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narawat
2026-02-19 11:23:15 +07:00
parent 9ea9d55eee
commit 51e494c48b
10 changed files with 74 additions and 939 deletions
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176
etc.jl
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@@ -1,168 +1,18 @@
using JSON
d = Dict(
"name"=>"ton",
"age"=> 20,
"metadata" => Dict(
"height"=> 155,
"wife"=> "jane"
)
)
using Revise
using NATS, JSON, UUIDs, Dates
using HTTP
# workdir =
# Include the bridge module
include("./src/NATSBridge.jl")
using .NATSBridge
# Configuration
const SUBJECT = "/NATSBridge_test"
const NATS_URL = "nats.yiem.cc"
const FILESERVER_URL = "http://192.168.88.104:8080"
# Create correlation ID for tracing
correlation_id = string(uuid4())
# ------------------------------------------------------------------------------------------------ #
# test file transfer #
# ------------------------------------------------------------------------------------------------ #
# File path for large binary payload test
const FILE_PATH = "./testFile_small.zip"
const filename = basename(FILE_PATH)
# Helper: Log with correlation ID
function log_trace(message)
timestamp = Dates.now()
println("[$timestamp] [Correlation: $correlation_id] $message")
end
function _serialize_data(data::Any, type::String)
if type == "text" # Text data - convert to UTF-8 bytes
if isa(data, String)
return bytes(data) # Convert string to UTF-8 bytes
else
error("Text data must be a String")
end
elseif type == "dictionary" # JSON data - serialize directly
json_str = JSON.json(data) # Convert Julia data to JSON string
return bytes(json_str) # Convert JSON string to bytes
elseif type == "table" # Table data - convert to Arrow IPC stream
io = IOBuffer() # Create in-memory buffer
Arrow.write(io, data) # Write data as Arrow IPC stream to buffer
return take!(io) # Return the buffer contents as bytes
elseif type == "image" # Image data - treat as binary
if isa(data, Vector{UInt8})
return data # Return binary data directly
else
error("Image data must be Vector{UInt8}")
end
elseif type == "audio" # Audio data - treat as binary
if isa(data, Vector{UInt8})
return data # Return binary data directly
else
error("Audio data must be Vector{UInt8}")
end
elseif type == "video" # Video data - treat as binary
if isa(data, Vector{UInt8})
return data # Return binary data directly
else
error("Video data must be Vector{UInt8}")
end
elseif type == "binary" # Binary data - treat as binary
if isa(data, IOBuffer) # Check if data is an IOBuffer
return take!(data) # Return buffer contents as bytes
elseif isa(data, Vector{UInt8}) # Check if data is already binary
return data # Return binary data directly
else # Unsupported binary data type
error("Binary data must be binary (Vector{UInt8} or IOBuffer)")
end
else # Unknown type
error("Unknown type: $type")
end
end
# File upload handler for plik server
function plik_upload_handler(fileserver_url::String, dataname::String, data::Vector{UInt8})::Dict{String, Any}
# Get upload ID
url_getUploadID = "$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"]
# Upload file
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 log_trace(correlation_id::String, message::String)
timestamp = Dates.now() # Get current timestamp
@info "[$timestamp] [Correlation: $correlation_id] $message" # Log formatted message
end
file_data = read(FILE_PATH)
file_size = length(file_data)
subject::String=SUBJECT
data::AbstractArray{Tuple{String, Array{UInt8, 1}, String}, 1}=[(filename, file_data, "binary")]
nats_url::String=DEFAULT_NATS_URL
fileserver_url::String=DEFAULT_FILESERVER_URL
fileserverUploadHandler::Function=plik_upload_handler
size_threshold::Int=1_000_000
correlation_id::Union{String, Nothing}=correlation_id
msg_purpose::String="chat"
sender_name::String="sender"
