chanmacro: Signal Expectancy Engine V1 — Market Memory System

Phase A-C complete: 4 core factors, regime detection, signal tracking, Bayesian expectancy.

chanmacro/ (32 files, ~4000 lines):
- models: 12 enums + 15 Pydantic v2 models (DateAwareModel, MarketStateVector, etc.)
- fetchers: OHLCV + Breadth (from data_provider) + Derivatives (new endpoint)
- scoring: Price Structure / Breadth (quantile buckets) / OI Matrix (5 discrete states) / Volatility Regime
- regime_detector: 3-state (TREND/RANGE/PANIC), factor-locked (Price+Breadth+Vol), versioned, 2-day confirmation
- expectancy: SignalTracker (record+outcomes), TimeDecay (half-life=180d), BayesianExpectancyEngine (Empirical Bayes, Leveled, SufficiencyGuard)
- validation: FactorValidator (IC/ICIR/Hit Ratio), RegimeValidator (MI/KL/ANOVA), TransitionValidator (stability)
- CLI: fetch|score|regime|track|backfill|expectancy|validate|serve
- tests: 52 passing (models, scoring, regime, expectancy)

data_provider:
- /api/derivatives endpoint: funding rate, OI, OI change, basis
- _derivatives storage: same persist pattern as K-line (merge→lock→snapshot→atomic write)
- background refresh every 60s

Co-Authored-By: Claude <noreply@anthropic.com>

ChanMacro/fetchers/base.py

@@ -0,0 +1,69 @@
+"""
+fetchers/base.py — Abstract base class for all macro data fetchers.
+
+Provides retry logic, rate limiting, and a common interface.
+"""
+
+from abc import ABC, abstractmethod
+from datetime import date as Date
+from typing import Optional
+import logging
+import time
+import requests
+
+
+class BaseFetcher(ABC):
+    """Abstract base for all macro data fetchers."""
+
+    def __init__(self, timeout: int = 30, max_retries: int = 3):
+        self.timeout = timeout
+        self.max_retries = max_retries
+        self.logger = logging.getLogger(self.__class__.__name__)
+
+    def _get(self, url: str, params: Optional[dict] = None,
+             headers: Optional[dict] = None) -> dict:
+        """GET with retry and exponential backoff."""
+        for attempt in range(self.max_retries):
+            try:
+                resp = requests.get(
+                    url, params=params, headers=headers, timeout=self.timeout
+                )
+                resp.raise_for_status()
+                return resp.json()
+            except requests.RequestException as e:
+                wait = 2 ** attempt
+                self.logger.warning(
+                    f"Request failed (attempt {attempt+1}/{self.max_retries}): {e}. "
+                    f"Retrying in {wait}s"
+                )
+                if attempt < self.max_retries - 1:
+                    time.sleep(wait)
+                else:
+                    raise
+
+    def _get_raw(self, url: str, params: Optional[dict] = None,
+                 headers: Optional[dict] = None) -> bytes:
+        """GET raw bytes with retry (for non-JSON endpoints)."""
+        for attempt in range(self.max_retries):
+            try:
+                resp = requests.get(
+                    url, params=params, headers=headers, timeout=self.timeout
+                )
+                resp.raise_for_status()
+                return resp.content
+            except requests.RequestException as e:
+                wait = 2 ** attempt
+                if attempt < self.max_retries - 1:
+                    time.sleep(wait)
+                else:
+                    raise
+
+    @abstractmethod
+    def fetch(self, target_date: Optional[Date] = None) -> list[dict]:
+        """Fetch raw data. Returns list of record dicts."""
+        ...
+
+    @abstractmethod
+    def store(self, db_path: str, records: list[dict]) -> int:
+        """Store raw records into SQLite. Returns count of new rows."""
+        ...