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File size: 1,513 Bytes
52cc99a 0269b4b 52cc99a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 | from pathlib import Path
from typing import Any, Dict, List
import logging
import yaml
from pydantic import BaseModel, ConfigDict
class ModelConfig(BaseModel):
name: str
description: str
tags: List[str]
class DataConfig(BaseModel):
features: List[str]
target: str
train_path: str
store_path: str
class PipelineConfig(BaseModel):
fourier_period: float = 365.25
fourier_order: int = 5
class Config(BaseModel):
model_config = ConfigDict(extra="ignore")
model: ModelConfig
data: DataConfig
pipeline: PipelineConfig
model_params: Dict[str, Dict[str, Any]]
PROJECT_ROOT = Path(__file__).resolve().parents[2]
DEFAULT_MODEL_PATH = PROJECT_ROOT / "models" / "rossmann_model.json"
DEFAULT_MODEL_METADATA_PATH = PROJECT_ROOT / "models" / "model_metadata.json"
def load_config(config_path: str = "config.yaml") -> Config:
"""Loads and validates the configuration from a YAML file."""
candidate_paths = [Path(config_path), PROJECT_ROOT / config_path]
actual_path = next((path for path in candidate_paths if path.exists()), None)
if actual_path is None:
raise FileNotFoundError(f"Configuration file '{config_path}' not found.")
with actual_path.open("r", encoding="utf-8") as f:
raw_config = yaml.safe_load(f)
return Config(**raw_config)
# Global configuration instance
try:
settings = load_config()
except Exception as e:
logging.error(f"Failed to load configuration: {e}")
settings = None # type: ignore
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