receiver_name::String="receiver_name"
receiver_id::String="receiver_id"
reply_to::String="reply_to"
reply_to_msg_id::String="reply_to_msg_id"
(dataname, payload_data, payload_type) = data[1]
payload_bytes = _serialize_data(payload_data, payload_type)
payload_size = length(payload_bytes) # Calculate payload size in bytes
log_trace(cid, "Serialized payload '$dataname' (type: $payload_type) size: $payload_size bytes") # Log payload size
payload_b64 = Base64.base64encode(payload_bytes) # Encode bytes as base64 string
log_trace(cid, "Using direct transport for $payload_size bytes")
payload = msgPayload_v1(
id = string(uuid4()),
dataname = dataname,
type = payload_type,
transport = "direct",
encoding = "base64",
size = payload_size,
data = payload_b64,
metadata = Dict("payload_bytes" => payload_size)
)
push!(payloads, payload)
json_str = JSON.json(d)
json_str_bytes = Vector{UInt8}(json_str)
json_str_2 = String(json_str_bytes)
json_obj = JSON.parse(json_str_2)

104
src/NATSBridge.jl
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@@ -457,48 +457,66 @@ binary_bytes_direct = _serialize_data(UInt8[1, 2, 3], "binary")
```
"""
function _serialize_data(data::Any, type::String)
if type == "text" # Text data - convert to UTF-8 bytes
if isa(data, String)
return bytes(data) # Convert string to UTF-8 bytes
else
error("Text data must be a String")
end
elseif type == "dictionary" # JSON data - serialize directly
json_str = JSON.json(data) # Convert Julia data to JSON string
return bytes(json_str) # Convert JSON string to bytes
elseif type == "table" # Table data - convert to Arrow IPC stream
io = IOBuffer() # Create in-memory buffer
Arrow.write(io, data) # Write data as Arrow IPC stream to buffer
return take!(io) # Return the buffer contents as bytes
elseif type == "image" # Image data - treat as binary
if isa(data, Vector{UInt8})
return data # Return binary data directly
else
error("Image data must be Vector{UInt8}")
end
elseif type == "audio" # Audio data - treat as binary
if isa(data, Vector{UInt8})
return data # Return binary data directly
else
error("Audio data must be Vector{UInt8}")
end
elseif type == "video" # Video data - treat as binary
if isa(data, Vector{UInt8})
return data # Return binary data directly
else
error("Video data must be Vector{UInt8}")
end
elseif type == "binary" # Binary data - treat as binary
if isa(data, IOBuffer) # Check if data is an IOBuffer
return take!(data) # Return buffer contents as bytes
elseif isa(data, Vector{UInt8}) # Check if data is already binary
return data # Return binary data directly
else # Unsupported binary data type
error("Binary data must be binary (Vector{UInt8} or IOBuffer)")
end
else # Unknown type
error("Unknown type: $type")
end
""" Example on how JSON.jl convert: dictionary -> json string -> json string bytes -> json string -> json object
d = Dict(
"name"=>"ton",
"age"=> 20,
"metadata" => Dict(
"height"=> 155,
"wife"=> "jane"
)
)
json_str = JSON.json(d)
json_str_bytes = Vector{UInt8}(json_str)
json_str_2 = String(json_str_bytes)
json_obj = JSON.parse(json_str_2)
"""
if type == "text" # Text data - convert to UTF-8 bytes
if isa(data, String)
data_bytes = Vector{UInt8}(data) # Convert string to UTF-8 bytes
return data_bytes
else
error("Text data must be a String")
end
elseif type == "dictionary" # JSON data - serialize directly
json_str = JSON.json(data) # Convert Julia data to JSON string
json_str_bytes = Vector{UInt8}(json_str) # Convert JSON string to bytes
return json_str_bytes
elseif type == "table" # Table data - convert to Arrow IPC stream
io = IOBuffer() # Create in-memory buffer
Arrow.write(io, data) # Write data as Arrow IPC stream to buffer
return take!(io) # Return the buffer contents as bytes
elseif type == "image" # Image data - treat as binary
if isa(data, Vector{UInt8})
