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src/NATSBridge.js
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/**
* NATSBridge.js - Bi-Directional Data Bridge for JavaScript
* Implements smartsend and smartreceive for NATS communication
*
* This module provides functionality for sending and receiving data across network boundaries
* using NATS as the message bus, with support for both direct payload transport and
* URL-based transport for larger payloads.
*
* File Server Handler Architecture:
* The system uses handler functions to abstract file server operations, allowing support
* for different file server implementations (e.g., Plik, AWS S3, custom HTTP server).
*
* Handler Function Signatures:
*
* ```javascript
* // Upload handler - uploads data to file server and returns URL
* // The handler is passed to smartsend as fileserverUploadHandler parameter
* // It receives: (fileserver_url, dataname, data)
* // Returns: { status, uploadid, fileid, url }
* async function plik_oneshot_upload(fileserver_url, dataname, data) { ... }
*
* // Download handler - fetches data from file server URL with exponential backoff
* // The handler is passed to smartreceive as fileserverDownloadHandler parameter
* // It receives: (url, max_retries, base_delay, max_delay, correlation_id)
* // Returns: ArrayBuffer (the downloaded data)
* async function fileserverDownloadHandler(url, max_retries, base_delay, max_delay, correlation_id) { ... }
* ```
*
* Multi-Payload Support (Standard API):
* The system uses a standardized list-of-tuples format for all payload operations.
* Even when sending a single payload, the user must wrap it in a list.
*
* API Standard:
* ```javascript
* // Input format for smartsend (always a list of tuples with type info)
* [{ dataname, data, type }, ...]
*
* // Output format for smartreceive (always returns a list of tuples)
* [{ dataname, data, type }, ...]
* ```
*
* Supported types: "text", "dictionary", "table", "image", "audio", "video", "binary"
*/
// ---------------------------------------------- 100 --------------------------------------------- #
// Constants
const DEFAULT_SIZE_THRESHOLD = 1_000_000; // 1MB - threshold for switching from direct to link transport
const DEFAULT_NATS_URL = "nats://localhost:4222"; // Default NATS server URL
const DEFAULT_FILESERVER_URL = "http://localhost:8080"; // Default HTTP file server URL for link transport
// Helper: Generate UUID v4
function uuid4() {
// Simple UUID v4 generator
return 'xxxxxxxx-xxxx-4xxx-yxxx-xxxxxxxxxxxx'.replace(/[xy]/g, function(c) {
var r = Math.random() * 16 | 0, v = c == 'x' ? r : (r & 0x3 | 0x8);
return v.toString(16);
});
}
// Helper: Log with correlation ID and timestamp
function log_trace(correlation_id, message) {
const timestamp = new Date().toISOString();
console.log(`[${timestamp}] [Correlation: ${correlation_id}] ${message}`);
}
// Helper: Get size of data in bytes
function getDataSize(data) {
if (typeof data === 'string') {
return new TextEncoder().encode(data).length;
} else if (data instanceof ArrayBuffer || data instanceof Uint8Array) {
return data.byteLength;
} else if (typeof data === 'object' && data !== null) {
// For objects, serialize to JSON and measure
return new TextEncoder().encode(JSON.stringify(data)).length;
}
return 0;
}
// Helper: Convert ArrayBuffer to Base64 string
function arrayBufferToBase64(buffer) {
const bytes = new Uint8Array(buffer);
let binary = '';
for (let i = 0; i < bytes.length; i++) {
binary += String.fromCharCode(bytes[i]);
}
return btoa(binary);
}
// Helper: Convert Base64 string to ArrayBuffer
function base64ToArrayBuffer(base64) {
const binaryString = atob(base64);
const len = binaryString.length;
const bytes = new Uint8Array(len);
for (let i = 0; i < len; i++) {
bytes[i] = binaryString.charCodeAt(i);
}
return bytes.buffer;
}
// Helper: Convert Uint8Array to Base64 string
function uint8ArrayToBase64(uint8array) {
let binary = '';
for (let i = 0; i < uint8array.byteLength; i++) {
binary += String.fromCharCode(uint8array[i]);
}
return btoa(binary);
}
// Helper: Convert Base64 string to Uint8Array
function base64ToUint8Array(base64) {
const binaryString = atob(base64);
const len = binaryString.length;
const bytes = new Uint8Array(len);
for (let i = 0; i < len; i++) {
bytes[i] = binaryString.charCodeAt(i);
}
return bytes;
}
// Helper: Serialize data based on type
function _serialize_data(data, type) {
/**
* Serialize data according to specified format
*
* Supported formats:
* - "text": Treats data as text and converts to UTF-8 bytes
* - "dictionary": Serializes data as JSON and returns the UTF-8 byte representation
* - "table": Serializes data as an Arrow IPC stream (table format) - NOT IMPLEMENTED (requires arrow library)
* - "image": Expects binary data (ArrayBuffer) and returns it as bytes
* - "audio": Expects binary data (ArrayBuffer) and returns it as bytes
* - "video": Expects binary data (ArrayBuffer) and returns it as bytes
* - "binary": Generic binary data (ArrayBuffer or Uint8Array) and returns bytes
*/
if (type === "text") {
if (typeof data === 'string') {
return new TextEncoder().encode(data);
} else {
throw new Error("Text data must be a String");
}
} else if (type === "dictionary") {
// JSON data - serialize directly
const jsonStr = JSON.stringify(data);
return new TextEncoder().encode(jsonStr);
} else if (type === "table") {
// Table data - convert to Arrow IPC stream (NOT IMPLEMENTED in pure JavaScript)
// This would require the apache-arrow library
throw new Error("Table serialization requires apache-arrow library");
} else if (type === "image") {
if (data instanceof ArrayBuffer || data instanceof Uint8Array) {
return data instanceof ArrayBuffer ? new Uint8Array(data) : data;
} else {
throw new Error("Image data must be ArrayBuffer or Uint8Array");
}
} else if (type === "audio") {
if (data instanceof ArrayBuffer || data instanceof Uint8Array) {
return data instanceof ArrayBuffer ? new Uint8Array(data) : data;
} else {
throw new Error("Audio data must be ArrayBuffer or Uint8Array");
}
} else if (type === "video") {
if (data instanceof ArrayBuffer || data instanceof Uint8Array) {
return data instanceof ArrayBuffer ? new Uint8Array(data) : data;
} else {
throw new Error("Video data must be ArrayBuffer or Uint8Array");
}
} else if (type === "binary") {
if (data instanceof ArrayBuffer || data instanceof Uint8Array) {
return data instanceof ArrayBuffer ? new Uint8Array(data) : data;
} else {
throw new Error("Binary data must be ArrayBuffer or Uint8Array");
}
} else {
throw new Error(`Unknown type: ${type}`);
}
}
// Helper: Deserialize bytes based on type
function _deserialize_data(data, type, correlation_id) {
/**
* Deserialize bytes to data based on type
*
* Supported formats:
* - "text": Converts bytes to string
* - "dictionary": Parses JSON string
* - "table": Parses Arrow IPC stream - NOT IMPLEMENTED (requires apache-arrow library)
* - "image": Returns binary data
* - "audio": Returns binary data
* - "video": Returns binary data
* - "binary": Returns binary data
*/
if (type === "text") {
const decoder = new TextDecoder();
return decoder.decode(data);
} else if (type === "dictionary") {
const decoder = new TextDecoder();
const jsonStr = decoder.decode(data);
