dtm_python/app/services/utils.py

"""
工具函数模块
"""
import numpy as np
import pandas as pd


def convert_to_native_types(obj):
    """递归地将 numpy/pandas 类型转换为 Python 原生类型，以便 JSON 序列化"""
    if isinstance(obj, (np.integer, np.int_, np.intc, np.intp, np.int8,
                        np.int16, np.int32, np.int64, np.uint8, np.uint16,
                        np.uint32, np.uint64)):
        return int(obj)
    elif isinstance(obj, (np.floating, np.float64, np.float16, np.float32, np.float64)):
        return float(obj)
    elif isinstance(obj, (np.bool_, np.bool)):
        return bool(obj)
    elif isinstance(obj, (np.ndarray, pd.Series)):
        return obj.tolist()
    elif isinstance(obj, pd.DataFrame):
        return obj.to_dict('records')
    elif isinstance(obj, dict):
        return {key: convert_to_native_types(value) for key, value in obj.items()}
    elif isinstance(obj, (list, tuple)):
        return [convert_to_native_types(item) for item in obj]
    elif isinstance(obj, (str, int, float, bool, type(None))):
        return obj
    else:
        try:
            return str(obj)
        except Exception:
            return obj


def ensure_native_type(value, target_type=float, decimal_places=2):
    """确保值为 Python 原生类型，并保留指定小数位数"""
    if isinstance(value, (np.integer, np.floating)):
        converted = target_type(value)
        if target_type == float and decimal_places is not None:
            return round(converted, decimal_places)
        return converted
    if isinstance(value, float) and decimal_places is not None:
        return round(value, decimal_places)
    return value