Backtester works

backend/data/loader.py

@@ -0,0 +1,27 @@
+print("File is running")
+import pandas as pd
+from data.model import Candle
+
+def load_candles(filepath: str) -> list[Candle]:
+    df = pd.read_csv(filepath, sep=";", header=None, names=["timestamp", "open", "high", "low", "close", "volume"])
+    df["timestamp"] = pd.to_datetime(df["timestamp"], format="%Y%m%d %H%M%S")
+
+    candles = []
+    for _, row in df.iterrows():
+        candle = Candle(
+            time_open=row["timestamp"],
+            open=row["open"],
+            high=row["high"],
+            low=row["low"],
+            close=row["close"],
+            volume=row["volume"]
+        )
+        candles.append(candle)
+
+    return candles
+
+if __name__ == "__main__":
+    candles = load_candles("data.csv")
+    print(f"Loaded {len(candles)} candles")
+    print(f"First: {candles[0]}")
+    print(f"Last: {candles[-1]}")

backend/data/model.py

@@ -1,4 +1,5 @@
 from dataclasses import dataclass
+from datetime import datetime
 
 @dataclass
 class Candle:

backend/engine/backtester.py

@@ -0,0 +1,37 @@
+from data.model import Candle, Trade
+from strategies.base import SimpleStrategy
+
+# takes a list of Candles and a starting balance, and returns a list of Trades
+def run_backtest(candles: list[Candle], starting_balance: float) -> list[Trade]:
+    balance = starting_balance
+    trades = []
+    position = None
+    strategy = SimpleStrategy()
+
+    for i, candle in enumerate(candles):
+        # pass 'i' or the sliced history to the strategy
+        signal = strategy.check_signal(candles[:i+1])
+        # If signal and no position, open trade
+        if signal == "BUY" and position is None:
+            position = {
+                "type": "long",
+                "entry_price": candle.close,
+                "enter_time": candle.time_open
+            }
+
+        # If signal and in position, close trade
+        elif signal == "SELL" and position is not None:
+            trade = Trade(
+                enter_time=position["enter_time"],
+                enter_price=position["entry_price"],
+                direction="long",
+                exit_time=candle.time_open,
+                exit_price=candle.close,
+                pnl=candle.close - position["entry_price"]
+            )
+            trades.append(trade)
+            position = None
+
+
+
+    return trades

backend/run.py

@@ -0,0 +1,11 @@
+from data.loader import load_candles
+from engine.backtester import run_backtest
+
+candles = load_candles("data/data.csv")
+print(f"Loaded {len(candles)} candles")
+
+trades = run_backtest(candles, starting_balance=10000.0)
+print(f"Completed {len(trades)} trades")
+
+for trade in trades[:5]:
+    print(trade)

backend/strategies/base.py

@@ -0,0 +1,21 @@
+class SimpleStrategy:
+    def __init__(self, fast_period=10, slow_period=20):
+        self.fast_period = fast_period
+        self.slow_period = slow_period
+
+    def check_signal(self, history):
+        if len(history) < self.slow_period + 1:
+            return None
+
+        fast_now = sum(c.close for c in history[-self.fast_period:]) / self.fast_period
+        slow_now = sum(c.close for c in history[-self.slow_period:]) / self.slow_period
+
+        fast_prev = sum(c.close for c in history[-self.fast_period-1:-1]) / self.fast_period
+        slow_prev = sum(c.close for c in history[-self.slow_period-1:-1]) / self.slow_period
+
+        if fast_prev <= slow_prev and fast_now > slow_now:
+            return "BUY"
+        elif fast_prev >= slow_prev and fast_now < slow_now:
+            return "SELL"
+
+        return None