# msghandler - Cross-Platform Bi-Directional Data Bridge A high-performance, bi-directional data bridge for **Julia**, **JavaScript**, **Python**, and **MicroPython** applications using NATS (Core & JetStream), implementing the Claim-Check pattern for large payloads. [![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)](https://opensource.org/licenses/MIT) [![NATS](https://img.shields.io/badge/NATS-Enabled-green.svg)](https://nats.io) --- ## Table of Contents - [Overview](#overview) - [Cross-Platform Support](#cross-platform-support) - [Features](#features) - [Quick Start](#quick-start) - [API Reference](#api-reference) - [Cross-Platform Examples](#cross-platform-examples) - [Testing](#testing) - [Documentation](#documentation) - [License](#license) --- ## Quick Data Format Reference All platforms use the same input format for `smartpack()`: ### Format: `[(dataname, data, type), ...]` | Element | Type | Description | |---------|------|-------------| | `dataname` | String | Name for the payload (e.g., `"message"`, `"config.json"`) | | `data` | Any | The actual data (type depends on the `type` parameter below) | | `type` | String | Payload type identifier | ### Supported Payload Types | Type | Julia Data | JavaScript Data | Python Data | Description | |------|------------|-----------------|-------------|-------------| | `"text"` | `String` | `string` | `str` | Plain text | | `"dictionary"` | `Dict` | `Object` | `dict` | JSON object | | `"arrowtable"` | `DataFrame` | ❌ | `pandas.DataFrame` | Arrow IPC table (Desktop only) | | `"jsontable"` | `DataFrame` | `Array` | `list[dict]` | JSON table | | `"image"` | `Vector{UInt8}` | `Uint8Array` | `bytes` | Image data | | `"audio"` | `Vector{UInt8}` | `Uint8Array` | `bytes` | Audio data | | `"video"` | `Vector{UInt8}` | `Uint8Array` | `bytes` | Video data | | `"binary"` | `Vector{UInt8}` | `Uint8Array` | `bytes` | Binary data | ### Examples **Sending multiple payloads:** ```julia # Julia data = [ ("message", "Hello!", "text"), ("config", Dict("key" => "value"), "dictionary"), ("file", file_bytes, "binary") ] env, json_str = msghandler.smartpack("subject", data, options...) ``` ```python # Python data = [ ("message", "Hello!", "text"), ("config", {"key": "value"}, "dictionary"), ("file", file_bytes, "binary") ] env, json_str = await smartpack("subject", data, **options) ``` ```javascript // JavaScript const data = [ ["message", "Hello!", "text"], ["config", {key: "value"}, "dictionary"], ["file", fileBytes, "binary"] ]; const [env, json_str] = await smartpack("subject", data, options); ``` **Important Notes:** - Always wrap payloads in a list `[]`, even for single payloads - Type must be one of the supported types above - Large payloads (≥500KB) automatically use link transport - Browser only supports: `"text"`, `"dictionary"`, `"jsontable"`, `"image"`, `"audio"`, `"video"`, `"binary"` (No Arrow IPC due to browser incompatibility) --- ## Overview msghandler enables seamless communication across multiple platforms through NATS, with intelligent transport selection based on payload size: | Transport | Payload Size | Method | |-----------|--------------|--------| | **Direct** | < 500KB | Sent directly via NATS (Base64 encoded) | | **Link** | ≥ 500KB | Uploaded to HTTP file server, URL sent via NATS | ### Use Cases - **Chat Applications**: Text, images, audio, video in a single message - **File Transfer**: Efficient transfer of large files using claim-check pattern - **IoT/Embedded**: Sensor data, telemetry, and analytics pipelines (MicroPython) - **Cross-Platform Communication**: Interoperability between Julia, JavaScript, Python, and MicroPython systems --- ## Cross-Platform Support | Platform | Implementation | Features | |----------|----------------|----------| | **Julia** | [`src/msghandler.jl`](src/msghandler.jl) | Full feature set, Arrow IPC, multiple dispatch | | **JavaScript (Node.js)** | [`src/msghandler_ssr.js`](src/msghandler_ssr.js) | Node.js, async/await, Arrow IPC | | **JavaScript (Browser)** | [`src/msghandler_csr.js`](src/msghandler_csr.js) | Browser, WebSocket NATS, async/await, JSON