10 Commits

Author SHA1 Message Date
ton
d950bbac23 Merge pull request 'smartreceive_return_envelope' (#7) from smartreceive_return_envelope into main
Reviewed-on: #7
2026-02-23 00:11:09 +00:00
fc8da2ebf5 update 2026-02-23 07:08:17 +07:00
f6e50c405f update 2026-02-23 07:06:53 +07:00
ton
c06f508e8f Merge pull request 'smartreceive_return_envelope' (#6) from smartreceive_return_envelope into main
Reviewed-on: #6
2026-02-22 23:59:13 +00:00
97bf1e47f4 update 2026-02-23 06:58:16 +07:00
ef47fddd56 update 2026-02-23 06:28:41 +07:00
896dd84d2a update 2026-02-22 22:19:47 +07:00
def75d8f86 update 2026-02-22 21:55:18 +07:00
69f2173f75 update 2026-02-22 20:52:13 +07:00
075d355c58 update 2026-02-22 20:43:28 +07:00
42 changed files with 3149 additions and 2202 deletions

View File

@@ -1,6 +1,6 @@
name = "NATSBridge" name = "NATSBridge"
uuid = "f2724d33-f338-4a57-b9f8-1be882570d10" uuid = "f2724d33-f338-4a57-b9f8-1be882570d10"
version = "0.4.1" version = "0.4.2"
authors = ["narawat <narawat@gmail.com>"] authors = ["narawat <narawat@gmail.com>"]
[deps] [deps]

