


Flask-Social: Adding social login to your Python web application
With the rapid development of social media, more and more websites and applications are beginning to use social login to simplify the user registration and login process. However, implementing such functionality is not easy. How to interact with social networks via the OAuth protocol? How to use the obtained user information? How to deal with permissions and security? Fortunately, there is an excellent Python application extension like Flask-Social that can help us achieve this function more easily. This article will introduce the usage and basic principles of Flask-Social.
Flask-Social installation and configuration
First, we need to install Flask-Social. Use the pip tool to install quickly:
pip install Flask-Social
After the installation is complete, we need to configure Flask-Social in the Flask project. First introduce it in the Flask application:
from flask import Flask from flask_sqlalchemy import SQLAlchemy from flask.ext.social import Social from flask.ext.social.datastore import SQLAlchemyConnectionDatastore app = Flask(__name__) app.config['SQLALCHEMY_DATABASE_URI'] = 'sqlite:///app.db' db = SQLAlchemy(app) app.config['SOCIAL_AUTH_TWITTER_KEY'] = 'your_key' app.config['SOCIAL_AUTH_TWITTER_SECRET'] = 'your_secret' social = Social(app, SQLAlchemyConnectionDatastore(db))
In the above code, we first introduce the necessary dependency libraries, including Flask, SQLAlchemy and Flask-Social. Then, we define a Flask application and a SQLAlchemy database, as well as the URL to connect to the database. Next, we set the key and secret for Twitter authentication. Twitter is used here as an example. Of course, information from other social media platforms can also be used. Finally, initialize the social
instance through the Social
class and connect it with the SQLAlchemyConnectionDatastore class.
Basic usage of Flask-Social
With the above settings, we can now use Flask-Social to add social login functionality. Suppose we want to add Twitter login to our application, we can use the following code:
from flask import Flask, request, redirect, url_for, render_template from flask_sqlalchemy import SQLAlchemy from flask.ext.social import Social from flask.ext.social.datastore import SQLAlchemyConnectionDatastore app = Flask(__name__) app.config['SQLALCHEMY_DATABASE_URI'] = 'sqlite:///app.db' app.secret_key = 'secret' db = SQLAlchemy(app) app.config['SOCIAL_AUTH_TWITTER_KEY'] = 'your_key' app.config['SOCIAL_AUTH_TWITTER_SECRET'] = 'your_secret' social = Social(app, SQLAlchemyConnectionDatastore(db)) @app.route('/') def home(): return render_template('home.html') @app.route('/login') def login(): return social.twitter.authorize(callback=url_for('auth_twitter', next=request.args.get('next') or request.referrer or None)) @app.route('/auth/twitter') def auth_twitter(): resp = social.twitter.authorized_response() if resp is None: return redirect(url_for('home')) session['twitter_token'] = ( resp['oauth_token'], resp['oauth_token_secret'] ) return redirect(url_for('profile')) @app.route('/profile') def profile(): return render_template('profile.html')
The code here is simple: we first define a homepage, and then we define a login route, using social. twitter.authorize()
function to generate the login page. Next, we handle the Twitter login information callback and store the token and secret in the session. Finally, we define a profile route to display user information.
Please note that in the above code, we also define an app.secret_key
, which is used to generate the session key, which is required by Flask-Social.
Advanced application of Flask-Social: Github login
Of course, Twitter is not the only common social login platform. As a developer social networking site, Github is also very popular. So we added Github login to the Flask application with only slight changes, for example:
from flask import Flask, request, redirect, url_for, render_template, session from flask_sqlalchemy import SQLAlchemy from flask.ext.social import Social from flask.ext.social.datastore import SQLAlchemyConnectionDatastore app = Flask(__name__) app.config['SQLALCHEMY_DATABASE_URI'] = 'sqlite:///app.db' app.secret_key = 'secret' db = SQLAlchemy(app) app.config['SOCIAL_AUTH_GITHUB_KEY'] = 'your_key' app.config['SOCIAL_AUTH_GITHUB_SECRET'] = 'your_secret' social = Social(app, SQLAlchemyConnectionDatastore(db)) @app.route('/') def home(): return render_template('home.html') @app.route('/login') def login(): return social.github.authorize(callback=url_for('auth_github', next=request.args.get('next') or request.referrer or None)) @app.route('/auth/github') def auth_github(): resp = social.github.authorized_response() if resp is None: return redirect(url_for('home')) session['github_token'] = ( resp['access_token'], '' ) return redirect(url_for('profile')) @app.route('/profile') def profile(): me = social.github.get('/user') return render_template('profile.html', name=me.data['name'])
As you can see, just modify the key and secret, and add it in authorize()
and authorized_response()
Use social.github
in the method to achieve social login based on Github.
Summary of Flask-Social
With Flask-Social, we can easily add social login functionality to our Flask applications. Using Flask-Social, we can directly use Python code to operate the social network's API without having to deal with the OAuth protocol manually. If you want to support multiple social networks, all it takes is a slight code modification. With such a simple operation, you will reduce the troubles of countless users and increase the user loyalty and stickiness of your application.
The above is the detailed content of Flask-Social: Adding social login to your Python web application. For more information, please follow other related articles on the PHP Chinese website!