table only | | **Python** | [`src/msghandler.py`](src/msghandler.py) | Desktop Python, asyncio, type hints, Arrow IPC | | **MicroPython** | [`src/msghandler_mpy.py`](src/msghandler_mpy.py) | Memory-constrained, synchronous API | ### Platform Comparison | Feature | Julia | JavaScript | JavaScript (Browser) | Python | MicroPython | |---------|-------|------------|----------------------|--------|-------------| | Multiple Dispatch | ✅ Native | ❌ | ❌ | ❌ | ❌ | | Async/Await | ❌ | ✅ Native | ✅ Native | ✅ Native | ⚠️ (uasyncio) | | Type Safety | ✅ Strong | ⚠️ (TypeScript) | ⚠️ (TypeScript) | ✅ (Type hints) | ❌ | | Arrow IPC | ✅ Native | ✅ Native | ❌ (Browser incompatible) | ✅ Native | ❌ | | JSON Table | ✅ | ✅ | ✅ (Only table type) | ✅ | ⚠️ (Limited) | | Direct Transport | ✅ | ✅ | ✅ | ✅ | ✅ | | Link Transport | ✅ | ✅ | ✅ | ✅ | ⚠️ (Limited) | | Handler Functions | ✅ | ✅ | ✅ | ✅ | ✅ | | Cross-Platform API | ✅ | ✅ | ✅ | ✅ | ✅ | | WebSocket NATS | ❌ | ❌ | ✅ | ❌ | ❌ | --- ## Features - ✅ **Cross-platform messaging** for Julia, JavaScript, Python, and MicroPython applications - ✅ **Bi-directional messaging** with request-reply patterns - ✅ **Multi-payload support** - send multiple payloads with different types in one message - ✅ **Automatic transport selection** - direct vs link based on payload size - ✅ **Claim-Check pattern** for payloads ≥ 500KB - ✅ **Apache Arrow IPC** support for tabular data (Desktop: Julia/Python/Node.js) - ✅ **JSON Table** support for tabular data (All platforms including Browser) - ✅ **Exponential backoff** for reliable file server downloads - ✅ **Correlation ID tracking** for message tracing - ✅ **Reply-to support** for request-response patterns - ✅ **Handler function abstraction** - pluggable file server implementations (Plik, AWS S3, custom) --- ## Quick Start ### Prerequisites 1. **NATS Server** - Install and run a NATS server: ```bash docker run -p 4222:4222 nats:latest ``` 2. **HTTP File Server** (optional, for large payloads) - Install and run a file server: ```bash # Using Plik docker run -p 8080:8080 -v /tmp/fileserver:/var/lib/plik -e PLIK_ADMIN_PASSWORD=admin plik/plik # OR using simple Python HTTP server mkdir -p /tmp/fileserver python3 -m http.server 8080 --directory /tmp/fileserver ``` ### Send Your First Message #### Julia ```julia using msghandler, NATS # Data format: [(dataname, data, type), ...] # Each tuple contains: # 1. dataname: String name for the payload (e.g., "message") # 2. data: The actual data (String, bytes, DataFrame, etc.) # 3. type: String type indicator (e.g., "text", "binary", "dictionary") # Supported types: "text", "dictionary", "arrowtable", "jsontable", # "image", "audio", "video", "binary" payload_1 = ("test_message", "Hello World", "text") file_path_large_image = "./test/large_image.png" file_data_large_image = read(file_path_large_image) filename_large_image = basename(file_path_large_image) payload_2 = (filename_large_image, file_data_large_image, "binary") payloads = [payload_1, payload_2] # List of tuples envelope, envelope_json_str = msghandler.smartpack("test.topic", payloads; broker_url="nats.yiem.cc", fileserver_url="http://192.168.88.104:8080") conn = NATS.connect("nats.yiem.cc") # Create NATS connection NATS.publish(conn, "test.topic", envelope_json_str) # Publish message to NATS NATS.drain(conn) ``` #### JavaScript (Node.js) ```javascript import msghandler from './src/msghandler_ssr.js'; const data = [["message", "Hello World", "text"]]; const [env, env_json_str] = await msghandler.smartpack( "/chat/room1", data, { broker_url: "nats://localhost:4222" } ); console.log("Message sent!"); ``` #### JavaScript (Browser) ```javascript import msghandler from './src/msghandler_csr.js'; const data = [["message", "Hello World", "text"]]; const [env, env_json_str] = await msghandler.smartpack( "/chat/room1", data, { broker_url: "ws://localhost:4222" } ); console.log("Message sent!"); ``` #### Python ```python from msghandler import smartpack # Data format: [(dataname, data, type), ...] # Each tuple contains: # 1. dataname: String name for the payload (e.g., "message") # 2. data: The