---
title: 'Django vs Flask vs FastAPI. Which Should You Learn?'
source: 'https://youtube.com/watch?v=UDrhJdWzEBk'
video_id: 'UDrhJdWzEBk'
date: 2026-06-16
duration_sec: 693
---

# Django vs Flask vs FastAPI. Which Should You Learn?

> Source: [Django vs Flask vs FastAPI. Which Should You Learn?](https://youtube.com/watch?v=UDrhJdWzEBk)

## Summary

The video provides an honest comparison of Django, Flask, and FastAPI based on the creator's real-world experience shipping production apps with all three. It breaks down performance, job market trends, AI integration, learning curves, and ecosystem to help viewers choose the right framework for their goals.

### Key Points

- **Real-world experience with all three frameworks** [0:00] — The creator has built e-commerce platforms with Django, microservices with Flask, and AI-powered apps with FastAPI, giving them a comprehensive perspective.
- **Why framework choice matters** [0:40] — Learning a framework takes 2-500 hours (3-6 months of evenings/weekends). Picking wrong wastes half a year on a skill that doesn't match your goals.
- **UK job market trends** [1:06] — Django has ~3,200 listings, Flask ~1,800, FastAPI ~1,400 but growing 340% in 2 years. FastAPI salaries are higher on average due to AI/ML roles.
- **Contenders overview** [1:26] — Django (2005): batteries-included, opinionated. Flask (2010): micro-framework, flexible. FastAPI (2018): async, type hints, automatic docs.
- **Comparison categories** [2:17] — Six categories: learning curve, performance, AI/ML integration, job market, ecosystem, development speed.
- **Learning curve: Flask wins hello world, Django ships faster** [2:48] — Flask: instant gratification but complexity grows. FastAPI: steeper start due to type hints/async, but automatic docs save time. Django: steepest initial curve but developers ship complete projects faster because they don't google authentication libraries at 2am.
- **Performance benchmarks** [3:41] — FastAPI: ~9,000 req/s, Flask: ~2,500, Django: ~1,800. FastAPI is 300% faster than Django. However, database and external API calls are usually the real bottleneck.
- **AI integration: FastAPI is purpose-built** [4:41] — FastAPI's native async supports calling AI APIs without blocking. Type hints work with Pydantic for structured outputs. Django's async is bolted on (v4.1). Flask requires manual wiring.
- **Job market details** [5:35] — Django: stable, enterprise-focused (internal tools, e-commerce). FastAPI: emerging, startup-heavy, AI-adjacent. Django pays reliably; FastAPI offers bigger opportunities.
- **Ecosystem comparison** [6:32] — Django: enormous ecosystem, 300k Stack Overflow questions. Flask: wide but fragmented (decision fatigue). FastAPI: smaller but modern (SQLModel, LangChain).
- **Development speed** [7:24] — Django: fastest for full web apps (MVP in a weekend). Flask: fastest for simple REST APIs. FastAPI: fastest for modern async APIs with auto-docs.
- **Decision matrix** [8:11] — AI APIs/async: FastAPI. Full web app/admin: Django. Learning fundamentals: Flask. Automation/microservices: Flask or FastAPI.
- **Recommendation for 2025** [8:58] — Learn Django fundamentals first, then add FastAPI for AI projects. Django teaches architecture and provides stable jobs; FastAPI is for future AI work.
- **90-day roadmap** [9:55] — Complete beginners: Python + Flask (days 1-30), Django (31-60), build project (61-90). Django devs: async Python (1-30), FastAPI + AI (31-60), rebuild API (61-90). Career changers: skip Flask, Django intensive (1-60), portfolio (61-90).

### Conclusion

Django is best for full applications and stable jobs, FastAPI for AI APIs and modern async, and Flask for learning fundamentals. The creator recommends learning Django first, then adding FastAPI for AI projects.

