jackyu66gitandClaude
71951019fb
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>
70 lines
2.4 KiB
Python
70 lines
2.4 KiB
Python
"""
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fetchers/base.py — Abstract base class for all macro data fetchers.
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Provides retry logic, rate limiting, and a common interface.
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"""
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from abc import ABC, abstractmethod
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from datetime import date as Date
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from typing import Optional
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import logging
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import time
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import requests
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class BaseFetcher(ABC):
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"""Abstract base for all macro data fetchers."""
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def __init__(self, timeout: int = 30, max_retries: int = 3):
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self.timeout = timeout
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self.max_retries = max_retries
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self.logger = logging.getLogger(self.__class__.__name__)
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def _get(self, url: str, params: Optional[dict] = None,
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headers: Optional[dict] = None) -> dict:
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"""GET with retry and exponential backoff."""
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for attempt in range(self.max_retries):
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try:
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resp = requests.get(
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url, params=params, headers=headers, timeout=self.timeout
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)
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resp.raise_for_status()
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return resp.json()
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except requests.RequestException as e:
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wait = 2 ** attempt
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self.logger.warning(
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f"Request failed (attempt {attempt+1}/{self.max_retries}): {e}. "
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f"Retrying in {wait}s"
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)
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if attempt < self.max_retries - 1:
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time.sleep(wait)
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else:
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raise
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def _get_raw(self, url: str, params: Optional[dict] = None,
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headers: Optional[dict] = None) -> bytes:
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"""GET raw bytes with retry (for non-JSON endpoints)."""
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for attempt in range(self.max_retries):
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try:
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resp = requests.get(
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url, params=params, headers=headers, timeout=self.timeout
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)
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resp.raise_for_status()
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return resp.content
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except requests.RequestException as e:
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wait = 2 ** attempt
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if attempt < self.max_retries - 1:
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time.sleep(wait)
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else:
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raise
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@abstractmethod
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def fetch(self, target_date: Optional[Date] = None) -> list[dict]:
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"""Fetch raw data. Returns list of record dicts."""
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...
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@abstractmethod
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def store(self, db_path: str, records: list[dict]) -> int:
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"""Store raw records into SQLite. Returns count of new rows."""
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...
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