Build a Regime-Aware Crypto Trading Bot in Python (50 Lines)

Most crypto trading bots lose money. Not because the strategy is bad, but because they trade the same way in every market condition. A momentum strategy that prints money in a bull market will bleed you dry in sideways chop. The fix is regime detection — classifying the market as bull, bear, or chop, and adjusting your behavior accordingly. In this tutorial, we'll build a simple bot that fetches live regime data, adjusts position sizing, and simulates trades — all in about 50 lines of Python. Why Regime Detection Matters Here's the uncomfortable truth from backtesting 302K+ candles across BTC, ETH, and SOL: 80%+ of losses come from trading against the prevailing regime A simple SMA crossover on ETH goes from mediocre to +166% when you scale position size by regime Stop losses at 3% with leverage actually hurt returns — the regime flip is a better exit signal The market spends roughly 30% of the time trending (bull or bear) and 70% chopping. If your bot doesn't know which state it's in,