chore: establish Strategy Lab source baseline (development, not release)

1 files changed, 39 insertions, 0 deletions

diff --git a/tests/fixtures_synth.py b/tests/fixtures_synth.py
new file mode 100644
index 0000000..69b305b
--- /dev/null
+++ b/tests/fixtures_synth.py
@@ -0,0 +1,39 @@
+"""Deterministic synthetic OHLCV fixtures for worker tests.
+
+Every object here carries ``_synthetic: true`` and must never be used as a
+production fallback. Values are simple deterministic series so accounting
+ assertions in backtest tests can be hand-verified.
+"""
+import pandas as pd
+
+_SYNTHETIC = {"_synthetic": True}
+
+
+def synthetic_daily(symbol: str = "SH#600000", start="2024-01-02", days=20,
+                    base=10.0, volume=1_000_000, extra_fields=True) -> pd.DataFrame:
+    dates = pd.bdate_range(start, periods=days)
+    rows = []
+    price = base
+    for i, d in enumerate(dates):
+        o = round(price, 2)
+        c = round(price * 1.02, 2) if i % 2 == 0 else round(price * 0.98, 2)
+        h = round(max(o, c) * 1.01, 2)
+        l = round(min(o, c) * 0.99, 2)
+        row = {
+            "date": d.strftime("%Y-%m-%d"),
+            "symbol": symbol,
+            "open": o, "high": h, "low": l, "close": c,
+            "volume": volume + i * 1000,
+        }
+        if extra_fields:
+            # raw provider-style extra fields preserved verbatim
+            row["amount"] = round((o + h + l + c) / 4 * (volume + i * 1000), 2)
+            row["turnover"] = round(0.5 + i * 0.01, 3)
+        rows.append(row)
+        price = c
+    df = pd.DataFrame(rows)
+    df.attrs["synthetic"] = True
+    return df
+
+
+SYNTH = _SYNTHETIC