return JSON.parse(jsonStr);
} else if (type === "table") {
// Table data - deserialize Arrow IPC stream (NOT IMPLEMENTED in pure JavaScript)
throw new Error("Table deserialization requires apache-arrow library");
} else if (type === "image") {
return data;
} else if (type === "audio") {
return data;
} else if (type === "video") {
return data;
} else if (type === "binary") {
return data;
} else {
throw new Error(`Unknown type: ${type}`);
}
}
// Helper: Upload data to file server
// Internal wrapper that adds correlation_id logging for smartsend
async function _upload_to_fileserver(fileserver_url, dataname, data, correlation_id) {
/**
* Internal upload helper - wraps plik_oneshot_upload to add correlation_id logging
* This allows smartsend to pass correlation_id for tracing without changing the handler signature
*/
log_trace(correlation_id, `Uploading ${dataname} to fileserver: ${fileserver_url}`);
const result = await plik_oneshot_upload(fileserver_url, dataname, data);
log_trace(correlation_id, `Uploaded to URL: ${result.url}`);
return result;
}
// Helper: Fetch data from URL with exponential backoff
async function _fetch_with_backoff(url, max_retries, base_delay, max_delay, correlation_id) {
/**
* Fetch data from URL with retry logic using exponential backoff
*/
let delay = base_delay;
for (let attempt = 1; attempt <= max_retries; attempt++) {
try {
const response = await fetch(url);
if (response.status === 200) {
log_trace(correlation_id, `Successfully fetched data from ${url} on attempt ${attempt}`);
const arrayBuffer = await response.arrayBuffer();
return new Uint8Array(arrayBuffer);
} else {
throw new Error(`Failed to fetch: ${response.status} ${response.statusText}`);
}
} catch (e) {
log_trace(correlation_id, `Attempt ${attempt} failed: ${e.message}`);
if (attempt < max_retries) {
// Sleep with exponential backoff
await new Promise(resolve => setTimeout(resolve, delay));
delay = Math.min(delay * 2, max_delay);
}
}
}
throw new Error(`Failed to fetch data after ${max_retries} attempts`);
}
// Helper: Get payload bytes from data
function _get_payload_bytes(data) {
if (data instanceof ArrayBuffer || data instanceof Uint8Array) {
return data instanceof ArrayBuffer ? new Uint8Array(data) : data;
} else if (typeof data === 'string') {
return new TextEncoder().encode(data);
} else {
// For objects, serialize to JSON
return new TextEncoder().encode(JSON.stringify(data));
}
}
// MessagePayload class - matches msg_payload_v1 Julia struct
class MessagePayload {
/**
* Represents a single payload in the message envelope
* Matches Julia's msg_payload_v1 struct
*
* @param {Object} options - Payload options
* @param {string} options.id - ID of this payload (e.g., "uuid4")
* @param {string} options.dataname - Name of this payload (e.g., "login_image")
* @param {string} options.payload_type - Payload type: "text", "dictionary", "table", "image", "audio", "video", "binary"
* @param {string} options.transport - "direct" or "link"
* @param {string} options.encoding - "none", "json", "base64", "arrow-ipc"
* @param {number} options.size - Data size in bytes
* @param {string|Uint8Array} options.data - Payload data (Uint8Array for direct, URL string for link)
* @param {Object} options.metadata - Metadata for this payload
*/
constructor(options) {
this.id = options.id || uuid4();
this.dataname = options.dataname;
this.payload_type = options.payload_type;
this.transport = options.transport;
this.encoding = options.encoding;
this.size = options.size;
this.data = options.data;
this.metadata = options.metadata || {};
}
// Convert to JSON object - uses snake_case to match Julia API
toJSON() {
const obj = {
id: this.id,
dataname: this.dataname,
payload_type: this.payload_type,
transport: this.transport,
encoding: this.encoding,
size: this.size
};
// Include data based on transport type
if (this.transport === "direct" && this.data !== null && this.data !== undefined) {
if (this.encoding === "base64" || this.encoding === "json") {
obj.data = this.data;
} else {
// For other encodings, use base64
const payloadBytes = _get_payload_bytes(this.data);
obj.data = uint8ArrayToBase64(payloadBytes);
}
} else if (this.transport === "link" && this.data !== null && this.data !== undefined) {
// For link transport, data is a URL string
obj.data = this.data;
}
if (Object.keys(this.metadata).length > 0) {
obj.metadata = this.metadata;
}
return obj;
}
}
// MessageEnvelope class - matches msg_envelope_v1 Julia struct
class MessageEnvelope {
/**
* Represents the message envelope containing metadata and payloads
* Matches Julia's msg_envelope_v1 struct
*
* @param {Object} options - Envelope options
* @param {string} options.correlation_id - Unique identifier to track messages
* @param {string} options.msg_id - This message id
* @param {string} options.timestamp - Message published timestamp
* @param {string} options.send_to - Topic/subject the sender sends to
* @param {string} options.msg_purpose - Purpose of this message
* @param {string} options.sender_name - Name of the sender
* @param {string} options.sender_id - UUID of the sender
* @param {string} options.receiver_name - Name of the receiver
* @param {string} options.receiver_id - UUID of the receiver
* @param {string} options.reply_to - Topic to reply to
* @param {string} options.reply_to_msg_id - Message id this message is replying to
* @param {string} options.broker_url - NATS server address
* @param {Object} options.metadata - Metadata for the envelope
* @param {Array<MessagePayload>} options.payloads - Array of payloads
*/
constructor(options) {
this.correlation_id = options.correlation_id || uuid4();
this.msg_id = options.msg_id || uuid4();
this.timestamp = options.timestamp || new Date().toISOString();
this.send_to = options.send_to;
this.msg_purpose = options.msg_purpose || "";
this.sender_name = options.sender_name || "";
this.sender_id = options.sender_id || uuid4();
this.receiver_name = options.receiver_name || "";
this.receiver_id = options.receiver_id || "";
this.reply_to = options.reply_to || "";
this.reply_to_msg_id = options.reply_to_msg_id || "";
this.broker_url = options.broker_url || DEFAULT_NATS_URL;
this.metadata = options.metadata || {};
this.payloads = options.payloads || [];
}
// Convert to JSON object - uses snake_case to match Julia API
toJSON() {
const obj = {
correlation_id: this.correlation_id,
msg_id: this.msg_id,
timestamp: this.timestamp,
send_to: this.send_to,
msg_purpose: this.msg_purpose,
sender_name: this.sender_name,
sender_id: this.sender_id,
receiver_name: this.receiver_name,
receiver_id: this.receiver_id,
reply_to: this.reply_to,
reply_to_msg_id: this.reply_to_msg_id,
broker_url: this.broker_url
};
if (Object.keys(this.metadata).length > 0) {
obj.metadata = this.metadata;
}
if (this.payloads.length > 0) {
obj.payloads = this.payloads.map(p => p.toJSON());
}
return obj;
}
// Convert to JSON string
toString() {
return JSON.stringify(this.toJSON());
}
}
// SmartSend function - matches Julia smartsend signature and behavior
async function smartsend(subject, data, options = {}) {
/**
* Send data either directly via NATS or via a fileserver URL, depending on payload size
*
* This function intelligently routes data delivery based on payload size relative to a threshold.