actual data (str, bytes, dict, list, etc.) # 3. type: String type indicator (e.g., "text", "binary", "dictionary") # Supported types: "text", "dictionary", "jsontable", "image", "audio", "video", "binary" data = [("message", "Hello World", "text")] env, env_json_str = await smartpack( "/chat/room1", data, broker_url="nats://localhost:4222" ) print("Message sent!") ``` #### MicroPython ```python from msghandler import smartpack data = [("message", "Hello World", "text")] env, env_json_str = smartpack( "/chat/room1", data, broker_url="nats://localhost:4222", size_threshold=100000 ) print("Message sent!") ``` ### Receive Your First Message #### Julia ```julia using msghandler, NATS conn = NATS.connect("nats.yiem.cc") NATS.subscribe(conn, "test.topic") do msg println("Received message on $(msg.subject)") envelope_json_str = String(msg.payload) envelope = msghandler.smartunpack( envelope_json_str; max_retries = 5, base_delay = 100, max_delay = 5000 ) println(envelope.payloads[1]) end ``` --- ## API Reference ### Unified API Standard All platforms use the same input/output format for payloads. #### Input Format for `smartpack` **Format:** `[(dataname1, data1, type1), (dataname2, data2, type2), ...]` **Each tuple contains 3 elements:** 1. **`dataname`** (String) - Name for the payload (e.g., `"message"`, `"config.json"`, `"avatar.png"`) 2. **`data`** (Any) - The actual data to send (type depends on `type`): - `text` → String - `dictionary` → Dict/Object - `arrowtable` → DataFrame/Arrow.Table - `jsontable` → List of dicts/Vector{Dict} - `image/audio/video/binary` → bytes/Uint8Array/Vector{UInt8} 3. **`type`** (String) - Payload type (required): - `"text"` - Plain text string - `"dictionary"` - JSON-serializable dictionary - `"arrowtable"` - Apache Arrow IPC table (Desktop only) - `"jsontable"` - JSON table (all platforms) - `"image"` - Image data (PNG, JPG) - `"audio"` - Audio data (WAV, MP3) - `"video"` - Video data (MP4, AVI) - `"binary"` - Generic binary data **Important:** - Always wrap payloads in a list, even for single payloads - Type must be one of the supported types above - Large payloads (≥500KB by default) automatically use link transport **Example:** ```julia # Julia data = [ ("message", "Hello World", "text"), ("config", Dict("key" => "value"), "dictionary"), ("file", file_bytes, "binary") ] ``` ```python # Python data = [ ("message", "Hello World", "text"), ("config", {"key": "value"}, "dictionary"), ("file", file_bytes, "binary") ] ``` ```javascript // JavaScript const data = [ ["message", "Hello World", "text"], ["config", {key: "value"}, "dictionary"], ["file", fileBytes, "binary"] ]; ``` ### Common Payload Examples | Use Case | Data Format | Type | |----------|-------------|------| | Simple text message | `("message", "Hello World", "text")` | `"text"` | | Configuration JSON | `("config", Dict("key" => "value"), "dictionary")` | `"dictionary"` | | Table as Arrow | `("data", dataframe, "arrowtable")` | `"arrowtable"` | | Table as JSON | `("data", [{"col": 1}], "jsontable")` | `"jsontable"` | | Image file | `("avatar.png", read("file.png"), "image")` | `"image"` | | Audio file | `("audio.mp3", audio_bytes, "audio")` | `"audio"` | | Video file | `("video.mp4", video_bytes, "video")` | `"video"` | | Binary file | `("data.bin", file_bytes, "binary")` | `"binary"` | #### Output Format for `smartunpack` ```json { "correlation_id": "...", "msg_id": "...", "timestamp": "...", "send_to": "...", "msg_purpose": "...", "sender_name": "...", "sender_id": "...", "receiver_name": "...", "receiver_id": "...", "reply_to": "...", "reply_to_msg_id": "...", "broker_url": "...", "metadata": {...