Python

IPRoyal Rotating Residential IP Proxy in Python IPRoyal’s residential IP pool has 20M+ IPs—the trick is knowing how to use them. Sticky mode (30 min per IP) suits account login scenarios, while rotating mode (new IP per request) excels at web scraping, bulk registration, and anti-detection. This guide implements a complete rotating + retry solution in Python. Two modes explained Mode IP Switch Frequency Use Case Sticky Rotate every 10/30 minutes Account login, API calls, long-running quant sessions Rotating New IP on every request Web scraping, bulk registration, anti-detection IPRoyal’s dashboard lets you generate credentials for both modes. ...

⚠️ Registration Threshold: Pionex doesn’t support KYC for mainland China ID cards. You’ll need a valid ID from Taiwan / Singapore / Malaysia / United States, etc. See Pionex Restricted Regions Official Notice. After running the Pionex grid bot for 4 months, the biggest pain point was no alert when price hits the range boundaries. When price breaks above or below your configured range, the bot stops automatically—but you won’t know when you need to step in (to reconfigure or pause). ...

Managing multiple VPS means one thing: you need to check their status every single day. Disk filling up, services crashing, memory spiking—catch these early or they become production incidents. This post covers a practical solution: Python script SSH’s into each server, collects metrics → Gemini CLI analyzes for anomalies → Telegram Bot sends a daily report. ...

A Quant Strategy Needs More Than Just Code: Building Your Complete Monitoring & Alerting Stack Running a quant strategy requires far more than the strategy itself—you need a full suite of tools to execute it reliably, monitor its state, and get alerted when things go wrong. This post shares my complete tooling setup, from strategy execution through alerts. Overall Architecture Strategy Layer (Python) ↓ Trading Orders Binance API ↓ Execution Results State Files / CF KV ↓ Metrics Prometheus + node_exporter ↓ Storage Grafana Visualization ↓ Alert Rules Alertmanager → Telegram Strategy Execution Layer Tech Stack Language: Python 3.11 Binance SDK: python-binance Scheduled Tasks: APScheduler or system cron Dependency Management: requirements.txt + venv Directory Structure quant/ ├── strategy/ │ ├── main.py # Core strategy logic (signal generation + order placement) │ ├── signals.py # Indicator calculations (technical indicator library) │ └── risk.py # Position sizing, stop-loss logic ├── exchange/ │ └── binance_client.py # Binance API wrapper ├── monitor/ │ └── exporter.py # Expose state metrics in Prometheus format ├── config/ │ └── settings.py # Configuration (read from environment variables) └── run.py # Entry point Key Code: Exposing State Metrics While your strategy runs, write key metrics in Prometheus text file format for node_exporter to scrape: ...

Stop-Loss Parameter Research in Quantitative Strategies Stop-loss distance is one of the hardest parameters to pin down in a quantitative strategy. Set it too tight and you get whipsawed constantly; set it too loose and a single trade can blow through your risk budget. Tuning by intuition doesn’t convince anyone. A more reliable approach: systematically study historical data to understand how different stop-loss distances affect strategy performance, then identify parameter ranges that balance well across multiple evaluation dimensions. ...

💡 China users: Binance’s official site can’t be accessed directly from mainland China—you’ll need your own networking tools. Fiat deposits don’t support bank cards; the main method is C2C (USDT↔CNY) channels. The Binance API is your gateway to quantitative trading. If you want your strategy to execute automatically—auto buy, auto stop-loss, auto position monitoring—you need the API. ...