Learn FastAPI, Django, or Flask in 2025? (Python)

[00:00] I recently made a video encouraging

[00:02] React developers to learn Python in 2025

[00:05] if they want to get a job. My reasoning

[00:07] in the video was I went through LinkedIn

[00:10] job postings for React developers. Seven

[00:13] out of 10 of them wanted you to also

[00:15] know Python. That's 70% of the React

[00:18] related job postings on LinkedIn. In

[00:21] this video, I want to talk about some of

[00:22] the popular Python frameworks out there

[00:25] and help you decide which framework you

[00:27] should learn in 2025. First off, the big

[00:30] three web frameworks for Python

[00:32] developers is Flask, Fast API, and

[00:36] Django. Flask and Django are both

[00:39] synchronous frameworks, which means you

[00:41] have to do everything in order. Fast API

[00:44] allows asynchronous development, which

[00:47] makes it up to 5 to 10 times faster than

[00:50] Django and Flask. Now, I'm not a Python

[00:53] expert yet. I'm just now starting to

[00:55] learn myself, but based on what I've

[00:56] studied, it sounds like Flask would be

[00:59] the quickest way to get up and running

[01:01] learning Python. You can whip up a

[01:03] server in no time, but there's not a lot

[01:06] of built-in libraries and features. So,

[01:09] as you're building, if you need to get

[01:10] more and more complex, you're probably

[01:12] going to have to install additional

[01:14] things into the framework as you go

[01:17] along. So Flask is kind of a good way to

[01:19] get started, but it may not be the best

[01:22] for production level development or for

[01:24] getting a job. Django, on the other

[01:26] hand, has everything included in the

[01:29] framework from the get- go. It has an

[01:31] OM, authentication, admin panels, forms,

[01:35] security patches. It's over 15 years

[01:37] old. It has a huge built-in ecosystem,

[01:40] and this is a big statistic. 76% of

[01:44] Python developers use Django. So really,

[01:47] if you're just looking to get a job at

[01:49] maybe an established company, Django's

[01:52] probably the smartest option, it's what

[01:54] most Python developers already use,

[01:57] especially if it's a an established

[01:59] company that maybe has a good bit of job

[02:02] security. Django seems like it would be

[02:04] the best framework to learn if you're

[02:06] just trying to get a job at an

[02:07] established company. Having said that,

[02:10] Fast API is really coming in fast. It's

[02:14] now used by 26% of Python developers.

[02:18] And one of the big reasons which I've

[02:19] already mentioned is that it allows

[02:21] asynchronous development. And so again,

[02:24] it can be 5 to 10 times faster than

[02:26] Django. And so you can be handling

[02:28] thousands of requests per second. And so

[02:31] it's got a lot going for it. Another

[02:33] cool thing about fast API is it

[02:36] generates its own open API docs the

[02:39] moment you hit save. And one of the

[02:41] things about fast API is it's used by a

[02:44] lot of startups and also I've read that

[02:46] a lot of large enterprise companies that

[02:49] currently use Java or.net a lot of these

[02:53] companies do not currently use Python

[02:55] but they're wanting to integrate AI into

[02:58] all of their systems but their systems

[03:00] are just so enormous that it would be

[03:02] impractical to move their entire system

[03:05] over to Python. So a lot of these bigger

[03:07] companies are kind of taking a hybrid

[03:09] approach instead of rewriting

[03:11] everything. They're using fast API to

[03:14] just connect part of their service, part

[03:17] of their codebase to Pythonbased AI

[03:20] systems. So a lot of enterprise level

[03:23] software companies are using fast API to

[03:26] integrate AI into their systems right

[03:29] now. And I read something like 45% of

[03:32] them are doing it. So while Django is

[03:34] used by 76% of Python developers,

[03:38] something to really think about is fast

[03:39] API is now being used by 45% of large

[03:43] companies who are trying to integrate AI

[03:46] into their systems. And again, it's just

[03:48] really fast. And so that could be a lot

[03:50] more attractive to startups that value

[03:53] being fast. And it's also great if you

[03:55] need to be running a lot of different

[03:57] functions at the same time, managing

[03:59] different calls at the same time. And so

[04:02] in conclusion, if I had to give you

[04:04] advice on what to learn, I would say it

[04:06] kind of depends on what you want to do

[04:08] in your career. If you're looking to get

[04:10] into anything related to AI, it seems

[04:13] like fast API would be the way to go. It

[04:16] seems to be used a lot for AI

[04:19] specifically. But if you're looking to

[04:20] get a stable, secure job at a

[04:23] well-established company, you may want

[04:24] to learn Django instead. That seems to

[04:26] be the smartest play simply because so

[04:29] many Python developers use Django.

[04:31] Again, 76% of Python developers use

[04:35] Django. But at the end of the day, it

[04:37] would be best to just learn both and

[04:38] even Flask so you can have it on your

[04:40] resume. Just learn all three. As for me,

[04:43] I plan to start with Fast API. I plan to

[04:46] be making some tutorial videos on Fast

[04:48] API soon. So, if you're interested in

[04:50] seeing more of that, I encourage you to

[04:52] subscribe and hit the bell icon to be

[04:54] notified when those videos come out. But

[04:56] I also plan to learn Django and Flask

[04:59] eventually. If you're a Python

[05:00] developer, let us know if I'm giving

[05:02] good advice or not. Maybe I'm not giving

[05:04] good advice. I spent quite a bit of time

[05:06] looking into all this. I hope I gave

[05:09] good advice, but maybe I didn't. Let us

[05:11] know in the comments below. Help us out.

[05:13] Don't forget to like, subscribe, and hit

[05:15] the bell icon if you'd like to see more

[05:17] content like this. Thanks for watching

[05:19] and I'll see you next