}, "payloads": [(dataname1, data1, type1), (dataname2, data2, type2), ...] } ``` ### smartpack Sends data either directly via NATS or via a fileserver URL, depending on payload size. #### Julia ```julia using msghandler env, env_json_str = msghandler.smartpack( subject::String, data::AbstractArray{Tuple{String, Any, String}}; broker_url::String = "nats://localhost:4222", fileserver_url = "http://localhost:8080", fileserver_upload_handler::Function = plik_oneshot_upload, size_threshold::Int = 500_000, correlation_id::String = string(uuid4()), msg_purpose::String = "chat", sender_name::String = "msghandler", receiver_name::String = "", receiver_id::String = "", reply_to::String = "", reply_to_msg_id::String = "", is_publish::Bool = true, NATS_connection::Union{NATS.Connection, Nothing} = nothing, msg_id::String = string(uuid4()), sender_id::String = string(uuid4()) ) # Returns: ::Tuple{msg_envelope_v1, String} ``` #### JavaScript (Node.js) ```javascript import msghandler from './src/msghandler_ssr.js'; const [env, env_json_str] = await msghandler.smartpack( subject, data, // Array of [dataname, data, type] tuples { broker_url: 'nats://localhost:4222', fileserver_url: 'http://localhost:8080', fileserver_upload_handler: msghandler.plikOneshotUpload, size_threshold: 500_000, correlation_id: uuidv4(), msg_purpose: 'chat', sender_name: 'msghandler', receiver_name: '', receiver_id: '', reply_to: '', reply_to_msg_id: '', is_publish: true, nats_connection: null, msg_id: uuidv4(), sender_id: uuidv4() } ); // Returns: Promise<[env, env_json_str]> ``` #### JavaScript (Browser) ```javascript import msghandler from './src/msghandler_csr.js'; const [env, env_json_str] = await msghandler.smartpack( subject, data, { broker_url: 'ws://localhost:4222', fileserver_url: 'http://localhost:8080', fileserver_upload_handler: msghandler.plikOneshotUpload, size_threshold: 500_000, correlation_id: uuidv4(), msg_purpose: 'chat', sender_name: 'msghandler', receiver_name: '', receiver_id: '', reply_to: '', reply_to_msg_id: '', is_publish: true, nats_connection: null, msg_id: uuidv4(), sender_id: uuidv4() } ); // Returns: Promise<[env, env_json_str]> ``` #### Python ```python from msghandler import msghandler env, env_json_str = await msghandler.smartpack( subject: str, data: List[Tuple[str, Any, str]], broker_url: str = "nats://localhost:4222", fileserver_url: str = "http://localhost:8080", fileserver_upload_handler: Callable = plik_oneshot_upload, size_threshold: int = 500_000, correlation_id: str = None, msg_purpose: str = "chat", sender_name: str = "msghandler", receiver_name: str = "", receiver_id: str = "", reply_to: str = "", reply_to_msg_id: str = "", is_publish: bool = True, nats_connection: Any = None, msg_id: str = None, sender_id: str = None ) # Returns: Tuple[Dict, str] ``` #### MicroPython ```python from msghandler import smartpack # Limited to direct transport (< 100KB threshold) env, env_json_str = smartpack( "/device/config", [("config", config, "dictionary")], broker_url="nats://localhost:4222", size_threshold=100000 ) print("Message sent!") ``` ### smartunpack Receives and processes messages from NATS, handling both direct and link transport. #### Julia ```julia using msghandler env = msghandler.smartunpack( msg::NATS.Msg; fileserver_download_handler::Function = _fetch_with_backoff, max_retries::Int = 5, base_delay::Int = 100, max_delay::Int = 5000 ) # Returns: ::JSON.Object{String, Any} ``` #### JavaScript (Node.js) ```javascript import msghandler from './src/msghandler_ssr.js'; const env = await msghandler.smartunpack( msg, { fileserver_download_handler: msghandler.fetchWithBackoff, max_retries: 5, base_delay: 100, max_delay: 5000 } ); // Returns: Promise ``` #### JavaScript (Browser) ```javascript import msghandler from './src/msghandler_csr.js'; const env = await msghandler.smartunpack( msg, { fileserver_download_handler: msghandler.fetchWithBackoff, max_retries: 5, base_delay: 100, max_delay: 5000 } ); // Returns: Promise ``` #### Python ```python from msghandler import msghandler env = await msghandler.smartunpack( msg, fileserver_download_handler=fetch_with_backoff, max_retries=5, base_delay=100, max_delay=5000 ) # Returns: Dict with "payloads" key ``` #### MicroPython ```python from msghandler import smartunpack env = smartunpack( msg, fileserver_download_handler=_sync_fileserver_download, max_retries=3, base_delay=100, max_delay=1000 ) print("Received payloads:", env["payloads"]) ``` --- ## Cross-Platform Examples ### Example 1: Chat with Mixed Content Send text, image, and large file in one