


Implementing a Scalable Forex WebSocket Using a Python Proxy
This guide will teach you how to create a WebSocket proxy server in Python.
Here's what the server will do:
- Verify client identity: Before allowing clients to connect, it will check whether each has a unique "user key (API Key)."
- Connect to another WebSocket: The server will connect to a separate WebSocket server.
- Relay messages: The server will receive messages from the connected WebSocket and send them to all verified clients.
Before you begin:
- Make sure you have installed Python 3.6 or a newer version. WebSockets need Python 3.6 or higher.
- Install the WebSockets library: You can install it using the following command in your terminal.
pip install websockets
1. Getting Started
- Create a new folder for your project.
- Create a new Python file inside the folder and name it 'websocket_proxy_server.py.' This file will hold all the code for your server.
2. Create the WebSocket Server
- Import the required libraries. You'll need the libraries you installed earlier.
- Build the basic structure of your server. Use the WebSockets library to create the foundation for your server.
import asyncio import websockets import json class WebSocketProxy: def init(self, source_url, symbols): self.source_url = source_url self.clients = set() self.symbols = symbols self.valid_user_key = "yourValidUserKey" # Single valid user key for authentication async def on_open(self, ws): print("Connected to source") symbols_str = ",".join(self.symbols.keys()) init_message = f"{{"userKey":"your_api_key", "symbol":"{symbols_str}"}}" await ws.send(init_message)
3. Connect and Verify Clients
- Ensure that the server is all set to accept connections from clients.
- Add a check to verify each client's identity. As a client tries to connect, the server should ask for a "user key." Only clients with the correct key will be allowed to connect.
async def client_handler(self, websocket, path): try: # Wait for a message that should contain the authentication key auth_message = await asyncio.wait_for(websocket.recv(), timeout=10) auth_data = json.loads(auth_message) user_key = auth_data.get("userKey") if user_key == self.valid_user_key: self.clients.add(websocket) print(f"Client authenticated with key: {user_key}") try: await websocket.wait_closed() finally: self.clients.remove(websocket) else: print("Authentication failed") await websocket.close(reason="Authentication failed") except (asyncio.TimeoutError, json.JSONDecodeError, KeyError): print("Failed to authenticate") await websocket.close(reason="Failed to authenticate")
4. Connect to the Source and Share Messages
- Create a function that keeps the server connected to the original WebSocket.
- This function should automatically send messages received from the original WebSocket to all successfully verified clients.
async def source_handler(self): async with websockets.connect(self.source_url) as websocket: await self.on_open(websocket) async for message in websocket: await self.broadcast(message) async def broadcast(self, message): if self.clients: await asyncio.gather(*(client.send(message) for client in self.clients))
5. Start the Server
- Create a function to start the server and listen for connections.
- Add code to run this function, starting your WebSocket proxy server.
def run(self, host="localhost", port=8765): start_server = websockets.serve(self.client_handler, host, port) asyncio.get_event_loop().run_until_complete(start_server) asyncio.get_event_loop().run_until_complete(self.source_handler()) asyncio.get_event_loop().run_forever() if name == "main": symbols = {"EURUSD": {}, "GBPUSD": {}, "USDJPY": {}, "AUDUSD": {}, "USDCAD": {}} source_url = "ws://example.com/source" proxy = WebSocketProxy(source_url, symbols) proxy.run()
In Summary
You have successfully developed a Python-based WebSocket proxy server. This server can authenticate client identities, maintain a persistent connection to a designated data source, and effectively distribute messages received from the source to all verified clients. This functionality proves invaluable for applications that necessitate the secure and instantaneous dissemination of data from a singular origin to a diverse user base.
Next Steps
Thorough server testing is crucial to ensure optimal performance and reliability. It verifies its proper handling of connections and message transmission. To enhance efficiency, consider implementing load-balancing mechanisms and customizing connection headers. Finally, it is advisable to deploy the server to a suitable environment for production deployment, such as a cloud service specifically designed to accommodate long-term network connections.
Also, please take a look at the originally published tutorial on our website: Scaling a Forex WebSocket with Python Proxy
The above is the detailed content of Implementing a Scalable Forex WebSocket Using a Python Proxy. For more information, please follow other related articles on the PHP Chinese website!

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

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Hot Topics











Python is suitable for data science, web development and automation tasks, while C is suitable for system programming, game development and embedded systems. Python is known for its simplicity and powerful ecosystem, while C is known for its high performance and underlying control capabilities.

You can learn the basics of Python within two hours. 1. Learn variables and data types, 2. Master control structures such as if statements and loops, 3. Understand the definition and use of functions. These will help you start writing simple Python programs.

Python excels in gaming and GUI development. 1) Game development uses Pygame, providing drawing, audio and other functions, which are suitable for creating 2D games. 2) GUI development can choose Tkinter or PyQt. Tkinter is simple and easy to use, PyQt has rich functions and is suitable for professional development.

You can learn basic programming concepts and skills of Python within 2 hours. 1. Learn variables and data types, 2. Master control flow (conditional statements and loops), 3. Understand the definition and use of functions, 4. Quickly get started with Python programming through simple examples and code snippets.

Python is easier to learn and use, while C is more powerful but complex. 1. Python syntax is concise and suitable for beginners. Dynamic typing and automatic memory management make it easy to use, but may cause runtime errors. 2.C provides low-level control and advanced features, suitable for high-performance applications, but has a high learning threshold and requires manual memory and type safety management.

Python is widely used in the fields of web development, data science, machine learning, automation and scripting. 1) In web development, Django and Flask frameworks simplify the development process. 2) In the fields of data science and machine learning, NumPy, Pandas, Scikit-learn and TensorFlow libraries provide strong support. 3) In terms of automation and scripting, Python is suitable for tasks such as automated testing and system management.

To maximize the efficiency of learning Python in a limited time, you can use Python's datetime, time, and schedule modules. 1. The datetime module is used to record and plan learning time. 2. The time module helps to set study and rest time. 3. The schedule module automatically arranges weekly learning tasks.

Python is highly favored for its simplicity and power, suitable for all needs from beginners to advanced developers. Its versatility is reflected in: 1) Easy to learn and use, simple syntax; 2) Rich libraries and frameworks, such as NumPy, Pandas, etc.; 3) Cross-platform support, which can be run on a variety of operating systems; 4) Suitable for scripting and automation tasks to improve work efficiency.