* If the serialized payload is smaller than `size_threshold`, it encodes the data as Base64 and publishes directly over NATS.
* Otherwise, it uploads the data to a fileserver and publishes only the download URL over NATS.
*
* @param {string} subject - NATS subject to publish the message to
* @param {Array} data - List of {dataname, data, type} objects to send (must be a list, even for single payload)
* @param {Object} options - Additional options
* @param {string} options.broker_url - URL of the NATS server (default: "nats://localhost:4222")
* @param {string} options.fileserver_url - Base URL of the file server (default: "http://localhost:8080")
* @param {Function} options.fileserver_upload_handler - Function to handle fileserver uploads
* @param {number} options.size_threshold - Threshold in bytes separating direct vs link transport (default: 1MB)
* @param {string} options.correlation_id - Optional correlation ID for tracing
* @param {string} options.msg_purpose - Purpose of the message (default: "chat")
* @param {string} options.sender_name - Name of the sender (default: "NATSBridge")
* @param {string} options.receiver_name - Name of the receiver (default: "")
* @param {string} options.receiver_id - UUID of the receiver (default: "")
* @param {string} options.reply_to - Topic to reply to (default: "")
* @param {string} options.reply_to_msg_id - Message ID this message is replying to (default: "")
* @param {boolean} options.is_publish - Whether to automatically publish the message to NATS (default: true)
* - When true: Message is published to NATS automatically
* - When false: Returns (env, env_json_str) without publishing, allowing manual publishing
* @returns {Promise<Object>} - A tuple-like object with { env: MessageEnvelope, env_json_str: string }
* - env: MessageEnvelope object with all metadata and payloads
* - env_json_str: JSON string representation of the envelope for manual publishing
*/
const {
broker_url = DEFAULT_NATS_URL,
fileserver_url = DEFAULT_FILESERVER_URL,
fileserver_upload_handler = _upload_to_fileserver,
size_threshold = DEFAULT_SIZE_THRESHOLD,
correlation_id = uuid4(),
msg_purpose = "chat",
sender_name = "NATSBridge",
receiver_name = "",
receiver_id = "",
reply_to = "",
reply_to_msg_id = "",
is_publish = true // Whether to automatically publish the message to NATS
} = options;
log_trace(correlation_id, `Starting smartsend for subject: ${subject}`);
// Generate message metadata
const msg_id = uuid4();
// Process each payload in the list
const payloads = [];
for (const payload of data) {
const dataname = payload.dataname;
const payloadData = payload.data;
const payloadType = payload.type;
// Serialize data based on type
const payloadBytes = _serialize_data(payloadData, payloadType);
const payloadSize = payloadBytes.byteLength;
log_trace(correlation_id, `Serialized payload '${dataname}' (payload_type: ${payloadType}) size: ${payloadSize} bytes`);
// Decision: Direct vs Link
if (payloadSize < size_threshold) {
// Direct path - Base64 encode and send via NATS
const payloadB64 = uint8ArrayToBase64(payloadBytes);
log_trace(correlation_id, `Using direct transport for ${payloadSize} bytes`);
// Create MessagePayload for direct transport
const payloadObj = new MessagePayload({
dataname: dataname,
payload_type: payloadType,
transport: "direct",
encoding: "base64",
size: payloadSize,
data: payloadB64,
metadata: { payload_bytes: payloadSize }
});
payloads.push(payloadObj);
} else {
// Link path - Upload to HTTP server, send URL via NATS
log_trace(correlation_id, `Using link transport, uploading to fileserver`);
// Upload to HTTP server using plik_oneshot_upload handler
const response = await fileserver_upload_handler(fileserver_url, dataname, payloadBytes);
if (response.status !== 200) {
throw new Error(`Failed to upload data to fileserver: ${response.status}`);
}
const url = response.url;
log_trace(correlation_id, `Uploaded to URL: ${url}`);
// Create MessagePayload for link transport
const payloadObj = new MessagePayload({
dataname: dataname,
payload_type: payloadType,
transport: "link",
encoding: "none",
size: payloadSize,
data: url,
metadata: {}
});
payloads.push(payloadObj);
}
}
// Create MessageEnvelope with all payloads
const env = new MessageEnvelope({
correlation_id: correlation_id,
msg_id: msg_id,
send_to: subject,
msg_purpose: msg_purpose,
sender_name: sender_name,
receiver_name: receiver_name,
receiver_id: receiver_id,
reply_to: reply_to,
reply_to_msg_id: reply_to_msg_id,
broker_url: broker_url,
payloads: payloads
});
// Convert envelope to JSON string
const env_json_str = env.toString();
// Publish to NATS if isPublish is true
if (is_publish) {
await publish_message(broker_url, subject, env_json_str, correlation_id);
}
// Return both envelope and JSON string (tuple-like structure, matching Julia API)
return {
env: env,
env_json_str: env_json_str
};
}
// Helper: Publish message to NATS
async function publish_message(broker_url, subject, message, correlation_id) {
/**
* Publish a message to a NATS subject with proper connection management
*
* @param {string} broker_url - NATS server URL
* @param {string} subject - NATS subject to publish to
* @param {string} message - JSON message to publish
* @param {string} correlation_id - Correlation ID for logging
*/
log_trace(correlation_id, `Publishing message to ${subject}`);
// For Node.js, we would use nats.js library
// This is a placeholder that throws an error
// In production, you would import and use the actual nats library
// Example with nats.js:
// import { connect } from 'nats';
// const nc = await connect({ servers: [broker_url] });
// await nc.publish(subject, message);
// nc.close();
// For now, just log the message
console.log(`[NATS PUBLISH] Subject: ${subject}, Message: ${message.substring(0, 100)}...`);
}
// SmartReceive function - matches Julia smartreceive signature and behavior
async function smartreceive(msg, options = {}) {
/**
* Receive and process messages from NATS
*
* This function processes incoming NATS messages, handling both direct transport
* (base64 decoded payloads) and link transport (URL-based payloads).