return data # Return binary data directly
else
error("Image data must be Vector{UInt8}")
end
elseif type == "audio" # Audio data - treat as binary
if isa(data, Vector{UInt8})
return data # Return binary data directly
else
error("Audio data must be Vector{UInt8}")
end
elseif type == "video" # Video data - treat as binary
if isa(data, Vector{UInt8})
return data # Return binary data directly
else
error("Video data must be Vector{UInt8}")
end
elseif type == "binary" # Binary data - treat as binary
if isa(data, IOBuffer) # Check if data is an IOBuffer
return take!(data) # Return buffer contents as bytes
elseif isa(data, Vector{UInt8}) # Check if data is already binary
return data # Return binary data directly
else # Unsupported binary data type
error("Binary data must be binary (Vector{UInt8} or IOBuffer)")
end
else # Unknown type
error("Unknown type: $type")
end
end
@@ -675,7 +693,7 @@ function _deserialize_data(
return String(data) # Convert bytes to string
elseif type == "dictionary" # JSON data - deserialize
json_str = String(data) # Convert bytes to string
return JSON.parse(json_str) # Parse JSON string to Julia data structure
return JSON.parse(json_str) # Parse JSON string to JSON object
elseif type == "table" # Table data - deserialize Arrow IPC stream
io = IOBuffer(data) # Create buffer from bytes
df = Arrow.Table(io) # Read Arrow IPC format from buffer

97
test/julia_to_julia_dict_receiver.jl
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@@ -1,97 +0,0 @@
#!/usr/bin/env julia
# Test script for dictionary transfer from Julia serviceA to Julia serviceB
# Demonstrates the "Command & Control" scenario (small dictionary) using NATSBridge
#
# This is serviceB - the receiver that receives a dummy dictionary from serviceA
using UUIDs
using JSON
using Dates
# Include the NATSBridge module
include("../src/NATSBridge.jl")
# Configuration
const SUBJECT = "/NATSBridge_dict_test"
const NATS_URL = "nats.yiem.cc"
# Helper: Log with correlation ID
function log_trace(correlation_id::String, message::String)
timestamp = Dates.now()
println("[$timestamp] [Correlation: $correlation_id] $message")
end
# Receiver: Receive and process dictionary from serviceA
function receive_dictionary()
# Connect to NATS
conn = NATS.connect(NATS_URL)
# Subscribe to the subject
subscription = NATS.subscribe(conn, SUBJECT)
println("Listening for dictionary messages on '$SUBJECT'...")
println("Press Ctrl+C to stop listening.")
# Listen for messages
while true
# Wait for a message with a 1-second timeout
msg = NATS.waitfor(subscription, 1.0)
if msg !== nothing
# Extract correlation ID for logging
json_data = JSON.parse(String(msg.payload))
cid = json_data["correlationId"]
log_trace(cid, "Received message from $(json_data["senderName"])")
# Process the message using smartreceive
payloads = NATSBridge.smartreceive(
msg;
fileserverDownloadHandler = (url, max_retries, base_delay, max_delay, cid) ->
NATSBridge._fetch_with_backoff(url, max_retries, base_delay, max_delay, cid),
max_retries = 5,
base_delay = 100,
max_delay = 5000
)
log_trace(cid, "Processed $(length(payloads)) payload(s)")
# Process each payload
for (dataname, data, payload_type) in payloads
log_trace(cid, "Payload '$dataname' type: $payload_type")
# Handle dictionary type
if payload_type == "dictionary"
println("\nReceived dictionary:")
println(JSON.json(data, 2))
# Extract and display specific fields
if isa(data, Dict)
command = get(data, "command", "unknown")
println("\nCommand: $command")
# Optionally send acknowledgment
reply_to = get(json_data, "replyTo", "")
if !isempty(reply_to)
log_trace(cid, "Reply to: $reply_to")
# Could send ACK here
end
end
else
println("\nReceived non-dictionary payload: $dataname (type: $payload_type)")
end
end
end
end
end
# Run the receiver
println("Starting dictionary receiver...")
