Crosspulse

✨ Features

🎯 Why Crosspulse?

// JavaScript
const result = await bridge.call("train_model", data);
console.log("Accuracy:", result.accuracy);

# Python (automatically responds)
bridge.register("train_model", train_ml_model)

📦 Installation

npm install crosspulse 

pip install crosspulse

crosspulse.py
crosspulse.js

🚀 Quick Start

Mode 1: JavaScript → Python

import Crosspulse from "crosspulse/src/crosspulse.js";
async function main() {
 // Create a bridge in "connect" mode
 const bridge = new Crosspulse("connect");
 
 // Connect to the Python script
 await bridge.connect("python main.py");
 
 // Call a Python function and get the result
 const result = await bridge.call("py_add", 10, 20);
 console.log(result); // 30
 
 // Disconnect the bridge
 bridge.disconnect();
}
// Run the main function
main();

import crosspulse
# Create a bridge in "listen" mode
bridge = crosspulse.Crosspulse(mode="listen")
# Register a Python method that JS can call
def py_add(a, b):
 return a + b
bridge.register("py_add", py_add)
# Start listening for incoming calls from JavaScript
bridge.listen()

node app.js

Mode 2: Python → JavaScript

import crosspulse
# Create a bridge in "connect" mode
bridge = crosspulse.Crosspulse(mode="connect")
# Connect to the JavaScript script
bridge.connect("node app.js")
# Call a JavaScript function and get the result
result = bridge.call("js_multiply", 100, 50)
print(result) # 5000
# Disconnect the bridge
bridge.disconnect()

import Crosspulse from "crosspulse/src/crosspulse.js";
// Create a bridge in "listen" mode
const bridge = new Crosspulse("listen");
// Register a JavaScript method that Python can call
bridge.register("js_multiply", (a, b) => a * b);
// Start listening for incoming calls from Python
bridge.listen();

python main.py

Mode 3: Bidirectional Communication

import crosspulse
# Create a bridge in "connect" mode
bridge = crosspulse.Crosspulse(mode="connect")
# Register Python methods that JavaScript can call
def py_square(x):
 return x ** 2
def py_reverse(s):
 return s[::-1]
bridge.register("py_square", py_square)
bridge.register("py_reverse", py_reverse)
# Connect to the JavaScript script
bridge.connect("node app.js")
# Call JavaScript methods
result = bridge.call("js_capitalize", "hello world")
print(result) # "HELLO WORLD"
# JavaScript can call py_square() or py_reverse() one request at a time

import Crosspulse from "crosspulse/src/crosspulse.js";
// Create a bridge in "listen" mode
const bridge = new Crosspulse("listen");
// Register JavaScript methods that Python can call
bridge.register("js_capitalize", (str) => str.toUpperCase());
bridge.register("js_length", (str) => str.length);
// Start listening for incoming calls from Python
bridge.listen();
// Python can call these methods one request at a time
// Incoming calls are automatically handled

📖 API Reference

Python

from crosspulse import Crosspulse
# Create instance
bridge = Crosspulse(mode="listen") # Listen mode
bridge = Crosspulse(mode="connect") # Connect mode
# Register method
bridge.register("method_name", callback_function)
# Listen for calls (listen mode)
bridge.listen()
# Connect to target (connect mode)
bridge.connect("node target_script.js")
# Call remote method
result = bridge.call("method_name", arg1, arg2)
# Disconnect
bridge.disconnect()

JavaScript

import Crosspulse from "crosspulse/src/crosspulse.js";
// Create instance
const bridge = new Crosspulse("listen"); // Listen mode
const bridge = new Crosspulse("connect"); // Connect mode
// Register method
bridge.register("method_name", (arg1, arg2) => { 
 return result;
});
// Listen for calls (listen mode)
bridge.listen();
// Connect to target (connect mode)
await bridge.connect("python target_script.py");
// Call remote method
const result = await bridge.call("method_name", arg1, arg2);
// Disconnect
bridge.disconnect();