*
* @param {Object} msg - NATS message object with payload property
* @param {Object} options - Additional options
* @param {Function} options.fileserver_download_handler - Function to handle downloading data from file server URLs
* @param {number} options.max_retries - Maximum retry attempts for fetching URL (default: 5)
* @param {number} options.base_delay - Initial delay for exponential backoff in ms (default: 100)
* @param {number} options.max_delay - Maximum delay for exponential backoff in ms (default: 5000)
*
* @returns {Promise<Object>} - JSON object of envelope with payloads field containing list of {dataname, data, type} tuples
*/
const {
fileserver_download_handler = _fetch_with_backoff,
max_retries = 5,
base_delay = 100,
max_delay = 5000
} = options;
// Parse the JSON envelope
const jsonStr = typeof msg.payload === 'string' ? msg.payload : new TextDecoder().decode(msg.payload);
const json_data = JSON.parse(jsonStr);
log_trace(json_data.correlation_id, `Processing received message`);
// Process all payloads in the envelope
const payloads_list = [];
// Get number of payloads
const num_payloads = json_data.payloads ? json_data.payloads.length : 0;
for (let i = 0; i < num_payloads; i++) {
const payload = json_data.payloads[i];
const transport = payload.transport;
const dataname = payload.dataname;
if (transport === "direct") {
// Direct transport - payload is in the message
log_trace(json_data.correlation_id, `Direct transport - decoding payload '${dataname}'`);
// Extract base64 payload from the payload
const payload_b64 = payload.data;
// Decode Base64 payload
const payload_bytes = base64ToUint8Array(payload_b64);
// Deserialize based on type
const data_type = payload.payload_type;
const data = _deserialize_data(payload_bytes, data_type, json_data.correlation_id);
payloads_list.push({ dataname, data, type: data_type });
} else if (transport === "link") {
// Link transport - payload is at URL
const url = payload.data;
log_trace(json_data.correlation_id, `Link transport - fetching '${dataname}' from URL: ${url}`);
// Fetch with exponential backoff using the download handler
const downloaded_data = await fileserver_download_handler(
url, max_retries, base_delay, max_delay, json_data.correlation_id
);
// Deserialize based on type
const data_type = payload.payload_type;
const data = _deserialize_data(downloaded_data, data_type, json_data.correlation_id);
payloads_list.push({ dataname, data, type: data_type });
} else {
throw new Error(`Unknown transport type for payload '${dataname}': ${transport}`);
}
}
// Replace payloads array with the processed list of {dataname, data, type} tuples
// This matches Julia's smartreceive return format
json_data.payloads = payloads_list;
return json_data;
}
// plik_oneshot_upload - matches Julia plik_oneshot_upload function
// Upload handler signature: plik_oneshot_upload(fileserver_url, dataname, data)
// Returns: { status, uploadid, fileid, url }
async function plik_oneshot_upload(file_server_url, dataname, data) {
/**
* Upload a single file to a plik server using one-shot mode
* This function uploads raw byte array to a plik server in one-shot mode (no upload session).
* It first creates a one-shot upload session by sending a POST request with {"OneShot": true},
* retrieves an upload ID and token, then uploads the file data as multipart form data using the token.
*
* This is the default upload handler used by smartsend.
* Custom handlers can be passed via the fileserver_upload_handler option.
*
* @param {string} file_server_url - Base URL of the plik server (e.g., "http://localhost:8080")
* @param {string} dataname - Name of the file being uploaded
* @param {Uint8Array} data - Raw byte data of the file content
* @returns {Promise<Object>} - Dictionary with keys: status, uploadid, fileid, url
*/
// Step 1: Get upload ID and token
const url_getUploadID = `${file_server_url}/upload`;
const headers = { "Content-Type": "application/json" };
const body = JSON.stringify({ OneShot: true });
let http_response = await fetch(url_getUploadID, {
method: "POST",
headers: headers,
body: body
});
const response_json = await http_response.json();
const uploadid = response_json.id;
const uploadtoken = response_json.uploadToken;
// Step 2: Upload file data
const url_upload = `${file_server_url}/file/${uploadid}`;
// Create multipart form data
const formData = new FormData();
const blob = new Blob([data], { type: "application/octet-stream" });
formData.append("file", blob, dataname);
http_response = await fetch(url_upload, {
method: "POST",
headers: { "X-UploadToken": uploadtoken },
body: formData
});
const fileResponseJson = await http_response.json();
const fileid = fileResponseJson.id;
// URL of the uploaded data e.g. "http://192.168.1.20:8080/file/3F62E/4AgGT/test.zip"
const url = `${file_server_url}/file/${uploadid}/${fileid}/${encodeURIComponent(dataname)}`;
return {
status: http_response.status,
uploadid: uploadid,
fileid: fileid,
url: url
};
}
// Export for Node.js
if (typeof module !== 'undefined' && module.exports) {
module.exports = {
MessageEnvelope,
MessagePayload,
smartsend,
smartreceive,
_serialize_data,
_deserialize_data,
_fetch_with_backoff,
_upload_to_fileserver,
plik_oneshot_upload,
DEFAULT_SIZE_THRESHOLD,
DEFAULT_NATS_URL,
DEFAULT_FILESERVER_URL,
uuid4,
log_trace
};
}
// Export for browser
if (typeof window !== 'undefined') {
window.NATSBridge = {
MessageEnvelope,
MessagePayload,
smartsend,
smartreceive,
_serialize_data,
_deserialize_data,
_fetch_with_backoff,
_upload_to_fileserver,
plik_oneshot_upload,
DEFAULT_SIZE_THRESHOLD,
DEFAULT_NATS_URL,
DEFAULT_FILESERVER_URL,
uuid4,
log_trace
};
}

871
src/nats_bridge.py
View File

@@ -1,871 +0,0 @@
"""
Python NATS Bridge - Bi-Directional Data Bridge
This module provides functionality for sending and receiving data over NATS
using the Claim-Check pattern for large payloads.
Supported types: "text", "dictionary", "table", "image", "audio", "video", "binary"
Multi-Payload Support (Standard API):
The system uses a standardized list-of-tuples format for all payload operations.
Even when sending a single payload, the user must wrap it in a list.
API Standard:
# Input format for smartsend (always a list of tuples with type info)
[(dataname1, data1, type1), (dataname2, data2, type2), ...]
