initial project setup with README and ignore
This commit is contained in:
204
app/config/dynamic_config.py
Normal file
204
app/config/dynamic_config.py
Normal file
@@ -0,0 +1,204 @@
|
||||
"""
|
||||
Dynamic Configuration - rider-api
|
||||
|
||||
Replaces all hardcoded hyperparameters with DB-backed values.
|
||||
The ML hypertuner writes optimal values here; services read from here.
|
||||
|
||||
Fallback: If DB is unavailable or no tuned values exist, defaults are used.
|
||||
This means zero risk - the system works day 1 with no data.
|
||||
"""
|
||||
|
||||
import json
|
||||
import logging
|
||||
import os
|
||||
import sqlite3
|
||||
from datetime import datetime
|
||||
from typing import Any, Dict, Optional
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# --- DB Path ------------------------------------------------------------------
|
||||
_DB_PATH = os.getenv("ML_DB_PATH", "ml_data/ml_store.db")
|
||||
|
||||
|
||||
# --- Hard Defaults (What the system used before ML) ---------------------------
|
||||
DEFAULTS: Dict[str, Any] = {
|
||||
# System Strategy / Prompt
|
||||
"ml_strategy": "balanced",
|
||||
|
||||
# AssignmentService
|
||||
"max_pickup_distance_km": 10.0,
|
||||
"max_kitchen_distance_km": 3.0,
|
||||
"max_orders_per_rider": 12,
|
||||
"ideal_load": 6,
|
||||
"workload_balance_threshold": 0.7,
|
||||
"workload_penalty_weight": 100.0,
|
||||
"distance_penalty_weight": 2.0,
|
||||
"preference_bonus": -15.0,
|
||||
"home_zone_bonus_4km": -3.0,
|
||||
"home_zone_bonus_2km": -5.0,
|
||||
"emergency_load_penalty": 3.0, # km penalty per order in emergency assign
|
||||
|
||||
# RouteOptimizer
|
||||
"search_time_limit_seconds": 5,
|
||||
"avg_speed_kmh": 18.0,
|
||||
"road_factor": 1.3,
|
||||
|
||||
# ClusteringService
|
||||
"cluster_radius_km": 3.0,
|
||||
|
||||
# KalmanFilter
|
||||
"kalman_process_noise": 1e-4,
|
||||
"kalman_measurement_noise": 0.01,
|
||||
|
||||
# RealisticETACalculator
|
||||
"eta_pickup_time_min": 3.0,
|
||||
"eta_delivery_time_min": 4.0,
|
||||
"eta_navigation_buffer_min": 1.5,
|
||||
"eta_short_trip_factor": 0.8, # speed multiplier for dist < 2km
|
||||
"eta_long_trip_factor": 1.1, # speed multiplier for dist > 8km
|
||||
}
|
||||
|
||||
|
||||
class DynamicConfig:
|
||||
"""
|
||||
Thread-safe, DB-backed configuration store.
|
||||
|
||||
Usage:
|
||||
cfg = DynamicConfig()
|
||||
max_dist = cfg.get("max_pickup_distance_km")
|
||||
all_params = cfg.get_all()
|
||||
"""
|
||||
|
||||
_instance: Optional["DynamicConfig"] = None
|
||||
|
||||
def __new__(cls) -> "DynamicConfig":
|
||||
"""Singleton - one config per process."""
|
||||
if cls._instance is None:
|
||||
cls._instance = super().__new__(cls)
|
||||
cls._instance._initialized = False
|
||||
return cls._instance
|
||||
|
||||
def __init__(self):
|
||||
if self._initialized:
|
||||
return
|
||||
self._initialized = True
|
||||
self._cache: Dict[str, Any] = {}
|
||||
self._last_loaded: Optional[datetime] = None
|
||||
self._ensure_db()
|
||||
self._load()
|
||||
|
||||
# --------------------------------------------------------------------------
|
||||
# Public API
|
||||
# --------------------------------------------------------------------------
|
||||
|
||||
def get(self, key: str, default: Any = None) -> Any:
|
||||
"""Get a config value. Returns ML-tuned value if available, else default."""
|
||||
self._maybe_reload()
|
||||
val = self._cache.get(key)
|
||||
if val is not None:
|
||||
return val
|
||||
fallback = default if default is not None else DEFAULTS.get(key)
|
||||
return fallback
|
||||
|
||||
def get_all(self) -> Dict[str, Any]:
|
||||
"""Return all current config values (ML-tuned + defaults for missing keys)."""