println("Subject: $SUBJECT")
println("NATS URL: $NATS_URL")
println("="^50)
# Run receiver (this will block and listen for messages)
receive_dictionary()

90
test/julia_to_julia_dict_sender.jl
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@@ -1,90 +0,0 @@
#!/usr/bin/env julia
# Test script for dictionary transfer from Julia serviceA to Julia serviceB
# Demonstrates the "Command & Control" scenario (small dictionary) using NATSBridge
#
# This is serviceA - the sender that sends a dummy dictionary to serviceB
using UUIDs
using JSON
using Dates
# Include the NATSBridge module
include("../src/NATSBridge.jl")
# Configuration
const SUBJECT = "/NATSBridge_dict_test"
const NATS_URL = "nats.yiem.cc"
const FILESERVER_URL = "http://192.168.88.104:8080"
# Create correlation ID for tracing
correlation_id = string(uuid4())
# ------------------------------------------------------------------------------------------------ #
# dictionary sender #
# ------------------------------------------------------------------------------------------------ #
# Helper: Log with correlation ID
function log_trace(message)
timestamp = Dates.now()
println("[$timestamp] [Correlation: $correlation_id] $message")
end
# Sender: Send a dummy dictionary to serviceB
function send_dictionary()
# Create a dummy dictionary to send
dummy_dict = Dict(
"command" => "start_simulation",
"simulation_id" => string(uuid4()),
"duration_seconds" => 60,
"parameters" => Dict(
"temperature" => 25.5,
"pressure" => 101.3,
"active" => true,
"tags" => ["test", "simulation", "julia_to_julia"]
),
"metadata" => Dict(
"sender" => "serviceA",
"timestamp" => string(Dates.now())
)
)
# Send the dictionary using smartsend with type="dictionary"
# API: smartsend(subject, [(dataname, data, type), ...]; keywords...)
env = NATSBridge.smartsend(
SUBJECT,
[("dummy_dict", dummy_dict, "dictionary")], # List of (dataname, data, type) tuples
nats_url = NATS_URL,
fileserver_url = FILESERVER_URL,
size_threshold = 1_000_000, # 1MB threshold - dictionary will use direct transport
correlation_id = correlation_id,
msg_purpose = "chat",
sender_name = "serviceA",
receiver_name = "serviceB",
reply_to = "",
reply_to_msg_id = ""
)
log_trace("Sent dictionary via $(env.payloads[1].transport) transport")
log_trace("Payload type: $(env.payloads[1].type)")
log_trace("Envelope correlationId: $(env.correlationId)")
# Display the sent dictionary
println("\nSent dictionary content:")
println(JSON.json(dummy_dict, 2))
end
# Run the test
println("Starting dictionary transfer test...")
println("Correlation ID: $correlation_id")
println("Subject: $SUBJECT")
println("NATS URL: $NATS_URL")
# Run sender
println("\n--- Sending dictionary ---")
send_dictionary()
println("\nTest completed.")