View File

@@ -1,8 +1,13 @@
# Architecture Documentation: Bi-Directional Data Bridge (Julia ↔ JavaScript) # Architecture Documentation: Bi-Directional Data Bridge
## Overview ## Overview
This document describes the architecture for a high-performance, bi-directional data bridge between a Julia service and a JavaScript (Node.js) service using NATS (Core & JetStream), implementing the Claim-Check pattern for large payloads. This document describes the architecture for a high-performance, bi-directional data bridge between **Julia**, **JavaScript**, and **Python/Micropython** applications using NATS (Core & JetStream), implementing the Claim-Check pattern for large payloads.
The system enables seamless communication across all three platforms:
- **Julia ↔ JavaScript** bi-directional messaging
- **JavaScript ↔ Python/Micropython** bi-directional messaging
- **Julia ↔ Python/Micropython** bi-directional messaging (via JSON serialization)
### File Server Handler Architecture ### File Server Handler Architecture
@@ -35,8 +40,24 @@ The system uses a **standardized list-of-tuples format** for all payload operati
# Input format for smartsend (always a list of tuples with type info) # Input format for smartsend (always a list of tuples with type info)
[(dataname1, data1, type1), (dataname2, data2, type2), ...] [(dataname1, data1, type1), (dataname2, data2, type2), ...]
# Output format for smartreceive (always returns a list of tuples) # Output format for smartreceive (returns envelope dictionary with payloads field)
[(dataname1, data1, type1), (dataname2, data2, type2), ...] # Returns: Dict with envelope metadata and payloads field containing list of tuples
# {
# "correlationId": "...",
# "msgId": "...",
# "timestamp": "...",
# "sendTo": "...",
# "msgPurpose": "...",
# "senderName": "...",
# "senderId": "...",
# "receiverName": "...",
# "receiverId": "...",
# "replyTo": "...",
# "replyToMsgId": "...",
# "brokerURL": "...",
# "metadata": {...},
# "payloads": [(dataname1, data1, type1), (dataname2, data2, type2), ...]
# }
``` ```
**Supported Types:** **Supported Types:**
@@ -81,9 +102,10 @@ smartsend(
nats_url="nats://localhost:4222" nats_url="nats://localhost:4222"
) )
# Receive always returns a list # Receive returns a dictionary envelope with all metadata and deserialized payloads
payloads = smartreceive(msg, fileserverDownloadHandler, max_retries, base_delay, max_delay) envelope = smartreceive(msg, fileserverDownloadHandler, max_retries, base_delay, max_delay)
# payloads = [("dataname1", data1, type1), ("dataname2", data2, type2), ...] # envelope["payloads"] = [("dataname1", data1, type1), ("dataname2", data2, type2), ...]
# envelope["correlationId"], envelope["msgId"], etc.
``` ```
## Architecture Diagram ## Architecture Diagram
@@ -118,7 +140,7 @@ flowchart TD
### 1. msgEnvelope_v1 - Message Envelope ### 1. msgEnvelope_v1 - Message Envelope
The `msgEnvelope_v1` structure provides a comprehensive message format for bidirectional communication between Julia and JavaScript services. The `msgEnvelope_v1` structure provides a comprehensive message format for bidirectional communication between Julia, JavaScript, and Python/Micropython applications.
**Julia Structure:** **Julia Structure:**
```julia ```julia
@@ -194,7 +216,7 @@ end
### 2. msgPayload_v1 - Payload Structure ### 2. msgPayload_v1 - Payload Structure
The `msgPayload_v1` structure provides flexible payload handling for various data types. The `msgPayload_v1` structure provides flexible payload handling for various data types across all supported platforms.
**Julia Structure:** **Julia Structure:**
```julia ```julia
@@ -222,15 +244,15 @@ end
┌─────────────────────────────────────────────────────────────┐ ┌─────────────────────────────────────────────────────────────┐
│ smartsend Function │ │ smartsend Function │
│ Accepts: [(dataname1, data1, type1), ...] │ │ Accepts: [(dataname1, data1, type1), ...] │
│ (No standalone type parameter - type per payload) │ (Type is per payload, not standalone)
└─────────────────────────────────────────────────────────────┘ └─────────────────────────────────────────────────────────────┘
┌─────────────────────────────────────────────────────────────┐ ┌─────────────────────────────────────────────────────────────┐
│ For each payload: │ │ For each payload: │
│ 1. Extract type from tuple │ │ 1. Extract type from tuple
│ 2. Serialize based on type │ │ 2. Serialize based on type
│ 3. Check payload size │ │ 3. Check payload size
└─────────────────────────────────────────────────────────────┘ └─────────────────────────────────────────────────────────────┘
┌────────────────┴─-────────────────┐ ┌────────────────┴─-────────────────┐
@@ -249,19 +271,77 @@ end
└─────────────────┘ └─────────────────┘ └─────────────────┘ └─────────────────┘
``` ```
### 4. Julia Module Architecture ### 4. Cross-Platform Architecture
```mermaid
flowchart TD
subgraph PythonMicropython
Py[Python/Micropython]
PySmartSend[smartsend]
PySmartReceive[smartreceive]
end
subgraph JavaScript
JS[JavaScript]
JSSmartSend[smartsend]
JSSmartReceive[smartreceive]
end
subgraph Julia
Julia[Julia]
JuliaSmartSend[smartsend]
JuliaSmartReceive[smartreceive]
end
subgraph NATS
NATSServer[NATS Server]
end
PySmartSend --> NATSServer
JSSmartSend --> NATSServer
JuliaSmartSend --> NATSServer
NATSServer --> PySmartReceive
NATSServer --> JSSmartReceive
NATSServer --> JuliaSmartReceive
style PythonMicropython fill:#e1f5fe
style JavaScript fill:#f3e5f5
style Julia fill:#e8f5e9
```
### 5. Python/Micropython Module Architecture
```mermaid ```mermaid
graph TD graph TD
subgraph JuliaModule subgraph PyModule
smartsendJulia[smartsend Julia] PySmartSend[smartsend]
SizeCheck[Size Check] SizeCheck[Size Check]
DirectPath[Direct Path] DirectPath[Direct Path]
LinkPath[Link Path] LinkPath[Link Path]
HTTPClient[HTTP Client] HTTPClient[HTTP Client]
end end
smartsendJulia --> SizeCheck PySmartSend --> SizeCheck
SizeCheck -->|< 1MB| DirectPath
SizeCheck -->|>= 1MB| LinkPath
LinkPath --> HTTPClient
style PyModule fill:#b3e5fc
```
### 6. Julia Module Architecture
```mermaid
graph TD
subgraph JuliaModule
JuliaSmartSend[smartsend]
SizeCheck[Size Check]
DirectPath[Direct Path]
LinkPath[Link Path]
HTTPClient[HTTP Client]
end
JuliaSmartSend --> SizeCheck
SizeCheck -->|< 1MB| DirectPath SizeCheck -->|< 1MB| DirectPath
SizeCheck -->|>= 1MB| LinkPath SizeCheck -->|>= 1MB| LinkPath
LinkPath --> HTTPClient LinkPath --> HTTPClient
@@ -269,19 +349,19 @@ graph TD
style JuliaModule fill:#c5e1a5 style JuliaModule fill:#c5e1a5
``` ```
### 5. JavaScript Module Architecture ### 7. JavaScript Module Architecture
```mermaid ```mermaid
graph TD graph TD
subgraph JSModule subgraph JSModule
smartsendJS[smartsend JS] JSSmartSend[smartsend]
smartreceiveJS[smartreceive JS] JSSmartReceive[smartreceive]
JetStreamConsumer[JetStream Pull Consumer] JetStreamConsumer[JetStream Pull Consumer]
ApacheArrow[Apache Arrow] ApacheArrow[Apache Arrow]
end end
smartsendJS --> NATS JSSmartSend --> NATS
smartreceiveJS --> JetStreamConsumer JSSmartReceive --> JetStreamConsumer
JetStreamConsumer --> ApacheArrow JetStreamConsumer --> ApacheArrow
style JSModule fill:#f3e5f5 style JSModule fill:#f3e5f5
@@ -338,23 +418,25 @@ function smartreceive(
# If direct: decode Base64 payload # If direct: decode Base64 payload
# If link: fetch from URL with exponential backoff using fileserverDownloadHandler # If link: fetch from URL with exponential backoff using fileserverDownloadHandler
# Deserialize payload based on type # Deserialize payload based on type
# Return list of (dataname, data, type) tuples # Return envelope dictionary with all metadata and deserialized payloads
end end
``` ```
**Output Format:** **Output Format:**
- Always returns a list of tuples: `[(dataname1, data1, type1), (dataname2, data2, type2), ...]` - Returns a dictionary (key-value map) containing all envelope fields:
- Even for single payloads: `[(dataname1, data1, type1)]` - `correlationId`, `msgId`, `timestamp`, `sendTo`, `msgPurpose`, `senderName`, `senderId`, `receiverName`, `receiverId`, `replyTo`, `replyToMsgId`, `brokerURL`
- `metadata` - Message-level metadata dictionary
- `payloads` - List of dictionaries, each containing deserialized payload data
**Process Flow:** **Process Flow:**
1. Parse the JSON envelope to extract the `payloads` array 1. Parse the JSON envelope to extract all fields
2. Iterate through each payload in `payloads` 2. Iterate through each payload in `payloads`
3. For each payload: 3. For each payload:
- Determine transport type (`direct` or `link`) - Determine transport type (`direct` or `link`)
- If `direct`: decode Base64 data from the message - If `direct`: decode Base64 data from the message
- If `link`: fetch data from URL using exponential backoff (via `fileserverDownloadHandler`) - If `link`: fetch data from URL using exponential backoff (via `fileserverDownloadHandler`)
- Deserialize based on payload type (`dictionary`, `table`, `binary`, etc.) - Deserialize based on payload type (`dictionary`, `table`, `binary`, etc.)
4. Return list of `(dataname, data, type)` tuples 4. Return envelope dictionary with `payloads` field containing list of `(dataname, data, type)` tuples
**Note:** The `fileserverDownloadHandler` receives `(url::String, max_retries::Int, base_delay::Int, max_delay::Int, correlation_id::String)` and returns `Vector{UInt8}`. **Note:** The `fileserverDownloadHandler` receives `(url::String, max_retries::Int, base_delay::Int, max_delay::Int, correlation_id::String)` and returns `Vector{UInt8}`.
@@ -401,21 +483,27 @@ async function smartreceive(msg, options = {})
// - correlationId: optional correlation ID for tracing // - correlationId: optional correlation ID for tracing
``` ```
**Output Format:**
- Returns a dictionary (key-value map) containing all envelope fields:
- `correlationId`, `msgId`, `timestamp`, `sendTo`, `msgPurpose`, `senderName`, `senderId`, `receiverName`, `receiverId`, `replyTo`, `replyToMsgId`, `brokerURL`
- `metadata` - Message-level metadata dictionary
- `payloads` - List of dictionaries, each containing deserialized payload data
**Process Flow:** **Process Flow:**
1. Parse the JSON envelope to extract the `payloads` array 1. Parse the JSON envelope to extract all fields
2. Iterate through each payload in `payloads` 2. Iterate through each payload in `payloads`
3. For each payload: 3. For each payload:
- Determine transport type (`direct` or `link`) - Determine transport type (`direct` or `link`)
- If `direct`: decode Base64 data from the message - If `direct`: decode Base64 data from the message
- If `link`: fetch data from URL using exponential backoff - If `link`: fetch data from URL using exponential backoff
- Deserialize based on payload type (`dictionary`, `table`, `binary`, etc.) - Deserialize based on payload type (`dictionary`, `table`, `binary`, etc.)
4. Return list of `(dataname, data, type)` tuples 4. Return envelope dictionary with `payloads` field containing list of `(dataname, data, type)` tuples
## Scenario Implementations ## Scenario Implementations
### Scenario 1: Command & Control (Small Dictionary) ### Scenario 1: Command & Control (Small Dictionary)
**Julia (Receiver):** **Julia (Sender/Receiver):**
```julia ```julia
# Subscribe to control subject # Subscribe to control subject
# Parse JSON envelope # Parse JSON envelope
@@ -423,15 +511,21 @@ async function smartreceive(msg, options = {})
# Send acknowledgment # Send acknowledgment
``` ```
**JavaScript (Sender):** **JavaScript (Sender/Receiver):**
```javascript ```javascript
// Create small dictionary config // Create small dictionary config
// Send via smartsend with type="dictionary" // Send via smartsend with type="dictionary"
``` ```
**Python/Micropython (Sender/Receiver):**
```python
# Create small dictionary config
# Send via smartsend with type="dictionary"
```
### Scenario 2: Deep Dive Analysis (Large Arrow Table) ### Scenario 2: Deep Dive Analysis (Large Arrow Table)
**Julia (Sender):** **Julia (Sender/Receiver):**
```julia ```julia
# Create large DataFrame # Create large DataFrame
# Convert to Arrow IPC stream # Convert to Arrow IPC stream
@@ -440,7 +534,7 @@ async function smartreceive(msg, options = {})
# Publish NATS with URL # Publish NATS with URL
``` ```
**JavaScript (Receiver):** **JavaScript (Sender/Receiver):**
```javascript ```javascript
// Receive NATS message with URL // Receive NATS message with URL
// Fetch data from HTTP server // Fetch data from HTTP server
@@ -448,42 +542,64 @@ async function smartreceive(msg, options = {})
// Load into Perspective.js or D3 // Load into Perspective.js or D3
``` ```
**Python/Micropython (Sender/Receiver):**
```python
# Create large DataFrame
# Convert to Arrow IPC stream
# Check size (> 1MB)
# Upload to HTTP server
# Publish NATS with URL
```
### Scenario 3: Live Audio Processing ### Scenario 3: Live Audio Processing
**JavaScript (Sender):** **JavaScript (Sender/Receiver):**
```javascript ```javascript
// Capture audio chunk // Capture audio chunk
// Send as binary with metadata headers // Send as binary with metadata headers
// Use smartsend with type="audio" // Use smartsend with type="audio"
``` ```
**Julia (Receiver):** **Julia (Sender/Receiver):**
```julia ```julia
// Receive audio data # Receive audio data
// Perform FFT or AI transcription # Perform FFT or AI transcription
// Send results back (JSON + Arrow table) # Send results back (JSON + Arrow table)
```
**Python/Micropython (Sender/Receiver):**
```python
# Capture audio chunk
# Send as binary with metadata headers
# Use smartsend with type="audio"
``` ```
### Scenario 4: Catch-Up (JetStream) ### Scenario 4: Catch-Up (JetStream)
**Julia (Producer):** **Julia (Producer/Consumer):**
```julia ```julia
# Publish to JetStream # Publish to JetStream
# Include metadata for temporal tracking # Include metadata for temporal tracking
``` ```
**JavaScript (Consumer):** **JavaScript (Producer/Consumer):**
```javascript ```javascript
// Connect to JetStream // Connect to JetStream
// Request replay from last 10 minutes // Request replay from last 10 minutes
// Process historical and real-time messages // Process historical and real-time messages
``` ```
**Python/Micropython (Producer/Consumer):**
```python
# Publish to JetStream
# Include metadata for temporal tracking
```
### Scenario 5: Selection (Low Bandwidth) ### Scenario 5: Selection (Low Bandwidth)
**Focus:** Small Arrow tables, Julia to JavaScript. The Action: Julia wants to send a small DataFrame to show on a JavaScript dashboard for the user to choose. **Focus:** Small Arrow tables, cross-platform communication. The Action: Any platform wants to send a small DataFrame to show on any receiving application for the user to choose.
**Julia (Sender):** **Julia (Sender/Receiver):**
```julia ```julia
# Create small DataFrame (e.g., 50KB - 500KB) # Create small DataFrame (e.g., 50KB - 500KB)
# Convert to Arrow IPC stream # Convert to Arrow IPC stream
@@ -492,7 +608,7 @@ async function smartreceive(msg, options = {})
# Include metadata for dashboard selection context # Include metadata for dashboard selection context
``` ```
**JavaScript (Receiver):** **JavaScript (Sender/Receiver):**
```javascript ```javascript
// Receive NATS message with direct transport // Receive NATS message with direct transport
// Decode Base64 payload // Decode Base64 payload
@@ -502,11 +618,20 @@ async function smartreceive(msg, options = {})
// Send selection back to Julia // Send selection back to Julia
``` ```
**Use Case:** Julia server generates a list of available options (e.g., file selections, configuration presets) as a small DataFrame and sends to JavaScript dashboard for user selection. The selection is then sent back to Julia for processing. **Python/Micropython (Sender/Receiver):**
```python
# Create small DataFrame (e.g., 50KB - 500KB)
# Convert to Arrow IPC stream
# Check payload size (< 1MB threshold)
# Publish directly to NATS with Base64-encoded payload
# Include metadata for dashboard selection context
```
**Use Case:** Any server generates a list of available options (e.g., file selections, configuration presets) as a small DataFrame and sends to any receiving application for user selection. The selection is then sent back to the sender for processing.
### Scenario 6: Chat System ### Scenario 6: Chat System
**Focus:** Every conversational message is composed of any number and any combination of components, spanning the full spectrum from small to large. This includes text, images, audio, video, tables, and files—specifically accommodating everything from brief snippets to high-resolution images, large audio files, extensive tables, and massive documents. Support for claim-check delivery and full bi-directional messaging. **Focus:** Every conversational message is composed of any number and any combination of components, spanning the full spectrum from small to large. This includes text, images, audio, video, tables, and files—specifically accommodating everything from brief snippets to high-resolution images, large audio files, extensive tables, and massive documents. Support for claim-check delivery and full bi-directional messaging across all platforms.
**Multi-Payload Support:** The system supports mixed-payload messages where a single message can contain multiple payloads with different transport strategies. The `smartreceive` function iterates through all payloads in the envelope and processes each according to its transport type. **Multi-Payload Support:** The system supports mixed-payload messages where a single message can contain multiple payloads with different transport strategies. The `smartreceive` function iterates through all payloads in the envelope and processes each according to its transport type.
@@ -545,7 +670,25 @@ async function smartreceive(msg, options = {})
// Support bidirectional reply with claim-check delivery confirmation // Support bidirectional reply with claim-check delivery confirmation
``` ```
**Use Case:** Full-featured chat system supporting rich media. User can send text, small images directly, or upload large files that get uploaded to HTTP server and referenced via URLs. Claim-check pattern ensures reliable delivery tracking for all message components. **Python/Micropython (Sender/Receiver):**
```python
# Build chat message with mixed payloads:
# - Text: direct transport (Base64)
# - Small images: direct transport (Base64)
# - Large images: link transport (HTTP URL)
# - Audio/video: link transport (HTTP URL)
# - Tables: direct or link depending on size
# - Files: link transport (HTTP URL)
#
# Each payload uses appropriate transport strategy:
# - Size < 1MB → direct (NATS + Base64)
# - Size >= 1MB → link (HTTP upload + NATS URL)
#
# Include claim-check metadata for delivery tracking
# Support bidirectional messaging with replyTo fields
```
**Use Case:** Full-featured chat system supporting rich media. User can send text, small images directly, or upload large files that get uploaded to HTTP server and referenced via URLs. Claim-check pattern ensures reliable delivery tracking for all message components across all platforms.
**Implementation Note:** The `smartreceive` function iterates through all payloads in the envelope and processes each according to its transport type. See the standard API format in Section 1: `msgEnvelope_v1` supports `AbstractArray{msgPayload_v1}` for multiple payloads. **Implementation Note:** The `smartreceive` function iterates through all payloads in the envelope and processes each according to its transport type. See the standard API format in Section 1: `msgEnvelope_v1` supports `AbstractArray{msgPayload_v1}` for multiple payloads.

View File

@@ -2,7 +2,22 @@
## Overview ## Overview
This document describes the implementation of the high-performance, bi-directional data bridge between Julia and JavaScript services using NATS (Core & JetStream), implementing the Claim-Check pattern for large payloads. This document describes the implementation of the high-performance, bi-directional data bridge between **Julia**, **JavaScript**, and **Python/Micropython** applications using NATS (Core & JetStream), implementing the Claim-Check pattern for large payloads.
The system enables seamless communication across all three platforms:
- **Julia ↔ JavaScript** bi-directional messaging
- **JavaScript ↔ Python/Micropython** bi-directional messaging
- **Julia ↔ Python/Micropython** bi-directional messaging (via JSON serialization)
### Implementation Files
NATSBridge is implemented in three languages, each providing the same API:
| Language | Implementation File | Description |
|----------|---------------------|-------------|
| **Julia** | [`src/NATSBridge.jl`](../src/NATSBridge.jl) | Full Julia implementation with Arrow IPC support |
| **JavaScript** | [`src/NATSBridge.js`](../src/NATSBridge.js) | JavaScript implementation for Node.js and browsers |
| **Python/Micropython** | [`src/nats_bridge.py`](../src/nats_bridge.py) | Python implementation for desktop and microcontrollers |
### Multi-Payload Support ### Multi-Payload Support
@@ -13,8 +28,24 @@ The implementation uses a **standardized list-of-tuples format** for all payload
# Input format for smartsend (always a list of tuples with type info) # Input format for smartsend (always a list of tuples with type info)
[(dataname1, data1, type1), (dataname2, data2, type2), ...] [(dataname1, data1, type1), (dataname2, data2, type2), ...]
# Output format for smartreceive (always returns a list of tuples with type info) # Output format for smartreceive (returns envelope dictionary with payloads field)
[(dataname1, data1, type1), (dataname2, data2, type2), ...] # Returns: Dict with envelope metadata and payloads field containing list of tuples
# {
# "correlationId": "...",
# "msgId": "...",
# "timestamp": "...",
# "sendTo": "...",
# "msgPurpose": "...",
# "senderName": "...",
# "senderId": "...",
# "receiverName": "...",
# "receiverId": "...",
# "replyTo": "...",
# "replyToMsgId": "...",
# "brokerURL": "...",
# "metadata": {...},
# "payloads": [(dataname1, data1, type1), (dataname2, data2, type2), ...]
# }
``` ```
Where `type` can be: `"text"`, `"dictionary"`, `"table"`, `"image"`, `"audio"`, `"video"`, `"binary"` Where `type` can be: `"text"`, `"dictionary"`, `"table"`, `"image"`, `"audio"`, `"video"`, `"binary"`
@@ -27,49 +58,103 @@ smartsend("/test", [(dataname1, data1, "text")], ...)
# Multiple payloads in one message (each payload has its own type) # Multiple payloads in one message (each payload has its own type)
smartsend("/test", [(dataname1, data1, "dictionary"), (dataname2, data2, "table")], ...) smartsend("/test", [(dataname1, data1, "dictionary"), (dataname2, data2, "table")], ...)
# Receive always returns a list with type info # Receive returns a dictionary envelope with all metadata and deserialized payloads
payloads = smartreceive(msg, ...) envelope = smartreceive(msg, ...)
# payloads = [(dataname1, data1, "text"), (dataname2, data2, "table"), ...] # envelope["payloads"] = [(dataname1, data1, "text"), (dataname2, data2, "table"), ...]
# envelope["correlationId"], envelope["msgId"], etc.
``` ```
## Cross-Platform Interoperability
NATSBridge is designed for seamless communication between Julia, JavaScript, and Python/Micropython applications. All three implementations share the same interface and data format, ensuring compatibility across platforms.
### Platform-Specific Features
| Feature | Julia | JavaScript | Python/Micropython |
|---------|-------|------------|-------------------|
| Direct NATS transport | ✅ | ✅ | ✅ |
| HTTP file server (Claim-Check) | ✅ | ✅ | ✅ |
| Arrow IPC tables | ✅ | ✅ | ✅ |
| Base64 encoding | ✅ | ✅ | ✅ |
| Exponential backoff | ✅ | ✅ | ✅ |
| Correlation ID tracking | ✅ | ✅ | ✅ |
| Reply-to support | ✅ | ✅ | ✅ |
### Data Type Mapping
| Type | Julia | JavaScript | Python/Micropython |
|------|-------|------------|-------------------|
| `text` | `String` | `String` | `str` |
| `dictionary` | `Dict` | `Object` | `dict` |
| `table` | `DataFrame` | `Array<Object>` | `DataFrame` / `list` |
| `image` | `Vector{UInt8}` | `ArrayBuffer/Uint8Array` | `bytes` |
| `audio` | `Vector{UInt8}` | `ArrayBuffer/Uint8Array` | `bytes` |
| `video` | `Vector{UInt8}` | `ArrayBuffer/Uint8Array` | `bytes` |
| `binary` | `Vector{UInt8}` | `ArrayBuffer/Uint8Array` | `bytes` |
### Example: Julia ↔ Python ↔ JavaScript
```julia
# Julia sender
using NATSBridge
data = [("message", "Hello from Julia!", "text")]
smartsend("/cross_platform", data, nats_url="nats://localhost:4222")
```
```javascript
// JavaScript receiver
const { smartreceive } = require('./src/NATSBridge');
const envelope = await smartreceive(msg);
// envelope.payloads[0].data === "Hello from Julia!"
```
```python
# Python sender
from nats_bridge import smartsend
data = [("response", "Hello from Python!", "text")]
smartsend("/cross_platform", data, nats_url="nats://localhost:4222")
```
All three platforms can communicate seamlessly using the same NATS subjects and data format.
## Architecture ## Architecture
The implementation follows the Claim-Check pattern: All three implementations (Julia, JavaScript, Python/Micropython) follow the same Claim-Check pattern:
``` ```
┌─────────────────────────────────────────────────────────────────────────┐ ┌─────────────────────────────────────────────────────────────────────────┐
│ SmartSend Function │ │ SmartSend Function │
└─────────────────────────────────────────────────────────────────────────┘ └─────────────────────────────────────────────────────────────────────────┘
┌─────────────────────────────────────────────────────────────────────────┐ ┌─────────────────────────────────────────────────────────────────────────┐
│ Is payload size < 1MB? │ │ Is payload size < 1MB? │
└─────────────────────────────────────────────────────────────────────────┘ └─────────────────────────────────────────────────────────────────────────┘
┌─────────────────┴─────────────────┐ ┌─────────────────┴─────────────────┐
▼ ▼ ▼ ▼
┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐
│ Direct Path │ │ Link Path │ │ Direct Path │ │ Link Path │
│ (< 1MB) │ │ (> 1MB) │ │ (< 1MB) │ │ (> 1MB) │
│ │ │ │ │ │ │ │
│ • Serialize to │ │ • Serialize to │ │ • Serialize to │ │ • Serialize to │
IOBuffer │ │ IOBuffer │ │ Buffer │ │ Buffer
│ • Base64 encode │ │ • Upload to │ │ • Base64 encode │ │ • Upload to │
│ • Publish to │ │ HTTP Server │ │ • Publish to │ │ HTTP Server │
│ NATS │ │ • Publish to │ │ NATS │ │ • Publish to │
│ │ │ NATS with URL │ │ │ │ NATS with URL │
└─────────────────┘ └─────────────────┘ └─────────────────┘ └─────────────────┘
``` ```
## Files ## Files
### Julia Module: [`src/julia_bridge.jl`](../src/julia_bridge.jl) ### Julia Module: [`src/NATSBridge.jl`](../src/NATSBridge.jl)
The Julia implementation provides: The Julia implementation provides:
- **[`MessageEnvelope`](../src/julia_bridge.jl)**: Struct for the unified JSON envelope - **[`MessageEnvelope`](src/NATSBridge.jl)**: Struct for the unified JSON envelope
- **[`SmartSend()`](../src/julia_bridge.jl)**: Handles transport selection based on payload size - **[`SmartSend()`](src/NATSBridge.jl)**: Handles transport selection based on payload size
- **[`SmartReceive()`](../src/julia_bridge.jl)**: Handles both direct and link transport - **[`SmartReceive()`](src/NATSBridge.jl)**: Handles both direct and link transport
### JavaScript Module: [`src/NATSBridge.js`](../src/NATSBridge.js) ### JavaScript Module: [`src/NATSBridge.js`](../src/NATSBridge.js)
@@ -77,8 +162,17 @@ The JavaScript implementation provides:
- **`MessageEnvelope` class**: For the unified JSON envelope - **`MessageEnvelope` class**: For the unified JSON envelope
- **`MessagePayload` class**: For individual payload representation - **`MessagePayload` class**: For individual payload representation
- **[`smartsend()`](../src/NATSBridge.js)**: Handles transport selection based on payload size - **[`smartsend()`](src/NATSBridge.js)**: Handles transport selection based on payload size
- **[`smartreceive()`](../src/NATSBridge.js)**: Handles both direct and link transport - **[`smartreceive()`](src/NATSBridge.js)**: Handles both direct and link transport
### Python/Micropython Module: [`src/nats_bridge.py`](../src/nats_bridge.py)
The Python/Micropython implementation provides:
- **`MessageEnvelope` class**: For the unified JSON envelope
- **`MessagePayload` class**: For individual payload representation
- **[`smartsend()`](src/nats_bridge.py)**: Handles transport selection based on payload size
- **[`smartreceive()`](src/nats_bridge.py)**: Handles both direct and link transport
## Installation ## Installation
@@ -100,6 +194,23 @@ Pkg.add("Dates")
npm install nats.js apache-arrow uuid base64-url npm install nats.js apache-arrow uuid base64-url
``` ```
### Python/Micropython Dependencies
1. Copy [`src/nats_bridge.py`](../src/nats_bridge.py) to your device
2. Ensure you have the following dependencies:
**For Python (desktop):**
```bash
pip install nats-py
```
**For Micropython:**
- `urequests` for HTTP requests
- `base64` for base64 encoding (built-in)
- `json` for JSON handling (built-in)
- `socket` for networking (built-in)
- `uuid` for UUID generation (built-in)
## Usage Tutorial ## Usage Tutorial
### Step 1: Start NATS Server ### Step 1: Start NATS Server
@@ -138,34 +249,31 @@ node test/scenario3_julia_to_julia.js
### Scenario 0: Basic Multi-Payload Example ### Scenario 0: Basic Multi-Payload Example
#### Julia (Sender) #### Python/Micropython (Sender)
```julia ```python
using NATSBridge from nats_bridge import smartsend
# Send multiple payloads in one message (type is required per payload) # Send multiple payloads in one message (type is required per payload)
smartsend( smartsend(
"/test", "/test",
[("dataname1", data1, "dictionary"), ("dataname2", data2, "table")], [("dataname1", data1, "dictionary"), ("dataname2", data2, "table")],
nats_url="nats://localhost:4222", nats_url="nats://localhost:4222",
fileserver_url="http://localhost:8080", fileserver_url="http://localhost:8080"
metadata=Dict("custom_key" => "custom_value")
) )
# Even single payload must be wrapped in a list with type # Even single payload must be wrapped in a list with type
smartsend("/test", [("single_data", mydata, "dictionary")]) smartsend("/test", [("single_data", mydata, "dictionary")])
``` ```
#### Julia (Receiver) #### Python/Micropython (Receiver)
```julia ```python
using NATSBridge from nats_bridge import smartreceive
# Receive returns a list of payloads with type info # Receive returns a list of (dataname, data, type) tuples
payloads = smartreceive(msg, "http://localhost:8080") payloads = smartreceive(msg)
# payloads = [(dataname1, data1, "dictionary"), (dataname2, data2, "table"), ...] # payloads = [(dataname1, data1, "dictionary"), (dataname2, data2, "table"), ...]
``` ```
### Scenario 1: Command & Control (Small JSON)
#### JavaScript (Sender) #### JavaScript (Sender)
```javascript ```javascript
const { smartsend } = require('./src/NATSBridge'); const { smartsend } = require('./src/NATSBridge');
@@ -198,27 +306,7 @@ const configs = [
await smartsend("control", configs); await smartsend("control", configs);
``` ```
#### Julia (Receiver) #### JavaScript (Receiver)
```julia
using NATS
using JSON3
# Subscribe to control subject
subscribe(nats, "control") do msg
env = MessageEnvelope(String(msg.data))
config = JSON3.read(env.payload)
# Execute simulation with parameters
step_size = config.step_size
iterations = config.iterations
# Send acknowledgment
response = Dict("status" => "Running", "correlation_id" => env.correlation_id)
publish(nats, "control_response", JSON3.stringify(response))
end
```
### JavaScript (Receiver)
```javascript ```javascript
const { smartreceive } = require('./src/NATSBridge'); const { smartreceive } = require('./src/NATSBridge');
@@ -227,13 +315,18 @@ const nc = await connect({ servers: ['nats://localhost:4222'] });
const sub = nc.subscribe("control"); const sub = nc.subscribe("control");
for await (const msg of sub) { for await (const msg of sub) {
const result = await smartreceive(msg); const envelope = await smartreceive(msg);
// Process the result // Process the payloads from the envelope
for (const { dataname, data, type } of result) { for (const payload of envelope.payloads) {
const { dataname, data, type } = payload;
console.log(`Received ${dataname} of type ${type}`); console.log(`Received ${dataname} of type ${type}`);
console.log(`Data: ${JSON.stringify(data)}`); console.log(`Data: ${JSON.stringify(data)}`);
} }
// Also access envelope metadata
console.log(`Correlation ID: ${envelope.correlationId}`);
console.log(`Message ID: ${envelope.msgId}`);
} }
``` ```
@@ -259,15 +352,35 @@ await SmartSend("analysis_results", [("table_data", df, "table")]);
```javascript ```javascript
const { smartreceive } = require('./src/NATSBridge'); const { smartreceive } = require('./src/NATSBridge');
const result = await smartreceive(msg); const envelope = await smartreceive(msg);
// Use table data for visualization with Perspective.js or D3 // Use table data from the payloads field
// Note: Tables are sent as arrays of objects in JavaScript // Note: Tables are sent as arrays of objects in JavaScript
const table = result; const table = envelope.payloads;
``` ```
### Scenario 3: Live Binary Processing ### Scenario 3: Live Binary Processing
#### Python/Micropython (Sender)
```python
from nats_bridge import smartsend
# Binary data wrapped in a list
binary_data = [
("audio_chunk", binary_buffer, "binary")
]
smartsend(
"binary_input",
binary_data,
nats_url="nats://localhost:4222",
metadata={
"sample_rate": 44100,
"channels": 1
}
)
```
#### JavaScript (Sender) #### JavaScript (Sender)
```javascript ```javascript
const { smartsend } = require('./src/NATSBridge'); const { smartsend } = require('./src/NATSBridge');
@@ -287,35 +400,35 @@ await smartsend("binary_input", binaryData, {
}); });
``` ```
#### Julia (Receiver) #### Python/Micropython (Receiver)
```julia ```python
using WAV from nats_bridge import smartreceive
using DSP
# Receive binary data # Receive binary data
function process_binary(data) def process_binary(msg):
# Perform FFT or AI transcription envelope = smartreceive(msg)
spectrum = fft(data)
# Send results back (JSON + Arrow table) # Process the binary data from envelope.payloads
results = Dict("transcription" => "sample text", "spectrum" => spectrum) for dataname, data, type in envelope["payloads"]:
await SmartSend("binary_output", results, "json") if type == "binary":
end # data is bytes
print(f"Received binary data: {dataname}, size: {len(data)}")
# Perform FFT or AI transcription here
``` ```
### JavaScript (Receiver) #### JavaScript (Receiver)
```javascript ```javascript
const { smartreceive } = require('./src/NATSBridge'); const { smartreceive } = require('./src/NATSBridge');
// Receive binary data // Receive binary data
function process_binary(msg) { function process_binary(msg) {
const result = await smartreceive(msg); const envelope = await smartreceive(msg);
// Process the binary data // Process the binary data from envelope.payloads
for (const { dataname, data, type } of result) { for (const payload of envelope.payloads) {
if (type === "binary") { if (payload.type === "binary") {
// data is an ArrayBuffer or Uint8Array // data is an ArrayBuffer or Uint8Array
console.log(`Received binary data: ${dataname}, size: ${data.length}`); console.log(`Received binary data: ${payload.dataname}, size: ${payload.data.length}`);
// Perform FFT or AI transcription here // Perform FFT or AI transcription here
} }
} }
@@ -353,13 +466,71 @@ const consumer = await js.pullSubscribe("health", {
// Process historical and real-time messages // Process historical and real-time messages
for await (const msg of consumer) { for await (const msg of consumer) {
const result = await smartreceive(msg); const envelope = await smartreceive(msg);
// result contains the list of payloads // envelope.payloads contains the list of payloads
// Each payload has: dataname, data, type // Each payload has: dataname, data, type
msg.ack(); msg.ack();
} }
``` ```
### Scenario 4: Micropython Device Control
**Focus:** Sending configuration to a Micropython device over NATS. This demonstrates the lightweight nature of the Python implementation suitable for microcontrollers.
**Python/Micropython (Receiver/Device):**
```python
from nats_bridge import smartsend, smartreceive
import json
# Device configuration handler
def handle_device_config(msg):
envelope = smartreceive(msg)
# Process configuration from payloads
for dataname, data, type in envelope["payloads"]:
if type == "dictionary":
print(f"Received configuration: {data}")
# Apply configuration to device
if "wifi_ssid" in data:
wifi_ssid = data["wifi_ssid"]
wifi_password = data["wifi_password"]
update_wifi_config(wifi_ssid, wifi_password)
# Send confirmation back
config = {
"status": "configured",
"wifi_ssid": "MyNetwork",
"ip": get_device_ip()
}
smartsend(
"device/response",
[("config", config, "dictionary")],
nats_url="nats://localhost:4222",
reply_to=envelope.get("replyTo")
)
```
**JavaScript (Sender/Controller):**
```javascript
const { smartsend } = require('./src/NATSBridge');
// Send configuration to Micropython device
await smartsend("device/config", [
{
dataname: "config",
data: {
wifi_ssid: "MyNetwork",
wifi_password: "password123",
update_interval: 60,
temperature_threshold: 30.0
},
type: "dictionary"
}
]);
```
**Use Case:** A controller sends WiFi and operational configuration to a Micropython device (e.g., ESP32). The device receives the configuration, applies it, and sends back a confirmation with its current status.
### Scenario 5: Selection (Low Bandwidth) ### Scenario 5: Selection (Low Bandwidth)
**Focus:** Small Arrow tables, Julia to JavaScript. The Action: Julia wants to send a small DataFrame to show on a JavaScript dashboard for the user to choose. **Focus:** Small Arrow tables, Julia to JavaScript. The Action: Julia wants to send a small DataFrame to show on a JavaScript dashboard for the user to choose.
@@ -395,11 +566,11 @@ smartsend(
const { smartreceive, smartsend } = require('./src/NATSBridge'); const { smartreceive, smartsend } = require('./src/NATSBridge');
// Receive NATS message with direct transport // Receive NATS message with direct transport
const result = await smartreceive(msg); const envelope = await smartreceive(msg);
// Decode Base64 payload (for direct transport) // Decode Base64 payload (for direct transport)
// For tables, data is an array of objects // For tables, data is in envelope.payloads
const table = result; // Array of objects const table = envelope.payloads; // Array of objects
// User makes selection // User makes selection
const selection = uiComponent.getSelectedOption(); const selection = uiComponent.getSelectedOption();
@@ -558,7 +729,7 @@ await smartsend("chat.room123", message);
### Exponential Backoff ### Exponential Backoff
- Maximum retry count: 5 - Maximum retry count: 5
- Base delay: 100ms, max delay: 5000ms - Base delay: 100ms, max delay: 5000ms
- Implemented in both Julia and JavaScript implementations - Implemented in all three implementations (Julia, JavaScript, Python/Micropython)
### Correlation ID Logging ### Correlation ID Logging
- Log correlation_id at every stage - Log correlation_id at every stage
@@ -567,14 +738,73 @@ await smartsend("chat.room123", message);
## Testing ## Testing
Run the test scripts: Run the test scripts for each platform:
### Python/Micropython Tests
```bash ```bash
# Scenario 1: Command & Control (JavaScript sender) # Basic functionality test
node test/scenario1_command_control.js python test/test_micropython_basic.py
```
# Scenario 2: Large Arrow Table (JavaScript sender) ### JavaScript Tests
node test/scenario2_large_table.js
```bash
# Text message exchange
node test/test_js_to_js_text_sender.js
node test/test_js_to_js_text_receiver.js
# Dictionary exchange
node test/test_js_to_js_dict_sender.js
node test/test_js_to_js_dict_receiver.js
# File transfer (direct transport)
node test/test_js_to_js_file_sender.js
node test/test_js_to_js_file_receiver.js
# Mixed payload types
node test/test_js_to_js_mix_payloads_sender.js
node test/test_js_to_js_mix_payloads_receiver.js
# Table (Arrow IPC) exchange
node test/test_js_to_js_table_sender.js
node test/test_js_to_js_table_receiver.js
```
### Julia Tests
```bash
# Text message exchange
julia test/test_julia_to_julia_text_sender.jl
julia test/test_julia_to_julia_text_receiver.jl
# Dictionary exchange
julia test/test_julia_to_julia_dict_sender.jl
julia test/test_julia_to_julia_dict_receiver.jl
# File transfer
julia test/test_julia_to_julia_file_sender.jl
julia test/test_julia_to_julia_file_receiver.jl
# Mixed payload types
julia test/test_julia_to_julia_mix_payloads_sender.jl
julia test/test_julia_to_julia_mix_payloads_receiver.jl
# Table exchange
julia test/test_julia_to_julia_table_sender.jl
julia test/test_julia_to_julia_table_receiver.jl
```
### Cross-Platform Tests
```bash
# Julia ↔ JavaScript communication
julia test/test_julia_to_julia_text_sender.jl
node test/test_js_to_js_text_receiver.js
# Python ↔ JavaScript communication
python test/test_micropython_basic.py
node test/test_js_to_js_text_receiver.js
``` ```
## Troubleshooting ## Troubleshooting
@@ -582,18 +812,24 @@ node test/scenario2_large_table.js
### Common Issues ### Common Issues
1. **NATS Connection Failed** 1. **NATS Connection Failed**
- Ensure NATS server is running - **Julia/JavaScript/Python**: Ensure NATS server is running
- Check NATS_URL configuration - **Python/Micropython**: Check `nats_url` parameter and network connectivity
2. **HTTP Upload Failed** 2. **HTTP Upload Failed**
- Ensure file server is running - Ensure file server is running
- Check FILESERVER_URL configuration - Check `fileserver_url` configuration
- Verify upload permissions - Verify upload permissions
- **Micropython**: Ensure `urequests` is available and network is connected
3. **Arrow IPC Deserialization Error** 3. **Arrow IPC Deserialization Error**
- Ensure data is properly serialized to Arrow format - Ensure data is properly serialized to Arrow format
- Check Arrow version compatibility - Check Arrow version compatibility
4. **Python/Micropython Specific Issues**
- **Import Error**: Ensure `nats_bridge.py` is in the correct path
- **Memory Error (Micropython)**: Reduce payload size or use link transport for large payloads
- **Unicode Error**: Ensure proper encoding when sending text data
## License ## License
MIT MIT

