Python Binance High-Frequency Bot
Budget: $30 – $250 USD
I need a Binance trading bot built in Python that can execute a true high-frequency strategy: rapid order placement, real-time order book listening, and sub-second decision making. The bot must connect through Binance’s REST and WebSocket APIs, manage authentication keys securely, and keep latency to an absolute minimum.
Key tasks and deliverables
• Design and code the core execution engine with efficient, non-blocking WebSocket handling.
• Implement a rules-based or micro-signal logic that chooses when to place, amend, or cancel orders within milliseconds.
• Provide configurable risk controls—position limits, max draw-down, and automatic circuit breakers.
• Log every decision and fill in a lightweight database so I can replay sessions for analysis.
• Package everything in a Docker image with clear README so setup on my VPS is one command.
Acceptance criteria
1. End-to-end demo on Binance testnet showing ≥100 orders/minute (fills not required).
2. CPU and memory footprint reported; the bot must run continuously for 4 hours without crash.
3. Source code passes my static lint checks (flake8) and is delivered via private Git repository.
If you are comfortable squeezing microseconds out of Python, handling WebSockets, and coding solid risk guards, let’s get this project started.
Key tasks and deliverables
• Design and code the core execution engine with efficient, non-blocking WebSocket handling.
• Implement a rules-based or micro-signal logic that chooses when to place, amend, or cancel orders within milliseconds.
• Provide configurable risk controls—position limits, max draw-down, and automatic circuit breakers.
• Log every decision and fill in a lightweight database so I can replay sessions for analysis.
• Package everything in a Docker image with clear README so setup on my VPS is one command.
Acceptance criteria
1. End-to-end demo on Binance testnet showing ≥100 orders/minute (fills not required).
2. CPU and memory footprint reported; the bot must run continuously for 4 hours without crash.
3. Source code passes my static lint checks (flake8) and is delivered via private Git repository.
If you are comfortable squeezing microseconds out of Python, handling WebSockets, and coding solid risk guards, let’s get this project started.