Nguyễn Đức Long oNddleo

+-------------+        +------------+        +--------------+
| Client Apps | <----> | WebSockets | -----> | Chat Service |
+-------------+        +------------+        +--------------+
                                                 |
                                                 v
                                         +----------------+
                                         | Message Service|
                                         +----------------+
                                                 |

Importing net/http/pprof adds HTTP endpoints to serve profile files that can be viewed or charted with a command line tool when the runtime.Set* functions are executed.

1. import pprof into the go program

import _ "net/http/pprof"

If your application is not already running an http or https server, add net/http to the program imports and the following code to the start of the main function:

go http.ListenAndServe(":8550", nil)

Technical summary Ultra Scale Kafka system

Core

Apache Kafka
- Usage: Message broker infrastructure, topic management, partition replication
- Key Components: Kafka Streams API for processing, AdminClient for topic management
Apache Avro

Usage: Schema definition, binary serialization/deserialization

Kafka Event Definition for Order Management in Trading

Here's a comprehensive definition for Kafka events in an order management trading system with hash verification for message producers:

{
  "eventType": "ORDER_CREATED",
  "version": "1.0",
  "timestamp": "2025-03-10T08:45:32.215Z",
 "orderId": "ORD-12345678",

I'll provide you with an example of using the sane_finances library to export S&P Dow Jones Indices (SPDJI) data in Python.

from decimal import Decimal
from datetime import date, datetime
import pandas as pd
from sane_finances.sources.spdji.v2021.exporters import SpdjIndicesExporter
from sane_finances.sources.spdji.v2021.parsers import SpdjIndicesParser

def export_spdji_index(index_code, start_date, end_date, output_file=None):

Detailed Trading System Design

Let's delve deeper into the architecture, data models, and flows for your trading system:

Data Layer: Detailed Design

Database Schema

Market Data (TimescaleDB/InfluxDB)

Architecture Overview

┌─────────────────┐     ┌──────────────┐     ┌─────────────────┐
│  Client Apps    │◄────┤  WebSockets  │────►│  Chat Service   │
└─────────────────┘     └──────────────┘     └────────┬────────┘
                                                      │
                                                      ▼
┌─────────────────┐     ┌──────────────┐     ┌─────────────────┐
│  Group Service  │◄────┤     NATS     │◄────┤ Message Service │

	-- ~/.config/nvim/init.lua
	-- Neovim configuration with snacks.nvim terminal and transparent background

	-- Basic settings
	vim.opt.number = true
	vim.opt.relativenumber = true
	vim.opt.tabstop = 2
	vim.opt.shiftwidth = 2
	vim.opt.expandtab = true
	vim.opt.smartindent = true

	SELECT symbol, close, date
	FROM public.historical_data
	WHERE symbol IN ({placeholders})
	AND date BETWEEN %s::date AND %s::date
	AND close IS NOT NULL
	ORDER BY symbol, date

	watch_stylesheet: true
	watch_config: true
	debug: false # Enable debug mode to see more logs

	# This komorebi setting will be used for tray context menu.
	# If you don't use komorebi, you can remove this section.
	komorebi:
	start_command: "komorebic start --whkd"
	stop_command: "komorebic stop --whkd"
	reload_command: "komorebic reload-configuration"