NumPyarraysarebetterfornumericaloperationsandmulti-dimensionaldata,whilethearraymoduleissuitableforbasic,memory-efficientarrays.1)NumPyexcelsinperformanceandfunctionalityforlargedatasetsandcomplexoperations.2)Thearraymoduleismorememory-efficientandfa

NumPyarraysarebetterforheavynumericalcomputing,whilethearraymoduleismoresuitableformemory-constrainedprojectswithsimpledatatypes.1)NumPyarraysofferversatilityandperformanceforlargedatasetsandcomplexoperations.2)Thearraymoduleislightweightandmemory-ef

ctypesallowscreatingandmanipulatingC-stylearraysinPython.1)UsectypestointerfacewithClibrariesforperformance.2)CreateC-stylearraysfornumericalcomputations.3)PassarraystoCfunctionsforefficientoperations.However,becautiousofmemorymanagement,performanceo

InPython,a"list"isaversatile,mutablesequencethatcanholdmixeddatatypes,whilean"array"isamorememory-efficient,homogeneoussequencerequiringelementsofthesametype.1)Listsareidealfordiversedatastorageandmanipulationduetotheirflexibility

Pythonlistsandarraysarebothmutable.1)Listsareflexibleandsupportheterogeneousdatabutarelessmemory-efficient.2)Arraysaremorememory-efficientforhomogeneousdatabutlessversatile,requiringcorrecttypecodeusagetoavoiderrors.

Python and C each have their own advantages, and the choice should be based on project requirements. 1) Python is suitable for rapid development and data processing due to its concise syntax and dynamic typing. 2)C is suitable for high performance and system programming due to its static typing and manual memory management.

Choosing Python or C depends on project requirements: 1) If you need rapid development, data processing and prototype design, choose Python; 2) If you need high performance, low latency and close hardware control, choose C.

By investing 2 hours of Python learning every day, you can effectively improve your programming skills. 1. Learn new knowledge: read documents or watch tutorials. 2. Practice: Write code and complete exercises. 3. Review: Consolidate the content you have learned. 4. Project practice: Apply what you have learned in actual projects. Such a structured learning plan can help you systematically master Python and achieve career goals.


Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

SecLists
SecLists is the ultimate security tester's companion. It is a collection of various types of lists that are frequently used during security assessments, all in one place. SecLists helps make security testing more efficient and productive by conveniently providing all the lists a security tester might need. List types include usernames, passwords, URLs, fuzzing payloads, sensitive data patterns, web shells, and more. The tester can simply pull this repository onto a new test machine and he will have access to every type of list he needs.

Dreamweaver CS6
Visual web development tools

DVWA
Damn Vulnerable Web App (DVWA) is a PHP/MySQL web application that is very vulnerable. Its main goals are to be an aid for security professionals to test their skills and tools in a legal environment, to help web developers better understand the process of securing web applications, and to help teachers/students teach/learn in a classroom environment Web application security. The goal of DVWA is to practice some of the most common web vulnerabilities through a simple and straightforward interface, with varying degrees of difficulty. Please note that this software

SublimeText3 English version
Recommended: Win version, supports code prompts!

EditPlus Chinese cracked version
Small size, syntax highlighting, does not support code prompt function