# Output format for smartreceive (returns a dictionary with payloads field containing list of tuples)
# Returns: Dict with envelope metadata and payloads field containing list of tuples
# {
# "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), ...]
# }
"""
import json
import time
import uuid
# Constants
DEFAULT_SIZE_THRESHOLD = 1000000 # 1MB - threshold for switching from direct to link transport
DEFAULT_BROKER_URL = "nats://localhost:4222"
DEFAULT_FILESERVER_URL = "http://localhost:8080"
# ============================================= 100 ============================================== #
class MessagePayload:
"""Internal message payload structure representing a single payload within a NATS message envelope.
This structure represents a single payload within a NATS message envelope.
It supports both direct transport (base64-encoded data) and link transport (URL-based).
Attributes:
id: Unique identifier for this payload (e.g., "uuid4")
dataname: Name of the payload (e.g., "login_image")
payload_type: Payload type ("text", "dictionary", "table", "image", "audio", "video", "binary")
transport: Transport method ("direct" or "link")
encoding: Encoding method ("none", "json", "base64", "arrow-ipc")
size: Size of the payload in bytes
data: Payload data (bytes for direct, URL for link)
metadata: Optional metadata dictionary
"""
def __init__(self, data, payload_type, id="", dataname="", transport="direct",
encoding="none", size=0, metadata=None):
"""
Initialize a MessagePayload.
Args:
data: Payload data (base64 string for direct, URL string for link)
payload_type: Payload type ("text", "dictionary", "table", "image", "audio", "video", "binary")
id: Unique identifier for this payload (auto-generated if empty)
dataname: Name of the payload (auto-generated UUID if empty)
transport: Transport method ("direct" or "link")
encoding: Encoding method ("none", "json", "base64", "arrow-ipc")
size: Size of the payload in bytes
metadata: Optional metadata dictionary
"""
self.id = id if id else self._generate_uuid()
self.dataname = dataname if dataname else self._generate_uuid()
self.payload_type = payload_type
self.transport = transport
self.encoding = encoding
self.size = size
self.data = data
self.metadata = metadata if metadata else {}
def _generate_uuid(self):
"""Generate a UUID string."""
return str(uuid.uuid4())
def to_dict(self):
"""Convert payload to dictionary for JSON serialization."""
payload_dict = {
"id": self.id,
"dataname": self.dataname,
"payload_type": self.payload_type,
"transport": self.transport,
"encoding": self.encoding,
"size": self.size,
}
# Include data based on transport type
if self.transport == "direct" and self.data is not None:
if self.encoding == "base64" or self.encoding == "json":
payload_dict["data"] = self.data
else:
# For other encodings, use base64
payload_dict["data"] = self._to_base64(self.data)
elif self.transport == "link" and self.data is not None:
# For link transport, data is a URL string
payload_dict["data"] = self.data
if self.metadata:
payload_dict["metadata"] = self.metadata
return payload_dict
def _to_base64(self, data):
"""Convert bytes to base64 string."""
if isinstance(data, bytes):
# Simple base64 encoding without library
import ubinascii
return ubinascii.b2a_base64(data).decode('utf-8').strip()
return data
def _from_base64(self, data):
"""Convert base64 string to bytes."""
import ubinascii
return ubinascii.a2b_base64(data)
class MessageEnvelope:
"""Internal message envelope structure containing multiple payloads with metadata."""
def __init__(self, send_to, payloads, correlation_id="", msg_id="", timestamp="",
msg_purpose="", sender_name="", sender_id="", receiver_name="",
receiver_id="", reply_to="", reply_to_msg_id="", broker_url=DEFAULT_BROKER_URL,
metadata=None):
"""
Initialize a MessageEnvelope.
Args:
send_to: NATS subject/topic to publish the message to
payloads: List of MessagePayload objects
correlation_id: Unique identifier to track messages (auto-generated if empty)
msg_id: Unique message identifier (auto-generated if empty)
timestamp: Message publication timestamp
msg_purpose: Purpose of the message ("ACK", "NACK", "updateStatus", "shutdown", "chat", etc.)
sender_name: Name of the sender
sender_id: UUID of the sender
receiver_name: Name of the receiver (empty means broadcast)
receiver_id: UUID of the receiver (empty means broadcast)
reply_to: Topic where receiver should reply
reply_to_msg_id: Message ID this message is replying to
broker_url: NATS broker URL
metadata: Optional message-level metadata
"""
self.correlation_id = correlation_id if correlation_id else self._generate_uuid()
self.msg_id = msg_id if msg_id else self._generate_uuid()
self.timestamp = timestamp if timestamp else self._get_timestamp()
self.send_to = send_to
self.msg_purpose = msg_purpose
self.sender_name = sender_name
self.sender_id = sender_id if sender_id else self._generate_uuid()
self.receiver_name = receiver_name
self.receiver_id = receiver_id if receiver_id else self._generate_uuid()
self.reply_to = reply_to
self.reply_to_msg_id = reply_to_msg_id
self.broker_url = broker_url
self.metadata = metadata if metadata else {}
self.payloads = payloads
def _generate_uuid(self):
"""Generate a UUID string."""
return str(uuid.uuid4())
def _get_timestamp(self):
"""Get current timestamp in ISO format."""
# Simplified timestamp - Micropython may not have full datetime
return "2026-02-21T" + time.strftime("%H:%M:%S", time.localtime())
def to_json(self):
"""Convert envelope to JSON string.
Returns:
str: JSON string representation of the envelope using snake_case field names
"""
obj = {
"correlation_id": self.correlation_id,
"msg_id": self.msg_id,
"timestamp": self.timestamp,
"send_to": self.send_to,
"msg_purpose": self.msg_purpose,
"sender_name": self.sender_name,
"sender_id": self.sender_id,
"receiver_name": self.receiver_name,
"receiver_id": self.receiver_id,
"reply_to": self.reply_to,
"reply_to_msg_id": self.reply_to_msg_id,
"broker_url": self.broker_url
}
# Include metadata if not empty
if self.metadata:
obj["metadata"] = self.metadata
# Convert payloads to JSON array
if self.payloads:
payloads_json = []
for payload in self.payloads:
payloads_json.append(payload.to_dict())
obj["payloads"] = payloads_json
return json.dumps(obj)
def log_trace(correlation_id, message):
"""Log a trace message with correlation ID and timestamp."""
timestamp = time.strftime("%Y-%m-%dT%H:%M:%S", time.localtime())
print("[{}] [Correlation: {}] {}".format(timestamp, correlation_id, message))
def _serialize_data(data, payload_type):
"""Serialize data according to specified format.
This function serializes arbitrary data into a binary representation based on the specified type.
It supports multiple serialization formats for different data types.
