Initial commit: manifoldbt public repo

Python DSL, examples, docs, benchmarks, and tests.
Rust engine distributed as pre-compiled wheel via PyPI.

examples/12_diagnostics.py

@@ -0,0 +1,89 @@
+"""Diagnostics -- look-ahead bias detection and exposure stability checks.
+
+Demonstrates:
+  - detect_lookahead(): split-test for look-ahead bias
+  - check_exposure_stability(): verify positions are consistent across time windows
+  - risk_check(): post-run risk metrics validation
+
+Usage:
+    python examples/12_diagnostics.py
+"""
+import os
+import time
+import manifoldbt as mbt
+from manifoldbt.indicators import close, ema
+from manifoldbt.helpers import time_range, Slippage, Interval
+
+# -- Strategy -----------------------------------------------------------------
+fast = ema(close, 12)
+slow = ema(close, 50)
+
+signal = mbt.when(fast > slow, 0.5, 0.0)
+
+strategy = (
+    mbt.Strategy.create("ema_trend")
+    .signal("fast", fast)
+    .signal("slow", slow)
+    .size(signal)
+    .stop_loss(pct=3.0)
+)
+
+# -- Config -------------------------------------------------------------------
+start, end = time_range("2022-01-01", "2025-01-01")
+
+config = mbt.BacktestConfig(
+    universe=[1],
+    time_range_start=start,
+    time_range_end=end,
+    bar_interval=Interval.hours(12),
+    initial_capital=10_000,
+    execution=mbt.ExecutionConfig(
+        allow_short=False,
+        max_position_pct=0.5,
+    ),
+    fees=mbt.FeeConfig.binance_perps(),
+    slippage=Slippage.fixed_bps(2),
+    warmup_bars=60,
+)
+
+# -- Run ----------------------------------------------------------------------
+if __name__ == "__main__":
+    root = os.path.join(os.path.dirname(__file__), "..")
+    store = mbt.DataStore(
+        data_root=os.path.abspath(os.path.join(root, "data")),
+        metadata_db=os.path.abspath(os.path.join(root, "metadata", "metadata.sqlite")),
+    )
+
+    # -- 1. Look-ahead bias detection -----------------------------------------
+    # Splits the time range and compares trades from shorter runs against
+    # the full run. If trades differ, the strategy uses future data.
+    print("1. Look-ahead bias detection")
+    print("-" * 40)
+    t0 = time.perf_counter()
+    lookahead = mbt.diagnostics.detect_lookahead(strategy, config, store)
+    print(lookahead)
+    print(f"   Elapsed: {time.perf_counter() - t0:.2f}s\n")
+
+    # -- 2. Exposure stability -------------------------------------------------
+    # Verifies that utilization and per-symbol exposure are identical
+    # across different time windows. Catches position sizing that leaks
+    # future data (e.g. z-score over the entire series).
+    print("2. Exposure stability")
+    print("-" * 40)
+    t0 = time.perf_counter()
+    stability = mbt.diagnostics.check_exposure_stability(strategy, config, store)
+    print(stability)
+    print(f"   Elapsed: {time.perf_counter() - t0:.2f}s\n")
+
+    # -- 3. Backtest + risk check ----------------------------------------------
+    # Run the strategy, then validate risk metrics against thresholds.
+    print("3. Backtest + risk check")
+    print("-" * 40)
+    t0 = time.perf_counter()
+    result = mbt.run(strategy, config, store)
+    print(result.summary())
+    print(f"   Elapsed: {time.perf_counter() - t0:.2f}s\n")
+
+    risk = mbt.diagnostics.risk_check(result)
+    print("Risk check:")
+    print(risk)