21
etc.jl
View File

@@ -1,21 +0,0 @@
Check architecture.jl, NATSBridge.jl and its test files:
- test_julia_to_julia_table_receiver.jl
- test_julia_to_julia_table_sender.jl.
Now I want to test sending a mix-content message from Julia serviceA to Julia serviceB, for example, a chat system.
The test message must show that any combination and any number and any data size of text | json | table | image | audio | video | binary can be send and receive.
Can you write me the following test files:
- test_julia_to_julia_mix_receiver.jl
- test_julia_to_julia_mix_sender.jl
1. create a tutorial file "tutorial_julia.md" for NATSBridge.jl
2. create a walkthrough file "walkthrough_julia.md" for NATSBridge.jl
You may consult architecture.md for more info.

View File

@@ -1,221 +0,0 @@
"""
Micropython NATS Bridge - Simple Example
This example demonstrates the basic usage of the NATSBridge for Micropython.
"""
import sys
sys.path.insert(0, "../src")
from nats_bridge import smartsend, smartreceive, log_trace
import json
def example_simple_chat():
"""
Simple chat example: Send text messages via NATS.
Sender (this script):
- Sends a text message to NATS
- Uses direct transport (no fileserver needed)
Receiver (separate script):
- Listens to NATS
- Receives and processes the message
"""
print("=== Simple Chat Example ===")
print()
# Define the message data as list of (dataname, data, type) tuples
data = [
("message", "Hello from Micropython!", "text")
]
# Send the message
env = smartsend(
"/chat/room1",
data,
nats_url="nats://localhost:4222",
msg_purpose="chat",
sender_name="micropython-client"
)
print("Message sent!")
print(" Subject: {}".format(env.send_to))
print(" Correlation ID: {}".format(env.correlation_id))
print(" Payloads: {}".format(len(env.payloads)))
print()
# Expected receiver output:
print("Expected receiver output:")
print(" [timestamp] [Correlation: ...] Starting smartsend for subject: /chat/room1")
print(" [timestamp] [Correlation: ...] Serialized payload 'message' (type: text) size: 22 bytes")
print(" [timestamp] [Correlation: ...] Using direct transport for 22 bytes")
print(" [timestamp] [Correlation: ...] Message published to /chat/room1")
print()
return env
def example_send_json():
"""
Example: Send JSON configuration to a Micropython device.
This demonstrates sending structured data (dictionary type).
"""
print("\n=== Send JSON Configuration ===")
print()
# Define configuration as dictionary
config = {
"wifi_ssid": "MyNetwork",
"wifi_password": "password123",
"server_host": "mqtt.example.com",
"server_port": 1883,
"update_interval": 60
}
# Send configuration
data = [
("device_config", config, "dictionary")
]
env = smartsend(
"/device/config",
data,
nats_url="nats://localhost:4222",
msg_purpose="updateStatus",
sender_name="server"
)
print("Configuration sent!")
print(" Subject: {}".format(env.send_to))
print(" Payloads: {}".format(len(env.payloads)))
print()
return env
def example_receive_message(msg):
"""
Example: Receive and process a NATS message.
Args:
msg: The NATS message received (should be dict or JSON string)
Returns:
list: List of (dataname, data, type) tuples
"""
print("\n=== Receive Message ===")
print()
# Process the message
payloads = smartreceive(
msg,
fileserver_download_handler=None, # Not needed for direct transport
max_retries=3,
base_delay=100,
max_delay=1000
)
print("Received {} payload(s):".format(len(payloads)))
for dataname, data, type in payloads:
print(" - {}: {} (type: {})".format(dataname, data, type))
return payloads
def example_mixed_content():
"""
Example: Send mixed content (text + dictionary + binary).
This demonstrates the multi-payload capability.
"""
print("\n=== Mixed Content Example ===")
print()
# Create mixed content
image_data = b"\x89PNG\r\n\x1a\n\x00\x00\x00\rIHDR" # Example PNG header
data = [
("message_text", "Hello with image!", "text"),
("user_config", {"theme": "dark", "notifications": True}, "dictionary"),
("user_avatar", image_data, "binary")
]
env = smartsend(
"/chat/mixed",
data,
nats_url="nats://localhost:4222",
msg_purpose="chat",
sender_name="micropython-client"
)
print("Mixed content sent!")
print(" Subject: {}".format(env.send_to))
print(" Payloads:")
for p in env.payloads:
print(" - {} (transport: {}, type: {}, size: {} bytes)".format(
p.dataname, p.transport, p.type, p.size))
return env
def example_reply():
"""
Example: Send a message with reply-to functionality.
This demonstrates request-response pattern.
"""
print("\n=== Request-Response Example ===")
print()
# Send command
data = [
("command", {"action": "read_sensor", "sensor_id": "temp1"}, "dictionary")
]
env = smartsend(
"/device/command",
data,
nats_url="nats://localhost:4222",
msg_purpose="command",
sender_name="server",
reply_to="/device/response",
reply_to_msg_id="cmd-001"
)
print("Command sent!")
print(" Subject: {}".format(env.send_to))
print(" Reply To: {}".format(env.reply_to))
print(" Reply To Msg ID: {}".format(env.reply_to_msg_id))
print()
print("Expected receiver behavior:")
print(" 1. Receive command on /device/command")
print(" 2. Process command")
print(" 3. Send response to /device/response")
print(" 4. Include replyToMsgId in response")
return env
if __name__ == "__main__":
print("Micropython NATS Bridge Examples")
print("================================")
print()
# Run examples
example_simple_chat()
example_send_json()
example_mixed_content()
example_reply()
print("\n=== Examples Completed ===")
print()
print("To run these examples, you need:")
print(" 1. A running NATS server at nats://localhost:4222")
print(" 2. Import the nats_bridge module")
print(" 3. Call the desired example function")
print()
print("For more examples, see test/test_micropython_basic.py")

604
examples/tutorial.md Normal file
View File

@@ -0,0 +1,604 @@
# NATSBridge Tutorial
A step-by-step guide to get started with NATSBridge - a high-performance, bi-directional data bridge for **Julia**, **JavaScript**, and **Python/Micropython**.
## Table of Contents
1. [Overview](#overview)
2. [Prerequisites](#prerequisites)
3. [Installation](#installation)
4. [Quick Start](#quick-start)
5. [Basic Examples](#basic-examples)
6. [Advanced Usage](#advanced-usage)
7. [Cross-Platform Communication](#cross-platform-communication)
---
## Overview
NATSBridge enables seamless communication between Julia, JavaScript, and Python/Micropython applications through NATS, with automatic transport selection based on payload size:
- **Direct Transport**: Payloads < 1MB are sent directly via NATS (Base64 encoded)
- **Link Transport**: Payloads >= 1MB are uploaded to an HTTP file server and referenced via URL
### Supported Payload Types
| Type | Description |
|------|-------------|
| `text` | Plain text strings |
| `dictionary` | JSON-serializable dictionaries |
| `table` | Tabular data (Arrow IPC format) |
| `image` | Image data (PNG, JPG bytes) |
| `audio` | Audio data (WAV, MP3 bytes) |
| `video` | Video data (MP4, AVI bytes) |
| `binary` | Generic binary data |
---
## Prerequisites
Before you begin, ensure you have:
1. **NATS Server** running (or accessible)
2. **HTTP File Server** (optional, for large payloads > 1MB)
3. **One of the supported platforms**: Julia, JavaScript (Node.js), or Python/Micropython
---
## Installation
### Julia
```julia
using Pkg
Pkg.add("NATS")
Pkg.add("Arrow")
Pkg.add("JSON3")
Pkg.add("HTTP")
Pkg.add("UUIDs")
Pkg.add("Dates")
```
### JavaScript
```bash
npm install nats.js apache-arrow uuid base64-url
```
### Python/Micropython
1. Copy `src/nats_bridge.py` to your device
2. Install dependencies:
**For Python (desktop):**
```bash
pip install nats-py
```
**For Micropython:**
- `urequests` for HTTP requests
- `base64` for base64 encoding (built-in)
- `json` for JSON handling (built-in)
---
## Quick Start
### Step 1: Start NATS Server
```bash
docker run -p 4222:4222 nats:latest
```
### Step 2: Start HTTP File Server (Optional)
```bash
# Create a directory for file uploads
mkdir -p /tmp/fileserver
# Use Python's built-in server
python3 -m http.server 8080 --directory /tmp/fileserver
```
### Step 3: Send Your First Message
#### Python/Micropython
```python
from nats_bridge import smartsend
# Send a text message
data = [("message", "Hello World", "text")]
env = smartsend("/chat/room1", data, nats_url="nats://localhost:4222")
print("Message sent!")
```
#### JavaScript
```javascript
const { smartsend } = require('./src/NATSBridge');
// Send a text message
await smartsend("/chat/room1", [
{ dataname: "message", data: "Hello World", type: "text" }
], { natsUrl: "nats://localhost:4222" });
console.log("Message sent!");
```
#### Julia
```julia
using NATSBridge
# Send a text message
data = [("message", "Hello World", "text")]
env = smartsend("/chat/room1", data, nats_url="nats://localhost:4222")
println("Message sent!")
```
### Step 4: Receive Messages
#### Python/Micropython
```python
from nats_bridge import smartreceive
# Receive and process message
envelope = smartreceive(msg)
for dataname, data, type in envelope["payloads"]:
print(f"Received {dataname}: {data}")
```
#### JavaScript
```javascript
const { smartreceive } = require('./src/NATSBridge');
// Receive and process message
const envelope = await smartreceive(msg);
for (const payload of envelope.payloads) {
console.log(`Received ${payload.dataname}: ${payload.data}`);
}
```
#### Julia
```julia
using NATSBridge
# Receive and process message
envelope = smartreceive(msg, fileserverDownloadHandler)
for (dataname, data, type) in envelope["payloads"]
println("Received $dataname: $data")
end
```
---
## Basic Examples
### Example 1: Sending a Dictionary
#### Python/Micropython
```python
from nats_bridge import smartsend
# Create configuration dictionary
config = {
"wifi_ssid": "MyNetwork",
"wifi_password": "password123",
"update_interval": 60
}
# Send as dictionary type
data = [("config", config, "dictionary")]
env = smartsend("/device/config", data, nats_url="nats://localhost:4222")
```
#### JavaScript
```javascript
const { smartsend } = require('./src/NATSBridge');
const config = {
wifi_ssid: "MyNetwork",
wifi_password: "password123",
update_interval: 60
};
await smartsend("/device/config", [
{ dataname: "config", data: config, type: "dictionary" }
]);
```
#### Julia
```julia
using NATSBridge
config = Dict(
"wifi_ssid" => "MyNetwork",
"wifi_password" => "password123",
"update_interval" => 60
)
data = [("config", config, "dictionary")]
smartsend("/device/config", data)
```
### Example 2: Sending Binary Data (Image)
#### Python/Micropython
```python
from nats_bridge import smartsend
# Read image file
with open("image.png", "rb") as f:
image_data = f.read()
# Send as binary type
data = [("user_image", image_data, "binary")]
env = smartsend("/chat/image", data, nats_url="nats://localhost:4222")
```
#### JavaScript
```javascript
const { smartsend } = require('./src/NATSBridge');
// Read image file (Node.js)
const fs = require('fs');
const image_data = fs.readFileSync('image.png');
await smartsend("/chat/image", [
{ dataname: "user_image", data: image_data, type: "binary" }
]);
```
#### Julia
```julia
using NATSBridge
# Read image file
image_data = read("image.png")
data = [("user_image", image_data, "binary")]
smartsend("/chat/image", data)
```
### Example 3: Request-Response Pattern
#### Python/Micropython (Requester)
```python
from nats_bridge import smartsend
# Send command with reply-to
data = [("command", {"action": "read_sensor"}, "dictionary")]
env = smartsend(
"/device/command",
data,
nats_url="nats://localhost:4222",
reply_to="/device/response",
reply_to_msg_id="cmd-001"
)
```
#### JavaScript (Responder)
```javascript
const { smartreceive, smartsend } = require('./src/NATSBridge');
// Subscribe to command topic
const sub = nc.subscribe("/device/command");
for await (const msg of sub) {
const envelope = await smartreceive(msg);
// Process command
for (const payload of envelope.payloads) {
if (payload.dataname === "command") {
const command = payload.data;
if (command.action === "read_sensor") {
// Read sensor and send response
const response = {
sensor_id: "sensor-001",
value: 42.5,
timestamp: new Date().toISOString()
};
await smartsend("/device/response", [
{ dataname: "sensor_data", data: response, type: "dictionary" }
], {
reply_to: envelope.replyTo,
reply_to_msg_id: envelope.msgId
});
}
}
}
}
```
---
## Advanced Usage
### Example 4: Large Payloads (File Server)
For payloads larger than 1MB, NATSBridge automatically uses the file server:
#### Python/Micropython
```python
from nats_bridge import smartsend
import os
# Create large data (> 1MB)
large_data = os.urandom(2_000_000) # 2MB of random data
# Send with file server URL
env = smartsend(
"/data/large",
[("large_file", large_data, "binary")],
nats_url="nats://localhost:4222",
fileserver_url="http://localhost:8080",
size_threshold=1_000_000
)
# The envelope will contain the download URL
print(f"File uploaded to: {env.payloads[0].data}")
```
#### JavaScript
```javascript
const { smartsend } = require('./src/NATSBridge');
// Create large data (> 1MB)
const largeData = new ArrayBuffer(2_000_000);
const view = new Uint8Array(largeData);
view.fill(42); // Fill with some data
await smartsend("/data/large", [
{ dataname: "large_file", data: largeData, type: "binary" }
], {
fileserverUrl: "http://localhost:8080",
sizeThreshold: 1_000_000
});
```
#### Julia
```julia
using NATSBridge
# Create large data (> 1MB)
large_data = rand(UInt8, 2_000_000)
env = smartsend(
"/data/large",
[("large_file", large_data, "binary")],
fileserver_url="http://localhost:8080"
)
# The envelope will contain the download URL
println("File uploaded to: $(env.payloads[1].data)")
```
### Example 5: Mixed Content (Chat with Text + Image)
NATSBridge supports sending multiple payloads with different types in a single message:
#### Python/Micropython
```python
from nats_bridge import smartsend
# Read image file
with open("avatar.png", "rb") as f:
image_data = f.read()
# Send mixed content
data = [
("message_text", "Hello with image!", "text"),
("user_avatar", image_data, "image")
]
env = smartsend("/chat/mixed", data, nats_url="nats://localhost:4222")
```
#### JavaScript
```javascript
const { smartsend } = require('./src/NATSBridge');
const fs = require('fs');
await smartsend("/chat/mixed", [
{
dataname: "message_text",
data: "Hello with image!",
type: "text"
},
{
dataname: "user_avatar",
data: fs.readFileSync("avatar.png"),
type: "image"
}
]);
```
#### Julia
```julia
using NATSBridge
image_data = read("avatar.png")
data = [
("message_text", "Hello with image!", "text"),
("user_avatar", image_data, "image")
]
smartsend("/chat/mixed", data)
```
### Example 6: Table Data (Arrow IPC)
For tabular data, NATSBridge uses Apache Arrow IPC format:
#### Python/Micropython
```python
from nats_bridge import smartsend
import pandas as pd
# Create DataFrame
df = pd.DataFrame({
"id": [1, 2, 3],
"name": ["Alice", "Bob", "Charlie"],
"score": [95, 88, 92]
})
# Send as table type
data = [("students", df, "table")]
env = smartsend("/data/students", data, nats_url="nats://localhost:4222")
```
#### Julia
```julia
using NATSBridge
using DataFrames
# Create DataFrame
df = DataFrame(
id = [1, 2, 3],
name = ["Alice", "Bob", "Charlie"],
score = [95, 88, 92]
)
data = [("students", df, "table")]
smartsend("/data/students", data)
```
---
## Cross-Platform Communication
NATSBridge enables seamless communication between different platforms:
### Julia ↔ JavaScript
#### Julia Sender
```julia
using NATSBridge
# Send dictionary from Julia to JavaScript
config = Dict("step_size" => 0.01, "iterations" => 1000)
data = [("config", config, "dictionary")]
smartsend("/analysis/config", data, nats_url="nats://localhost:4222")
```
#### JavaScript Receiver
```javascript
const { smartreceive } = require('./src/NATSBridge');
// Receive dictionary from Julia
const envelope = await smartreceive(msg);
for (const payload of envelope.payloads) {
if (payload.type === "dictionary") {
console.log("Received config:", payload.data);
// payload.data = { step_size: 0.01, iterations: 1000 }
}
}
```
### JavaScript ↔ Python
#### JavaScript Sender
```javascript
const { smartsend } = require('./src/NATSBridge');
await smartsend("/data/transfer", [
{ dataname: "message", data: "Hello from JS!", type: "text" }
]);
```
#### Python Receiver
```python
from nats_bridge import smartreceive
envelope = smartreceive(msg)
for dataname, data, type in envelope["payloads"]:
if type == "text":
print(f"Received from JS: {data}")
```
### Python ↔ Julia
#### Python Sender
```python
from nats_bridge import smartsend
data = [("message", "Hello from Python!", "text")]
smartsend("/chat/python", data)
```
#### Julia Receiver
```julia
using NATSBridge
envelope = smartreceive(msg, fileserverDownloadHandler)
for (dataname, data, type) in envelope["payloads"]
if type == "text"
println("Received from Python: $data")
end
end
```
---
## Next Steps
1. **Explore the test directory** for more examples
2. **Check the documentation** for advanced configuration options
3. **Join the community** to share your use cases
---
## Troubleshooting
### Connection Issues
- Ensure NATS server is running: `docker ps | grep nats`
- Check firewall settings
- Verify NATS URL configuration
### File Server Issues
- Ensure file server is running and accessible
- Check upload permissions
- Verify file server URL configuration
### Serialization Errors
- Verify data type matches the specified type
- Check that binary data is in the correct format (bytes/Vector{UInt8})
---
## License
MIT