131
test/julia_to_julia_mix_payload_receiver.jl
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@@ -1,131 +0,0 @@
using NATSBridge
using UUIDs
using JSON
using DataFrames
using Dates
# Include the NATSBridge module
include("src/NATSBridge.jl")
# Constants
const NATS_URL = "nats://localhost:4222"
const FILESERVER_URL = "http://localhost:8080"
# Main chat receiver function for scenario 6
function chat_receiver(
subject::String = "/chat/test";
nats_url::String = NATS_URL,
fileserver_url::String = FILESERVER_URL,
duration::Int = 60, # Duration in seconds to listen for messages
max_messages::Int = 100 # Maximum number of messages to receive
)
println("\n=== Chat Receiver (ServiceB) ===")
println("Subject: $subject")
println("NATS URL: $nats_url")
println("Fileserver URL: $fileserver_url")
println("Listening duration: $(duration)s")
println("Max messages: $max_messages")
println("="^50)
# Create a handler for the fileserver download
# This will be passed to smartreceive as fileserverDownloadHandler parameter
fileserverDownloadHandler = (url, max_retries, base_delay, max_delay, correlation_id) ->
NATSBridge._fetch_with_backoff(url, max_retries, base_delay, max_delay, correlation_id)
# Connect to NATS and subscribe to the chat subject
conn = NATS.connect(nats_url)
# Track received messages
message_count = 0
total_payloads = 0
# Subscribe to the subject
subscription = NATS.subscribe(conn, subject)
@info "Listening for chat messages on '$subject'..."
# Listen for messages for the specified duration
timeout = time() + duration
while time() < timeout && message_count < max_messages
# Wait for a message with a short timeout
msg = NATS.waitfor(subscription, 1.0) # 1 second timeout
if msg !== nothing
message_count += 1
println("\n--- Message $(message_count) Received ---")
# Process the message using smartreceive
payloads = NATSBridge.smartreceive(
msg;
fileserverDownloadHandler = fileserverDownloadHandler,
max_retries = 5,
base_delay = 100,
max_delay = 5000
)
println("Payloads received: $(length(payloads))")
total_payloads += length(payloads)
# Process each payload
for (dataname, data, payload_type) in payloads
println(" - $dataname (type: $payload_type)")
# Handle different types differently for display
if payload_type == "text"
println(" Text content: $(String(data))")
elseif payload_type == "dictionary"
println(" Dictionary content: $(JSON.json(data, 2))")
elseif payload_type == "table"
println(" Table content: $(size(data, 1)) rows, $(size(data, 2)) columns")
if size(data, 1) <= 10
println(" Sample: $(DataFrames.show(data))")
end
elseif payload_type == "image"
println(" Image: $(length(data)) bytes")
elseif payload_type == "audio"
println(" Audio: $(length(data)) bytes")
elseif payload_type == "video"
println(" Video: $(length(data)) bytes")
elseif payload_type == "binary"
println(" Binary: $(length(data)) bytes")
end
end
# Extract correlation ID from the message
json_data = JSON.parse(String(msg.payload))
println(" Correlation ID: $(json_data["correlationId"])")
println(" Message ID: $(json_data["msgId"])")
# Optional: Send ACK reply
reply_to = get(json_data, "replyTo", "")
if !isempty(reply_to)
println(" Reply to: $reply_to")
# Could send an ACK message here
end
end
end
println("\n=== Chat Receiver Summary ===")
println("Total messages received: $message_count")
println("Total payloads processed: $total_payloads")
println("Average payloads per message: $(round(total_payloads / max(message_count, 1), digits=2))")
println("="^50)
# Cleanup
NATS.drain(conn)
return message_count
end
# Example usage
if abspath(PROGRAM_FILE) == @__FILE__
# Parse command line arguments
if length(ARGS) >= 1
subject = ARGS[1]
else
subject = "/chat/test"
end
chat_receiver(subject)
end

219
test/julia_to_julia_mix_payload_sender.jl
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@@ -1,219 +0,0 @@
using NATSBridge
using UUIDs
using JSON
using DataFrames
using Random
# Include the NATSBridge module
include("src/NATSBridge.jl")
# Constants
const NATS_URL = "nats://localhost:4222"
const FILESERVER_URL = "http://localhost:8080"
# Chat message types for scenario 6
const CHAT_TYPES = ["text", "dictionary", "table", "image", "audio", "video", "binary"]
# Helper function to create sample text data
function create_text_payload()
texts = [
"Hello!",
"How are you doing today?",
"This is a test message.",
"Chat with mixed content is fun!",
"Short text payload."
