base_node.py

"""
This module defines the base node class for the ScrapeGraphAI application.
"""

import re
from abc import ABC, abstractmethod
from typing import List, Optional

from ..utils import get_logger


class BaseNode(ABC):
    """
    An abstract base class for nodes in a graph-based workflow,
    designed to perform specific actions when executed.

    Attributes:
        node_name (str): The unique identifier name for the node.
        input (str): Boolean expression defining the input keys needed from the state.
        output (List[str]): List of
        min_input_len (int): Minimum required number of input keys.
        node_config (Optional[dict]): Additional configuration for the node.
        logger (logging.Logger): The centralized root logger

    Args:
        node_name (str): Name for identifying the node.
        node_type (str): Type of the node; must be 'node' or 'conditional_node'.
        input (str): Expression defining the input keys needed from the state.
        output (List[str]): List of output keys to be updated in the state.
        min_input_len (int, optional): Minimum required number of input keys; defaults to 1.
        node_config (Optional[dict], optional): Additional configuration
                                                for the node; defaults to None.

    Raises:
        ValueError: If `node_type` is not one of the allowed types.

    Example:
        >>> class MyNode(BaseNode):
        ...     def execute(self, state):
        ...         # Implementation of node logic here
        ...         return state
        ...
        >>> my_node = MyNode("ExampleNode", "node", "input_spec", ["output_spec"])
        >>> updated_state = my_node.execute({'key': 'value'})
        {'key': 'value'}
    """

    def __init__(
        self,
        node_name: str,
        node_type: str,
        input: str,
        output: List[str],
        min_input_len: int = 1,
        node_config: Optional[dict] = None,
    ):

        self.node_name = node_name
        self.input = input
        self.output = output
        self.min_input_len = min_input_len
        self.node_config = node_config
        self.logger = get_logger()

        if node_type not in ["node", "conditional_node"]:
            raise ValueError(
                f"node_type must be 'node' or 'conditional_node', got '{node_type}'"
            )
        self.node_type = node_type

    @abstractmethod
    def execute(self, state: dict) -> dict:
        """
        Execute the node's logic based on the current state and update it accordingly.

        Args:
            state (dict): The current state of the graph.

        Returns:
            dict: The updated state after executing the node's logic.
        """

        pass

    def update_config(self, params: dict, overwrite: bool = False):
        """
        Updates the node_config dictionary as well as attributes with same key.

        Args:
            param (dict): The dictionary to update node_config with.
            overwrite (bool): Flag indicating if the values of node_config
            should be overwritten if their value is not None.
        """
        for key, val in params.items():
            if hasattr(self, key) and not overwrite:
                continue
            setattr(self, key, val)

    def get_input_keys(self, state: dict) -> List[str]:
        """
        Determines the necessary state keys based on the input specification.

        Args:
            state (dict): The current state of the graph used to parse input keys.

        Returns:
            List[str]: A list of input keys required for node operation.

        Raises:
            ValueError: If error occurs in parsing input keys.
        """

        try:
            input_keys = self._parse_input_keys(state, self.input)
            self._validate_input_keys(input_keys)
            return input_keys
        except ValueError as e:
            raise ValueError(f"Error parsing input keys for {self.node_name}") from e

    def _validate_input_keys(self, input_keys):
        """
        Validates if the provided input keys meet the minimum length requirement.

        Args:
            input_keys (List[str]): The list of input keys to validate.

        Raises:
            ValueError: If the number of input keys is less than the minimum required.
        """

        if len(input_keys) < self.min_input_len:
            raise ValueError(
                f"""{self.node_name} requires at least {self.min_input_len} input keys,
                  got {len(input_keys)}."""
            )

    def _parse_input_keys(self, state: dict, expression: str) -> List[str]:
        """
        Parses the input keys expression to extract
        relevant keys from the state based on logical conditions.
        The expression can contain AND (&), OR (|), and parentheses to group conditions.

        Args:
            state (dict): The current state of the graph.
            expression (str): The input keys expression to parse.

        Returns:
            List[str]: A list of key names that match the input keys expression logic.

        Raises:
            ValueError: If the expression is invalid or if no state keys match the expression.
        """

        if not expression:
            raise ValueError("Empty expression.")

        pattern = (
            r"\b("
            + "|".join(re.escape(key) for key in state.keys())
            + r")(\b\s*\b)("
            + "|".join(re.escape(key) for key in state.keys())
            + r")\b"
        )
        if re.search(pattern, expression):
            raise ValueError(
                "Adjacent state keys found without an operator between them."
            )

        expression = expression.replace(" ", "")

        if (
            expression[0] in "&|"
            or expression[-1] in "&|"
            or "&&" in expression
            or "||" in expression
            or "&|" in expression
            or "|&" in expression
        ):
            raise ValueError("Invalid operator usage.")

        open_parentheses = close_parentheses = 0
        for i, char in enumerate(expression):
            if char == "(":
                open_parentheses += 1
            elif char == ")":
                close_parentheses += 1
            # Check for invalid operator sequences
            if char in "&|" and i + 1 < len(expression) and expression[i + 1] in "&|":
                raise ValueError(
                    "Invalid operator placement: operators cannot be adjacent."
                )

        if open_parentheses != close_parentheses:
            raise ValueError("Missing or unbalanced parentheses in expression.")

        def evaluate_simple_expression(exp: str) -> List[str]:
            """Evaluate an expression without parentheses."""

            for or_segment in exp.split("|"):

                and_segment = or_segment.split("&")
                if all(elem.strip() in state for elem in and_segment):
                    return [
                        elem.strip() for elem in and_segment if elem.strip() in state
                    ]
            return []

        def evaluate_expression(expression: str) -> List[str]:
            """Evaluate an expression with parentheses."""

            while "(" in expression:
                start = expression.rfind("(")
                end = expression.find(")", start)
                sub_exp = expression[start + 1 : end]

                sub_result = evaluate_simple_expression(sub_exp)

                expression = (
                    expression[:start] + "|".join(sub_result) + expression[end + 1 :]
                )
            return evaluate_simple_expression(expression)

        result = evaluate_expression(expression)

        if not result:
            raise ValueError(
                f"""No state keys matched the expression.
                             Expression was {expression}.
                             State contains keys: {', '.join(state.keys())}"""
            )

        final_result = []
        for key in result:
            if key not in final_result:
                final_result.append(key)

        return final_result