1045
examples/walkthrough.md Normal file

File diff suppressed because it is too large Load Diff

View File

@@ -759,8 +759,8 @@ function smartreceive(
error("Unknown transport type for payload '$dataname': $(transport)") # Throw error for unknown transport error("Unknown transport type for payload '$dataname': $(transport)") # Throw error for unknown transport
end end
end end
json_data["payloads"] = payloads_list
return payloads_list # Return list of (dataname, data, data_type) tuples return json_data # Return envelope with list of (dataname, data, data_type) tuples in payloads field
end end

View File

@@ -603,7 +603,7 @@ async function smartreceive(msg, options = {}) {
* @param {number} options.baseDelay - Initial delay for exponential backoff in ms (default: 100) * @param {number} options.baseDelay - Initial delay for exponential backoff in ms (default: 100)
* @param {number} options.maxDelay - Maximum delay for exponential backoff in ms (default: 5000) * @param {number} options.maxDelay - Maximum delay for exponential backoff in ms (default: 5000)
* *
* @returns {Promise<Array>} - List of {dataname, data, type} objects * @returns {Promise<Object>} - Envelope dictionary with metadata and payloads field containing list of {dataname, data, type} objects
*/ */
const { const {
fileserverDownloadHandler = _fetch_with_backoff, fileserverDownloadHandler = _fetch_with_backoff,
@@ -664,7 +664,10 @@ async function smartreceive(msg, options = {}) {
} }
} }
return payloads_list; // Replace payloads array with the processed list of {dataname, data, type} tuples
json_data.payloads = payloads_list;
return json_data;
} }
// Export for Node.js // Export for Node.js

View File

@@ -1,17 +1,17 @@
# NATSBridge for Micropython # NATSBridge
A high-performance, bi-directional data bridge for Micropython devices using NATS (Core & JetStream), implementing the Claim-Check pattern for large payloads. A high-performance, bi-directional data bridge for **Julia**, **JavaScript**, and **Python/Micropython** using NATS (Core & JetStream), implementing the Claim-Check pattern for large payloads.
## Overview ## Overview
This module provides functionality for sending and receiving data over NATS with automatic transport selection based on payload size: NATSBridge enables seamless communication between Julia, JavaScript, and Python/Micropython applications through NATS, with automatic transport selection based on payload size:
- **Direct Transport**: Payloads < 1MB are sent directly via NATS (Base64 encoded) - **Direct Transport**: Payloads < 1MB are sent directly via NATS (Base64 encoded)
- **Link Transport**: Payloads >= 1MB are uploaded to an HTTP file server and referenced via URL - **Link Transport**: Payloads >= 1MB are uploaded to an HTTP file server and referenced via URL
## Features ## Features
- ✅ Bi-directional NATS communication - ✅ Bi-directional NATS communication across Julia ↔ JavaScript ↔ Python/Micropython
- ✅ Multi-payload support (mixed content in single message) - ✅ Multi-payload support (mixed content in single message)
- ✅ Automatic transport selection based on payload size - ✅ Automatic transport selection based on payload size
- ✅ File server integration for large payloads - ✅ File server integration for large payloads
@@ -31,19 +31,56 @@ This module provides functionality for sending and receiving data over NATS with
| `video` | Video data (MP4, AVI bytes) | | `video` | Video data (MP4, AVI bytes) |
| `binary` | Generic binary data | | `binary` | Generic binary data |
## Implementation Guides
### [Julia Implementation](../tutorial_julia.md)
See the [Julia tutorial](../tutorial_julia.md) for getting started with Julia.
### [JavaScript Implementation](#javascript-implementation)
See [`NATSBridge.js`](NATSBridge.js) for the JavaScript implementation.
### [Python/Micropython Implementation](#pythonmicropython-implementation)
See [`nats_bridge.py`](nats_bridge.py) for the Python/Micropython implementation.
## Installation ## Installation
1. Copy `nats_bridge.py` to your Micropython device ### Julia
```julia
using Pkg
Pkg.add("NATS")
Pkg.add("Arrow")
Pkg.add("JSON3")
Pkg.add("HTTP")
Pkg.add("UUIDs")
Pkg.add("Dates")
```
### JavaScript
```bash
npm install nats.js apache-arrow uuid base64-url
```
### Python/Micropython
1. Copy `nats_bridge.py` to your device
2. Ensure you have the following dependencies: 2. Ensure you have the following dependencies:
- `urequests` for HTTP requests - `urequests` for HTTP requests (Micropython)
- `ubinascii` for base64 encoding - `requests` for HTTP requests (Python)
- `ujson` for JSON handling - `base64` for base64 encoding
- `usocket` for networking - `json` for JSON handling
- `socket` for networking (Micropython)
## Usage ## Usage
### Basic Text Message ### Basic Text Message
#### Python/Micropython
```python ```python
from nats_bridge import smartsend, smartreceive from nats_bridge import smartsend, smartreceive
@@ -57,8 +94,39 @@ for dataname, data, type in payloads:
print("Received {}: {}".format(dataname, data)) print("Received {}: {}".format(dataname, data))
``` ```
#### Julia
```julia
using NATSBridge
# Sender
data = [("message", "Hello World", "text")]
env = smartsend("/chat/room1", data, nats_url="nats://localhost:4222")
# Receiver
envelope = smartreceive(msg, fileserverDownloadHandler)
# envelope["payloads"] = [("message", "Hello World", "text"), ...]
```
#### JavaScript
```javascript
const { smartsend, smartreceive } = require('./src/NATSBridge');
// Sender
await smartsend("/chat/room1", [
{ dataname: "message", data: "Hello World", type: "text" }
], { natsUrl: "nats://localhost:4222" });
// Receiver
const envelope = await smartreceive(msg);
// envelope.payloads = [{ dataname: "message", data: "Hello World", type: "text" }, ...]
```
### Sending JSON Configuration ### Sending JSON Configuration
#### Python/Micropython
```python ```python
from nats_bridge import smartsend from nats_bridge import smartsend
@@ -74,6 +142,8 @@ env = smartsend("/device/config", data, nats_url="nats://localhost:4222")
### Mixed Content (Chat with Text + Image) ### Mixed Content (Chat with Text + Image)
#### Python/Micropython
```python ```python
from nats_bridge import smartsend from nats_bridge import smartsend
@@ -89,6 +159,8 @@ env = smartsend("/chat/mixed", data, nats_url="nats://localhost:4222")
### Request-Response Pattern ### Request-Response Pattern
#### Python/Micropython
```python ```python
from nats_bridge import smartsend from nats_bridge import smartsend
@@ -105,6 +177,8 @@ env = smartsend(
### Large Payloads (File Server) ### Large Payloads (File Server)
#### Python/Micropython
```python ```python
from nats_bridge import smartsend from nats_bridge import smartsend
@@ -191,21 +265,30 @@ Represents a single payload within a message envelope.
## Examples ## Examples
See `examples/micropython_example.py` for more detailed examples. See [`examples/micropython_example.py`](../examples/micropython_example.py) for more detailed examples.
## Testing ## Testing
Run the test suite: Run the test suite:
```bash ```bash
# Python/Micropython
python test/test_micropython_basic.py python test/test_micropython_basic.py
# JavaScript
node test/test_js_to_js_text_sender.js
node test/test_js_to_js_text_receiver.js
# Julia
julia test/test_julia_to_julia_text_sender.jl
julia test/test_julia_to_julia_text_receiver.jl
``` ```
## Requirements ## Requirements
- Micropython with networking support - **Julia**: NATS server (nats.io), HTTP file server (optional)
- NATS server (nats.io) - **JavaScript**: NATS server (nats.io), HTTP file server (optional)
- HTTP file server (optional, for large payloads) - **Python/Micropython**: NATS server (nats.io), HTTP file server (optional)
## License ## License

View File

@@ -559,7 +559,7 @@ def smartsend(subject, data, nats_url=DEFAULT_NATS_URL, fileserver_url=DEFAULT_F
def smartreceive(msg, fileserver_download_handler=_fetch_with_backoff, max_retries=5, def smartreceive(msg, fileserver_download_handler=_fetch_with_backoff, max_retries=5,
base_delay=100, max_delay=5000): base_delay=100, max_delay=5000):
"""Receive and process messages from NATS. """Receive and process messages from NATS.
This function processes incoming NATS messages, handling both direct transport This function processes incoming NATS messages, handling both direct transport
@@ -573,7 +573,7 @@ def smartreceive(msg, fileserver_download_handler=_fetch_with_backoff, max_retri
max_delay: Maximum delay for exponential backoff in ms max_delay: Maximum delay for exponential backoff in ms
Returns: Returns:
list: List of (dataname, data, type) tuples dict: Envelope dictionary with metadata and 'payloads' field containing list of (dataname, data, type) tuples
""" """
# Parse the JSON envelope # Parse the JSON envelope
json_data = msg if isinstance(msg, dict) else json.loads(msg) json_data = msg if isinstance(msg, dict) else json.loads(msg)
@@ -611,7 +611,7 @@ def smartreceive(msg, fileserver_download_handler=_fetch_with_backoff, max_retri
# Extract download URL from the payload # Extract download URL from the payload
url = payload.get("data", "") url = payload.get("data", "")
log_trace(json_data.get("correlationId", ""), log_trace(json_data.get("correlationId", ""),
"Link transport - fetching '{}' from URL: {}".format(dataname, url)) "Link transport - fetching '{}' from URL: {}".format(dataname, url))
# Fetch with exponential backoff # Fetch with exponential backoff
downloaded_data = fileserver_download_handler( downloaded_data = fileserver_download_handler(
@@ -627,7 +627,10 @@ def smartreceive(msg, fileserver_download_handler=_fetch_with_backoff, max_retri
else: else:
raise ValueError("Unknown transport type for payload '{}': {}".format(dataname, transport)) raise ValueError("Unknown transport type for payload '{}': {}".format(dataname, transport))
return payloads_list # Replace payloads field with the processed list of (dataname, data, type) tuples
json_data["payloads"] = payloads_list
return json_data
# Utility functions # Utility functions

View File

@@ -37,8 +37,9 @@ async function test_dict_receive() {
} }
); );
// Result is a list of {dataname, data, type} objects // Result is an envelope dictionary with payloads field
for (const { dataname, data, type } of result) { // Access payloads with result.payloads
for (const { dataname, data, type } of result.payloads) {
if (typeof data === 'object' && data !== null && !Array.isArray(data)) { if (typeof data === 'object' && data !== null && !Array.isArray(data)) {
log_trace(`Received Dictionary '${dataname}' of type ${type}`); log_trace(`Received Dictionary '${dataname}' of type ${type}`);

View File

@@ -36,8 +36,9 @@ async function test_large_binary_receive() {
} }
); );
// Result is a list of {dataname, data, type} objects // Result is an envelope dictionary with payloads field
for (const { dataname, data, type } of result) { // Access payloads with result.payloads
for (const { dataname, data, type } of result.payloads) {
if (data instanceof Uint8Array || Array.isArray(data)) { if (data instanceof Uint8Array || Array.isArray(data)) {
const file_size = data.length; const file_size = data.length;
log_trace(`Received ${file_size} bytes of binary data for '${dataname}' of type ${type}`); log_trace(`Received ${file_size} bytes of binary data for '${dataname}' of type ${type}`);

View File

@@ -40,10 +40,11 @@ async function test_mix_receive() {
} }
); );
log_trace(`Received ${result.length} payloads`); log_trace(`Received ${result.payloads.length} payloads`);
// Result is a list of {dataname, data, type} objects // Result is an envelope dictionary with payloads field
for (const { dataname, data, type } of result) { // Access payloads with result.payloads
for (const { dataname, data, type } of result.payloads) {
log_trace(`\n=== Payload: ${dataname} (type: ${type}) ===`); log_trace(`\n=== Payload: ${dataname} (type: ${type}) ===`);
// Handle different data types // Handle different data types
@@ -122,13 +123,13 @@ async function test_mix_receive() {
// Summary // Summary
console.log("\n=== Verification Summary ==="); console.log("\n=== Verification Summary ===");
const text_count = result.filter(x => x.type === "text").length; const text_count = result.payloads.filter(x => x.type === "text").length;
const dict_count = result.filter(x => x.type === "dictionary").length; const dict_count = result.payloads.filter(x => x.type === "dictionary").length;
const table_count = result.filter(x => x.type === "table").length; const table_count = result.payloads.filter(x => x.type === "table").length;
const image_count = result.filter(x => x.type === "image").length; const image_count = result.payloads.filter(x => x.type === "image").length;
const audio_count = result.filter(x => x.type === "audio").length; const audio_count = result.payloads.filter(x => x.type === "audio").length;
const video_count = result.filter(x => x.type === "video").length; const video_count = result.payloads.filter(x => x.type === "video").length;
const binary_count = result.filter(x => x.type === "binary").length; const binary_count = result.payloads.filter(x => x.type === "binary").length;
log_trace(`Text payloads: ${text_count}`); log_trace(`Text payloads: ${text_count}`);
log_trace(`Dictionary payloads: ${dict_count}`); log_trace(`Dictionary payloads: ${dict_count}`);
@@ -140,7 +141,7 @@ async function test_mix_receive() {
// Print transport type info for each payload if available // Print transport type info for each payload if available
console.log("\n=== Payload Details ==="); console.log("\n=== Payload Details ===");
for (const { dataname, data, type } of result) { for (const { dataname, data, type } of result.payloads) {
if (["image", "audio", "video", "binary"].includes(type)) { if (["image", "audio", "video", "binary"].includes(type)) {
log_trace(`${dataname}: ${data.length} bytes (binary)`); log_trace(`${dataname}: ${data.length} bytes (binary)`);
} else if (type === "table") { } else if (type === "table") {

View File

@@ -40,8 +40,9 @@ async function test_table_receive() {
} }
); );
// Result is a list of {dataname, data, type} objects // Result is an envelope dictionary with payloads field
for (const { dataname, data, type } of result) { // Access payloads with result.payloads
for (const { dataname, data, type } of result.payloads) {
if (Array.isArray(data)) { if (Array.isArray(data)) {
log_trace(`Received Table '${dataname}' of type ${type}`); log_trace(`Received Table '${dataname}' of type ${type}`);

View File

@@ -37,8 +37,9 @@ async function test_text_receive() {
} }
); );
// Result is a list of {dataname, data, type} objects // Result is an envelope dictionary with payloads field
for (const { dataname, data, type } of result) { // Access payloads with result.payloads
for (const { dataname, data, type } of result.payloads) {
if (typeof data === 'string') { if (typeof data === 'string') {
log_trace(`Received text '${dataname}' of type ${type}`); log_trace(`Received text '${dataname}' of type ${type}`);
log_trace(` Length: ${data.length} characters`); log_trace(` Length: ${data.length} characters`);

View File

@@ -42,8 +42,8 @@ function test_dict_receive()
max_delay = 5000 max_delay = 5000
) )
# Result is a list of (dataname, data, data_type) tuples # Result is an envelope dictionary with payloads field containing list of (dataname, data, data_type) tuples
for (dataname, data, data_type) in result for (dataname, data, data_type) in result["payloads"]
if isa(data, JSON.Object{String, Any}) if isa(data, JSON.Object{String, Any})
log_trace("Received Dictionary '$dataname' of type $data_type") log_trace("Received Dictionary '$dataname' of type $data_type")

View File

@@ -94,7 +94,7 @@ function test_dict_send()
# For large Dictionary: will use link transport (uploaded to fileserver) # For large Dictionary: will use link transport (uploaded to fileserver)
env = NATSBridge.smartsend( env = NATSBridge.smartsend(
SUBJECT, SUBJECT,
[data1, data2], # List of (dataname, data, type) tuples [data1, data2]; # List of (dataname, data, type) tuples
nats_url = NATS_URL, nats_url = NATS_URL,
fileserver_url = FILESERVER_URL, fileserver_url = FILESERVER_URL,
fileserverUploadHandler = plik_upload_handler, fileserverUploadHandler = plik_upload_handler,

View File

@@ -44,8 +44,8 @@ function test_large_binary_receive()
max_delay = 5000 max_delay = 5000
) )
# Result is a list of (dataname, data) tuples # Result is an envelope dictionary with payloads field containing list of (dataname, data, data_type) tuples
for (dataname, data, data_type) in result for (dataname, data, data_type) in result["payloads"]
# Check transport type from the envelope # Check transport type from the envelope
# For link transport, data is the URL string # For link transport, data is the URL string
# For direct transport, data is the actual payload bytes # For direct transport, data is the actual payload bytes

View File

@@ -81,7 +81,7 @@ function test_large_binary_send()
# API: smartsend(subject, [(dataname, data, type), ...]; keywords...) # API: smartsend(subject, [(dataname, data, type), ...]; keywords...)
env = NATSBridge.smartsend( env = NATSBridge.smartsend(
SUBJECT, SUBJECT,
[data1, data2], # List of (dataname, data, type) tuples [data1, data2]; # List of (dataname, data, type) tuples
nats_url = NATS_URL; nats_url = NATS_URL;
fileserver_url = FILESERVER_URL, fileserver_url = FILESERVER_URL,
fileserverUploadHandler = plik_upload_handler, fileserverUploadHandler = plik_upload_handler,