## Transcript

I've shipped production apps with all
these three frameworks. Django, Flask,
and Fast API. And here's what nobody on
Reddit will tell you. They're all lying
to you. Not intentionally, but every
Django is dead or Flask is outdated post
written by someone who's never actually
built something real with all three. I
have e-commerce platforms for Django,
microservices in Flask, and AI powered
apps and APIs for fast API. And the
answer to which one should I learn isn't
what you think. In this video, I'm going
to give you the honest breakdown,
performance, jobs, AI integration,
learning curve, everything that you need
to make the right decision for your
situation. Let's settle this.
Here's why this decision matters more
than ever. Learning a framework properly
takes between 2 to 500 hours. That's 3
to 6 months of your evenings and
weekends. Pick wrong. You've just burnt
half a year on a skill that doesn't even
match your goals. And now the world is
different. AI integration isn't optional
anymore. Clients expect it. Employers
require it. So, the framework that you
choose determines how painful or how
seamless that integration can be. So,
let's have a look at the UK job market
right now. Django posts are pretty
steady. Flask sits just below, but fast
API, it's grown 340% in 2 years. The
landscape is shifting and choosing based
on a tutorial that you watched in 2021,
that's a mistake. So, let me show you
what's actually changed.
Let's meet our contenders. Django born
in 2005. The batteries included
framework. Everything you need comes out
of the box. Authentication, admin panel,
OM security. It's opinionated and it's
proud of it. Then we have Flask. Born in
2010, the micro framework. Minimal core,
maximum flexibility. You choose every
component. Perfect for learning how web
apps actually work. And then we have
fast API. Born in 2018, the modern
asynchronous framework built for APIs
from day one. Type hints, automatic
documentation, and speed that
embarrasses the competition. Three
different philosophies, three different
eras of Python development. The question
is not which is best. It's which matches
what you're trying to build and where
you want to end up. Let's break down
exactly how they compare.
And here's how we'll compare them. Six
categories that actually matter.
Learning curve, how fast can you
actually build something real?
Performance, raw speed when it counts,
AI and ML integration, the modern
factor. Job market, where's the money?
Ecosystem packages plugins community
support, all that good stuff. And then
finally, development speed from zero to
production, how long does it actually
take? By the end, you'll know exactly
which framework deserves your next 6
months. So, let's start with the
question everyone asks first. How fast
can you build something real? Flask wins
the hello world race. You can have a
working API in under 20 lines of code.
Instant gratification. But here's the
trap. That simplicity disappears fast.
Add authentication. You're choosing
between five different libraries. A
database and other decision. Every
feature means more research. Fast API
sits in the middle. Slightly steeper
start because of the type hints and
asynchronous concepts, but once they
click, they click forever. and the
automatic documentation saves hours.
Now, Django has the steepest initial
curve. Models, views, templates, the OM.
There's a lot to learn up front, but
here's what I discovered after teaching
all three. Django developers ship
complete projects faster because they're
not googling best flask authentication
library at 2 a.m. The investment pays
off. It just takes longer to start
paying. Now, let's talk speed. Raw
performance numbers. Fast API handles
around 9,000 requests per second in
standard benchmarks. Flask manages about
2,500. Django trails at roughly 1,800.
Fast API is 300% faster than Django.
Those numbers are real. But here's what
benchmark obsessives won't tell you.
Your database is slower than any
framework. Your external API calls are
slower. Your business logic is slower.
Unless you're building a highfrequency
trading platform or handling millions of
concurrent connections, framework speed
is rarely your bottleneck. I've built
Django apps that serve hundreds of
thousands of daily users. Never once was
Django the performance problem. It was
always the database queries or something
else wrapped around it. That said, if
you're building real-time features,
websocket connections, or AI inference
APIs where every millisecond counts,
Fast API's asynchronous architecture
genuinely matters. So know your use
case, then worry about the benchmarks.
This is the factor that matters a lot
today and it might be the deciding one
for you. If you're building AI powered
applications, fast API is purpose-built
for this. Native asynchronous support
means you can call claude open AAI or
your local LLM without blocking other
requests. Type hints work beautifully
with Pyantic models for structured AI
outputs. and the automatic open API docs
perfect for integrating with AI
orchestration tools like Langchain.
Django's catching up. Asynchronous views
landed in version 4.1, but it's bolted
on. It's not builtin. You'll fight the
framework occasionally. Flask can do
everything, but you're assembling it all
yourself. Every async pattern, every AI
integration requires manual wiring. Now,
when I show you the decision matrix in a
few minutes, you'll see exactly when
fast API becomes the obvious choice. If
AI APIs are your focus, fast API isn't
