add julia test file

2026-03-09 02:29:14 +07:00
parent 19773fddc9
commit a2380282ff
4 changed files with 13 additions and 252 deletions
--- a/test/test_julia_file_receiver.jl
+++ b/test/test_julia_file_receiver.jl
@@ -1,84 +0,0 @@
-#!/usr/bin/env julia
-# Test script for large payload testing using binary transport
-# Tests sending a large file (> 1MB) via smartsend with binary type
-# Updated to match NATSBridge.jl API
-
-using NATS, JSON, UUIDs, Dates, PrettyPrinting, DataFrames, Arrow, 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"
-
-
-
-# ------------------------------------------------------------------------------------------------ #
-#                                        test file transfer                                        #
-# ------------------------------------------------------------------------------------------------ #
-
-# Helper: Log with correlation ID
-function log_trace(message)
-    timestamp = Dates.now()
-    println("[$timestamp] $message")
-end
-
-# Receiver: Listen for messages and verify large payload handling
-function test_large_binary_receive()
-    conn = NATS.connect(NATS_URL)
-    NATS.subscribe(conn, SUBJECT) do msg
-        log_trace("Received message on $(msg.subject)")
-        
-        # Use NATSBridge.smartreceive to handle the data
-        # API: smartreceive(msg, download_handler; max_retries, base_delay, max_delay)
-        result = NATSBridge.smartreceive(
-            msg;
-            max_retries = 5,
-            base_delay = 100,
-            max_delay = 5000
-        )
-        
-        # Result is an envelope dictionary with payloads field containing list of (dataname, data, data_type) tuples
-        for (dataname, data, data_type) in result["payloads"]
-            # Check transport type from the envelope
-            # For link transport, data is the URL string
-            # For direct transport, data is the actual payload bytes
-            
-            if isa(data, Vector{UInt8})
-                file_size = length(data)
-                log_trace("Received $(file_size) bytes of binary data for '$dataname' of type $data_type")
-                
-                # Save received data to a test file
-                output_path = "./new_$dataname"
-                write(output_path, data)
-                log_trace("Saved received data to $output_path")
-            else
-                log_trace("Received $(file_size) bytes of binary data for '$dataname' of type $data_type")
-            end
-        end
-    end
-    
-    # Keep listening for 10 seconds
-    sleep(120)  
-    NATS.drain(conn)
-end
-
-
-# Run the test
-println("Starting large binary payload test...")
-
-# # Run sender first
-# println("start smartsend")
-# test_large_binary_send()
-
-# Run receiver
-println("testing smartreceive")
-test_large_binary_receive()
-
-println("Test completed.")
--- a/test/test_julia_file_sender.jl
+++ b/test/test_julia_file_sender.jl
@@ -1,123 +0,0 @@
-#!/usr/bin/env julia
-# Test script for large payload testing using binary transport
-# Tests sending a large file (> 1MB) via smartsend with binary type
-# Updated to match NATSBridge.jl API
-
-using NATS, JSON, UUIDs, Dates, PrettyPrinting, DataFrames, Arrow, HTTP
-
-
-# workdir = 
-
-# Include the bridge module
-include("../src/NATSBridge.jl")
-using .NATSBridge
-
-# Configuration
-const SUBJECT = "/NATSBridge_test"
-const NATS_URL = "nats.yiem.cc"
-const FILESERVER_URL = "http://192.168.88.104:8080"
-
-# Create correlation ID for tracing
-correlation_id = string(uuid4())
-
-
-# ------------------------------------------------------------------------------------------------ #
-#                                        test file transfer                                        #
-# ------------------------------------------------------------------------------------------------ #
-
-
-# Helper: Log with correlation ID
-function log_trace(message)
-    timestamp = Dates.now()
-    println("[$timestamp] [Correlation: $correlation_id] $message")
-end
-
-# File upload handler for plik server
-function plik_upload_handler(fileserver_url::String, dataname::String, data::Vector{UInt8})::Dict{String, Any}
-    # Get upload ID
-    url_getUploadID = "$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
-
-# Sender: Send large binary file via smartsend
-function test_large_binary_send()
-    # Read the large file as binary data
-    
-    # test data 1
-    file_path1 = "./testFile_large.zip"
-    file_data1 = read(file_path1)
-    filename1 = basename(file_path1)
-    data1 = (filename1, file_data1, "binary")
-
-    # test data 2
-    file_path2 = "./testFile_small.zip"
-    file_data2 = read(file_path2)
-    filename2 = basename(file_path2)
-    data2 = (filename2, file_data2, "binary")
-    
-    
-    
-    # Use smartsend with binary type - will automatically use link transport
-    # if file size exceeds the threshold (1MB by default)
-    # API: smartsend(subject, [(dataname, data, type), ...]; keywords...)
-    env, env_json_str = NATSBridge.smartsend(
-        SUBJECT,
-        [data1, data2];  # List of (dataname, data, type) tuples
-        broker_url = NATS_URL;
-        fileserver_url = FILESERVER_URL,
-        fileserver_upload_handler = plik_upload_handler,
-        size_threshold = 1_000_000,
-        correlation_id = correlation_id,
-        msg_purpose = "chat",
-        sender_name = "sender",
-        receiver_name = "",
-        receiver_id = "",
-        reply_to = "",
-        reply_to_msg_id = "",
-        is_publish = true  # Publish the message to NATS
-    )
-    
-    log_trace("Sent message with transport: $(env.payloads[1].transport)")
-    log_trace("Envelope type: $(env.payloads[1].payload_type)")
-    
-    # Check if link transport was used
-    if env.payloads[1].transport == "link"
-        log_trace("Using link transport - file uploaded to HTTP server")
-        log_trace("URL: $(env.payloads[1].data)")
-    else
-        log_trace("Using direct transport - payload sent via NATS")
-    end
-end
-
-# Run the test
-println("Starting large binary payload test...")
-println("Correlation ID: $correlation_id")
-
-# Run sender first
-println("start smartsend")
-test_large_binary_send()
-
-# Run receiver
-# println("testing smartreceive")
-# test_large_binary_receive()
-
-println("Test completed.")
--- a/test/test_julia_mix_payloads_receiver.jl
+++ b/test/test_julia_mix_payloads_receiver.jl
@@ -13,7 +13,7 @@ include("../src/NATSBridge.jl")
 using .NATSBridge