View File

@@ -45,10 +45,10 @@ function test_mix_receive()
max_delay = 5000 max_delay = 5000
) )
log_trace("Received $(length(result)) payloads") log_trace("Received $(length(result["payloads"])) payloads")
# Result is a list of (dataname, data, data_type) tuples # Result is an envelope dictionary with payloads field containing list of (dataname, data, data_type) tuples
for (dataname, data, data_type) in result for (dataname, data, data_type) in result["payloads"]
log_trace("\n=== Payload: $dataname (type: $data_type) ===") log_trace("\n=== Payload: $dataname (type: $data_type) ===")
# Handle different data types # Handle different data types
@@ -178,13 +178,13 @@ function test_mix_receive()
# Summary # Summary
println("\n=== Verification Summary ===") println("\n=== Verification Summary ===")
text_count = count(x -> x[3] == "text", result) text_count = count(x -> x[3] == "text", result["payloads"])
dict_count = count(x -> x[3] == "dictionary", result) dict_count = count(x -> x[3] == "dictionary", result["payloads"])
table_count = count(x -> x[3] == "table", result) table_count = count(x -> x[3] == "table", result["payloads"])
image_count = count(x -> x[3] == "image", result) image_count = count(x -> x[3] == "image", result["payloads"])
audio_count = count(x -> x[3] == "audio", result) audio_count = count(x -> x[3] == "audio", result["payloads"])
video_count = count(x -> x[3] == "video", result) video_count = count(x -> x[3] == "video", result["payloads"])
binary_count = count(x -> x[3] == "binary", result) binary_count = count(x -> x[3] == "binary", result["payloads"])
log_trace("Text payloads: $text_count") log_trace("Text payloads: $text_count")
log_trace("Dictionary payloads: $dict_count") log_trace("Dictionary payloads: $dict_count")
@@ -196,7 +196,7 @@ function test_mix_receive()
# Print transport type info for each payload if available # Print transport type info for each payload if available
println("\n=== Payload Details ===") println("\n=== Payload Details ===")
for (dataname, data, data_type) in result for (dataname, data, data_type) in result["payloads"]
if data_type in ["image", "audio", "video", "binary"] if data_type in ["image", "audio", "video", "binary"]
log_trace("$dataname: $(length(data)) bytes (binary)") log_trace("$dataname: $(length(data)) bytes (binary)")
elseif data_type == "table" elseif data_type == "table"

View File

@@ -188,7 +188,7 @@ function test_mix_send()
# Use smartsend with mixed content # Use smartsend with mixed content
env = NATSBridge.smartsend( env = NATSBridge.smartsend(
SUBJECT, SUBJECT,
payloads, # List of (dataname, data, type) tuples payloads; # List of (dataname, data, type) tuples
nats_url = NATS_URL, nats_url = NATS_URL,
fileserver_url = FILESERVER_URL, fileserver_url = FILESERVER_URL,
fileserverUploadHandler = plik_upload_handler, fileserverUploadHandler = plik_upload_handler,

View File

@@ -42,8 +42,8 @@ function test_table_receive()
max_delay = 5000 max_delay = 5000
) )
# Result is a list of (dataname, data, data_type) tuples # Result is an envelope dictionary with payloads field containing list of (dataname, data, data_type) tuples
for (dataname, data, data_type) in result for (dataname, data, data_type) in result["payloads"]
data = DataFrame(data) data = DataFrame(data)
if isa(data, DataFrame) if isa(data, DataFrame)
log_trace("Received DataFrame '$dataname' of type $data_type") log_trace("Received DataFrame '$dataname' of type $data_type")

View File

@@ -92,7 +92,7 @@ function test_table_send()
# For large DataFrame: will use link transport (uploaded to fileserver) # For large DataFrame: will use link transport (uploaded to fileserver)
env = NATSBridge.smartsend( env = NATSBridge.smartsend(
SUBJECT, SUBJECT,
[data1, data2], # List of (dataname, data, type) tuples [data1, data2]; # List of (dataname, data, type) tuples
nats_url = NATS_URL, nats_url = NATS_URL,
fileserver_url = FILESERVER_URL, fileserver_url = FILESERVER_URL,
fileserverUploadHandler = plik_upload_handler, fileserverUploadHandler = plik_upload_handler,

View File

@@ -42,8 +42,8 @@ function test_text_receive()
max_delay = 5000 max_delay = 5000
) )
# Result is a list of (dataname, data, data_type) tuples # Result is an envelope dictionary with payloads field containing list of (dataname, data, data_type) tuples
for (dataname, data, data_type) in result for (dataname, data, data_type) in result["payloads"]
if isa(data, String) if isa(data, String)
log_trace("Received text '$dataname' of type $data_type") log_trace("Received text '$dataname' of type $data_type")
log_trace(" Length: $(length(data)) characters") log_trace(" Length: $(length(data)) characters")

View File

@@ -77,7 +77,7 @@ function test_text_send()
# For large text: will use link transport (uploaded to fileserver) # For large text: will use link transport (uploaded to fileserver)
env = NATSBridge.smartsend( env = NATSBridge.smartsend(
SUBJECT, SUBJECT,
[data1, data2], # List of (dataname, data, type) tuples [data1, data2]; # List of (dataname, data, type) tuples
nats_url = NATS_URL, nats_url = NATS_URL,
fileserver_url = FILESERVER_URL, fileserver_url = FILESERVER_URL,
fileserverUploadHandler = plik_upload_handler, fileserverUploadHandler = plik_upload_handler,

View File

@@ -1,220 +1,207 @@
#!/usr/bin/env python3
""" """
Micropython NATS Bridge - Basic Test Examples Basic functionality test for nats_bridge.py
Tests the core classes and functions without NATS connection
This module demonstrates basic usage of the NATSBridge for Micropython.
""" """
import sys import sys
sys.path.insert(0, "../src") import os
from nats_bridge import MessageEnvelope, MessagePayload, smartsend, smartreceive, log_trace # Add src to path for import
sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'src'))
from nats_bridge import (
MessagePayload,
MessageEnvelope,
smartsend,
smartreceive,
log_trace,
generate_uuid,
get_timestamp,
_serialize_data,
_deserialize_data
)
import json import json
# ============================================= 100 ============================================== #
def test_message_payload():
def test_text_message(): """Test MessagePayload class"""
"""Test sending and receiving text messages.""" print("\n=== Testing MessagePayload ===")
print("\n=== Test 1: Text Message ===")
# Send text message # Test direct transport with text
data = [ payload1 = MessagePayload(
("message", "Hello World", "text"), data="Hello World",
("greeting", "Good morning!", "text") msg_type="text",
] id="test-id-1",
dataname="message",
env = smartsend( transport="direct",
"/test/text", encoding="base64",
data, size=11
nats_url="nats://localhost:4222",
size_threshold=1000000
) )
print("Sent envelope:") assert payload1.id == "test-id-1"
print(" Subject: {}".format(env.send_to)) assert payload1.dataname == "message"
print(" Correlation ID: {}".format(env.correlation_id)) assert payload1.type == "text"
print(" Payloads: {}".format(len(env.payloads))) assert payload1.transport == "direct"
assert payload1.encoding == "base64"
assert payload1.size == 11
print(" [PASS] MessagePayload with text data")
# Expected output on receiver: # Test link transport with URL
# payloads = smartreceive(msg) payload2 = MessagePayload(
# for dataname, data, type in payloads: data="http://example.com/file.txt",
# print("Received {}: {}".format(dataname, data)) msg_type="binary",
id="test-id-2",
dataname="file",
def test_dictionary_message(): transport="link",
"""Test sending and receiving dictionary messages.""" encoding="none",
print("\n=== Test 2: Dictionary Message ===") size=1000
# Send dictionary message
config = {
"step_size": 0.01,
"iterations": 1000,
"threshold": 0.5
}
data = [
("config", config, "dictionary")
]
env = smartsend(
"/test/dictionary",
data,
nats_url="nats://localhost:4222",
size_threshold=1000000
) )
print("Sent envelope:") assert payload2.transport == "link"
print(" Subject: {}".format(env.send_to)) assert payload2.data == "http://example.com/file.txt"
print(" Payloads: {}".format(len(env.payloads))) print(" [PASS] MessagePayload with link transport")
# Expected output on receiver: # Test to_dict method
# payloads = smartreceive(msg) payload_dict = payload1.to_dict()
# for dataname, data, type in payloads: assert "id" in payload_dict
# if type == "dictionary": assert "dataname" in payload_dict
# print("Config: {}".format(data)) assert "type" in payload_dict
assert "transport" in payload_dict
assert "data" in payload_dict
print(" [PASS] MessagePayload.to_dict() method")
def test_mixed_payloads(): def test_message_envelope():
"""Test sending mixed payload types in a single message.""" """Test MessageEnvelope class"""
print("\n=== Test 3: Mixed Payloads ===") print("\n=== Testing MessageEnvelope ===")
# Mixed content: text, dictionary, and binary # Create payloads
image_data = b"\x89PNG\r\n\x1a\n\x00\x00\x00\rIHDR" # PNG header (example) payload1 = MessagePayload("Hello", "text", id="p1", dataname="msg1")
payload2 = MessagePayload("http://example.com/file", "binary", id="p2", dataname="file", transport="link")
data = [ # Create envelope
("message_text", "Hello!", "text"), env = MessageEnvelope(
("user_config", {"theme": "dark", "volume": 80}, "dictionary"), send_to="/test/subject",
("user_image", image_data, "binary") payloads=[payload1, payload2],
] correlation_id="test-correlation-id",
msg_id="test-msg-id",
env = smartsend( msg_purpose="chat",
"/test/mixed", sender_name="test_sender",
data, receiver_name="test_receiver",
nats_url="nats://localhost:4222", reply_to="/test/reply"
size_threshold=1000000
) )
print("Sent envelope:") assert env.send_to == "/test/subject"
print(" Subject: {}".format(env.send_to)) assert env.correlation_id == "test-correlation-id"
print(" Payloads: {}".format(len(env.payloads))) assert env.msg_id == "test-msg-id"
assert env.msg_purpose == "chat"
assert len(env.payloads) == 2
print(" [PASS] MessageEnvelope creation")
# Expected output on receiver: # Test to_json method
# payloads = smartreceive(msg) json_str = env.to_json()
# for dataname, data, type in payloads: json_data = json.loads(json_str)
# print("Received {}: {} (type: {})".format(dataname, data if type != "binary" else len(data), type)) assert json_data["sendTo"] == "/test/subject"
assert json_data["correlationId"] == "test-correlation-id"
assert json_data["msgPurpose"] == "chat"
assert len(json_data["payloads"]) == 2
print(" [PASS] MessageEnvelope.to_json() method")
def test_large_payload(): def test_serialize_data():
"""Test sending large payloads that require fileserver upload.""" """Test _serialize_data function"""
print("\n=== Test 4: Large Payload (Link Transport) ===") print("\n=== Testing _serialize_data ===")
# Create large data (> 1MB would trigger link transport) # Test text serialization
# For testing, we'll use a smaller size but configure threshold lower text_bytes = _serialize_data("Hello", "text")
large_data = b"A" * 100000 # 100KB assert isinstance(text_bytes, bytes)
assert text_bytes == b"Hello"
print(" [PASS] Text serialization")
data = [ # Test dictionary serialization
("large_data", large_data, "binary") dict_data = {"key": "value", "number": 42}
] dict_bytes = _serialize_data(dict_data, "dictionary")
assert isinstance(dict_bytes, bytes)
parsed = json.loads(dict_bytes.decode('utf-8'))
assert parsed["key"] == "value"
print(" [PASS] Dictionary serialization")
# Use a lower threshold for testing # Test binary serialization
env = smartsend( binary_data = b"\x00\x01\x02"
"/test/large", binary_bytes = _serialize_data(binary_data, "binary")
data, assert binary_bytes == b"\x00\x01\x02"
nats_url="nats://localhost:4222", print(" [PASS] Binary serialization")
fileserver_url="http://localhost:8080",
size_threshold=50000 # 50KB threshold for testing
)
print("Sent envelope:") # Test image serialization
print(" Subject: {}".format(env.send_to)) image_data = bytes([1, 2, 3, 4, 5])
print(" Payloads: {}".format(len(env.payloads))) image_bytes = _serialize_data(image_data, "image")
for p in env.payloads: assert image_bytes == image_data
print(" - Transport: {}, Type: {}".format(p.transport, p.type)) print(" [PASS] Image serialization")
def test_reply_to(): def test_deserialize_data():
"""Test sending messages with reply-to functionality.""" """Test _deserialize_data function"""
print("\n=== Test 5: Reply To ===") print("\n=== Testing _deserialize_data ===")
data = [ # Test text deserialization
("command", {"action": "start"}, "dictionary") text_bytes = b"Hello"
] text_data = _deserialize_data(text_bytes, "text", "test-correlation-id")
assert text_data == "Hello"
print(" [PASS] Text deserialization")
env = smartsend( # Test dictionary deserialization
"/test/command", dict_bytes = b'{"key": "value"}'
data, dict_data = _deserialize_data(dict_bytes, "dictionary", "test-correlation-id")
nats_url="nats://localhost:4222", assert dict_data == {"key": "value"}
reply_to="/test/response", print(" [PASS] Dictionary deserialization")
reply_to_msg_id="reply-123",
msg_purpose="command"
)
print("Sent envelope:") # Test binary deserialization
print(" Subject: {}".format(env.send_to)) binary_data = b"\x00\x01\x02"
print(" Reply To: {}".format(env.reply_to)) binary_result = _deserialize_data(binary_data, "binary", "test-correlation-id")
print(" Reply To Msg ID: {}".format(env.reply_to_msg_id)) assert binary_result == b"\x00\x01\x02"
print(" [PASS] Binary deserialization")
def test_correlation_id(): def test_utilities():
"""Test using custom correlation IDs for tracing.""" """Test utility functions"""
print("\n=== Test 6: Custom Correlation ID ===") print("\n=== Testing Utility Functions ===")
custom_cid = "trace-abc123" # Test generate_uuid
data = [ uuid1 = generate_uuid()
("message", "Test with correlation ID", "text") uuid2 = generate_uuid()
] assert uuid1 != uuid2
print(f" [PASS] generate_uuid() - generated: {uuid1}")
env = smartsend( # Test get_timestamp
"/test/correlation", timestamp = get_timestamp()
data, assert "T" in timestamp
nats_url="nats://localhost:4222", print(f" [PASS] get_timestamp() - generated: {timestamp}")
correlation_id=custom_cid
)
print("Sent envelope with correlation ID: {}".format(env.correlation_id))
print("This ID can be used to trace the message flow.")
def test_multiple_payloads(): def main():
"""Test sending multiple payloads in one message.""" """Run all tests"""
print("\n=== Test 7: Multiple Payloads ===") print("=" * 60)
print("NATSBridge Python/Micropython - Basic Functionality Tests")
print("=" * 60)
data = [ try:
("text_message", "Hello", "text"), test_message_payload()
("json_data", {"key": "value", "number": 42}, "dictionary"), test_message_envelope()
("table_data", b"\x01\x02\x03\x04", "binary"), test_serialize_data()
("audio_data", b"\x00\x01\x02\x03", "binary") test_deserialize_data()
] test_utilities()
env = smartsend( print("\n" + "=" * 60)
"/test/multiple", print("ALL TESTS PASSED!")
data, print("=" * 60)
nats_url="nats://localhost:4222",
size_threshold=1000000 except Exception as e:
) print(f"\n[FAIL] Test failed with error: {e}")
import traceback
print("Sent {} payloads in one message".format(len(env.payloads))) traceback.print_exc()
sys.exit(1)
if __name__ == "__main__": if __name__ == "__main__":
print("Micropython NATS Bridge Test Suite") main()
print("==================================")
print()
# Run tests
test_text_message()
test_dictionary_message()
test_mixed_payloads()
test_large_payload()
test_reply_to()
test_correlation_id()
test_multiple_payloads()
print("\n=== All tests completed ===")
print()
print("Note: These tests require:")
print(" 1. A running NATS server at nats://localhost:4222")
print(" 2. An HTTP file server at http://localhost:8080 (for large payloads)")
print()
print("To run the tests:")
print(" python test_micropython_basic.py")

View File

@@ -0,0 +1,70 @@
#!/usr/bin/env python3
"""
Test script for dictionary transport testing - Receiver
Tests receiving dictionary messages via NATS using nats_bridge.py smartreceive
"""
import sys
import os
import json
# Add src to path for import
sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'src'))
from nats_bridge import smartreceive, log_trace
import nats
import asyncio
# Configuration
SUBJECT = "/NATSBridge_dict_test"
NATS_URL = "nats://nats.yiem.cc:4222"
async def main():
log_trace("", f"Starting dictionary transport receiver test...")
log_trace("", f"Note: This receiver will wait for messages from the sender.")
log_trace("", f"Run test_micropython_dict_sender.py first to send test data.")
# Connect to NATS
nc = await nats.connect(NATS_URL)
log_trace("", f"Connected to NATS at {NATS_URL}")
# Subscribe to the subject
async def message_handler(msg):
log_trace("", f"Received message on {msg.subject}")
# Use smartreceive to handle the data
result = smartreceive(msg.data)
# Result is an envelope dictionary with payloads field containing list of (dataname, data, data_type) tuples
for dataname, data, data_type in result["payloads"]:
if isinstance(data, dict):
log_trace(result.get("correlationId", ""), f"Received dictionary '{dataname}' of type {data_type}")
log_trace(result.get("correlationId", ""), f" Keys: {list(data.keys())}")
# Display first few items for small dicts
if isinstance(data, dict) and len(data) <= 10:
log_trace(result.get("correlationId", ""), f" Content: {json.dumps(data, indent=2)}")
else:
# For large dicts, show summary
log_trace(result.get("correlationId", ""), f" Summary: {json.dumps(data, default=str)[:200]}...")
# Save to file
output_path = f"./received_{dataname}.json"
with open(output_path, 'w') as f:
json.dump(data, f, indent=2)
log_trace(result.get("correlationId", ""), f"Saved dictionary to {output_path}")
else:
log_trace(result.get("correlationId", ""), f"Received unexpected data type for '{dataname}': {type(data)}")
sid = await nc.subscribe(SUBJECT, cb=message_handler)
log_trace("", f"Subscribed to {SUBJECT} with subscription ID: {sid}")
# Keep listening for 120 seconds
await asyncio.sleep(120)
await nc.close()
log_trace("", "Test completed.")
if __name__ == "__main__":
asyncio.run(main())

View File

@@ -0,0 +1,99 @@
#!/usr/bin/env python3
"""
Test script for dictionary transport testing - Micropython
Tests sending dictionary messages via NATS using nats_bridge.py smartsend
"""
import sys
import os
# Add src to path for import
sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'src'))
from nats_bridge import smartsend, log_trace
import uuid
# Configuration
SUBJECT = "/NATSBridge_dict_test"
NATS_URL = "nats://nats.yiem.cc:4222"
FILESERVER_URL = "http://192.168.88.104:8080"
SIZE_THRESHOLD = 1_000_000 # 1MB
# Create correlation ID for tracing
correlation_id = str(uuid.uuid4())
def main():
# Create a small dictionary (will use direct transport)
small_dict = {
"name": "test",
"value": 42,
"enabled": True,
"metadata": {
"version": "1.0.0",
"timestamp": "2026-02-22T12:00:00Z"
}
}
# Create a large dictionary (will use link transport if > 1MB)
# Generate a larger dictionary (~2MB to ensure link transport)
large_dict = {
"id": str(uuid.uuid4()),
"items": [
{
"index": i,
"name": f"item_{i}",
"value": i * 1.5,
"data": "x" * 10000 # Large string per item
}
for i in range(200)
],
"metadata": {
"count": 200,
"created": "2026-02-22T12:00:00Z"
}
}
# Test data 1: small dictionary
data1 = ("small_dict", small_dict, "dictionary")
# Test data 2: large dictionary
data2 = ("large_dict", large_dict, "dictionary")
log_trace(correlation_id, f"Starting smartsend for subject: {SUBJECT}")
log_trace(correlation_id, f"Correlation ID: {correlation_id}")
# Use smartsend with dictionary type
env = smartsend(
SUBJECT,
[data1, data2], # List of (dataname, data, type) tuples
nats_url=NATS_URL,
fileserver_url=FILESERVER_URL,
size_threshold=SIZE_THRESHOLD,
correlation_id=correlation_id,
msg_purpose="chat",
sender_name="dict_sender",
receiver_name="",
receiver_id="",
reply_to="",
reply_to_msg_id=""
)
log_trace(correlation_id, f"Sent message with {len(env.payloads)} payloads")
# Log transport type for each payload
for i, payload in enumerate(env.payloads):
log_trace(correlation_id, f"Payload {i+1} ('{payload.dataname}'):")
log_trace(correlation_id, f" Transport: {payload.transport}")
log_trace(correlation_id, f" Type: {payload.type}")
log_trace(correlation_id, f" Size: {payload.size} bytes")
log_trace(correlation_id, f" Encoding: {payload.encoding}")
if payload.transport == "link":
log_trace(correlation_id, f" URL: {payload.data}")
print(f"Test completed. Correlation ID: {correlation_id}")
if __name__ == "__main__":
main()