message. #### Julia ```julia using msghandler data = [ ("message_text", "Hello!", "text"), ("user_avatar", image_data, "image"), ("large_document", large_file_data, "binary") ] env, env_json_str = smartpack("/chat/room1", data; fileserver_url="http://localhost:8080") ``` #### JavaScript (Node.js) ```javascript import msghandler from './src/msghandler_ssr.js'; const data = [ ["message_text", "Hello!", "text"], ["user_avatar", imageData, "image"], ["large_document", largeFileData, "binary"] ]; const [env, env_json_str] = await msghandler.smartpack( "/chat/room1", data, { fileserver_url: 'http://localhost:8080' } ); ``` #### JavaScript (Browser) ```javascript import msghandler from './src/msghandler_csr.js'; const data = [ ["message_text", "Hello!", "text"], ["user_avatar", image_data, "image"] ]; const [env, env_json_str] = await msghandler.smartpack( "/chat/room1", data, { broker_url: 'ws://localhost:4222' } ); console.log("Message sent!"); ``` #### Python ```python import asyncio from msghandler import smartpack async def main(): image_data = open("user_avatar.png", "rb").read() large_file_data = open("large_document.pdf", "rb").read() data = [ ("message_text", "Hello!", "text"), ("user_avatar", image_data, "image"), ("large_document", large_file_data, "binary") ] env, env_json_str = await smartpack( "/chat/room1", data, fileserver_url="http://localhost:8080" ) print("Message sent!") if __name__ == "__main__": asyncio.run(main()) ``` #### MicroPython ```python from msghandler import smartpack # Note: MicroPython only supports direct transport (< 100KB threshold) # Large files must be uploaded via file server first data = [ ("message_text", "Hello!", "text"), ("user_avatar", image_bytes, "image") ] env, env_json_str = smartpack( "/chat/room1", data, broker_url="nats://localhost:4222", size_threshold=100000 ) print("Message sent!") ``` ### Example 2: Dictionary Exchange Send configuration data between platforms. #### Julia ```julia using msghandler config = Dict( "wifi_ssid" => "MyNetwork", "wifi_password" => "password123", "update_interval" => 60 ) data = [("config", config, "dictionary")] env, env_json_str = smartpack("/device/config", data) ``` #### JavaScript (Node.js) ```javascript import msghandler from './src/msghandler_ssr.js'; const config = { wifi_ssid: "MyNetwork", wifi_password: "password123", update_interval: 60 }; const [env, env_json_str] = await msghandler.smartpack( "/device/config", [["config", config, "dictionary"]] ); console.log("Message sent!"); ``` #### Python ```python import asyncio from msghandler import smartpack async def main(): config = { "wifi_ssid": "MyNetwork", "wifi_password": "password123", "update_interval": 60 } data = [("config", config, "dictionary")] env, env_json_str = await smartpack("/device/config", data) print("Message sent!") if __name__ == "__main__": asyncio.run(main()) ``` #### MicroPython ```python from msghandler import smartpack config = { "wifi_ssid": "MyNetwork", "wifi_password": "password123", "update_interval": 60 } data = [("config", config, "dictionary")] env, env_json_str = smartpack( "/device/config", data, broker_url="nats://localhost:4222", size_threshold=100000 ) print("Message sent!") ``` ### Example 3: Table Data (Arrow IPC) Send tabular data using Apache Arrow IPC format. #### Julia ```julia using msghandler using DataFrames df = DataFrame( id = [1, 2, 3], name = ["Alice", "Bob", "Charlie"], score = [95, 88, 92] ) data = [("students", df, "arrowtable")] env, env_json_str = smartpack("/data/analysis", data) ``` #### JavaScript (Node.js) ```javascript import msghandler from './src/msghandler_ssr.js'; const df = [ { id: 1, name: "Alice", score: 95 }, { id: 2, name: "Bob", score: 88 }, { id: 3, name: "Charlie", score: 92 } ]; const [env, env_json_str] = await msghandler.smartpack( "/data/analysis", [["students", df, "arrowtable"]] ); ``` #### Python ```python from msghandler import msghandler import pandas as pd df = pd.DataFrame({ "id": [1, 2, 3], "name": ["Alice", "Bob", "Charlie"], "score": [95, 88, 92] }) data = [("students", df, "arrowtable")] env, env_json_str = await