"""TOML-based graph configuration loader."""

from pathlib import Path
from typing import Any

import tomllib

from engine.pipeline.graph import Graph, NodeType
from engine.pipeline.graph_adapter import graph_to_pipeline


def load_graph_from_toml(toml_path: str | Path) -> Graph:
    """Load a graph from a TOML file.

    Args:
        toml_path: Path to the TOML file

    Returns:
        Graph instance loaded from the TOML file
    """
    with open(toml_path, "rb") as f:
        data = tomllib.load(f)

    return graph_from_dict(data)


def graph_from_dict(data: dict[str, Any]) -> Graph:
    """Create a graph from a dictionary (TOML-compatible structure).

    Args:
        data: Dictionary with 'nodes' and 'connections' keys

    Returns:
        Graph instance
    """
    graph = Graph()

    # Parse nodes
    nodes_data = data.get("nodes", {})
    for name, node_info in nodes_data.items():
        if isinstance(node_info, str):
            # Simple format: "source": "headlines"
            graph.node(name, NodeType.SOURCE, source=node_info)
        elif isinstance(node_info, dict):
            # Full format: {"type": "camera", "mode": "scroll"}
            node_type = node_info.get("type", "custom")
            config = {k: v for k, v in node_info.items() if k != "type"}
            graph.node(name, node_type, **config)

    # Parse connections
    connections_data = data.get("connections", {})
    if isinstance(connections_data, dict):
        # Format: {"list": ["source -> camera -> display"]}
        connections_list = connections_data.get("list", [])
    else:
        # Format: ["source -> camera -> display"]
        connections_list = connections_data

    for conn in connections_list:
        if isinstance(conn, str):
            # Parse "source -> target" format
            parts = conn.split("->")
            if len(parts) >= 2:
                # Connect all nodes in the chain
                for i in range(len(parts) - 1):
                    source = parts[i].strip()
                    target = parts[i + 1].strip()
                    graph.connect(source, target)

    return graph


def load_pipeline_from_toml(
    toml_path: str | Path, viewport_width: int = 80, viewport_height: int = 24
):
    """Load a pipeline from a TOML file.

    Args:
        toml_path: Path to the TOML file
        viewport_width: Terminal width for the pipeline
        viewport_height: Terminal height for the pipeline

    Returns:
        Pipeline instance loaded from the TOML file
    """
    graph = load_graph_from_toml(toml_path)
    return graph_to_pipeline(graph, viewport_width, viewport_height)


# Example TOML structure:
EXAMPLE_TOML = """
# Graph-based pipeline configuration
[nodes.source]
type = "source"
source = "headlines"

[nodes.camera]
type = "camera"
mode = "scroll"
speed = 1.0

[nodes.noise]
type = "effect"
effect = "noise"
intensity = 0.3

[nodes.display]
type = "display"
backend = "terminal"

[connections]
list = ["source -> camera -> noise -> display"]
"""