Args:
data: Data to serialize
- "text": String
- "dictionary": JSON-serializable dict
- "table": Tabular data (pandas DataFrame or list of dicts)
- "image", "audio", "video", "binary": bytes
payload_type: Target format ("text", "dictionary", "table", "image", "audio", "video", "binary")
Returns:
bytes: Binary representation of the serialized data
Example:
>>> text_bytes = _serialize_data("Hello World", "text")
>>> json_bytes = _serialize_data({"key": "value"}, "dictionary")
>>> table_bytes = _serialize_data([{"id": 1, "name": "Alice"}], "table")
"""
if payload_type == "text":
if isinstance(data, str):
return data.encode('utf-8')
else:
raise ValueError("Text data must be a string")
elif payload_type == "dictionary":
if isinstance(data, dict):
json_str = json.dumps(data)
return json_str.encode('utf-8')
else:
raise ValueError("Dictionary data must be a dict")
elif payload_type == "table":
# Support pandas DataFrame or list of dicts
try:
import pandas as pd
if isinstance(data, pd.DataFrame):
# Convert DataFrame to JSON and then to bytes
json_str = data.to_json(orient='records', force_ascii=False)
return json_str.encode('utf-8')
elif isinstance(data, list) and len(data) > 0 and isinstance(data[0], dict):
# List of dicts
json_str = json.dumps(data)
return json_str.encode('utf-8')
else:
raise ValueError("Table data must be a pandas DataFrame or list of dicts")
except ImportError:
# Fallback: if pandas not available, treat as list of dicts
if isinstance(data, list):
json_str = json.dumps(data)
return json_str.encode('utf-8')
else:
raise ValueError("Table data requires pandas DataFrame or list of dicts (pandas not available)")
elif payload_type in ("image", "audio", "video", "binary"):
if isinstance(data, bytes):
return data
else:
raise ValueError("{} data must be bytes".format(payload_type.capitalize()))
else:
raise ValueError("Unknown payload_type: {}".format(payload_type))
def _deserialize_data(data_bytes, payload_type, correlation_id):
"""Deserialize bytes to data based on type.
This function converts serialized bytes back to Python data based on type.
It handles "text" (string), "dictionary" (JSON deserialization), "table" (JSON deserialization),
"image" (binary data), "audio" (binary data), "video" (binary data), and "binary" (binary data).
Args:
data_bytes: Serialized data as bytes
payload_type: Data type ("text", "dictionary", "table", "image", "audio", "video", "binary")
correlation_id: Correlation ID for logging
Returns:
Deserialized data:
- "text": str
- "dictionary": dict
- "table": list of dicts (or pandas DataFrame if available)
- "image", "audio", "video", "binary": bytes
Example:
>>> text_data = _deserialize_data(b"Hello", "text", "corr_id")
>>> json_data = _deserialize_data(b'{"key": "value"}', "dictionary", "corr_id")
>>> table_data = _deserialize_data(b'[{"id": 1}]', "table", "corr_id")
"""
if payload_type == "text":
return data_bytes.decode('utf-8')
elif payload_type == "dictionary":
json_str = data_bytes.decode('utf-8')
return json.loads(json_str)
elif payload_type == "table":
# Deserialize table data (JSON format)
json_str = data_bytes.decode('utf-8')
table_data = json.loads(json_str)
# If pandas is available, try to convert to DataFrame
try:
import pandas as pd
return pd.DataFrame(table_data)
except ImportError:
return table_data
elif payload_type in ("image", "audio", "video", "binary"):
return data_bytes
else:
raise ValueError("Unknown payload_type: {}".format(payload_type))
class NATSConnection:
"""Simple NATS connection for Python and Micropython."""
def __init__(self, url=DEFAULT_BROKER_URL):
"""Initialize NATS connection.
Args:
url: NATS server URL (e.g., "nats://localhost:4222")
"""
self.url = url
self.host = "localhost"
self.port = 4222
self.conn = None
self._parse_url(url)
def _parse_url(self, url):
"""Parse NATS URL to extract host and port."""
if url.startswith("nats://"):
url = url[7:]
elif url.startswith("tls://"):
url = url[6:]
if ":" in url:
self.host, port_str = url.split(":")
self.port = int(port_str)
else:
self.host = url
def connect(self):
"""Connect to NATS server."""
# Use socket for both Python and Micropython
try:
import socket
addr = socket.getaddrinfo(self.host, self.port)[0][-1]
self.conn = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
self.conn.connect(addr)
except NameError:
# Micropython fallback
import usocket
addr = usocket.getaddrinfo(self.host, self.port)[0][-1]
self.conn = usocket.socket()
self.conn.connect(addr)
log_trace("", "Connected to NATS server at {}:{}".format(self.host, self.port))
def publish(self, subject, message):
"""Publish a message to a NATS subject.
Args:
subject: NATS subject to publish to
message: Message to publish (should be bytes or string)
"""
if isinstance(message, str):
message = message.encode('utf-8')
# Simple NATS protocol implementation
msg = "PUB {} {}\r\n".format(subject, len(message))
msg = msg.encode('utf-8') + message + b"\r\n"
try:
import socket
self.conn.send(msg)
except NameError:
# Micropython fallback
import usocket
self.conn.send(msg)
log_trace("", "Message published to {}".format(subject))
def subscribe(self, subject, callback):
"""Subscribe to a NATS subject.
Args:
subject: NATS subject to subscribe to
callback: Callback function to handle incoming messages
"""
log_trace("", "Subscribed to {}".format(subject))
# Simplified subscription - in a real implementation, you'd handle SUB/PUB messages
# For Micropython, we'll use a simple polling approach
self.subscribed_subject = subject
self.subscription_callback = callback
def wait_message(self, timeout=1000):
"""Wait for incoming message.
Args:
timeout: Timeout in milliseconds
Returns:
NATS message object or None if timeout
"""
# Simplified message reading
# In a real implementation, you'd read from the socket
# For now, this is a placeholder
return None
def close(self):
"""Close the NATS connection."""
if self.conn:
self.conn.close()
self.conn = None
log_trace("", "NATS connection closed")
def _fetch_with_backoff(url, max_retries=5, base_delay=100, max_delay=5000, correlation_id=""):
"""Fetch data from URL with exponential backoff.
This function retrieves data from a URL with retry logic using
exponential backoff to handle transient failures.
Args:
url: URL to fetch from
max_retries: Maximum number of retry attempts (default: 5)
base_delay: Initial delay in milliseconds (default: 100)
max_delay: Maximum delay in milliseconds (default: 5000)
correlation_id: Correlation ID for logging
Returns:
bytes: Fetched data
Raises:
Exception: If all retry attempts fail
Example:
>>> data = _fetch_with_backoff("http://example.com/file.zip", 5, 100, 5000, "corr_id")
"""
delay = base_delay
for attempt in range(1, max_retries + 1):
try:
# Simple HTTP GET request
# Try urequests for Micropython first, then requests for Python
try:
import urequests
response = urequests.get(url)
status_code = response.status_code
content = response.content
except ImportError:
try:
import requests
response = requests.get(url)
response.raise_for_status()
status_code = response.status_code
content = response.content
except ImportError:
raise Exception("No HTTP library available (urequests or requests)")
if status_code == 200:
log_trace(correlation_id, "Successfully fetched data from {} on attempt {}".format(url, attempt))
return content
else:
raise Exception("Failed to fetch: {}".format(status_code))
except Exception as e:
log_trace(correlation_id, "Attempt {} failed: {}".format(attempt, str(e)))
if attempt < max_retries:
time.sleep(delay / 1000.0)
delay = min(delay * 2, max_delay)
raise Exception("Failed to fetch data after {} attempts".format(max_retries))
def plik_oneshot_upload(fileserver_url, dataname, data):
"""Upload a single file to a plik server using one-shot mode.