🎯 Real-World Examples

Example 1: Data Processing Pipeline

# data_processor.py
import pandas as pd
from crosspulse import Crosspulse
bridge = Crosspulse("connect")
bridge.connect("node visualizer.js")
# Process data in Python
df = pd.read_csv("sales_data.csv")
insights = analyze_sales(df)
# Visualize in JavaScript
chart = bridge.call("create_chart", insights.to_dict())
print(f"Chart created: {chart}")

// visualizer.js
import Crosspulse from "crosspulse/src/crosspulse.js";
const bridge = new Crosspulse("listen");
bridge.register("create_chart", (data) => {
 // Use Chart.js, D3.js, or any JS library
 const chart = generateChart(data);
 return chart.id;
});
bridge.listen();

Example 2: Machine Learning UI

// ml_interface.js
import Crosspulse from "crosspulse/src/crosspulse.js";
const bridge = new Crosspulse("connect");
async function trainModel(dataset) {
 await bridge.connect("python ml_model.py");
 
 const progress = await bridge.call("train", dataset);
 console.log("Training progress:", progress);
 
 const predictions = await bridge.call("predict", testData);
 displayResults(predictions);
}

# ml_model.py
from sklearn.ensemble import RandomForestClassifier
from crosspulse import Crosspulse
bridge = Crosspulse("listen")
model = RandomForestClassifier()
def train_model(data):
 X, y = prepare_data(data)
 model.fit(X, y)
 return {"status": "trained", "accuracy": model.score(X, y)}
bridge.register("train", train_model)
bridge.listen()

Example 3: Web Scraping + Frontend

# scraper.py
from crosspulse import Crosspulse
import requests
from bs4 import BeautifulSoup
bridge = Crosspulse("connect")
def scrape_news():
 # Scrape with Python
 data = scrape_website()
 
 # Send to JavaScript for display
 bridge.call("update_ui", data)
bridge.connect("node server.js")
scrape_news()

Example 4: Desktop App (Electron + Python)

// electron_main.js
import Crosspulse from "crosspulse/src/crosspulse.js";
const bridge = new Crosspulse("connect");
ipcMain.on("process-image", async (event, imagePath) => {
 await bridge.connect("python image_processor.py");
 
 const processed = await bridge.call("enhance_image", imagePath);
 event.reply("image-ready", processed);
});

🔧 Advanced Usage

Error Handling

try {
 const result = await bridge.call("risky_operation", data);
 console.log("Success:", result);
} catch (error) {
 console.error("Python error:", error.message);
}

try:
 result = bridge.call("risky_operation", data)
 print(f"Success: {result}")
except Exception as e:
 print(f"JavaScript error: {e}")

Multiple Arguments & Complex Data

// JavaScript
const result = await bridge.call("process_user", {
 name: "John",
 age: 30,
 tags: ["developer", "python", "javascript"]
});

# Python
def process_user(user_data):
 return {
 "id": generate_id(),
 "name": user_data["name"],
 "processed": True
 }
bridge.register("process_user", process_user)

Async Operations

# Python
import time
def long_running_task(duration):
 time.sleep(duration)
 return "Task completed"
bridge.register("long_task", long_running_task)

// JavaScript
const result = await bridge.call("long_task", 5);
console.log(result); // "Task completed" (after 5 seconds)

🎨 Use Cases

⚡ Performance

🛡️ Security Notes

🐛 Troubleshooting

"Method not found" error

# Make sure method is registered before listening
bridge.register("my_method", my_function)
bridge.listen() # Must be after register

Connection timeout

// Ensure Python script is running
await bridge.connect("python script.py");
// Python should be in listen mode

JSON serialization errors

# Only use JSON-serializable types
# ✅ str, int, float, list, dict, bool, None
# ❌ Custom objects, functions, file handles

🤝 Contributing

git clone https://github.com/AnarDevStudio/crosspulse.git
cd crosspulse

📄 License

MIT License
Copyright (c) 2026 AnarEsgerzade
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.

🌟 Show Your Support

📞 Support