Abstract: Learn how to build a real-time chat application using Flask and its StreamingAsyncResponse feature.
2024-06-17 by DevCodeF1 Editors
Streaming Async Function with Flask: Building a Real-time Chat App
In this article, we will explore how to build a real-time chat app using Flask and Python. We will focus on the use of async functions and streaming responses to create a responsive and scalable application.
Why Flask and Async Functions?
Flask is a popular web framework for Python, known for its simplicity and flexibility. With the addition of async functions in Python 3.7, it is now possible to build scalable and high-performance web applications using Flask.
Async functions allow for non-blocking I/O operations, which can greatly improve the performance of IO-bound applications such as real-time chat apps. By using async functions and streaming responses, we can build a chat app that can handle many simultaneous connections without blocking the main thread.
Building the Chat App
To build the chat app, we will start by creating a new Flask application and defining a route for the chat stream.
from flask import Flask, Responseapp = Flask(__name__)@app.route('/chatstm', methods=['POST'])async def chatstm(): user\_id = session.get('user\_id') if not user\_id: return jsonify({'error': 'Unauthorized'}), 401 # Code for handling the chat stream will go here
In the code above, we define a new route called /chatstm that only accepts POST requests. We also check if the user is authorized by looking for a user\_id in the session. If the user is not authorized, we return a 401 Unauthorized error.
Now, let's add the code for handling the chat stream.
async def chatstm(): user\_id = session.get('user\_id') if not user\_id: return jsonify({'error': 'Unauthorized'}), 401 # Get the latest messages from the database messages = db.session.query(Message).filter\_by(user\_id=user\_id).all() # Create a streaming response response = Response(status=200) response.headers['Content-Type'] = 'text/plain' response.headers['Cache-Control'] = 'no-cache' response.headers['X-Accel-Buffering'] = 'no' # Send the latest messages to the client for message in messages: await response.write(f'{message.text}') # Start a loop to receive and send new messages while True: # Receive a new message from the client data = await request.stream.readline() message\_text = data.decode('utf-8').strip() # Save the message to the database new\_message = Message(user\_id=user\_id, text=message\_text) db.session.add(new\_message) db.session.commit() # Send the new message to all connected clients await response.write(f'{message\_text}')
In the code above, we first get the latest messages from the database and send them to the client. We then start a loop to receive and send new messages. The loop reads a new line from the client's request stream, saves the message to the database, and sends it to all connected clients.
Note that we use the await keyword to wait for I/O operations to complete, such as reading from the request stream or writing to the response. This allows other operations to continue in the meantime, improving the performance of the application.
Testing the Chat App
To test the chat app, we can run the Flask application and send POST requests to the /chatstm route. We can use a tool like curl to send the requests and receive the chat stream.
curl -X POST -H "Content-Type: application/json" -d '{"user\_id": "123"}' http://localhost:5000/chatstm
In the code above, we send a POST request to the /chatstm route with a JSON payload containing the user's ID.
In this article, we explored how to build a real-time chat app using Flask and Python. We used async functions and streaming responses to create a scalable and high-performance application. We also covered the basics of handling the chat stream and testing the app.
References
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Flask Documentation: https://flask.palletsprojects.com/en/2.1.x/
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Python Async Functions: https://docs.python.org/3/library/asyncio.html
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curl Documentation: https://curl.se/
Explore the implementation of a simple yet efficient real-time chat application using Flask's StreamingAsyncResponse. Get started now!
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