Python Crypto Bot with Persistent State
A Python spot-trading engine designed around exchange API execution, breakeven, ATR trailing, cooldown logic, persistent state and operational alerts.
The challenge
A live crypto bot must remember what happened before a restart, reconcile its position state and avoid treating every process start as a clean slate. Trade management also needed to react dynamically after entry.
The engineering approach
The bot architecture keeps strategy state separate from exchange communication and persists critical position information. Trade lifecycle rules include breakeven, ATR-based trailing and cooldown behavior, with notifications and logs for remote operation.
Recovery and failure handling
Persisted state, restart reconciliation, API-error handling, cooldown transitions and structured alerts provide observable checkpoints. The evidence is whether the system recovers consistently and reports uncertainty, not whether a backtest produced an attractive return.
The bot can preserve operational context across restarts and apply trade-management rules consistently instead of relying only on in-memory state.
Engineering case study. Exchange names and proprietary entry logic are not required to demonstrate the pattern. No client identity, audited live result or performance claim is presented.
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