msghandler.smartpack("/data/analysis", data) ``` #### JavaScript (Browser) ```javascript import msghandler from './src/msghandler_csr.js'; const df = [ { id: 1, name: "Alice", score: 95 }, { id: 2, name: "Bob", score: 88 }, { id: 3, name: "Charlie", score: 92 } ]; const [env, env_json_str] = await msghandler.smartpack( "/data/analysis", [["students", df, "jsontable"]], { broker_url: 'ws://localhost:4222' } ); console.log("Message sent!"); ``` #### MicroPython ```python from msghandler import smartpack # Note: MicroPython only supports direct transport (< 100KB threshold) # MicroPython doesn't support Arrow IPC, only jsontable df = [ {"id": 1, "name": "Alice", "score": 95}, {"id": 2, "name": "Bob", "score": 88}, {"id": 3, "name": "Charlie", "score": 92} ] data = [("students", df, "jsontable")] env, env_json_str = smartpack( "/data/analysis", data, broker_url="nats://localhost:4222", size_threshold=100000 ) print("Message sent!") ``` ### Example 4: Request-Response Pattern Bi-directional communication with reply-to support. #### Julia ```julia using msghandler, NATS # Requester env, env_json_str = msghandler.smartpack( "/device/command", [("command", Dict("action" => "read_sensor"), "dictionary")]; broker_url="nats://localhost:4222", reply_to="/device/response" ) conn = NATS.connect("nats://localhost:4222") NATS.publish(conn, "/device/command", env_json_str) NATS.drain(conn) # Receiver (in separate application) conn = NATS.connect("nats://localhost:4222") NATS.subscribe(conn, "/device/command") do msg env = msghandler.smartunpack(msg) println("Received command: ", env["payloads"]) result = Dict("value" => 42) response_env, response_json = msghandler.smartpack( "/device/response", [("result", result, "dictionary")], reply_to="/device/command", reply_to_msg_id=env["msg_id"] ) NATS.publish(conn, "/device/response", response_json) NATS.drain(conn) end ``` #### JavaScript (Node.js) ```javascript import msghandler from './src/msghandler_ssr.js'; import { connect } from 'nats'; // Requester const [env, env_json_str] = await msghandler.smartpack( "/device/command", [["command", { action: "read_sensor" }, "dictionary"]], { broker_url: 'nats://localhost:4222', reply_to: '/device/response' } ); const nc = await connect({ port: 4222 }); nc.publish("/device/command", env_json_str); await nc.flush(); // Receiver (in separate application) const nc = await connect({ port: 4222 }); const sub = nc.subscribe("/device/command"); for await (const msg of sub) { const env = await msghandler.smartunpack(msg); console.log("Received command:", env.payloads); const response_env, response_json = await msghandler.smartpack( "/device/response", [["result", { value: 42 }, "dictionary"]], { reply_to: '/device/command', reply_to_msg_id: env.msg_id } ); nc.publish("/device/response", response_json); await nc.flush(); } ``` #### Python ```python import asyncio from msghandler import smartpack async def main(): # Requester env, env_json_str = await smartpack( "/device/command", [("command", {"action": "read_sensor"}, "dictionary")], broker_url="nats://localhost:4222", reply_to="/device/response" ) print("Request sent!") # Receiver (in separate application) # await nats_consumer.next() # env = await smartunpack(msg) # Process request and send response # response_env, response_json = await smartpack( # "/device/response", # [("result", {"value": 42}, "dictionary")], # reply_to="/device/command", # reply_to_msg_id=env["msg_id"] # ) if __name__ == "__main__": asyncio.run(main()) ``` #### JavaScript (Browser) ```javascript import msghandler from './src/msghandler_csr.js'; // Requester const [env, env_json_str] = await msghandler.smartpack( "/device/command", [["command", { action: "read_sensor" }, "dictionary"]], { broker_url: 'ws://localhost:4222', reply_to: '/device/response' } ); console.log("Request sent!"); // Receiver (in separate application) // const msg = await natsConsumer.next(); // const env = await msghandler.smartunpack(msg); // console.log("Received command:", env.payloads); // const response_env, response_json = await msghandler.smartpack( // "/device/response", // [["result", { value: 