Top 10 Python Frameworks for 2024

Python is one of the most versatile programming languages available today. Whether you’re building web applications, APIs, or machine learning models, Python has a framework to simplify the process. Below are the top 10 Python frameworks to learn, along with a brief description, example code, and a link to their official documentation or website.

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1. Django

Category: Web Development
Description: Django is a high-level Python web framework that promotes rapid development and clean, pragmatic design. It’s fully featured and comes with a built-in admin panel, ORM, and many other tools for building scalable web applications.

Why Use It: Fast development, security features, scalability.
Use Cases: Content management systems, e-commerce, social networks.
Example Code:

# Install Django
pip install django
# Create a new Django project
django-admin startproject mysite
# Create a new app
cd mysite
python manage.py startapp myapp
# Example view (in myapp/views.py)
from django.http import HttpResponse
def hello_world(request):
    return HttpResponse("Hello, Django!")
# Install Django
pip install django

# Create a new Django project
django-admin startproject mysite

# Create a new app
cd mysite
python manage.py startapp myapp

# Example view (in myapp/views.py)
from django.http import HttpResponse

def hello_world(request):
    return HttpResponse("Hello, Django!")
# Install Django
pip install django

# Create a new Django project
django-admin startproject mysite

# Create a new app
cd mysite
python manage.py startapp myapp

# Example view (in myapp/views.py)
from django.http import HttpResponse

def hello_world(request):
    return HttpResponse("Hello, Django!")

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link: Django Documentation

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2. Flask

Category: Web Development
Description: Flask is a lightweight and easy-to-use web framework. It’s often called a “micro-framework” because it keeps the core simple but allows you to add plugins and extensions as your project grows.

Why Use It: Simple, highly customizable, lightweight.
Use Cases: APIs, web apps, microservices.
Example Code:

# Install Flask
pip install flask
# Simple Flask app
from flask import Flask
app = Flask(__name__)
@app.route('/')
def hello_world():
    return 'Hello, World!'
if __name__ == '__main__':
    app.run(debug=True)
# Install Flask
pip install flask

# Simple Flask app
from flask import Flask
app = Flask(__name__)

@app.route('/')
def hello_world():
    return 'Hello, World!'

if __name__ == '__main__':
    app.run(debug=True)
# Install Flask
pip install flask

# Simple Flask app
from flask import Flask
app = Flask(__name__)

@app.route('/')
def hello_world():
    return 'Hello, World!'

if __name__ == '__main__':
    app.run(debug=True)

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link: Flask Documentation

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3. FastAPI

Category: Web Development / APIs
Description: FastAPI is one of the fastest frameworks for building APIs with Python, using asynchronous programming. It also includes automatic data validation and documentation generation.

Why Use It: High performance, automatic validation, asynchronous programming.
Use Cases: APIs, microservices, web apps.
Example Code:

# Install FastAPI and Uvicorn
pip install fastapi uvicorn
# Simple FastAPI app
from fastapi import FastAPI
app = FastAPI()
@app.get("/")
def read_root():
    return {"Hello": "World"}
# Run the server: uvicorn main:app --reload
# Install FastAPI and Uvicorn
pip install fastapi uvicorn

# Simple FastAPI app
from fastapi import FastAPI
app = FastAPI()

@app.get("/")
def read_root():
    return {"Hello": "World"}

# Run the server: uvicorn main:app --reload
# Install FastAPI and Uvicorn
pip install fastapi uvicorn

# Simple FastAPI app
from fastapi import FastAPI
app = FastAPI()

@app.get("/")
def read_root():
    return {"Hello": "World"}

# Run the server: uvicorn main:app --reload

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link: FastAPI Documentation

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4. Pyramid

Category: Web Development
Description: Pyramid is a highly flexible web framework that allows developers to build web apps from simple to complex. It is suitable for both large and small projects.