just good, it is the answer.
Let's look at real job data from 2025.
Django dominates volume around 3,200 UK
listings right now. Average salary
65,000. Senior roles pushing 85,000
plus. Flask holds steady at just below
about 1,800 listings, often paired with
data science roles. Salaries similar to
Django. Now, Fast API has fewer total
listings around 1,400. But look at that
growth arrow. That's 340% increase in 2
years, and the salaries higher on
average because they're mostly AI and ML
engineering roles. Here's the pattern
that I'm seeing. Django jobs are stable,
enterprise focused. You'll be building
internal tools, e-commerce platforms,
content management systems. Fast API
jobs are emerging, startupheavy, AI
adjacent, cutting edge, but fewer
positions. Django pays the bills
reliably. Fast API might be where the
bigger opportunities emerge. It depends
on your risk tolerance.
Packages, plugins, and getting unstuck
at midnight. Ecosystem really does
matter. Django's ecosystem is enormous.
Django rest framework for APIs, Django
admin that clients genuinely love.
Authentication permissions caching
all battle tested for 15 years. Stack
Overflow alone has 300,000 Django
questions. Whatever problem you hit,
somebody has already solved it. Flask's
ecosystem is wide but fragmented. Five
different ways to do everything.
Freedom, yes, but also decision fatigue.
Fast API's ecosystem is smaller but
modern. Purpose-built for contemporary
workflows. SQL model for databases.
Excellent lang chain integration, but
when you hit a weird edge case, fewer
Stack Overflow answers waiting. If this
is clicking for you so far, hit that
like button. It helps other developers
to find this breakdown. Now, let's talk
development speed. From zero to
production, how long does it actually
take? For a full web application with
user or admin panel, and database,
Django wins. I've shipped MVPs in a
weekend using Django's built-in
components. For a simple REST API
serving JSON, Flask gets you there the
fastest. Minimal code, minimal setup.
For a modern async API with automatic
documentation, fast API. The docs alone
save you days of writing swagger specs
manually. Now remember what I said about
Django's learning curve. This is where
it pays off. Yes, you spend more time up
front learning the framework, but you
spend less time building every project
after that. Flask simplicity becomes
complexity at scale. Every project
you're making the same decisions over
and over again. So pick your pain. Steep
learning curve once or gradual
complexity forever.
Now here's your decision matrix.
Screenshot this. Building AI powered
APIs, async services, real-time
features, fast API, no question.
Building a full web application, need an
admin panel, user management,
e-commerce, Django, it's not even close.
Learning Python web development for the
first time, want to understand how
everything works under the hood? Start
with Flask, then graduate to the others.
Building automation scripts or
microservices for internal tools? Flask
or Fast API? Either works. Pick based on
what you need and whether you need
async. Now, notice that I didn't say use
Django for everything or fast API is
always better because that's nonsense.
Tools have purposes. The framework
debates on Reddit, ignore them. Match
the right tool for the right job.
Speaking of which, here's my actual
recommendation. My honest recommendation
for 2025, learn Django fundamentals
first, then add fast API for AI
projects. Here's why. Django teaches you
proper web application architecture,
models, views, security patterns,
authentication. These concepts transfer
everywhere, even when you switch
frameworks. And Django jobs, they're
abundant and stable. You can earn while
you learn. Then when you're comfortable,
add fast API to your toolkit
specifically for AI and async work. This
combination makes you incredibly value.
You can build out the full web
application in Django, then create the
lightning fast AI inference API and fast
API. One developer, both skills. Now,
Flask, it's worth understanding. Read
the source code. It's beautifully
simple, but it's not where I'd invest 6
months in 2025.
The market wants Django experience. The
future wants fast API skills. Get both.
Your 90-day road map. Three paths
depending on where you're starting. If
you're a complete beginner, days 1 to
30, Python fundamentals and flask
basics. Days 31 to 60, Django models,
views, and templates. And then days 61
to 90, build and deploy a complete
project. I've linked the resources in
the description below. Now, if you
already know Django, day 1 to 30, learn
async Python properly. Day 31 to 60,
fast API core concepts plus AI
integration. And then days 61 to 90,
rebuild one of your Django APIs in fast
API. Compare the experience and see what
you think. And then lastly, are you a
career changer from another language?
Skip flask entirely. Days 1 to 60,
Django intensive. Follow the official
tutorial twice. Day 61 to 90, build a
portfolio project and start applying. So
that's the complete breakdown. Django
versus Flask versus Fast API 2025
edition. Quick recap. Django for full
applications and stable jobs. Fast API
for AI APIs and modern async. Flask for
learning fundamentals.
My recommendation, learn Django first,
add fast API second. Now, I'd love to
hear from you. Drop a comment. Which
framework are you choosing and why? I
read all of the comments that you guys
add, so please do let me know. If this
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