#!/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.")