Why Use It: Flexible, scalable, minimal setup.
Use Cases: Large-scale apps, APIs, customizable systems.
Example Code:

# Install Pyramid
pip install "pyramid==2.0"
# Create a Pyramid project
cookiecutter gh:Pylons/pyramid-cookiecutter-starter
# Example view (in views.py)
from pyramid.view import view_config
@view_config(route_name='home', renderer='templates/mytemplate.jinja2')
def my_view(request):
    return {'project': 'Pyramid'}
# Install Pyramid
pip install "pyramid==2.0"

# Create a Pyramid project
cookiecutter gh:Pylons/pyramid-cookiecutter-starter

# Example view (in views.py)
from pyramid.view import view_config

@view_config(route_name='home', renderer='templates/mytemplate.jinja2')
def my_view(request):
    return {'project': 'Pyramid'}
# Install Pyramid
pip install "pyramid==2.0"

# Create a Pyramid project
cookiecutter gh:Pylons/pyramid-cookiecutter-starter

# Example view (in views.py)
from pyramid.view import view_config

@view_config(route_name='home', renderer='templates/mytemplate.jinja2')
def my_view(request):
    return {'project': 'Pyramid'}

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link: Pyramid Documentation

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5. Tornado

Category: Web Development / Networking
Description: Tornado is a web framework and asynchronous networking library that handles long-lived network connections. It’s perfect for building real-time applications such as chat apps.

Why Use It: Asynchronous programming, real-time support.
Use Cases: Real-time apps, chat applications, streaming.
Example Code:

# Install Tornado
pip install tornado
# Simple Tornado app
import tornado.ioloop
import tornado.web
class MainHandler(tornado.web.RequestHandler):
    def get(self):
        self.write("Hello, Tornado!")
def make_app():
    return tornado.web.Application([
        (r"/", MainHandler),
    ])
if __name__ == "__main__":
    app = make_app()
    app.listen(8888)
    tornado.ioloop.IOLoop.current().start()
# Install Tornado
pip install tornado

# Simple Tornado app
import tornado.ioloop
import tornado.web

class MainHandler(tornado.web.RequestHandler):
    def get(self):
        self.write("Hello, Tornado!")

def make_app():
    return tornado.web.Application([
        (r"/", MainHandler),
    ])

if __name__ == "__main__":
    app = make_app()
    app.listen(8888)
    tornado.ioloop.IOLoop.current().start()
# Install Tornado
pip install tornado

# Simple Tornado app
import tornado.ioloop
import tornado.web

class MainHandler(tornado.web.RequestHandler):
    def get(self):
        self.write("Hello, Tornado!")

def make_app():
    return tornado.web.Application([
        (r"/", MainHandler),
    ])

if __name__ == "__main__":
    app = make_app()
    app.listen(8888)
    tornado.ioloop.IOLoop.current().start()

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link: Tornado Documentation

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6. Bottle

Category: Web Development
Description: Bottle is a simple and lightweight web framework for building small web apps. It’s perfect for small projects or for prototyping quickly.

Why Use It: Simple, lightweight, fast to prototype.
Use Cases: Prototypes, small web applications.
Example Code:

# Install Bottle
pip install bottle
# Simple Bottle app
from bottle import route, run
@route('/hello')
def hello():
    return "Hello, Bottle!"
run(host='localhost', port=8080)
# Install Bottle
pip install bottle

# Simple Bottle app
from bottle import route, run

@route('/hello')
def hello():
    return "Hello, Bottle!"

run(host='localhost', port=8080)
# Install Bottle
pip install bottle

# Simple Bottle app
from bottle import route, run

@route('/hello')
def hello():
    return "Hello, Bottle!"

run(host='localhost', port=8080)

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link: Bottle Documentation

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7. CherryPy

Category: Web Development
Description: CherryPy is an object-oriented web framework that allows developers to build web applications in a Pythonic way. It’s a scalable and flexible solution.

Why Use It: Object-oriented, scalable, simple.
Use Cases: Web applications, custom servers.
Example Code:

# Install CherryPy
pip install cherrypy
# Simple CherryPy app
import cherrypy
class HelloWorld(object):
    @cherrypy.expose
    def index(self):
        return "Hello, CherryPy!"
if __name__ == '__main__':
    cherrypy.quickstart(HelloWorld())
# Install CherryPy
pip install cherrypy

# Simple CherryPy app
import cherrypy

class HelloWorld(object):
    @cherrypy.expose
    def index(self):
        return "Hello, CherryPy!"

if __name__ == '__main__':
    cherrypy.quickstart(HelloWorld())
# Install CherryPy
pip install cherrypy

# Simple CherryPy app
import cherrypy

class HelloWorld(object):
    @cherrypy.expose
    def index(self):
        return "Hello, CherryPy!"

if __name__ == '__main__':
    cherrypy.quickstart(HelloWorld())

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link: CherryPy Documentation

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8. Web2py

Category: Web Development
Description: Web2py is a full-stack web framework with an integrated IDE, web server, and database abstraction layer. It’s great for rapid application development.