42 }, "dictionary"]], // { reply_to: '/device/command', reply_to_msg_id: env.msg_id } // ); ``` #### MicroPython ```python from msghandler import smartpack # Requester env, env_json_str = smartpack( "/device/command", [("command", {"action": "read_sensor"}, "dictionary")], broker_url="nats://localhost:4222", reply_to="/device/response", size_threshold=100000 ) print("Request sent!") ``` --- ## Testing ### Test File Organization | Platform | Sender Tests | Receiver Tests | |----------|--------------|----------------| | **Julia** | `test/test_julia_*_sender.jl` | `test/test_julia_*_receiver.jl` | | **JavaScript** | `test/test_js_*_sender.js` | `test/test_js_*_receiver.js` | | **Python** | `test/test_py_*_sender.py` | `test/test_py_*_receiver.py` | ### Run Tests #### Julia ```bash # Text message exchange julia test/test_julia_text_sender.jl julia test/test_julia_text_receiver.jl # Dictionary exchange julia test/test_julia_dict_sender.jl julia test/test_julia_dict_receiver.jl # File transfer julia test/test_julia_file_sender.jl julia test/test_julia_file_receiver.jl # Mixed payload types julia test/test_julia_mix_payloads_sender.jl julia test/test_julia_mix_payloads_receiver.jl # Table exchange julia test/test_julia_table_sender.jl julia test/test_julia_table_receiver.jl ``` #### JavaScript (Node.js) ```bash # Text message exchange node test/test_js_text_sender.js node test/test_js_text_receiver.js # Dictionary exchange node test/test_js_dictionary_sender.js node test/test_js_dictionary_receiver.js # Binary transfer node test/test_js_binary_sender.js node test/test_js_binary_receiver.js # Table exchange node test/test_js_table_sender.js node test/test_js_table_receiver.js ``` #### Python ```bash # Text message exchange python3 test/test_py_text_sender.py python3 test/test_py_text_receiver.py # Dictionary exchange python3 test/test_py_dictionary_sender.py python3 test/test_py_dictionary_receiver.py # Binary transfer python3 test/test_py_binary_sender.py python3 test/test_py_binary_receiver.py # Table exchange python3 test/test_py_table_sender.py python3 test/test_py_table_receiver.py ``` --- ## Browser Deployment ### Using with Node.js Build Tools The browser implementation (`src/msghandler_csr.js`) can be bundled for production deployment using modern JavaScript build tools. #### Prerequisites ```bash # Install the browser-compatible NATS client npm install nats.ws ``` #### Vite (Recommended) ```bash npm create vite@latest my-app -- --template vanilla cd my-app npm install nats.ws ``` In `vite.config.js`: ```javascript import { defineConfig } from 'vite'; export default defineConfig({ resolve: { alias: { 'nats.ws': 'nats.ws/dist/esm/browser.js' } } }); ``` Build command: ```bash npm run build # Outputs to dist/ folder ``` #### Webpack ```bash npm install webpack webpack-cli --save-dev npm install nats.ws ``` In `webpack.config.js`: ```javascript module.exports = { entry: './src/index.js', output: { filename: 'bundle.js', path: __dirname + '/dist' }, resolve: { alias: { 'nats.ws': 'nats.ws/dist/esm/browser.js' } } }; ``` Build command: ```bash npx webpack ``` #### esbuild (Simple & Fast) ```bash npm install esbuild nats.ws --save-dev ``` Create `build.js`: ```javascript import esbuild from 'esbuild'; esbuild.buildSync({ entryPoints: ['src/msghandler_csr.js'], bundle: true, outfile: 'dist/msghandler-csr-bundle.js', format: 'esm', platform: 'browser', target: 'es2020' }); ``` Build command: ```bash node build.js ``` ### Using in Your HTML ```html My App ``` --- ## Documentation For detailed architecture and implementation information, see: - [`docs/architecture.md`](docs/architecture.md) - Cross-platform architecture, API parity, platform-specific patterns - [`docs/requirements.md`](docs/requirements.md) - Business requirements and user stories - [`docs/spec.md`](docs/spec.md) - Technical specification and contracts - [`docs/walkthrough.md`](docs/walkthrough.md) - Real-world application building guides --- ## License MIT License Copyright (c) 2026 msghandler Contributors 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.