]
return (rand(texts), "text")
end
# Helper function to create sample dictionary data
function create_dictionary_payload()
dictionaries = [
Dict("greeting" => "Hello", "status" => "active", "count" => 42),
Dict("user" => "alice", "message_id" => string(uuid4()), "timestamp" => Dates.now().iso8601),
Dict("config" => Dict("theme" => "dark", "notifications" => true))
]
return (rand(dictionaries), "dictionary")
end
# Helper function to create sample table data (DataFrame)
function create_table_payload()
# Small DataFrame
df_small = DataFrame(
id = 1:5,
name = ["Alice", "Bob", "Charlie", "Diana", "Eve"],
score = [95, 88, 92, 78, 85],
status = ["active", "active", "inactive", "active", "pending"]
)
# Large DataFrame (> 1MB)
df_large = DataFrame(
id = 1:50000,
name = ["User_$i" for i in 1:50000],
value = rand(50000) .* 100,
status = ["active", "inactive", "pending"][rand(1:3, 50000)]
)
# Randomly choose small or large
return (rand([df_small, df_large]), "table")
end
# Helper function to create sample image data (Vector{UInt8})
function create_image_payload()
# Create random image bytes (small)
small_image = rand(UInt8, 100_000) # ~100KB
# Large image (> 1MB)
large_image = rand(UInt8, 2_000_000) # ~2MB
return (rand([small_image, large_image]), "image")
end
# Helper function to create sample audio data (Vector{UInt8})
function create_audio_payload()
# Create random audio bytes (small)
small_audio = rand(UInt8, 150_000) # ~150KB
# Large audio (> 1MB)
large_audio = rand(UInt8, 3_000_000) # ~3MB
return (rand([small_audio, large_audio]), "audio")
end
# Helper function to create sample video data (Vector{UInt8})
function create_video_payload()
# Create random video bytes (small)
small_video = rand(UInt8, 200_000) # ~200KB
# Large video (> 1MB)
large_video = rand(UInt8, 5_000_000) # ~5MB
return (rand([small_video, large_video]), "video")
end
# Helper function to create sample binary data (Vector{UInt8})
function create_binary_payload()
# Create random binary bytes (small)
small_binary = rand(UInt8, 50_000) # ~50KB
# Large binary (> 1MB)
large_binary = rand(UInt8, 1_500_000) # ~1.5MB
return (rand([small_binary, large_binary]), "binary")
end
# Main chat sender function for scenario 6
function chat_sender(
subject::String = "/chat/test",
num_messages::Int = 10;
nats_url::String = NATS_URL,
fileserver_url::String = FILESERVER_URL
)
println("\n=== Chat Sender (ServiceA) ===")
println("Subject: $subject")
println("Number of messages: $num_messages")
println("NATS URL: $nats_url")
println("Fileserver URL: $fileserver_url")
println("="^50)
# Create a handler for the fileserver upload
# This will be passed to smartsend as fileserverUploadHandler parameter
fileserverUploadHandler = (url, dataname, data) -> NATSBridge.plik_oneshot_upload(url, dataname, data)
for i in 1:num_messages
# Generate random chat message with mixed content
# Each message can have 1-5 payloads with different types
num_payloads = rand(1:5)
# Create payloads list
payloads = Tuple{String, Any, String}[]
# Track if we need to include text (required for chat)
has_text = false
# Create random payloads
for j in 1:num_payloads
# Randomly select a payload type
payload_type = rand(CHAT_TYPES)
# Create the payload based on type
payload_data, payload_type = if payload_type == "text"
create_text_payload()
elseif payload_type == "dictionary"
create_dictionary_payload()
elseif payload_type == "table"
create_table_payload()
elseif payload_type == "image"
create_image_payload()
elseif payload_type == "audio"
create_audio_payload()
elseif payload_type == "video"
create_video_payload()
elseif payload_type == "binary"
create_binary_payload()
end
# Ensure at least one text payload
if payload_type == "text"
has_text = true
end
push!(payloads, ("payload_$j", payload_data, payload_type))
end
# Ensure at least one text payload exists
if !has_text
text_data, text_type = create_text_payload()
push!(payloads, ("message_text", text_data, text_type))
end
# Generate chat message metadata
chat_metadata = Dict(
"message_index" => i,
"timestamp" => Dates.now().iso8601,
"sender" => "serviceA",
"payload_count" => length(payloads)
)
# Send the chat message with mixed content
println("\n--- Message $i ---")
println("Payloads: $(length(payloads))")
for (dataname, data, type) in payloads
println(" - $dataname (type: $type)")
end
env = NATSBridge.smartsend(
subject,
payloads;
nats_url = nats_url,
fileserver_url = fileserver_url,
fileserverUploadHandler = fileserverUploadHandler,
size_threshold = 1_000_000, # 1MB threshold
correlation_id = string(uuid4()),
msg_purpose = "chat",
sender_name = "serviceA",
receiver_name = "serviceB",
reply_to = "/chat/reply",
reply_to_msg_id = ""
)
println("Envelope created with correlationId: $(env.correlationId)")
println("Message published successfully!")