View File

@@ -0,0 +1,65 @@
#!/usr/bin/env python3
"""
Test script for file transport testing - Receiver
Tests receiving binary files via NATS using nats_bridge.py smartreceive
"""
import sys
import os
# Add src to path for import
sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'src'))
from nats_bridge import smartreceive, log_trace
import nats
import asyncio
# Configuration
SUBJECT = "/NATSBridge_file_test"
NATS_URL = "nats://nats.yiem.cc:4222"
async def main():
log_trace("", f"Starting file transport receiver test...")
log_trace("", f"Note: This receiver will wait for messages from the sender.")
log_trace("", f"Run test_micropython_file_sender.py first to send test data.")
# Connect to NATS
nc = await nats.connect(NATS_URL)
log_trace("", f"Connected to NATS at {NATS_URL}")
# Subscribe to the subject
async def message_handler(msg):
log_trace("", f"Received message on {msg.subject}")
# Use smartreceive to handle the data
result = smartreceive(msg.data)
# Result is an envelope dictionary with payloads field containing list of (dataname, data, data_type) tuples
for dataname, data, data_type in result["payloads"]:
if isinstance(data, bytes):
log_trace(result.get("correlationId", ""), f"Received binary '{dataname}' of type {data_type}")
log_trace(result.get("correlationId", ""), f" Size: {len(data)} bytes")
# Display first 100 bytes as hex
log_trace(result.get("correlationId", ""), f" First 100 bytes (hex): {data[:100].hex()}")
# Save to file
output_path = f"./received_{dataname}.bin"
with open(output_path, 'wb') as f:
f.write(data)
log_trace(result.get("correlationId", ""), f"Saved binary to {output_path}")
else:
log_trace(result.get("correlationId", ""), f"Received unexpected data type for '{dataname}': {type(data)}")
sid = await nc.subscribe(SUBJECT, cb=message_handler)
log_trace("", f"Subscribed to {SUBJECT} with subscription ID: {sid}")
# Keep listening for 120 seconds
await asyncio.sleep(120)
await nc.close()
log_trace("", "Test completed.")
if __name__ == "__main__":
asyncio.run(main())

View File

@@ -0,0 +1,79 @@
#!/usr/bin/env python3
"""
Test script for file transport testing - Micropython
Tests sending binary files via NATS using nats_bridge.py smartsend
"""
import sys
import os
# Add src to path for import
sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'src'))
from nats_bridge import smartsend, log_trace
import uuid
# Configuration
SUBJECT = "/NATSBridge_file_test"
NATS_URL = "nats://nats.yiem.cc:4222"
FILESERVER_URL = "http://192.168.88.104:8080"
SIZE_THRESHOLD = 1_000_000 # 1MB
# Create correlation ID for tracing
correlation_id = str(uuid.uuid4())
def main():
# Create small binary data (will use direct transport)
small_binary = b"This is small binary data for testing direct transport."
small_binary += b"\x00" * 100 # Add some null bytes
# Create large binary data (will use link transport if > 1MB)
# Generate a larger binary (~2MB to ensure link transport)
large_binary = bytes([
(i * 7) % 256 for i in range(2_000_000)
])
# Test data 1: small binary (direct transport)
data1 = ("small_binary", small_binary, "binary")
# Test data 2: large binary (link transport)
data2 = ("large_binary", large_binary, "binary")
log_trace(correlation_id, f"Starting smartsend for subject: {SUBJECT}")
log_trace(correlation_id, f"Correlation ID: {correlation_id}")
# Use smartsend with binary type
env = smartsend(
SUBJECT,
[data1, data2], # List of (dataname, data, type) tuples
nats_url=NATS_URL,
fileserver_url=FILESERVER_URL,
size_threshold=SIZE_THRESHOLD,
correlation_id=correlation_id,
msg_purpose="chat",
sender_name="file_sender",
receiver_name="",
receiver_id="",
reply_to="",
reply_to_msg_id=""
)
log_trace(correlation_id, f"Sent message with {len(env.payloads)} payloads")
# Log transport type for each payload
for i, payload in enumerate(env.payloads):
log_trace(correlation_id, f"Payload {i+1} ('{payload.dataname}'):")
log_trace(correlation_id, f" Transport: {payload.transport}")
log_trace(correlation_id, f" Type: {payload.type}")
log_trace(correlation_id, f" Size: {payload.size} bytes")
log_trace(correlation_id, f" Encoding: {payload.encoding}")
if payload.transport == "link":
log_trace(correlation_id, f" URL: {payload.data}")
print(f"Test completed. Correlation ID: {correlation_id}")
if __name__ == "__main__":
main()

View File

@@ -0,0 +1,97 @@
#!/usr/bin/env python3
"""
Test script for mixed payload testing - Receiver
Tests receiving mixed payload types via NATS using nats_bridge.py smartreceive
"""
import sys
import os
import json
# Add src to path for import
sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'src'))
from nats_bridge import smartreceive, log_trace
import nats
import asyncio
# Configuration
SUBJECT = "/NATSBridge_mixed_test"
NATS_URL = "nats://nats.yiem.cc:4222"
async def main():
log_trace("", f"Starting mixed payload receiver test...")
log_trace("", f"Note: This receiver will wait for messages from the sender.")
log_trace("", f"Run test_micropython_mixed_sender.py first to send test data.")
# Connect to NATS
nc = await nats.connect(NATS_URL)
log_trace("", f"Connected to NATS at {NATS_URL}")
# Subscribe to the subject
async def message_handler(msg):
log_trace("", f"Received message on {msg.subject}")
# Use smartreceive to handle the data
result = smartreceive(msg.data)
log_trace(result.get("correlationId", ""), f"Received envelope with {len(result['payloads'])} payloads")
# Result is an envelope dictionary with payloads field containing list of (dataname, data, data_type) tuples
for dataname, data, data_type in result["payloads"]:
log_trace(result.get("correlationId", ""), f"\n--- Payload: {dataname} (type: {data_type}) ---")
if isinstance(data, str):
log_trace(result.get("correlationId", ""), f" Type: text/string")
log_trace(result.get("correlationId", ""), f" Length: {len(data)} characters")
if len(data) <= 100:
log_trace(result.get("correlationId", ""), f" Content: {data}")
else:
log_trace(result.get("correlationId", ""), f" First 100 chars: {data[:100]}...")
# Save to file
output_path = f"./received_{dataname}.txt"
with open(output_path, 'w') as f:
f.write(data)
log_trace(result.get("correlationId", ""), f" Saved to: {output_path}")
elif isinstance(data, dict):
log_trace(result.get("correlationId", ""), f" Type: dictionary")
log_trace(result.get("correlationId", ""), f" Keys: {list(data.keys())}")
log_trace(result.get("correlationId", ""), f" Content: {json.dumps(data, indent=2)}")
# Save to file
output_path = f"./received_{dataname}.json"
with open(output_path, 'w') as f:
json.dump(data, f, indent=2)
log_trace(result.get("correlationId", ""), f" Saved to: {output_path}")
elif isinstance(data, bytes):
log_trace(result.get("correlationId", ""), f" Type: binary")
log_trace(result.get("correlationId", ""), f" Size: {len(data)} bytes")
log_trace(result.get("correlationId", ""), f" First 100 bytes (hex): {data[:100].hex()}")
# Save to file
output_path = f"./received_{dataname}.bin"
with open(output_path, 'wb') as f:
f.write(data)
log_trace(result.get("correlationId", ""), f" Saved to: {output_path}")
else:
log_trace(result.get("correlationId", ""), f" Received unexpected data type: {type(data)}")
# Log envelope metadata
log_trace(result.get("correlationId", ""), f"\n--- Envelope Metadata ---")
log_trace(result.get("correlationId", ""), f" Correlation ID: {result.get('correlationId', 'N/A')}")
log_trace(result.get("correlationId", ""), f" Message ID: {result.get('msgId', 'N/A')}")
log_trace(result.get("correlationId", ""), f" Sender: {result.get('senderName', 'N/A')}")
log_trace(result.get("correlationId", ""), f" Purpose: {result.get('msgPurpose', 'N/A')}")
sid = await nc.subscribe(SUBJECT, cb=message_handler)
log_trace("", f"Subscribed to {SUBJECT} with subscription ID: {sid}")
# Keep listening for 120 seconds
await asyncio.sleep(120)
await nc.close()
log_trace("", "Test completed.")
if __name__ == "__main__":
asyncio.run(main())

View File

@@ -0,0 +1,93 @@
#!/usr/bin/env python3
"""
Test script for mixed payload testing - Micropython
Tests sending mixed payload types via NATS using nats_bridge.py smartsend
"""
import sys
import os
# Add src to path for import
sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'src'))
from nats_bridge import smartsend, log_trace
import uuid
# Configuration
SUBJECT = "/NATSBridge_mixed_test"
NATS_URL = "nats://nats.yiem.cc:4222"
FILESERVER_URL = "http://192.168.88.104:8080"
SIZE_THRESHOLD = 1_000_000 # 1MB
# Create correlation ID for tracing
correlation_id = str(uuid.uuid4())
def main():
# Create payloads for mixed content test
# 1. Small text (direct transport)
text_data = "Hello, this is a text message for testing mixed payloads!"
# 2. Small dictionary (direct transport)
dict_data = {
"status": "ok",
"code": 200,
"message": "Test successful",
"items": [1, 2, 3]
}
# 3. Small binary (direct transport)
binary_data = b"\x00\x01\x02\x03\x04\x05" + b"\xff" * 100
# 4. Large text (link transport - will use fileserver)
large_text = "\n".join([
f"Line {i}: This is a large text payload for link transport testing. " * 50
for i in range(100)
])
# Test data list - mixed payload types
data = [
("message_text", text_data, "text"),
("config_dict", dict_data, "dictionary"),
("small_binary", binary_data, "binary"),
("large_text", large_text, "text"),
]
log_trace(correlation_id, f"Starting smartsend for subject: {SUBJECT}")
log_trace(correlation_id, f"Correlation ID: {correlation_id}")
# Use smartsend with mixed types
env = smartsend(
SUBJECT,
data, # List of (dataname, data, type) tuples
nats_url=NATS_URL,
fileserver_url=FILESERVER_URL,
size_threshold=SIZE_THRESHOLD,
correlation_id=correlation_id,
msg_purpose="chat",
sender_name="mixed_sender",
receiver_name="",
receiver_id="",
reply_to="",
reply_to_msg_id=""
)
log_trace(correlation_id, f"Sent message with {len(env.payloads)} payloads")
# Log transport type for each payload
for i, payload in enumerate(env.payloads):
log_trace(correlation_id, f"Payload {i+1} ('{payload.dataname}'):")
log_trace(correlation_id, f" Transport: {payload.transport}")
log_trace(correlation_id, f" Type: {payload.type}")
log_trace(correlation_id, f" Size: {payload.size} bytes")
log_trace(correlation_id, f" Encoding: {payload.encoding}")
if payload.transport == "link":
log_trace(correlation_id, f" URL: {payload.data}")
print(f"Test completed. Correlation ID: {correlation_id}")
if __name__ == "__main__":
main()

View File

@@ -0,0 +1,69 @@
#!/usr/bin/env python3
"""
Test script for text transport testing - Receiver
Tests receiving text messages via NATS using nats_bridge.py smartreceive
"""
import sys
import os
import json
# Add src to path for import
sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'src'))
from nats_bridge import smartreceive, log_trace
import nats
import asyncio
# Configuration
SUBJECT = "/NATSBridge_text_test"
NATS_URL = "nats://nats.yiem.cc:4222"
async def main():
log_trace("", f"Starting text transport receiver test...")
log_trace("", f"Note: This receiver will wait for messages from the sender.")
log_trace("", f"Run test_micropython_text_sender.py first to send test data.")
# Connect to NATS
nc = await nats.connect(NATS_URL)
log_trace("", f"Connected to NATS at {NATS_URL}")
# Subscribe to the subject
async def message_handler(msg):
log_trace("", f"Received message on {msg.subject}")
# Use smartreceive to handle the data
result = smartreceive(msg.data)
# Result is an envelope dictionary with payloads field containing list of (dataname, data, data_type) tuples
for dataname, data, data_type in result["payloads"]:
if isinstance(data, str):
log_trace(result.get("correlationId", ""), f"Received text '{dataname}' of type {data_type}")
log_trace(result.get("correlationId", ""), f" Length: {len(data)} characters")
# Display first 100 characters
if len(data) > 100:
log_trace(result.get("correlationId", ""), f" First 100 characters: {data[:100]}...")
else:
log_trace(result.get("correlationId", ""), f" Content: {data}")
# Save to file
output_path = f"./received_{dataname}.txt"
with open(output_path, 'w') as f:
f.write(data)
log_trace(result.get("correlationId", ""), f"Saved text to {output_path}")
else:
log_trace(result.get("correlationId", ""), f"Received unexpected data type for '{dataname}': {type(data)}")
sid = await nc.subscribe(SUBJECT, cb=message_handler)
log_trace("", f"Subscribed to {SUBJECT} with subscription ID: {sid}")
# Keep listening for 120 seconds
await asyncio.sleep(120)
await nc.close()
log_trace("", "Test completed.")
if __name__ == "__main__":
asyncio.run(main())

View File

@@ -0,0 +1,81 @@
#!/usr/bin/env python3
"""
Test script for text transport testing - Micropython
Tests sending text messages via NATS using nats_bridge.py smartsend
"""
import sys
import os
# Add src to path for import
sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'src'))
from nats_bridge import smartsend, log_trace
import uuid
# Configuration
SUBJECT = "/NATSBridge_text_test"
NATS_URL = "nats://nats.yiem.cc:4222"
FILESERVER_URL = "http://192.168.88.104:8080"
SIZE_THRESHOLD = 1_000_000 # 1MB
# Create correlation ID for tracing
correlation_id = str(uuid.uuid4())
def main():
# Create a small text (will use direct transport)
small_text = "Hello, this is a small text message. Testing direct transport via NATS."
# Create a large text (will use link transport if > 1MB)
# Generate a larger text (~2MB to ensure link transport)
large_text = "\n".join([
f"Line {i}: This is a sample text line with some content to pad the size. " * 100
for i in range(500)
])
# Test data 1: small text
data1 = ("small_text", small_text, "text")
# Test data 2: large text
data2 = ("large_text", large_text, "text")
log_trace(correlation_id, f"Starting smartsend for subject: {SUBJECT}")
log_trace(correlation_id, f"Correlation ID: {correlation_id}")
# Use smartsend with text type
# For small text: will use direct transport (Base64 encoded UTF-8)
# For large text: will use link transport (uploaded to fileserver)
env = smartsend(
SUBJECT,
[data1, data2], # List of (dataname, data, type) tuples
nats_url=NATS_URL,
fileserver_url=FILESERVER_URL,
size_threshold=SIZE_THRESHOLD,
correlation_id=correlation_id,
msg_purpose="chat",
sender_name="text_sender",
receiver_name="",
receiver_id="",
reply_to="",
reply_to_msg_id=""
)
log_trace(correlation_id, f"Sent message with {len(env.payloads)} payloads")
# Log transport type for each payload
for i, payload in enumerate(env.payloads):
log_trace(correlation_id, f"Payload {i+1} ('{payload.dataname}'):")
log_trace(correlation_id, f" Transport: {payload.transport}")
log_trace(correlation_id, f" Type: {payload.type}")
log_trace(correlation_id, f" Size: {payload.size} bytes")
log_trace(correlation_id, f" Encoding: {payload.encoding}")
if payload.transport == "link":
log_trace(correlation_id, f" URL: {payload.data}")
print(f"Test completed. Correlation ID: {correlation_id}")
if __name__ == "__main__":
main()

