Python trading frameworks

Python trading frameworks - Libraries and platforms for algorithmic strategies. Common ones include Backtrader and Zipline. These allow traders to write strategies in Python for backtesting and live execution. For instance, in Backtrader one defines a Strategy class with logic in its next() method. You can add indicators and signals and then call cerebro.add_signal() to tie indicators to buy/sell signals. A Python bot might loop over historical or live data, computing a signal (e.g. using Pandas or NumPy) and then executing orders via a broker API. Zipline (Quantopian) strategies use functions like order_target_percent() to set portfolio weight. Python frameworks provide flexibility: for example, one could combine multiple assets (multi-dimensional stat arb) or apply ML models. This entry emphasizes that beyond MQL or C#, modern algo traders often use Python, leveraging its libraries for strategy components (and then connecting to MT5 or brokers via API).