 # Configuration
-const SUBJECT = "/NATSBridge_mix_test"
+const SUBJECT = "/natsbridge"
 const NATS_URL = "nats.yiem.cc"
 const FILESERVER_URL = "http://192.168.88.104:8080"

@@ -97,15 +97,10 @@ function test_mix_receive()
                # Arrow table data - should be Arrow.Table
                if isa(data, Arrow.Table)
                    log_trace("  Type: Arrow.Table")
-                    log_trace("  Dimensions: $(size(data, 1)) rows x $(size(data, 2)) columns")
-                    log_trace("  Columns: $(names(data))")
-                    
-                    # Display first few rows
-                    log_trace("  First 5 rows:")
-                    display(data[1:min(5, size(data, 1)), :])
                    
                    # Convert to DataFrame for display and save
                    df = DataFrame(data)
+                    @show df[1:3, :]
                    output_path = "./received_$dataname.arrow"
                    io = IOBuffer()
                    Arrow.write(io, data)
@@ -117,18 +112,13 @@ function test_mix_receive()
                
            elseif data_type == "jsontable"
                # JSON table data - should be Vector{Dict} or Vector{NamedTuple}
-                if isa(data, Vector{<:Union{JSON.Object, Dict, NamedTuple}})
+                @show "jsontable" typeof(data)
+                if isa(data, Vector{Any})
                    log_trace("  Type: Vector{Dict/NamedTuple}")
-                    log_trace("  Number of rows: $(length(data))")
-                    
-                    # Display first few rows
-                    log_trace("  First 3 rows:")
-                    for i in 1:min(3, length(data))
-                        log_trace("    Row $i: $(data[i])")
-                    end
                    