This function uploads raw byte data to a plik server in one-shot mode (no upload session).
It first creates a one-shot upload session by sending a POST request with {"OneShot": true},
retrieves an upload ID and token, then uploads the file data as multipart form data using the token.
Args:
fileserver_url: Base URL of the plik server (e.g., "http://localhost:8080")
dataname: Name of the file being uploaded
data: Raw byte data of the file content
Returns:
dict: Dictionary with keys:
- "status": HTTP server response status
- "uploadid": ID of the one-shot upload session
- "fileid": ID of the uploaded file within the session
- "url": Full URL to download the uploaded file
Example:
>>> result = plik_oneshot_upload("http://localhost:8080", "test.txt", b"hello world")
>>> result["status"], result["uploadid"], result["fileid"], result["url"]
"""
import json
try:
import urequests
except ImportError:
import requests as urequests
# Get upload ID
url_get_upload_id = "{}/upload".format(fileserver_url)
headers = {"Content-Type": "application/json"}
body = json.dumps({"OneShot": True})
response = urequests.post(url_get_upload_id, headers=headers, data=body)
response_json = json.loads(response.text if hasattr(response, 'text') else response.content)
uploadid = response_json.get("id")
uploadtoken = response_json.get("uploadToken")
# Upload file
url_upload = "{}/file/{}".format(fileserver_url, uploadid)
headers = {"X-UploadToken": uploadtoken}
# For Micropython, we need to construct the multipart form data manually
# This is a simplified approach
boundary = "----WebKitFormBoundary{}".format(uuid.uuid4().hex[:16])
# Create multipart body
part1 = "--{}\r\n".format(boundary)
part1 += "Content-Disposition: form-data; name=\"file\"; filename=\"{}\"\r\n".format(dataname)
part1 += "Content-Type: application/octet-stream\r\n\r\n"
part1_bytes = part1.encode('utf-8')
part2 = "\r\n--{}--".format(boundary)
part2_bytes = part2.encode('utf-8')
# Combine all parts
full_body = part1_bytes + data + part2_bytes
# Set content type with boundary
content_type = "multipart/form-data; boundary={}".format(boundary)
response = urequests.post(url_upload, headers={"Content-Type": content_type}, data=full_body)
response_json = json.loads(response.text if hasattr(response, 'text') else response.content)
fileid = response_json.get("id")
url = "{}/file/{}/{}".format(fileserver_url, uploadid, dataname)
return {
"status": response.status_code,
"uploadid": uploadid,
"fileid": fileid,
"url": url
}
def smartsend(subject, data, broker_url=DEFAULT_BROKER_URL, fileserver_url=DEFAULT_FILESERVER_URL,
fileserver_upload_handler=plik_oneshot_upload, size_threshold=DEFAULT_SIZE_THRESHOLD,
correlation_id=None, msg_purpose="chat", sender_name="NATSBridge",
receiver_name="", receiver_id="", reply_to="", reply_to_msg_id="", is_publish=True):
"""Send data either directly via NATS or via a fileserver URL, depending on payload size.
This function intelligently routes data delivery based on payload size relative to a threshold.
If the serialized payload is smaller than `size_threshold`, it encodes the data as Base64 and
publishes directly over NATS. Otherwise, it uploads the data to a fileserver and publishes
only the download URL over NATS.
API Standard:
- Input format: List of (dataname, data, payload_type) tuples
- Even single payloads must be wrapped in a list
- Each payload can have a different type, enabling mixed-content messages
Args:
subject: NATS subject to publish the message to
data: List of (dataname, data, payload_type) tuples to send
- dataname: Name of the payload
- data: The actual data to send
- payload_type: Payload type ("text", "dictionary", "table", "image", "audio", "video", "binary")
- Example: [("message", "Hello World!", "text"), ("config", {"key": "value"}, "dictionary")]
broker_url: URL of the NATS server
fileserver_url: URL of the HTTP file server
fileserver_upload_handler: Function to handle fileserver uploads (must return dict with "status", "uploadid", "fileid", "url" keys)
size_threshold: Threshold in bytes separating direct vs link transport (default: 1MB)
correlation_id: Optional correlation ID for tracing; if None, a UUID is generated
msg_purpose: Purpose of the message ("ACK", "NACK", "updateStatus", "shutdown", "chat", etc.)
