from __future__ import annotations
import numpy as np
import pandas as pd
from dataclasses import dataclass
from typing import Dict, Optional, List, Tuple, Any

from ..base import _sigmoid, _logit

@dataclass
class InstrumentalGenerator:
    """
    Generator for synthetic causal inference datasets with instrumental variables.

    Placeholder implementation for future use.

    Parameters
    ----------
    seed : int, optional
        Random seed for reproducibility.
    """
    seed: Optional[int] = None

    def generate(self, n: int) -> pd.DataFrame:
        """
        Draw a synthetic dataset of size `n`.

        Parameters
        ----------
        n : int
            Number of samples to generate.

        Returns
        -------
        pandas.DataFrame
            An empty DataFrame (placeholder).
        """
        # Future implementation
        return pd.DataFrame()
