logos-blockchain-simulations/simlib/blendnet-sims/scripts/batch.py

import csv
import json
import os
import subprocess
from collections import OrderedDict
from dataclasses import asdict

import latency
import mixlog

STEP_DURATION_MS = 50


def bandwidth_result(log_path: str) -> dict[str, float]:
    max_step_id = 0
    for _, json_msg in mixlog.get_input_stream(log_path):
        if (step_id := json_msg.get("step_id")) is not None:
            max_step_id = max(max_step_id, step_id)

    with open(log_path, "r") as file:
        for line in file:
            if "total_outbound_bandwidth" in line:
                line = line[line.find("{") :]
                line = line.replace("{ ", '{"')
                line = line.replace(": ", '": ')
                line = line.replace(", ", ', "')
                record = json.loads(line)

                elapsed = (max_step_id * STEP_DURATION_MS) / 1000.0
                return {
                    "min": float(record["min_node_total_bandwidth"]) / elapsed,
                    "avg": float(record["avg_node_total_bandwidth"]) / elapsed,
                    "max": float(record["max_node_total_bandwidth"]) / elapsed,
                }

    raise Exception("No bandwidth data found in log file")


def topology_result(log_path: str) -> dict[str, int]:
    for topic, json_msg in mixlog.get_input_stream(log_path):
        if topic == "Topology":
            return json_msg
    raise Exception("No topology found in log file")


# Read the CSV data
csv_data = []
with open("params.csv", mode="r") as csvfile:  # Replace with your CSV file name
    reader = csv.DictReader(csvfile, delimiter=",")
    csv_data = list(reader)

# Read the original blendnet.json
with open("../config/blendnet.json", "r") as jsonfile:
    original_json = json.load(jsonfile)

# Directory to save modified JSON files
output_dir = "modified_configs"
os.makedirs(output_dir, exist_ok=True)

# Modify and save JSON files for each row in CSV
config_paths = []
for idx, row in enumerate(csv_data):
    modified_json = OrderedDict(original_json)  # Preserve original field order

    # Apply modifications
    modified_json["network_settings"]["regions"]["north america"] = 0.0
    modified_json["network_settings"]["regions"]["europe"] = 1.0
    modified_json["network_settings"]["regions"]["asia"] = 0.0
    modified_json["step_time"] = f"{STEP_DURATION_MS}ms"
    modified_json["node_count"] = int(row["network_size"])
    modified_json["wards"][0]["sum"] = 1000
    modified_json["connected_peers_count"] = int(row["peering_degree"])
    modified_json["data_message_lottery_interval"] = "20s"
    modified_json["stake_proportion"] = 0.0
    modified_json["persistent_transmission"]["max_emission_frequency"] = 1.0
    modified_json["persistent_transmission"]["drop_message_probability"] = 0.0
    modified_json["epoch_duration"] = (
        f"{int(row['cover_slots_per_epoch']) * int(row['cover_slot_duration'])}s"
    )
    modified_json["slots_per_epoch"] = int(row["cover_slots_per_epoch"])
    modified_json["slot_duration"] = f"{row['cover_slot_duration']}s"
    modified_json["max_delay_seconds"] = int(row["max_temporal_delay"])
    modified_json["number_of_hops"] = int(row["blend_hops"])
    modified_json["number_of_blend_layers"] = int(row["blend_hops"])

    # Save modified JSON
    output_path = os.path.join(output_dir, f"{idx}.json")
    with open(output_path, "w") as outfile:
        json.dump(modified_json, outfile, indent=2)
        print("Saved modified JSON to:", output_path)
    config_paths.append(output_path)

# Directory to save logs
log_dir = "logs"
os.makedirs(log_dir, exist_ok=True)

log_paths = []
for idx, config_path in enumerate(config_paths):
    log_path = f"{log_dir}/{idx}.log"
    with open(log_path, "w") as log_file:
        print(f"Running simulation-{idx}: {log_file.name} with config: {config_path}")
        subprocess.run(
            ["../../target/release/blendnet-sims", "--input-settings", config_path],
            stdout=log_file,
        )
        print(f"Simulation-{idx} completed: {log_file.name}")
    log_paths.append(log_path)


print("Analyzing logs...")
print("=================")
print(
    "network_diameter,msg_count,min_latency_msg_id,max_latency_msg_id,min_latency,avg_latency,median_latency,max_latency,min_bandwidth_kbps,avg_bandwidth_kbps,max_bandwidth_kbps"
)
for idx, log_path in enumerate(log_paths):
    network_diameter = topology_result(log_path)["diameter"]
    message_stroage = latency.parse_record_stream(mixlog.get_input_stream(log_path))
    with open(f"{log_dir}/msgs-{idx}.json", "w") as file:
        json.dump(
            {msg_id: asdict(msg) for msg_id, msg in message_stroage.items()},
            file,
            indent=2,
        )

    latency_res = latency.compute_results(message_stroage, STEP_DURATION_MS)
    msg_count = latency_res["total_complete_messages"]
    min_latency = float(latency_res["min_latency_ms"]) / 1000.0
    min_latency_msg_id = latency_res["min_latency_message_id"]
    avg_latency = float(latency_res["latency_average_ms"]) / 1000.0
    median_latency = float(latency_res["latency_median_ms"]) / 1000.0
    max_latency = float(latency_res["max_latency_ms"]) / 1000.0
    max_latency_msg_id = latency_res["max_latency_message_id"]

    bandwidth_res = bandwidth_result(log_path)
    min_bandwidth_kpbs = bandwidth_res["min"] * 8 / 1000.0
    avg_bandwidth_kpbs = bandwidth_res["avg"] * 8 / 1000.0
    max_bandwidth_kpbs = bandwidth_res["max"] * 8 / 1000.0

    print(
        f"{network_diameter},{msg_count},{min_latency_msg_id},{max_latency_msg_id},{min_latency},{avg_latency},{median_latency},{max_latency},{min_bandwidth_kpbs},{avg_bandwidth_kpbs},{max_bandwidth_kpbs}"
    )