Why Use It: All-in-one solution, easy deployment, integrated IDE.
Use Cases: Full-stack applications, rapid prototyping.
Example Code:

# Install Web2py
pip install web2py
# Start the web2py server
python web2py.py
# Install Web2py
pip install web2py

# Start the web2py server
python web2py.py
# Install Web2py
pip install web2py

# Start the web2py server
python web2py.py

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link: Web2py Documentation

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9. Dash

Category: Data Visualization
Description: Dash is a Python framework for building web-based data visualizations. It integrates with Plotly to create interactive charts and dashboards.

Why Use It: Great for data visualization, easy to use, integrates with Plotly.
Use Cases: Data dashboards, visualizations, analytics.
Example Code:

# Install Dash and Plotly
pip install dash plotly
# Simple Dash app
import dash
from dash import dcc, html
import plotly.express as px
app = dash.Dash(__name__)
# Create a plot
fig = px.bar(x=["A", "B", "C"], y=[4, 3, 2])
app.layout = html.Div(children=[
    html.H1(children="Hello Dash"),
    dcc.Graph(figure=fig)
])
if __name__ == '__main__':
    app.run_server(debug=True)
# Install Dash and Plotly
pip install dash plotly

# Simple Dash app
import dash
from dash import dcc, html
import plotly.express as px

app = dash.Dash(__name__)

# Create a plot
fig = px.bar(x=["A", "B", "C"], y=[4, 3, 2])

app.layout = html.Div(children=[
    html.H1(children="Hello Dash"),
    dcc.Graph(figure=fig)
])

if __name__ == '__main__':
    app.run_server(debug=True)
# Install Dash and Plotly
pip install dash plotly

# Simple Dash app
import dash
from dash import dcc, html
import plotly.express as px

app = dash.Dash(__name__)

# Create a plot
fig = px.bar(x=["A", "B", "C"], y=[4, 3, 2])

app.layout = html.Div(children=[
    html.H1(children="Hello Dash"),
    dcc.Graph(figure=fig)
])

if __name__ == '__main__':
    app.run_server(debug=True)

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link: Dash Documentation

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10. PyTorch

Category: Machine Learning
Description: PyTorch is a deep learning framework known for its flexibility and ease of use. It’s widely used for developing neural networks and working with complex data.

Why Use It: Dynamic computation, flexible, great for deep learning.
Use Cases: Deep learning, neural networks, computer vision.
Example Code:

# Install PyTorch
pip install torch torchvision
# Simple PyTorch model
import torch
import torch.nn as nn
class SimpleModel(nn.Module):
    def __init__(self):
        super(SimpleModel, self).__init__()
        self.fc = nn.Linear(10, 2)
    def forward(self, x):
        return self.fc(x)
model = SimpleModel()
input_tensor = torch.randn(1, 10)
output = model(input_tensor)
print(output)
# Install PyTorch
pip install torch torchvision

# Simple PyTorch model
import torch
import torch.nn as nn

class SimpleModel(nn.Module):
    def __init__(self):
        super(SimpleModel, self).__init__()
        self.fc = nn.Linear(10, 2)

    def forward(self, x):
        return self.fc(x)

model = SimpleModel()
input_tensor = torch.randn(1, 10)
output = model(input_tensor)
print(output)
# Install PyTorch
pip install torch torchvision

# Simple PyTorch model
import torch
import torch.nn as nn

class SimpleModel(nn.Module):
    def __init__(self):
        super(SimpleModel, self).__init__()
        self.fc = nn.Linear(10, 2)

    def forward(self, x):
        return self.fc(x)

model = SimpleModel()
input_tensor = torch.randn(1, 10)
output = model(input_tensor)
print(output)

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link: PyTorch Documentation

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Conclusion

These 10 Python frameworks are an excellent starting point for building web applications, APIs, data visualizations, and machine learning models. Whether you’re a beginner or an experienced developer, these frameworks offer a range of tools to accelerate your projects. Happy coding!

原文链接：Top 10 Python Frameworks for 2024