View File

@@ -1,634 +0,0 @@
# NATSBridge.jl Tutorial
A comprehensive tutorial for learning how to use NATSBridge.jl for bi-directional communication between Julia and JavaScript services using NATS.
## Table of Contents
1. [What is NATSBridge.jl?](#what-is-natsbridgejl)
2. [Key Concepts](#key-concepts)
3. [Installation](#installation)
4. [Basic Usage](#basic-usage)
5. [Payload Types](#payload-types)
6. [Transport Strategies](#transport-strategies)
7. [Advanced Features](#advanced-features)
8. [Complete Examples](#complete-examples)
---
## What is NATSBridge.jl?
NATSBridge.jl is a Julia module that provides a high-level API for sending and receiving data across network boundaries using NATS as the message bus. It implements the **Claim-Check pattern** for handling large payloads efficiently.
### Core Features
- **Bi-directional communication**: Julia ↔ JavaScript
- **Smart transport selection**: Automatic direct vs link transport based on payload size
- **Multi-payload support**: Send multiple payloads of different types in a single message
- **Claim-check pattern**: Upload large files to HTTP server, send only URLs via NATS
- **Type-aware serialization**: Different serialization strategies for different data types
---
## Key Concepts
### 1. msgEnvelope_v1 (Message Envelope)
The `msgEnvelope_v1` structure provides a comprehensive message format for bidirectional communication:
```julia
struct msgEnvelope_v1
correlationId::String # Unique identifier to track messages
msgId::String # This message id
timestamp::String # Message published timestamp
sendTo::String # Topic/subject the sender sends to
msgPurpose::String # Purpose (ACK | NACK | updateStatus | shutdown | chat)
senderName::String # Sender name (e.g., "agent-wine-web-frontend")
senderId::String # Sender id (uuid4)
receiverName::String # Message receiver name (e.g., "agent-backend")
receiverId::String # Message receiver id (uuid4 or nothing for broadcast)
replyTo::String # Topic to reply to
replyToMsgId::String # Message id this message is replying to
brokerURL::String # NATS server address
metadata::Dict{String, Any}
payloads::AbstractArray{msgPayload_v1} # Multiple payloads stored here
end
```
### 2. msgPayload_v1 (Payload Structure)
The `msgPayload_v1` structure provides flexible payload handling:
```julia
struct msgPayload_v1
id::String # Id of this payload (e.g., "uuid4")
dataname::String # Name of this payload (e.g., "login_image")
type::String # "text | dictionary | table | image | audio | video | binary"
transport::String # "direct | link"
encoding::String # "none | json | base64 | arrow-ipc"
size::Integer # Data size in bytes
data::Any # Payload data in case of direct transport or a URL in case of link
metadata::Dict{String, Any} # Dict("checksum" => "sha256_hash", ...)
end
```
### 3. Standard API Format
The system uses a **standardized list-of-tuples format** for all payload operations:
```julia
# Input format for smartsend (always a list of tuples with type info)
[(dataname1, data1, type1), (dataname2, data2, type2), ...]
# Output format for smartreceive (always returns a list of tuples)
[(dataname1, data1, type1), (dataname2, data2, type2), ...]
```
**Important**: Even when sending a single payload, you must wrap it in a list.
---
## Installation
```julia
using Pkg
Pkg.add("NATS")
Pkg.add("JSON")
Pkg.add("Arrow")
Pkg.add("HTTP")
Pkg.add("UUIDs")
Pkg.add("Dates")
Pkg.add("Base64")
Pkg.add("PrettyPrinting")
Pkg.add("DataFrames")
```
Then include the NATSBridge module:
```julia
include("NATSBridge.jl")
using .NATSBridge
```
---
## Basic Usage
### Sending Data (smartsend)
```julia
using NATSBridge
# Send a simple dictionary
data = Dict("key" => "value")
env = NATSBridge.smartsend("my.subject", [("dataname1", data, "dictionary")])
```
### Receiving Data (smartreceive)
```julia
using NATSBridge
# Subscribe to a NATS subject
NATS.subscribe("my.subject") do msg
# Process the message
result = NATSBridge.smartreceive(
msg,
max_retries = 5,
base_delay = 100,
max_delay = 5000
)
# result is a list of (dataname, data, type) tuples
for (dataname, data, type) in result
println("Received $dataname of type $type")
println("Data: $data")
end
end
```
---
## Payload Types
NATSBridge.jl supports the following payload types:
| Type | Description | Serialization |
|------|-------------|---------------|
| `text` | Plain text | UTF-8 encoding |
| `dictionary` | JSON-serializable data (Dict, NamedTuple) | JSON |
| `table` | Tabular data (DataFrame, array of structs) | Apache Arrow IPC |
| `image` | Image data (Bitmap, PNG/JPG bytes) | Binary |
| `audio` | Audio data (WAV, MP3 bytes) | Binary |
| `video` | Video data (MP4, AVI bytes) | Binary |
| `binary` | Generic binary data | Binary |
---
## Transport Strategies
NATSBridge.jl automatically selects the appropriate transport strategy based on payload size:
### Direct Transport (< 1MB)
Small payloads are encoded as Base64 and sent directly over NATS.
```julia
# Small data (< 1MB) - uses direct transport
small_data = rand(1000) # ~8KB
env = NATSBridge.smartsend("small", [("data", small_data, "table")])
```
### Link Transport (≥ 1MB)
Large payloads are uploaded to an HTTP file server, and only the URL is sent via NATS.
```julia
# Large data (≥ 1MB) - uses link transport
large_data = rand(10_000_000) # ~80MB
env = NATSBridge.smartsend("large", [("data", large_data, "table")])
```
---
## Complete Examples
### Example 1: Text Message
**Sender:**
```julia
using NATSBridge
using UUIDs
const SUBJECT = "/NATSBridge_text_test"
const NATS_URL = "nats://localhost:4222"
const FILESERVER_URL = "http://localhost:8080"
function plik_upload_handler(fileserver_url::String, dataname::String, data::Vector{UInt8})::Dict{String, Any}
url_getUploadID = "$fileserver_url/upload"
headers = ["Content-Type" => "application/json"]
body = """{ "OneShot" : true }"""
httpResponse = HTTP.request("POST", url_getUploadID, headers, body; body_is_form=false)
responseJson = JSON.parse(String(httpResponse.body))
uploadid = responseJson["id"]
uploadtoken = responseJson["uploadToken"]
file_multipart = HTTP.Multipart(dataname, IOBuffer(data), "application/octet-stream")
url_upload = "$fileserver_url/file/$uploadid"
headers = ["X-UploadToken" => uploadtoken]
form = HTTP.Form(Dict("file" => file_multipart))
httpResponse = HTTP.post(url_upload, headers, form)
responseJson = JSON.parse(String(httpResponse.body))
fileid = responseJson["id"]
url = "$fileserver_url/file/$uploadid/$fileid/$dataname"
return Dict("status" => httpResponse.status, "uploadid" => uploadid, "fileid" => fileid, "url" => url)
end
function test_text_send()
small_text = "Hello, this is a small text message."
large_text = join(["Line $i: " for i in 1:50000], "")
data1 = ("small_text", small_text, "text")
data2 = ("large_text", large_text, "text")
env = NATSBridge.smartsend(
SUBJECT,
[data1, data2],
nats_url = NATS_URL,
fileserver_url = FILESERVER_URL,
fileserverUploadHandler = plik_upload_handler,
size_threshold = 1_000_000,
correlation_id = string(uuid4()),
msg_purpose = "chat",
sender_name = "text_sender"
)
end
```
**Receiver:**
```julia
using NATSBridge
const SUBJECT = "/NATSBridge_text_test"
const NATS_URL = "nats://localhost:4222"
function test_text_receive()
conn = NATS.connect(NATS_URL)
NATS.subscribe(conn, SUBJECT) do msg
result = NATSBridge.smartreceive(
msg,
max_retries = 5,
base_delay = 100,
max_delay = 5000
)
for (dataname, data, data_type) in result
if data_type == "text"
println("Received text: $data")
write("./received_$dataname.txt", data)
end
end
end
sleep(120)
NATS.drain(conn)
end
```
### Example 2: Dictionary (JSON) Message
**Sender:**
```julia
using NATSBridge
using UUIDs
const SUBJECT = "/NATSBridge_dict_test"
const NATS_URL = "nats://localhost:4222"
const FILESERVER_URL = "http://localhost:8080"
function plik_upload_handler(fileserver_url::String, dataname::String, data::Vector{UInt8})::Dict{String, Any}
url_getUploadID = "$fileserver_url/upload"
headers = ["Content-Type" => "application/json"]
body = """{ "OneShot" : true }"""
httpResponse = HTTP.request("POST", url_getUploadID, headers, body; body_is_form=false)
responseJson = JSON.parse(String(httpResponse.body))
uploadid = responseJson["id"]
uploadtoken = responseJson["uploadToken"]
file_multipart = HTTP.Multipart(dataname, IOBuffer(data), "application/octet-stream")
url_upload = "$fileserver_url/file/$uploadid"
headers = ["X-UploadToken" => uploadtoken]
form = HTTP.Form(Dict("file" => file_multipart))
httpResponse = HTTP.post(url_upload, headers, form)
responseJson = JSON.parse(String(httpResponse.body))
fileid = responseJson["id"]
url = "$fileserver_url/file/$uploadid/$fileid/$dataname"
return Dict("status" => httpResponse.status, "uploadid" => uploadid, "fileid" => fileid, "url" => url)
end
function test_dict_send()
small_dict = Dict("name" => "Alice", "age" => 30)
large_dict = Dict("ids" => collect(1:50000), "names" => ["User_$i" for i in 1:50000])
data1 = ("small_dict", small_dict, "dictionary")
data2 = ("large_dict", large_dict, "dictionary")
env = NATSBridge.smartsend(
SUBJECT,
[data1, data2],
nats_url = NATS_URL,
fileserver_url = FILESERVER_URL,
fileserverUploadHandler = plik_upload_handler,
size_threshold = 1_000_000,
correlation_id = string(uuid4()),
msg_purpose = "chat"
)
end
```
**Receiver:**
```julia
using NATSBridge
const SUBJECT = "/NATSBridge_dict_test"
const NATS_URL = "nats://localhost:4222"
function test_dict_receive()
conn = NATS.connect(NATS_URL)
NATS.subscribe(conn, SUBJECT) do msg
result = NATSBridge.smartreceive(
msg,
max_retries = 5,
base_delay = 100,
max_delay = 5000
)
for (dataname, data, data_type) in result
if data_type == "dictionary"
println("Received dictionary: $data")
write("./received_$dataname.json", JSON.json(data, 2))
end
end
end
sleep(120)
NATS.drain(conn)
end
```
### Example 3: DataFrame (Table) Message
**Sender:**
```julia
using NATSBridge
using DataFrames
using UUIDs
const SUBJECT = "/NATSBridge_table_test"
const NATS_URL = "nats://localhost:4222"
const FILESERVER_URL = "http://localhost:8080"
function plik_upload_handler(fileserver_url::String, dataname::String, data::Vector{UInt8})::Dict{String, Any}
url_getUploadID = "$fileserver_url/upload"
headers = ["Content-Type" => "application/json"]
body = """{ "OneShot" : true }"""
httpResponse = HTTP.request("POST", url_getUploadID, headers, body; body_is_form=false)
responseJson = JSON.parse(String(httpResponse.body))
uploadid = responseJson["id"]
uploadtoken = responseJson["uploadToken"]
file_multipart = HTTP.Multipart(dataname, IOBuffer(data), "application/octet-stream")
url_upload = "$fileserver_url/file/$uploadid"
headers = ["X-UploadToken" => uploadtoken]
form = HTTP.Form(Dict("file" => file_multipart))
httpResponse = HTTP.post(url_upload, headers, form)
responseJson = JSON.parse(String(httpResponse.body))
fileid = responseJson["id"]
url = "$fileserver_url/file/$uploadid/$fileid/$dataname"
return Dict("status" => httpResponse.status, "uploadid" => uploadid, "fileid" => fileid, "url" => url)
end
function test_table_send()
small_df = DataFrame(id = 1:10, name = ["Alice", "Bob", "Charlie"], score = [95, 88, 92])
large_df = DataFrame(id = 1:50000, name = ["User_$i" for i in 1:50000], score = rand(1:100, 50000))
data1 = ("small_table", small_df, "table")
data2 = ("large_table", large_df, "table")
env = NATSBridge.smartsend(
SUBJECT,
[data1, data2],
nats_url = NATS_URL,
fileserver_url = FILESERVER_URL,
fileserverUploadHandler = plik_upload_handler,
size_threshold = 1_000_000,
correlation_id = string(uuid4()),
msg_purpose = "chat"
)
end
```
**Receiver:**
```julia
using NATSBridge
using DataFrames
const SUBJECT = "/NATSBridge_table_test"
const NATS_URL = "nats://localhost:4222"
function test_table_receive()
conn = NATS.connect(NATS_URL)
NATS.subscribe(conn, SUBJECT) do msg
result = NATSBridge.smartreceive(
msg,
max_retries = 5,
base_delay = 100,
max_delay = 5000
)
for (dataname, data, data_type) in result
if data_type == "table"
data = DataFrame(data)
println("Received DataFrame with $(size(data, 1)) rows")
display(data[1:min(5, size(data, 1)), :])
end
end
end
sleep(120)
NATS.drain(conn)
end
```
### Example 4: Mixed Content (Chat with Text, Image, Audio)
**Sender:**
```julia
using NATSBridge
using DataFrames
using UUIDs
const SUBJECT = "/NATSBridge_mix_test"
const NATS_URL = "nats://localhost:4222"
const FILESERVER_URL = "http://localhost:8080"
function plik_upload_handler(fileserver_url::String, dataname::String, data::Vector{UInt8})::Dict{String, Any}
url_getUploadID = "$fileserver_url/upload"
headers = ["Content-Type" => "application/json"]
body = """{ "OneShot" : true }"""
httpResponse = HTTP.request("POST", url_getUploadID, headers, body; body_is_form=false)
responseJson = JSON.parse(String(httpResponse.body))
uploadid = responseJson["id"]
uploadtoken = responseJson["uploadToken"]
file_multipart = HTTP.Multipart(dataname, IOBuffer(data), "application/octet-stream")
url_upload = "$fileserver_url/file/$uploadid"
headers = ["X-UploadToken" => uploadtoken]
form = HTTP.Form(Dict("file" => file_multipart))
httpResponse = HTTP.post(url_upload, headers, form)
responseJson = JSON.parse(String(httpResponse.body))
fileid = responseJson["id"]
url = "$fileserver_url/file/$uploadid/$fileid/$dataname"
return Dict("status" => httpResponse.status, "uploadid" => uploadid, "fileid" => fileid, "url" => url)
end
function test_mix_send()
# Text data
text_data = "Hello! This is a test chat message. 🎉"
# Dictionary data
dict_data = Dict("type" => "chat", "sender" => "serviceA")
# Small table data
table_data_small = DataFrame(id = 1:10, name = ["msg_$i" for i in 1:10])
# Large table data (link transport)
table_data_large = DataFrame(id = 1:150_000, name = ["msg_$i" for i in 1:150_000])
# Small image data (direct transport)
image_data = UInt8[rand(1:255) for _ in 1:100]
# Large image data (link transport)
large_image_data = UInt8[rand(1:255) for _ in 1:1_500_000]
# Small audio data (direct transport)
audio_data = UInt8[rand(1:255) for _ in 1:100]
# Large audio data (link transport)
large_audio_data = UInt8[rand(1:255) for _ in 1:1_500_000]
# Small video data (direct transport)
video_data = UInt8[rand(1:255) for _ in 1:150]
# Large video data (link transport)
large_video_data = UInt8[rand(1:255) for _ in 1:1_500_000]
# Small binary data (direct transport)
binary_data = UInt8[rand(1:255) for _ in 1:200]
# Large binary data (link transport)
large_binary_data = UInt8[rand(1:255) for _ in 1:1_500_000]
# Create payloads list - mixed content
payloads = [
# Small data (direct transport)
("chat_text", text_data, "text"),
("chat_json", dict_data, "dictionary"),
("chat_table_small", table_data_small, "table"),
# Large data (link transport)
("chat_table_large", table_data_large, "table"),
("user_image_large", large_image_data, "image"),
("audio_clip_large", large_audio_data, "audio"),
("video_clip_large", large_video_data, "video"),
("binary_file_large", large_binary_data, "binary")
]
env = NATSBridge.smartsend(
SUBJECT,
payloads,
nats_url = NATS_URL,
fileserver_url = FILESERVER_URL,
fileserverUploadHandler = plik_upload_handler,
size_threshold = 1_000_000,
correlation_id = string(uuid4()),
msg_purpose = "chat",
sender_name = "mix_sender"
)
end
```
**Receiver:**
```julia
using NATSBridge
using DataFrames
const SUBJECT = "/NATSBridge_mix_test"
const NATS_URL = "nats://localhost:4222"
function test_mix_receive()
conn = NATS.connect(NATS_URL)
NATS.subscribe(conn, SUBJECT) do msg
result = NATSBridge.smartreceive(
msg,
max_retries = 5,
base_delay = 100,
max_delay = 5000
)
println("Received $(length(result)) payloads")
for (dataname, data, data_type) in result
println("\n=== Payload: $dataname (type: $data_type) ===")
if data_type == "text"
println(" Type: String")
println(" Length: $(length(data)) characters")
elseif data_type == "dictionary"
println(" Type: JSON Object")
println(" Keys: $(keys(data))")
elseif data_type == "table"
data = DataFrame(data)
println(" Type: DataFrame")
println(" Dimensions: $(size(data, 1)) rows x $(size(data, 2)) columns")
elseif data_type == "image"
println(" Type: Vector{UInt8}")
println(" Size: $(length(data)) bytes")
write("./received_$dataname.bin", data)
elseif data_type == "audio"
println(" Type: Vector{UInt8}")
println(" Size: $(length(data)) bytes")
write("./received_$dataname.bin", data)
elseif data_type == "video"
println(" Type: Vector{UInt8}")
println(" Size: $(length(data)) bytes")
write("./received_$dataname.bin", data)
elseif data_type == "binary"
println(" Type: Vector{UInt8}")
println(" Size: $(length(data)) bytes")
write("./received_$dataname.bin", data)
end
end
end
sleep(120)
NATS.drain(conn)
end
```
---
## Best Practices
1. **Always wrap payloads in a list** - Even for single payloads: `[("dataname", data, "type")]`
2. **Use appropriate transport** - Let NATSBridge handle size-based routing (default 1MB threshold)
3. **Customize size threshold** - Use `size_threshold` parameter to adjust the direct/link split
4. **Provide fileserver handler** - Implement `fileserverUploadHandler` for link transport
5. **Include correlation IDs** - Track messages across distributed systems
6. **Handle errors** - Implement proper error handling for network failures
7. **Close connections** - Ensure NATS connections are properly closed using `NATS.drain()`
---
## Conclusion
NATSBridge.jl provides a powerful abstraction for bi-directional communication between Julia and JavaScript services. By understanding the key concepts and following the best practices, you can build robust, scalable applications that leverage the full power of NATS messaging.
For more information, see:
- [`docs/architecture.md`](./architecture.md) - Detailed architecture documentation
- [`docs/implementation.md`](./implementation.md) - Implementation details