|
||||
self._maybe_reload()
|
||||
result = dict(DEFAULTS)
|
||||
result.update(self._cache)
|
||||
return result
|
||||
|
||||
def set(self, key: str, value: Any, source: str = "manual") -> None:
|
||||
"""Write a config value to DB (used by hypertuner)."""
|
||||
try:
|
||||
os.makedirs(os.path.dirname(_DB_PATH) or ".", exist_ok=True)
|
||||
conn = sqlite3.connect(_DB_PATH)
|
||||
conn.execute("""
|
||||
INSERT INTO dynamic_config (key, value, source, updated_at)
|
||||
VALUES (?, ?, ?, ?)
|
||||
ON CONFLICT(key) DO UPDATE SET
|
||||
value=excluded.value,
|
||||
source=excluded.source,
|
||||
updated_at=excluded.updated_at
|
||||
""", (key, json.dumps(value), source, datetime.utcnow().isoformat()))
|
||||
conn.commit()
|
||||
conn.close()
|
||||
self._cache[key] = value
|
||||
logger.info(f"[DynamicConfig] Set {key}={value} (source={source})")
|
||||
except Exception as e:
|
||||
logger.error(f"[DynamicConfig] Failed to set {key}: {e}")
|
||||
|
||||
def set_bulk(self, params: Dict[str, Any], source: str = "ml_hypertuner") -> None:
|
||||
"""Write multiple config values at once (called after each Optuna study)."""
|
||||
for key, value in params.items():
|
||||
self.set(key, value, source=source)
|
||||
logger.info(f"[DynamicConfig] Bulk update: {len(params)} params from {source}")
|
||||
|
||||
def reset_to_defaults(self) -> None:
|
||||
"""Wipe all ML-tuned values, revert to hardcoded defaults."""
|
||||
try:
|
||||
conn = sqlite3.connect(_DB_PATH)
|
||||
conn.execute("DELETE FROM dynamic_config")
|
||||
conn.commit()
|
||||
conn.close()
|
||||
self._cache.clear()
|
||||
logger.warning("[DynamicConfig] Reset to factory defaults.")
|
||||
except Exception as e:
|
||||
logger.error(f"[DynamicConfig] Reset failed: {e}")
|
||||
|
||||
# --------------------------------------------------------------------------
|
||||
# Internal
|
||||
# --------------------------------------------------------------------------
|
||||
|
||||
def _ensure_db(self) -> None:
|
||||
try:
|
||||
os.makedirs(os.path.dirname(_DB_PATH) or ".", exist_ok=True)
|
||||
conn = sqlite3.connect(_DB_PATH)
|
||||
conn.execute("""
|
||||
CREATE TABLE IF NOT EXISTS dynamic_config (
|
||||
key TEXT PRIMARY KEY,
|
||||
value TEXT NOT NULL,
|
||||
source TEXT DEFAULT 'manual',
|
||||
updated_at TEXT
|
||||
)
|
||||
""")
|
||||
conn.commit()
|
||||
conn.close()
|
||||
except Exception as e:
|
||||
logger.error(f"[DynamicConfig] DB init failed: {e}")
|
||||
|
||||
def _load(self) -> None:
|
||||
try:
|
||||
conn = sqlite3.connect(_DB_PATH)
|
||||
rows = conn.execute("SELECT key, value FROM dynamic_config").fetchall()
|
||||
conn.close()
|
||||
self._cache = {}
|
||||
for key, raw in rows:
|
||||
try:
|
||||
self._cache[key] = json.loads(raw)
|
||||
except Exception:
|
||||
self._cache[key] = raw
|
||||
self._last_loaded = datetime.utcnow()
|
||||
if self._cache:
|
||||
logger.info(f"[DynamicConfig] Loaded {len(self._cache)} ML-tuned params from DB")
|
||||
except Exception as e:
|
||||
logger.warning(f"[DynamicConfig] Could not load from DB (using defaults): {e}")
|
||||
self._cache = {}
|
||||
|
||||
def _maybe_reload(self, interval_seconds: int = 300) -> None:
|
||||
"""Reload from DB every 5 minutes - picks up new tuned params without restart."""
|
||||
if self._last_loaded is None:
|
||||
self._load()
|
||||
return
|
||||
delta = (datetime.utcnow() - self._last_loaded).total_seconds()
|
||||
if delta > interval_seconds:
|
||||
self._load()
|
||||
|
||||
|
||||
# --- Module-level convenience singleton ---------------------------------------
|
||||
_cfg = DynamicConfig()
|
||||
|
||||
|
||||
def get_config() -> DynamicConfig:
|
||||
"""Get the global DynamicConfig singleton."""
|
||||
return _cfg
|
||||
Reference in New Issue
Block a user