sender_name: Name of the sender
receiver_name: Name of the receiver (empty string means broadcast)
receiver_id: UUID of the receiver (empty string means broadcast)
reply_to: Topic to reply to (empty string if no reply expected)
reply_to_msg_id: Message ID this message is replying to
is_publish: Whether to automatically publish the message to NATS (default: True)
- When True: message is published to NATS
- When False: returns envelope and JSON string without publishing
Returns:
tuple: (env, env_json_str) where:
- env: MessageEnvelope object with all metadata and payloads
- env_json_str: JSON string representation of the envelope for publishing
Example:
>>> data = [("message", "Hello World!", "text")]
>>> env, env_json_str = smartsend("/test", data)
>>> # env: MessageEnvelope with all metadata and payloads
>>> # env_json_str: JSON string for publishing
"""
# Generate correlation ID if not provided
cid = correlation_id if correlation_id is not None else str(uuid.uuid4())
log_trace(cid, "Starting smartsend for subject: {}".format(subject))
# Generate message metadata
msg_id = str(uuid.uuid4())
# Process each payload in the list
payloads = []
for dataname, payload_data, payload_type in data:
# Serialize data based on type
payload_bytes = _serialize_data(payload_data, payload_type)
payload_size = len(payload_bytes)
log_trace(cid, "Serialized payload '{}' (payload_type: {}) size: {} bytes".format(
dataname, payload_type, payload_size))
# Decision: Direct vs Link
if payload_size < size_threshold:
# Direct path - Base64 encode and send via NATS
# Convert to base64 string for JSON
try:
import ubinascii
payload_b64_str = ubinascii.b2a_base64(payload_bytes).decode('utf-8').strip()
except ImportError:
import base64
payload_b64_str = base64.b64encode(payload_bytes).decode('utf-8')
log_trace(cid, "Using direct transport for {} bytes".format(payload_size))
# Create MessagePayload for direct transport
payload = MessagePayload(
payload_b64_str,
payload_type,
id=str(uuid.uuid4()),
dataname=dataname,
transport="direct",
encoding="base64",
size=payload_size,
metadata={"payload_bytes": payload_size}
)
payloads.append(payload)
else:
# Link path - Upload to HTTP server, send URL via NATS
log_trace(cid, "Using link transport, uploading to fileserver")
# Upload to HTTP server
response = fileserver_upload_handler(fileserver_url, dataname, payload_bytes)
if response.get("status") != 200:
raise Exception("Failed to upload data to fileserver: {}".format(response.get("status")))
url = response.get("url")
log_trace(cid, "Uploaded to URL: {}".format(url))
# Create MessagePayload for link transport
payload = MessagePayload(
url,
payload_type,
id=str(uuid.uuid4()),
dataname=dataname,
transport="link",
encoding="none",
size=payload_size,
metadata={}
)
payloads.append(payload)
# Create MessageEnvelope with all payloads
env = MessageEnvelope(
subject,
payloads,
correlation_id=cid,
msg_id=msg_id,
msg_purpose=msg_purpose,
sender_name=sender_name,
sender_id=str(uuid.uuid4()),
receiver_name=receiver_name,
receiver_id=receiver_id,
reply_to=reply_to,
reply_to_msg_id=reply_to_msg_id,
broker_url=broker_url,
metadata={}
)
msg_json = env.to_json()
# Publish to NATS if is_publish is True
if is_publish:
nats_conn = NATSConnection(broker_url)
nats_conn.connect()
nats_conn.publish(subject, msg_json)
nats_conn.close()
# Return tuple of (envelope, json_string) for both direct and link transport
return (env, msg_json)
def smartreceive(msg, fileserver_download_handler=_fetch_with_backoff, max_retries=5,
base_delay=100, max_delay=5000):
"""Receive and process messages from NATS.
This function processes incoming NATS messages, handling both direct transport
(base64 decoded payloads) and link transport (URL-based payloads).
API Standard:
- Returns a dictionary with envelope metadata and 'payloads' field
- payloads field contains list of (dataname, data, payload_type) tuples
- Supports mixed-content messages with different payload types
Args:
msg: NATS message to process (dict or JSON string with envelope data)
fileserver_download_handler: Function to handle downloading data from file server URLs
Receives: (url, max_retries, base_delay, max_delay, correlation_id)
Returns: bytes (the downloaded data)
max_retries: Maximum retry attempts for fetching URL (default: 5)
base_delay: Initial delay for exponential backoff in ms (default: 100)
max_delay: Maximum delay for exponential backoff in ms (default: 5000)
Returns:
dict: Envelope dictionary with metadata and 'payloads' field containing list of
(dataname, data, payload_type) tuples
- Envelope fields: 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: List of (dataname, data, payload_type) tuples
Example:
>>> env = smartreceive(msg)
>>> # env contains envelope metadata and payloads field
>>> # env["payloads"] = [(dataname1, data1, payload_type1), ...]
>>> for dataname, data, payload_type in env["payloads"]:
... print("Received {} of type {}: {}".format(dataname, payload_type, data))
"""
# Parse the JSON envelope
json_data = msg if isinstance(msg, dict) else json.loads(msg)
correlation_id = json_data.get("correlation_id", "")
log_trace(correlation_id, "Processing received message")
# Process all payloads in the envelope
payloads_list = []
# Get number of payloads
num_payloads = len(json_data.get("payloads", []))
for i in range(num_payloads):
payload = json_data["payloads"][i]
transport = payload.get("transport", "")
dataname = payload.get("dataname", "")
if transport == "direct":
log_trace(correlation_id,
"Direct transport - decoding payload '{}'".format(dataname))
# Extract base64 payload from the payload
payload_b64 = payload.get("data", "")
# Decode Base64 payload
try:
import ubinascii
payload_bytes = ubinascii.a2b_base64(payload_b64.encode('utf-8'))
except ImportError:
import base64
payload_bytes = base64.b64decode(payload_b64)
# Deserialize based on type
payload_type = payload.get("payload_type", "")
data = _deserialize_data(payload_bytes, payload_type, correlation_id)
payloads_list.append((dataname, data, payload_type))
elif transport == "link":
# Extract download URL from the payload
url = payload.get("data", "")
log_trace(correlation_id,
"Link transport - fetching '{}' from URL: {}".format(dataname, url))
# Fetch with exponential backoff
downloaded_data = fileserver_download_handler(
url, max_retries, base_delay, max_delay, correlation_id
)
# Deserialize based on type
payload_type = payload.get("payload_type", "")
data = _deserialize_data(downloaded_data, payload_type, correlation_id)
payloads_list.append((dataname, data, payload_type))
else:
raise ValueError("Unknown transport type for payload '{}': {}".format(dataname, transport))
# Replace payloads field with the processed list of (dataname, data, payload_type) tuples
json_data["payloads"] = payloads_list
return json_data
# Utility functions
def generate_uuid():
"""Generate a UUID string."""
return str(uuid.uuid4())
def get_timestamp():
"""Get current timestamp in ISO format."""
return time.strftime("%Y-%m-%dT%H:%M:%S", time.localtime())
# Example usage
if __name__ == "__main__":
print("NATSBridge - Bi-Directional Data Bridge")
print("=======================================")
print("This module provides:")
print(" - MessageEnvelope: Message envelope structure with snake_case fields")
print(" - MessagePayload: Payload structure with payload_type field")
print(" - smartsend: Send data via NATS with automatic transport selection")
print(" - smartreceive: Receive and process messages from NATS")
print(" - plik_oneshot_upload: Upload files to HTTP file server")
print(" - _fetch_with_backoff: Fetch data from URLs with retry logic")
print()
print("Usage:")
print(" from nats_bridge import smartsend, smartreceive")
print()
print(" # Send data (list of (dataname, data, payload_type) tuples)")
print(" # Even single payloads must be wrapped in a list")
print(" data = [(\"message\", \"Hello World!\", \"text\")]")
print(" env, env_json_str = smartsend(\"my.subject\", data)")
print()
print(" # On receiver:")
print(" env = smartreceive(msg)")
print(" # env contains envelope metadata and payloads field")
print(" for dataname, data, payload_type in env[\"payloads\"]:")
print(" print(\"Received {} of type {}: {}\".format(dataname, payload_type, data))")
print()
print(" # Mixed-content message example:")
print(" mixed_data = [")
print(" (\"text\", \"Hello!\", \"text\"),")
print(" (\"config\", {\"key\": \"value\"}, \"dictionary\"),")
print(" (\"table\", [{\"id\": 1}], \"table\")")
print(" ]")
print(" smartsend(\"/chat\", mixed_data)")