# Wait a bit between messages
sleep(rand(0.1:0.3))
end
println("\n=== Chat Sender Complete ===")
return true
end
# Example usage
if abspath(PROGRAM_FILE) == @__FILE__
# Parse command line arguments
if length(ARGS) >= 2
subject = ARGS[1]
num_messages = parse(Int, ARGS[2])
else
subject = "/chat/test"
num_messages = 5
end
chat_sender(subject, num_messages)
end

99
test/julia_to_julia_table_receiver.jl
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@@ -1,99 +0,0 @@
#!/usr/bin/env julia
# Test script for DataFrame transfer from Julia serviceA to Julia serviceB
# Demonstrates the "Selection" scenario (small Arrow table) using NATSBridge
#
# This is serviceB - the receiver that receives a dummy DataFrame from serviceA
using NATSBridge
using UUIDs
using DataFrames
using JSON
using Dates
# Include the NATSBridge module
include("src/NATSBridge.jl")
# Configuration
const SUBJECT = "/NATSBridge_table_test"
const NATS_URL = "nats://localhost:4222"
# Helper: Log with correlation ID
function log_trace(correlation_id::String, message::String)
timestamp = Dates.now()
println("[$timestamp] [Correlation: $correlation_id] $message")
end
# Receiver: Receive and process DataFrame from serviceA
function receive_dataframe()
# Connect to NATS
conn = NATS.connect(NATS_URL)
# Subscribe to the subject
subscription = NATS.subscribe(conn, SUBJECT)
println("Listening for DataFrame messages on '$SUBJECT'...")
println("Press Ctrl+C to stop listening.")
# Listen for messages
while true
# Wait for a message with a 1-second timeout
msg = NATS.waitfor(subscription, 1.0)
if msg !== nothing
# Extract correlation ID for logging
json_data = JSON.parse(String(msg.payload))
cid = json_data["correlationId"]
log_trace(cid, "Received message from $(json_data["senderName"])")
# Process the message using smartreceive
payloads = NATSBridge.smartreceive(
msg;
fileserverDownloadHandler = (url, max_retries, base_delay, max_delay, cid) ->
NATSBridge._fetch_with_backoff(url, max_retries, base_delay, max_delay, cid),
max_retries = 5,
base_delay = 100,
max_delay = 5000
)
log_trace(cid, "Processed $(length(payloads)) payload(s)")
# Process each payload
for (dataname, data, payload_type) in payloads
log_trace(cid, "Payload '$dataname' type: $payload_type")
# Handle table (DataFrame) type
if payload_type == "table"
println("\nReceived DataFrame:")
println(data)
# Display DataFrame dimensions
println("\nDataFrame dimensions: $(size(data, 1)) rows x $(size(data, 2)) columns")
# Display column names
println("Column names: $(names(data))")
# Optionally send acknowledgment
reply_to = get(json_data, "replyTo", "")
if !isempty(reply_to)
log_trace(cid, "Reply to: $reply_to")
# Could send ACK here
end
else
println("\nReceived non-table payload: $dataname (type: $payload_type)")
end
end
end
end
end
# Run the receiver
println("Starting DataFrame receiver...")
