"""
Export tools — graph export (JSON/RDF/CSV/GraphML/Parquet) and provenance.
"""

from __future__ import annotations

import logging

from mcp.schemas import EXPORT_GRAPH, GET_PROVENANCE
from mcp.session import get_graph

log = logging.getLogger("semantica.mcp.tools.export")

_FORMAT_ALIASES: dict[str, str] = {
    "ttl": "turtle",
    "turtle": "turtle",
    "nt": "nt",
    "xml": "xml",
    "json-ld": "json-ld",
    "jsonld": "json-ld",
}


def handle_export_graph(args: dict) -> dict:
    """Export the knowledge graph to a structured format."""
    fmt = str(args.get("format", "json")).lower().strip()
    include_metadata = bool(args.get("include_metadata", True))
    try:
        graph = get_graph()

        if fmt == "json":
            nodes = list(graph.find_nodes())
            edges: list = []
            if hasattr(graph, "find_edges"):
                try:
                    edges = list(graph.find_edges())
                except Exception as exc:
                    log.debug("Failed to collect edges during JSON export; continuing with empty edges: %s", exc)
            payload: dict = {"nodes": nodes, "edges": edges}
            if include_metadata:
                payload["meta"] = {
                    "node_count": len(nodes),
                    "edge_count": len(edges),
                    "format": "json",
                }
            return {"format": "json", "data": payload}

        if fmt in ("csv",):
            nodes = list(graph.find_nodes())
            rows = []
            for n in nodes:
                rows.append(",".join([
                    str(n.get("id", "")),
                    str(n.get("label", "")),
                    str(n.get("type", "")),
                ]))
            header = "id,label,type"
            return {"format": "csv", "data": header + "\n" + "\n".join(rows)}

        if fmt in ("graphml",):
            try:
                from semantica.export import GraphMLExporter
                exporter = GraphMLExporter()
                data = exporter.export(graph)
                return {"format": "graphml", "data": data}
            except Exception as exc:
                return {"error": f"GraphML export failed: {exc}"}

        if fmt in ("parquet",):
            try:
                from semantica.export import ParquetExporter
                exporter = ParquetExporter()
                data = exporter.export(graph, include_metadata)
                return {"format": "parquet", "data": str(data)}
            except Exception as exc:
                return {"error": f"Parquet export failed: {exc}"}

        # RDF formats
        rdf_fmt = _FORMAT_ALIASES.get(fmt)
        if rdf_fmt:
            try:
                from semantica.export import RDFExporter
                # RDFExporter.export_to_rdf() expects the canonical kg dict
                # {"entities": [...], "relationships": [...]}, not a ContextGraph
                # object.  Convert before handing off; passing the raw graph
                # caused AttributeError: 'ContextGraph' object has no attribute
                # 'get' on every RDF format.
                rdf_str = RDFExporter().export_to_rdf(graph.to_kg_dict(), format=rdf_fmt)
                return {"format": rdf_fmt, "data": rdf_str}
            except Exception as exc:
                return {"error": f"RDF export failed: {exc}"}

        return {"error": f"Unsupported format '{fmt}'. Supported: json, csv, graphml, parquet, turtle, nt, xml, json-ld"}

    except Exception as exc:
        log.exception("export_graph failed")
        return {"error": str(exc)}


def handle_get_provenance(args: dict) -> dict:
    """Retrieve the provenance / audit history for a node."""
    node_id = args.get("node_id", "").strip()
    if not node_id:
        return {"error": "node_id is required", "provenance": []}
    include_metadata = bool(args.get("include_metadata", True))
    try:
        graph = get_graph()

        # Try ProvenanceTracker first
        try:
            from semantica.kg import ProvenanceTracker
            tracker = ProvenanceTracker()
            records = tracker.get_provenance(node_id)
            result = records if isinstance(records, list) else list(records)
        except (ImportError, AttributeError):
            # Fallback: look for provenance on the node itself
            nodes = list(graph.find_nodes())
            matched = [n for n in nodes if n.get("id") == node_id]
            if matched:
                node = matched[0]
                prov = node.get("provenance") or node.get("source") or node.get("metadata", {})
                result = [prov] if prov else []
            else:
                result = []

        payload: dict = {"node_id": node_id, "provenance": result, "count": len(result)}
        if include_metadata and result:
            payload["sources"] = list({
                str(r.get("source", r.get("origin", "")))
                for r in result
                if isinstance(r, dict)
            })
        return payload
    except Exception as exc:
        log.exception("get_provenance failed")
        return {"error": str(exc), "provenance": []}


EXPORT_TOOLS = [
    {
        "name": "export_graph",
        "description": (
            "Export the Semantica knowledge graph to JSON, CSV, GraphML, Parquet, "
            "Turtle (RDF), N-Triples, RDF/XML, or JSON-LD."
        ),
        "inputSchema": EXPORT_GRAPH,
        "_handler": handle_export_graph,
    },
    {
        "name": "get_provenance",
        "description": "Retrieve the provenance and audit history for a specific node in the knowledge graph.",
        "inputSchema": GET_PROVENANCE,
        "_handler": handle_get_provenance,
    },
]