FastAPI Handles Requests Behind the Scenes

Рет қаралды 24,909

Күн бұрын

Unleash the power of FastAPI! Discover how Asyncio and blocking I/O impact performance. Learn to handle requests concurrently for a blazing-fast API! In this video, we explore FastAPI's handling of concurrent requests. We'll compare Asyncio vs Blocking methods and see how normal functions differ. Understand when to use each approach for optimal performance. Optimize your FastAPI application and handle more requests efficiently. Subscribe for more FastAPI deep dives!
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#FastAPI #Asyncio #Python #WebDevelopment

Пікірлер: 38

@moneeshkumar1838 4 ай бұрын

Great content brother Quick Modification: sync router is Concurrency not Parallelism. In python parallelism is achieved only by multiprocessing

@vladhaidukkk-learning 5 ай бұрын

Great video, but I think it’s important to mention that multi-threading in Python is not parallel

@bakasenpaidesu 4 ай бұрын

Multi processing*

@vladhaidukkk-learning 4 ай бұрын

@@bakasenpaidesu Actually you are wrong; multiprocessing is parallel because Python spawns an entirely new process with an entirely new interpreter.

@benshapiro9731 3 ай бұрын

Multi threading in python is technically also parallel programming whenever a thread releases the GIL, such as during time.sleep or open calls. In those specific instances, there can be two (or more) threads truly executing in parallel in the same python process, because one thread is waiting for the results of a system call, during which time it releases the GIL since reference counts don’t need to be updated, allowing another thread to acquire the GIL and execute a piece of code in parallel.

@benshapiro9731 3 ай бұрын

On this topic also: check out the beta of. Python 3.13! There is a flag that can be passed when launching python that removes the GIL, allowing truly parallelized execution with just threads. Been playing around with asyncio and concurrent.futures.ThreadPoolExecutor -> noticeable speed up. Shame that c-extension based libraries like numpy are unusable with this setting

@vladhaidukkk-learning 3 ай бұрын

@@benshapiro9731 This is called concurrency, not parallelism. Parallelism is when two or more tasks can run simultaneously, using the CPU, without waiting for I/O-bound operations. While the GIL doesn't prevent Python from switching context between threads waiting for I/O-bound operations, this is still considered concurrency, not parallelism.

@정하은-h6s 5 ай бұрын

OMG! This is so helpful and a great video. Thank you and please post more videos like this!

@ishaquenizamani9800 4 ай бұрын

Thanks for clearing this concept.

@AnaskiBaithak 6 ай бұрын

Thank you for this, I always wondered the difference between async def and def

@hyakuheli 4 күн бұрын

what happens if the server is created with multiple processes (for multiple cores) with uvicorn main:app --workers 4. The first 4 clients are given a new process? or it can be either a process or another thread if a thread is in a non-blocking task? and what happens when there are more than 4 clients at the same time in this case? the new clients are assigned to threads randomly across the 4 processes?

@sany2k8 3 ай бұрын

Great explanation, you should create more videos bro...

@PyPeak 3 ай бұрын

Beautifully explained!

@Shane1994322 3 ай бұрын

Clearly explained!! Thank you

@rainbowrunner1136 Ай бұрын

Hello, great video. I am super new to python. And started using very recently for backend where its being used along with FastAPI. Can you please tell me what are some concepts/ topics which I should be aware for developing efficient code. For eg from this video, I learnt that which function runs concurrently and which doesn't. I had no idea tbh about this before. If you could spare few minutes and share some stuff which I should know it would be great.

@sticksen 3 ай бұрын

My question would be how FastAPI then manages workload when it´s handed over to the worker thread. Because I can only see one worker thread running, at the same time it handles 40 'workloads' concurrently.

@ArulMuruganAS 23 күн бұрын

its working as explained in unix but for some reason its a different behavior in windows

@lwangacaleb2729 4 ай бұрын

I need some help, I want to create a fast api endpoint that calls a synchronous function that has a lot of blocking I/0 operations. But I want the endpoint function to run asynchronously so it can accept many requests at the same time. How should I do this, is there an alternative approach?

@Praise-rs4mc 3 ай бұрын

The only way to achieve that is to use multi-threading which I advice against.... instead, make the function asynchronous and try to find the non-blocking function for what you want to do...

@Praise-rs4mc 3 ай бұрын

Better still, use the run_in_threadpool function from fastapi to run the process in a different thread so that you don't block the event...better than implementing multi threading on your own.

@lwangacaleb2729 3 ай бұрын

@@Praise-rs4mc thanks alot, I will give it a try.

@PriyankRupareliya 5 күн бұрын

This is very valuable content. New job, starting to work on FastAPI. The whole python paradigm is new for me. This video helped clear one of the most critical concept for me. Thanks brother.

@adityahpatel 15 күн бұрын

2 and 3 look the same. hello of each is printed first then bye from each. how is 2 and 3 different? its not explained crystal clearly

@thanhlongle6276 5 ай бұрын

Thanks man for the video. I am trying to use fast api for db CRUD, which one do you think i should use for get post put and delete?

@codecollider 5 ай бұрын

It depends on whether your database library supports non-blocking queries. Ideally, for endpoints involving database calls, use async def if your library allows awaiting query execution (like await db.execute()). If you're using SQLAlchemy, it provides both blocking and non-blocking methods for queries. It's generally recommended to use the non-blocking approach for better performance.

@thanhlongle6276 5 ай бұрын

@@codecollider thank you, everything i write is in normal, non async, and I am using sqlite3 package. I think i will use normal def for all of it, since they are all parallel, and the blocking of read and write on database is performed by SQLite itself

@arjunc5896 3 ай бұрын

def endpoint3() is not running parallely for me as supposed to what u said in the video. Instead it is sunning one at a time. Do u know why?

@codecollider 3 ай бұрын

I believe you are testing APIs in the browser. Sometimes, browsers like Chrome have limitations on making parallel requests to the same URL. In the video, if you look closely, I am using two different browsers to hit the same API in parallel. You can try the same approach.

@arjunc5896 3 ай бұрын

@@codecollider Yes you are right. I tried from different browsers and it worked. Strange though. Thanks