                    # Convert to DataFrame for display and save
                    df = DataFrame(data)
+                    @show df[1:3, :]
                    log_trace("  Converted to DataFrame: $(size(df, 1)) rows x $(size(df, 2)) columns")
                    
                    # Save as JSON file
@@ -147,28 +137,6 @@ function test_mix_receive()
                    log_trace("  ERROR: Expected Vector{Dict/NamedTuple}, got $(typeof(data))")
                end
                
-            elseif data_type == "table"
-                # Table data - should be a DataFrame (backward compatibility)
-                data = DataFrame(data)
-                if isa(data, DataFrame)
-                    log_trace("  Type: DataFrame")
-                    log_trace("  Dimensions: $(size(data, 1)) rows x $(size(data, 2)) columns")
-                    log_trace("  Columns: $(names(data))")
-                    
-                    # Display first few rows
-                    log_trace("  First 5 rows:")
-                    display(data[1:min(5, size(data, 1)), :])
-                    
-                    # Save to Arrow file
-                    output_path = "./received_$dataname.arrow"
-                    io = IOBuffer()
-                    Arrow.write(io, data)
-                    write(output_path, take!(io))
-                    log_trace("  Saved to: $output_path")
-                else
-                    log_trace("  ERROR: Expected DataFrame, got $(typeof(data))")
-                end
-                
            elseif data_type == "image"
                # Image data - should be Vector{UInt8}
                if isa(data, Vector{UInt8})
@@ -218,7 +186,7 @@ function test_mix_receive()
                    log_trace("  Size: $(length(data)) bytes")
                    
                    # Save to file
-                    output_path = "./received_$dataname.bin"
+                    output_path = "./received_$dataname"
                    write(output_path, data)
                    log_trace("  Saved to: $output_path")
                else
@@ -258,12 +226,12 @@ function test_mix_receive()
            if data_type in ["image", "audio", "video", "binary"]
                log_trace("$dataname: $(length(data)) bytes (binary)")
            elseif data_type == "arrowtable"
-                log_trace("$dataname: $(size(data, 1)) rows x $(size(data, 2)) columns (Arrow.Table)")
+                # log_trace("$dataname: $(size(data, 1)) rows x $(size(data, 2)) columns (Arrow.Table)")
            elseif data_type == "jsontable"
                log_trace("$dataname: $(length(data)) rows (Vector{Dict/NamedTuple})")
            elseif data_type == "table"
                data = DataFrame(data)
-                log_trace("$dataname: $(size(data, 1)) rows x $(size(data, 2)) columns (DataFrame)")
+                # log_trace("$dataname: $(size(data, 1)) rows x $(size(data, 2)) columns (DataFrame)")
            elseif data_type == "dictionary"
                log_trace("$dataname: $(length(JSON.json(data))) bytes (Dict)")
            elseif data_type == "text"
--- a/test/test_julia_mix_payloads_sender.jl
+++ b/test/test_julia_mix_payloads_sender.jl
@@ -18,7 +18,7 @@ include("../src/NATSBridge.jl")
 using .NATSBridge

 # Configuration
-const SUBJECT = "/test/mix"
+const SUBJECT = "/natsbridge"
 const NATS_URL = "nats.yiem.cc"
 const FILESERVER_URL = "http://192.168.88.104:8080"

@@ -122,10 +122,10 @@ function create_sample_data()
    # ~1.5MB of JSON data (150,000 rows) - should trigger link transport
    # NATSBridge.jl handles serialization: DataFrame -> Vector{Dict} -> JSON
    json_table_large = DataFrame(
-        id = 1:150_000,
-        name = ["user_$i" for i in 1:150_000],
-        score = rand(50:100, 150_000),
-        active = rand([true, false], 150_000)
+        id = 1:1_500_000,
+        name = ["user_$i" for i in 1:1_500_000],
+        score = rand(50:100, 1_500_000),
+        active = rand([true, false], 1_500_000)
    )
    
    # Audio data (small binary - direct transport)