println("Subject: $SUBJECT")
println("NATS URL: $NATS_URL")
println("="^50)
# Run receiver (this will block and listen for messages)
receive_dataframe()

97
test/julia_to_julia_table_sender.jl
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#!/usr/bin/env julia
# Test script for DataFrame transfer from Julia serviceA to Julia serviceB
# Demonstrates the "Selection" scenario (small Arrow table) using NATSBridge
#
# This is serviceA - the sender that sends a dummy DataFrame to serviceB
using NATSBridge
using UUIDs
using DataFrames
using JSON
using Dates
# Include the NATSBridge module
include("src/NATSBridge.jl")
# Configuration
const SUBJECT = "/NATSBridge_table_test"
const NATS_URL = "nats://localhost:4222"
const FILESERVER_URL = "http://localhost:8080"
# Create correlation ID for tracing
correlation_id = string(uuid4())
# ------------------------------------------------------------------------------------------------ #
# DataFrame sender #
# ------------------------------------------------------------------------------------------------ #
# Helper: Log with correlation ID
function log_trace(message)
timestamp = Dates.now()
println("[$timestamp] [Correlation: $correlation_id] $message")
end
# Sender: Send a dummy DataFrame to serviceB
function send_dataframe()
# Create a dummy DataFrame (table) to send
# This simulates a selection scenario where Julia server generates options for user selection
dummy_df = DataFrame(
id = 1:10,
name = ["Option A", "Option B", "Option C", "Option D", "Option E",
"Option F", "Option G", "Option H", "Option I", "Option J"],
score = [95, 88, 92, 78, 85, 90, 87, 93, 89, 91],
category = ["A", "B", "A", "C", "B", "A", "C", "A", "B", "C"],
active = [true, true, false, true, true, false, true, true, true, false]
)
# Calculate approximate size
df_size = sizeof(dummy_df)
log_trace("DataFrame size: $(df_size / 1024) KB")
# Check if DataFrame is small enough for direct transport (< 1MB)
if df_size < 1_000_000
log_trace("Using direct transport (size < 1MB)")
else
log_trace("Using link transport (size >= 1MB)")
end
# Send the DataFrame using smartsend with type="table"
# API: smartsend(subject, [(dataname, data, type), ...]; keywords...)
env = NATSBridge.smartsend(
SUBJECT,
[("selection_table", dummy_df, "table")], # List of (dataname, data, type) tuples
nats_url = NATS_URL,
fileserver_url = FILESERVER_URL,
size_threshold = 1_000_000, # 1MB threshold
correlation_id = correlation_id,
msg_purpose = "chat",
sender_name = "serviceA",
receiver_name = "serviceB",
reply_to = "",
reply_to_msg_id = ""
)
log_trace("Sent DataFrame via $(env.payloads[1].transport) transport")
log_trace("Payload type: $(env.payloads[1].type)")
log_trace("Envelope correlationId: $(env.correlationId)")
# Display the sent DataFrame
println("\nSent DataFrame content:")
println(dummy_df)
end
# Run the test
println("Starting DataFrame transfer test...")
println("Correlation ID: $correlation_id")
println("Subject: $SUBJECT")
println("NATS URL: $NATS_URL")
# Run sender
println("\n--- Sending DataFrame ---")
send_dataframe()
println("\nTest completed.")

0
test/julia_to_julia_file_receiver.jl → test/test_julia_to_julia_file_receiver.jl
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0
test/julia_to_julia_file_sender.jl → test/test_julia_to_julia_file_sender.jl
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