View File

@@ -1,939 +0,0 @@
# NATSBridge.jl Walkthrough: Building a Chat System
A step-by-step guided walkthrough for building a real-time chat system using NATSBridge.jl with mixed content support (text, images, audio, video, and files).
## Prerequisites
- Julia 1.7+
- NATS server running
- HTTP file server (Plik) running
## Step 1: Understanding the Chat System Architecture
### System Components
```
┌─────────────────────────────────────────────────────────────────────────────┐
│ Chat System │
├─────────────────────────────────────────────────────────────────────────────┤
│ │
│ ┌──────────────┐ NATS ┌──────────────┐ │
│ │ Julia │◄───────┬───────► │ JavaScript │ │
│ │ Service │ │ │ Client │ │
│ │ │ │ │ │ │
│ │ - Text │ │ │ - Text │ │
│ │ - Images │ │ │ - Images │ │
│ │ - Audio │ ▼ │ - Audio │ │
│ │ - Video │ NATSBridge.jl │ - Files │ │
│ │ - Files │ │ │ - Tables │ │
│ └──────────────┘ │ └──────────────┘ │
│ │ │
│ ┌───────┴───────┐ │
│ │ NATS │ │
│ │ Server │ │
│ └─────────────┘ │
│ │
└─────────────────────────────────────────────────────────────────────────────┘
For large payloads (> 1MB):
┌─────────────────────────────────────────────────────────────────────────────┐
│ File Server (Plik) │
│ │
│ Julia Service ──► Upload ──► File Server ──► Download ◄── JavaScript Client│
│ │
└─────────────────────────────────────────────────────────────────────────────┘
```
### Message Format
Each chat message is an envelope containing multiple payloads:
```json
{
"correlationId": "uuid4",
"msgId": "uuid4",
"timestamp": "2024-01-15T10:30:00Z",
"sendTo": "/chat/room1",
"msgPurpose": "chat",
"senderName": "user-1",
"senderId": "uuid4",
"receiverName": "user-2",
"receiverId": "uuid4",
"brokerURL": "nats://localhost:4222",
"payloads": [
{
"id": "uuid4",
"dataname": "message_text",
"type": "text",
"transport": "direct",
"encoding": "base64",
"size": 256,
"data": "SGVsbG8gV29ybGQh",
"metadata": {}
},
{
"id": "uuid4",
"dataname": "user_image",
"type": "image",
"transport": "link",
"encoding": "none",
"size": 15433,
"data": "http://localhost:8080/file/UPLOAD_ID/FILE_ID/image.jpg",
"metadata": {}
}
]
}
```
## Step 2: Setting Up the Environment
### 1. Start NATS Server
```bash
# Using Docker
docker run -d -p 4222:4222 -p 8222:8222 --name nats-server nats:latest
# Or download from https://github.com/nats-io/nats-server/releases
./nats-server
```
### 2. Start HTTP File Server (Plik)
```bash
# Using Docker
docker run -d -p 8080:8080 --name plik plik/plik:latest
# Or download from https://github.com/arnaud-lb/plik/releases
./plikd -d
```
### 3. Install Julia Dependencies
```julia
using Pkg
Pkg.add("NATS")
Pkg.add("JSON")
Pkg.add("Arrow")
Pkg.add("HTTP")
Pkg.add("UUIDs")
Pkg.add("Dates")
Pkg.add("Base64")
Pkg.add("PrettyPrinting")
Pkg.add("DataFrames")
```
## Step 3: Basic Text-Only Chat
### Sender (User 1)
```julia
using NATS
using JSON
using UUIDs
using Dates
using PrettyPrinting
using DataFrames
using Arrow
using HTTP
using Base64
# Include the bridge module
include("NATSBridge.jl")
using .NATSBridge
# Configuration
const NATS_URL = "nats://localhost:4222"
const FILESERVER_URL = "http://localhost:8080"
const SUBJECT = "/chat/room1"
# File upload handler for plik server
function plik_upload_handler(fileserver_url::String, dataname::String, data::Vector{UInt8})::Dict{String, Any}
url_getUploadID = "$fileserver_url/upload"
headers = ["Content-Type" => "application/json"]
body = """{ "OneShot" : true }"""
httpResponse = HTTP.request("POST", url_getUploadID, headers, body; body_is_form=false)
responseJson = JSON.parse(String(httpResponse.body))
uploadid = responseJson["id"]
uploadtoken = responseJson["uploadToken"]
file_multipart = HTTP.Multipart(dataname, IOBuffer(data), "application/octet-stream")
url_upload = "$fileserver_url/file/$uploadid"
headers = ["X-UploadToken" => uploadtoken]
form = HTTP.Form(Dict("file" => file_multipart))
httpResponse = HTTP.post(url_upload, headers, form)
responseJson = JSON.parse(String(httpResponse.body))
fileid = responseJson["id"]
url = "$fileserver_url/file/$uploadid/$fileid/$dataname"
return Dict("status" => httpResponse.status, "uploadid" => uploadid, "fileid" => fileid, "url" => url)
end
# Send a simple text message
function send_text_message()
message_text = "Hello, how are you today?"
env = NATSBridge.smartsend(
SUBJECT,
[("message", message_text, "text")],
nats_url = NATS_URL,
fileserver_url = FILESERVER_URL,
fileserverUploadHandler = plik_upload_handler,
size_threshold = 1_000_000,
correlation_id = string(uuid4()),
msg_purpose = "chat",
sender_name = "user-1"
)
println("Sent text message with correlation ID: $(env.correlationId)")
end
send_text_message()
```
### Receiver (User 2)
```julia
using NATS
using JSON
using UUIDs
using Dates
using PrettyPrinting
using DataFrames
using Arrow
using HTTP
using Base64
# Include the bridge module
include("NATSBridge.jl")
using .NATSBridge
# Configuration
const NATS_URL = "nats://localhost:4222"
const SUBJECT = "/chat/room1"
# Message handler
function message_handler(msg::NATS.Msg)
payloads = NATSBridge.smartreceive(
msg,
max_retries = 5,
base_delay = 100,
max_delay = 5000
)
# Extract the text message
for (dataname, data, data_type) in payloads
if data_type == "text"
println("Received message: $data")
# Save to file
write("./received_$dataname.txt", data)
end
end
end
# Subscribe to the chat room
NATS.subscribe(SUBJECT) do msg
message_handler(msg)
end
# Keep the program running
while true
sleep(1)
end
```
## Step 4: Adding Image Support
### Sending an Image
```julia
using NATS
using JSON
using UUIDs
using Dates
using PrettyPrinting
using DataFrames
using Arrow
using HTTP
using Base64
include("NATSBridge.jl")
using .NATSBridge
const NATS_URL = "nats://localhost:4222"
const FILESERVER_URL = "http://localhost:8080"
const SUBJECT = "/chat/room1"
function plik_upload_handler(fileserver_url::String, dataname::String, data::Vector{UInt8})::Dict{String, Any}
url_getUploadID = "$fileserver_url/upload"
headers = ["Content-Type" => "application/json"]
body = """{ "OneShot" : true }"""
httpResponse = HTTP.request("POST", url_getUploadID, headers, body; body_is_form=false)
responseJson = JSON.parse(String(httpResponse.body))
uploadid = responseJson["id"]
uploadtoken = responseJson["uploadToken"]
file_multipart = HTTP.Multipart(dataname, IOBuffer(data), "application/octet-stream")
url_upload = "$fileserver_url/file/$uploadid"
headers = ["X-UploadToken" => uploadtoken]
form = HTTP.Form(Dict("file" => file_multipart))
httpResponse = HTTP.post(url_upload, headers, form)
responseJson = JSON.parse(String(httpResponse.body))
fileid = responseJson["id"]
url = "$fileserver_url/file/$uploadid/$fileid/$dataname"
return Dict("status" => httpResponse.status, "uploadid" => uploadid, "fileid" => fileid, "url" => url)
end
function send_image()
# Read image file
image_data = read("screenshot.png", Vector{UInt8})
# Send with text message
env = NATSBridge.smartsend(
SUBJECT,
[
("text", "Check out this screenshot!", "text"),
("screenshot", image_data, "image")
],
nats_url = NATS_URL,
fileserver_url = FILESERVER_URL,
fileserverUploadHandler = plik_upload_handler,
size_threshold = 1_000_000,
correlation_id = string(uuid4()),
msg_purpose = "chat",
sender_name = "user-1"
)
println("Sent image with correlation ID: $(env.correlationId)")
end
send_image()
```
### Receiving an Image
```julia
using NATS
using JSON
using UUIDs
using Dates
using PrettyPrinting
using DataFrames
using Arrow
using HTTP
using Base64
include("NATSBridge.jl")
using .NATSBridge
const NATS_URL = "nats://localhost:4222"
const SUBJECT = "/chat/room1"
function message_handler(msg::NATS.Msg)
payloads = NATSBridge.smartreceive(
msg,
max_retries = 5,
base_delay = 100,
max_delay = 5000
)
for (dataname, data, data_type) in payloads
if data_type == "text"
println("Text: $data")
elseif data_type == "image"
# Save image to file
filename = "received_$dataname.bin"
write(filename, data)
println("Saved image: $filename")
end
end
end
NATS.subscribe(SUBJECT) do msg
message_handler(msg)
end
```
## Step 5: Handling Large Files with Link Transport
### Automatic Transport Selection
```julia
using NATS
using JSON
using UUIDs
using Dates
using PrettyPrinting
using DataFrames
using Arrow
using HTTP
using Base64
include("NATSBridge.jl")
using .NATSBridge
const NATS_URL = "nats://localhost:4222"
const FILESERVER_URL = "http://localhost:8080"
const SUBJECT = "/chat/room1"
function plik_upload_handler(fileserver_url::String, dataname::String, data::Vector{UInt8})::Dict{String, Any}
url_getUploadID = "$fileserver_url/upload"
headers = ["Content-Type" => "application/json"]
body = """{ "OneShot" : true }"""
httpResponse = HTTP.request("POST", url_getUploadID, headers, body; body_is_form=false)
responseJson = JSON.parse(String(httpResponse.body))
uploadid = responseJson["id"]
uploadtoken = responseJson["uploadToken"]
file_multipart = HTTP.Multipart(dataname, IOBuffer(data), "application/octet-stream")
url_upload = "$fileserver_url/file/$uploadid"
headers = ["X-UploadToken" => uploadtoken]
form = HTTP.Form(Dict("file" => file_multipart))
httpResponse = HTTP.post(url_upload, headers, form)
responseJson = JSON.parse(String(httpResponse.body))
fileid = responseJson["id"]
url = "$fileserver_url/file/$uploadid/$fileid/$dataname"
return Dict("status" => httpResponse.status, "uploadid" => uploadid, "fileid" => fileid, "url" => url)
end
function send_large_file()
# Create a large file (> 1MB triggers link transport)
large_data = rand(10_000_000) # ~80MB
env = NATSBridge.smartsend(
SUBJECT,
[("large_file", large_data, "binary")],
nats_url = NATS_URL,
fileserver_url = FILESERVER_URL,
fileserverUploadHandler = plik_upload_handler,
size_threshold = 1_000_000,
correlation_id = string(uuid4()),
msg_purpose = "chat",
sender_name = "user-1"
)
println("Uploaded large file to: $(env.payloads[1].data)")
println("Correlation ID: $(env.correlationId)")
end
send_large_file()
```
## Step 6: Audio and Video Support
### Sending Audio
```julia
using NATS
using JSON
using UUIDs
using Dates
using PrettyPrinting
using DataFrames
using Arrow
using HTTP
using Base64
include("NATSBridge.jl")
using .NATSBridge
const NATS_URL = "nats://localhost:4222"
const FILESERVER_URL = "http://localhost:8080"
const SUBJECT = "/chat/room1"
function plik_upload_handler(fileserver_url::String, dataname::String, data::Vector{UInt8})::Dict{String, Any}
url_getUploadID = "$fileserver_url/upload"
headers = ["Content-Type" => "application/json"]
body = """{ "OneShot" : true }"""
httpResponse = HTTP.request("POST", url_getUploadID, headers, body; body_is_form=false)
responseJson = JSON.parse(String(httpResponse.body))
uploadid = responseJson["id"]
uploadtoken = responseJson["uploadToken"]
file_multipart = HTTP.Multipart(dataname, IOBuffer(data), "application/octet-stream")
url_upload = "$fileserver_url/file/$uploadid"
headers = ["X-UploadToken" => uploadtoken]
form = HTTP.Form(Dict("file" => file_multipart))
httpResponse = HTTP.post(url_upload, headers, form)
responseJson = JSON.parse(String(httpResponse.body))
fileid = responseJson["id"]
url = "$fileserver_url/file/$uploadid/$fileid/$dataname"
return Dict("status" => httpResponse.status, "uploadid" => uploadid, "fileid" => fileid, "url" => url)
end
function send_audio()
# Read audio file (WAV, MP3, etc.)
audio_data = read("voice_message.mp3", Vector{UInt8})
env = NATSBridge.smartsend(
SUBJECT,
[("voice_message", audio_data, "audio")],
nats_url = NATS_URL,
fileserver_url = FILESERVER_URL,
fileserverUploadHandler = plik_upload_handler,
size_threshold = 1_000_000,
correlation_id = string(uuid4()),
msg_purpose = "chat",
sender_name = "user-1"
)
println("Sent audio message: $(env.correlationId)")
end
send_audio()
```
### Sending Video
```julia
using NATS
using JSON
using UUIDs
using Dates
using PrettyPrinting
using DataFrames
using Arrow
using HTTP
using Base64
include("NATSBridge.jl")
using .NATSBridge
const NATS_URL = "nats://localhost:4222"
const FILESERVER_URL = "http://localhost:8080"
const SUBJECT = "/chat/room1"
function plik_upload_handler(fileserver_url::String, dataname::String, data::Vector{UInt8})::Dict{String, Any}
url_getUploadID = "$fileserver_url/upload"
headers = ["Content-Type" => "application/json"]
body = """{ "OneShot" : true }"""
httpResponse = HTTP.request("POST", url_getUploadID, headers, body; body_is_form=false)
responseJson = JSON.parse(String(httpResponse.body))
uploadid = responseJson["id"]
uploadtoken = responseJson["uploadToken"]
file_multipart = HTTP.Multipart(dataname, IOBuffer(data), "application/octet-stream")
url_upload = "$fileserver_url/file/$uploadid"
headers = ["X-UploadToken" => uploadtoken]
form = HTTP.Form(Dict("file" => file_multipart))
httpResponse = HTTP.post(url_upload, headers, form)
responseJson = JSON.parse(String(httpResponse.body))
fileid = responseJson["id"]
url = "$fileserver_url/file/$uploadid/$fileid/$dataname"
return Dict("status" => httpResponse.status, "uploadid" => uploadid, "fileid" => fileid, "url" => url)
end
function send_video()
# Read video file (MP4, AVI, etc.)
video_data = read("video_message.mp4", Vector{UInt8})
env = NATSBridge.smartsend(
SUBJECT,
[("video_message", video_data, "video")],
nats_url = NATS_URL,
fileserver_url = FILESERVER_URL,
fileserverUploadHandler = plik_upload_handler,
size_threshold = 1_000_000,
correlation_id = string(uuid4()),
msg_purpose = "chat",
sender_name = "user-1"
)
println("Sent video message: $(env.correlationId)")
end
send_video()
```
## Step 7: Table/Data Exchange
### Sending Tabular Data
```julia
using NATS
using JSON
using UUIDs
using Dates
using PrettyPrinting
using DataFrames
using Arrow
using HTTP
using Base64
include("NATSBridge.jl")
using .NATSBridge
const NATS_URL = "nats://localhost:4222"
const FILESERVER_URL = "http://localhost:8080"
const SUBJECT = "/chat/room1"
function plik_upload_handler(fileserver_url::String, dataname::String, data::Vector{UInt8})::Dict{String, Any}
url_getUploadID = "$fileserver_url/upload"
headers = ["Content-Type" => "application/json"]
body = """{ "OneShot" : true }"""
httpResponse = HTTP.request("POST", url_getUploadID, headers, body; body_is_form=false)
responseJson = JSON.parse(String(httpResponse.body))
uploadid = responseJson["id"]
uploadtoken = responseJson["uploadToken"]
file_multipart = HTTP.Multipart(dataname, IOBuffer(data), "application/octet-stream")
url_upload = "$fileserver_url/file/$uploadid"
headers = ["X-UploadToken" => uploadtoken]
form = HTTP.Form(Dict("file" => file_multipart))
httpResponse = HTTP.post(url_upload, headers, form)
responseJson = JSON.parse(String(httpResponse.body))
fileid = responseJson["id"]
url = "$fileserver_url/file/$uploadid/$fileid/$dataname"
return Dict("status" => httpResponse.status, "uploadid" => uploadid, "fileid" => fileid, "url" => url)
end
function send_table()
# Create a DataFrame
df = DataFrame(
id = 1:5,
name = ["Alice", "Bob", "Charlie", "Diana", "Eve"],
score = [95, 88, 92, 98, 85],
grade = ['A', 'B', 'A', 'B', 'B']
)
env = NATSBridge.smartsend(
SUBJECT,
[("student_scores", df, "table")],
nats_url = NATS_URL,
fileserver_url = FILESERVER_URL,
fileserverUploadHandler = plik_upload_handler,
size_threshold = 1_000_000,
correlation_id = string(uuid4()),
msg_purpose = "chat",
sender_name = "user-1"
)
println("Sent table with $(nrow(df)) rows")
end
send_table()
```
### Receiving and Using Tables
```julia
using NATS
using JSON
using UUIDs
using Dates
using PrettyPrinting
using DataFrames
using Arrow
using HTTP
using Base64
include("NATSBridge.jl")
using .NATSBridge
const NATS_URL = "nats://localhost:4222"
const SUBJECT = "/chat/room1"
function message_handler(msg::NATS.Msg)
payloads = NATSBridge.smartreceive(
msg,
max_retries = 5,
base_delay = 100,
max_delay = 5000
)
for (dataname, data, data_type) in payloads
if data_type == "table"
data = DataFrame(data)
println("Received table:")
show(data)
println("\nAverage score: $(mean(data.score))")
end
end
end
NATS.subscribe(SUBJECT) do msg
message_handler(msg)
end
```
## Step 8: Bidirectional Communication
### Request-Response Pattern
```julia
using NATS
using JSON
using UUIDs
using Dates
using PrettyPrinting
using DataFrames
using Arrow
using HTTP
using Base64
include("NATSBridge.jl")
using .NATSBridge
const NATS_URL = "nats://localhost:4222"
const SUBJECT = "/api/query"
const REPLY_SUBJECT = "/api/response"
# Request
function send_request()
query_data = Dict("query" => "SELECT * FROM users")
env = NATSBridge.smartsend(
SUBJECT,
[("sql_query", query_data, "dictionary")],
nats_url = NATS_URL,
fileserver_url = "http://localhost:8080",
fileserverUploadHandler = plik_upload_handler,
size_threshold = 1_000_000,
correlation_id = string(uuid4()),
msg_purpose = "request",
sender_name = "frontend",
receiver_name = "backend",
reply_to = REPLY_SUBJECT,
reply_to_msg_id = string(uuid4())
)
println("Request sent: $(env.correlationId)")
end
# Response handler
function response_handler(msg::NATS.Msg)
payloads = NATSBridge.smartreceive(
msg,
max_retries = 5,
base_delay = 100,
max_delay = 5000
)
for (dataname, data, data_type) in payloads
if data_type == "table"
data = DataFrame(data)
println("Query results:")
show(data)
end
end
end
NATS.subscribe(REPLY_SUBJECT) do msg
response_handler(msg)
end
```
## Step 9: Complete Chat Application
### Full Chat System
```julia
module ChatApp
using NATS
using JSON
using UUIDs
using Dates
using PrettyPrinting
using DataFrames
using Arrow
using HTTP
using Base64
# Include the bridge module
include("../src/NATSBridge.jl")
using .NATSBridge
# Configuration
const NATS_URL = "nats://localhost:4222"
const FILESERVER_URL = "http://localhost:8080"
const SUBJECT = "/chat/room1"
# File upload handler for plik server
function plik_upload_handler(fileserver_url::String, dataname::String, data::Vector{UInt8})::Dict{String, Any}
url_getUploadID = "$fileserver_url/upload"
headers = ["Content-Type" => "application/json"]
body = """{ "OneShot" : true }"""
httpResponse = HTTP.request("POST", url_getUploadID, headers, body; body_is_form=false)
responseJson = JSON.parse(String(httpResponse.body))
uploadid = responseJson["id"]
uploadtoken = responseJson["uploadToken"]
file_multipart = HTTP.Multipart(dataname, IOBuffer(data), "application/octet-stream")
url_upload = "$fileserver_url/file/$uploadid"
headers = ["X-UploadToken" => uploadtoken]
form = HTTP.Form(Dict("file" => file_multipart))
httpResponse = HTTP.post(url_upload, headers, form)
responseJson = JSON.parse(String(httpResponse.body))
fileid = responseJson["id"]
url = "$fileserver_url/file/$uploadid/$fileid/$dataname"
return Dict("status" => httpResponse.status, "uploadid" => uploadid, "fileid" => fileid, "url" => url)
end
function send_chat_message(
text::String,
image_path::Union{String, Nothing}=nothing,
audio_path::Union{String, Nothing}=nothing
)
# Build payloads list
payloads = [("message_text", text, "text")]
if image_path !== nothing
image_data = read(image_path, Vector{UInt8})
push!(payloads, ("user_image", image_data, "image"))
end
if audio_path !== nothing
audio_data = read(audio_path, Vector{UInt8})
push!(payloads, ("user_audio", audio_data, "audio"))
end
env = NATSBridge.smartsend(
SUBJECT,
payloads,
nats_url = NATS_URL,
fileserver_url = FILESERVER_URL,
fileserverUploadHandler = plik_upload_handler,
size_threshold = 1_000_000,
correlation_id = string(uuid4()),
msg_purpose = "chat",
sender_name = "user-1"
)
println("Message sent with correlation ID: $(env.correlationId)")
end
function receive_chat_messages()
function message_handler(msg::NATS.Msg)
payloads = NATSBridge.smartreceive(
msg,
max_retries = 5,
base_delay = 100,
max_delay = 5000
)
println("\n--- New Message ---")
for (dataname, data, data_type) in payloads
if data_type == "text"
println("Text: $data")
elseif data_type == "image"
filename = "received_$dataname.bin"
write(filename, data)
println("Image saved: $filename")
elseif data_type == "audio"
filename = "received_$dataname.bin"
write(filename, data)
println("Audio saved: $filename")
elseif data_type == "table"
println("Table received:")
data = DataFrame(data)
show(data)
end
end
end
NATS.subscribe(SUBJECT) do msg
message_handler(msg)
end
println("Subscribed to: $SUBJECT")
end
function run_interactive_chat()
println("\n=== Interactive Chat ===")
println("1. Send a message")
println("2. Join a chat room")
println("3. Exit")
while true
print("\nSelect option (1-3): ")
choice = readline()
if choice == "1"
print("Enter message text: ")
text = readline()
send_chat_message(text)
elseif choice == "2"
receive_chat_messages()
elseif choice == "3"
break
end
end
end
end # module
# Run the chat app
using .ChatApp
ChatApp.run_interactive_chat()
```
## Step 10: Testing the Chat System
### Test Scenario 1: Text-Only Chat
```bash
# Terminal 1: Start the chat receiver
julia test_julia_to_julia_text_receiver.jl
# Terminal 2: Send a message
julia test_julia_to_julia_text_sender.jl
```
### Test Scenario 2: Image Chat
```bash
# Terminal 1: Receive messages
julia test_julia_to_julia_mix_payloads_receiver.jl
# Terminal 2: Send image
julia test_julia_to_julia_mix_payload_sender.jl
```
### Test Scenario 3: Large File Transfer
```bash
# Terminal 2: Send large file
julia test_julia_to_julia_mix_payload_sender.jl
```
## Conclusion
This walkthrough demonstrated how to build a chat system using NATSBridge.jl with support for:
- Text messages
- Images (direct transport for small, link transport for large)
- Audio files
- Video files
- Tabular data (DataFrames)
- Bidirectional communication
- Mixed-content messages
The key takeaways are:
1. **Always wrap payloads in a list** - Even for single payloads: `[("dataname", data, "type")]`
2. **Use appropriate transport** - NATSBridge automatically handles size-based routing
3. **Support mixed content** - Multiple payloads of different types in one message
4. **Handle errors** - Implement proper error handling for network failures
5. **Use correlation IDs** - Track messages across distributed systems
For more information, see:
- [`docs/architecture.md`](./docs/architecture.md) - Detailed architecture documentation
- [`docs/implementation.md`](./docs/implementation.md) - Implementation details