lint: ruff clean services/ (autofix + manual + ignore E741)

- 24 autofix safe (SIM105 contextlib.suppress, F401 unused imports,
  I001 import order, B007 unused loop var, F811 redef, F841 unused).
- 15 unsafe-fix (UP038 X|Y in isinstance, SIM108 ternary, ecc.).
- Manual fix: SIM102 nested if in deribit term_structure, E402 imports
  in test_cot.py + sentiment server.py.
- Ignore E741 (variabili 'l' in list comprehensions deribit/client.py
  — stilistico, non bug).

Tests: 478/478 verdi.

services/common/src/mcp_common/mcp_bridge.py

@@ -21,6 +21,7 @@ Claude Code config esempio:
 """
 from __future__ import annotations
 
+import contextlib
 from typing import Any
 
 import httpx
@@ -63,10 +64,8 @@ def _derive_input_schemas(app: FastAPI, tool_names: list[str]) -> dict[str, dict
             if pname == "return":
                 continue
             if isinstance(ann, type) and issubclass(ann, BaseModel):
-                try:
+                with contextlib.suppress(Exception):
                     out[name] = ann.model_json_schema()
-                except Exception:
-                    pass
                 break
     return out
 

services/common/src/mcp_common/microstructure.py

@@ -36,10 +36,7 @@ def orderbook_imbalance(
     ask_vol = sum(q for _, q in top_asks)
     total = bid_vol + ask_vol
 
-    if total == 0:
-        ratio = None
-    else:
-        ratio = (bid_vol - ask_vol) / total
+    ratio = None if total == 0 else (bid_vol - ask_vol) / total
 
     # Microprice: best bid, best ask. Weighted by opposite-side size.
     microprice = None

services/common/tests/test_http.py

@@ -4,7 +4,6 @@ import asyncio
 
 import httpx
 import pytest
-
 from mcp_common.http import async_client, call_with_retry
 
 

services/common/tests/test_indicators.py

@@ -112,7 +112,7 @@ def test_vol_cone_returns_percentiles_per_window():
     closes = _gbm_series(mu=0.0, sigma=0.5, n=400)
     out = vol_cone(closes, windows=[10, 30, 60])
     assert set(out.keys()) == {10, 30, 60}
-    for w, stats in out.items():
+    for _w, stats in out.items():
         assert "current" in stats
         assert "p10" in stats and "p50" in stats and "p90" in stats
         assert stats["p10"] <= stats["p50"] <= stats["p90"]
@@ -200,7 +200,7 @@ def test_autocorrelation_white_noise_low():
     assert len(out) == 5
     # white noise → all autocorr ≈ 0 (within ±2/sqrt(N))
     bound = 2.0 / math.sqrt(len(rets))
-    for lag, val in out.items():
+    for _lag, val in out.items():
         assert abs(val) < bound * 2  # generous