"""Deduplication workflow.

Reuses:
    - ``databridge.reconciler.fuzzy_deduplicate(source_path, column, threshold, limit)``

IKE integration (optional):
    - P1 Knowledge Base: Ingest dedup patterns into institutional memory
"""

from __future__ import annotations

from typing import Any, Dict, List, Optional

from databridge_core.sdk.core.context import SDKContext
from databridge_core.sdk.core.exceptions import NotImplementedStubError
from databridge_core.sdk.core.types import CompiledArtifact, Result
from databridge_core.sdk.workflows.base import BaseWorkflow
from databridge_core.sdk.workflows.result import WorkflowResult
from databridge_core.sdk.workflows.step import workflow_step


class DeduplicationWorkflow(BaseWorkflow):
    """Fuzzy-deduplicate records in a data source.

    When IKE is available, deduplication patterns are ingested into
    IKE's P1 knowledge base for institutional memory.

    Reuses:
        - ``databridge.reconciler.fuzzy_deduplicate(source_path, column, threshold, limit)``
    """

    name = "data_cleaning.deduplication"
    category = "data_cleaning"
    description = "Fuzzy-deduplicate records by column similarity"
    required_params = ["source_path", "column"]
    optional_params = {
        "threshold": 90,
        "limit": 10,
        "ike_ingest": True,
    }

    def validate(self, params: Dict[str, Any]) -> Dict[str, Any]:
        self._check_required(params)
        return self._apply_defaults(params)

    def execute(
        self, params: Dict[str, Any], ctx: Optional[SDKContext] = None
    ) -> Result:
        steps = [self._deduplicate(params, ctx)]
        # IKE P1: Ingest dedup patterns into KB
        if params.get("ike_ingest") and ctx and ctx.ike.available:
            steps.append(self._ike_ingest_dedup(params, ctx))
        # Graph integration
        if ctx and ctx.graphs.available:
            steps.append(self._graph_record_lineage(params, ctx))
            steps.append(self._graph_index_vectors(params, ctx))
        return WorkflowResult.from_steps(self.name, steps)

    def compile_to_snowflake(
        self, params: Dict[str, Any], ctx: Optional[SDKContext] = None
    ) -> List[CompiledArtifact]:
        raise NotImplementedStubError(
            self.name,
            "compile_to_snowflake",
            "Generate QUALIFY ROW_NUMBER() OVER (PARTITION BY ...) dedup pattern",
        )

    @workflow_step("deduplicate", "Run fuzzy deduplication")
    def _deduplicate(self, params: Dict[str, Any], ctx: Optional[SDKContext] = None):
        # REUSE: databridge.reconciler.fuzzy_deduplicate(
        #     source_path=params["source_path"],
        #     column=params["column"],
        #     threshold=params["threshold"],
        #     limit=params["limit"],
        # )
        raise NotImplementedStubError(
            self.name,
            "deduplicate",
            "databridge.reconciler.fuzzy_deduplicate(source_path, column, threshold, limit)",
        )

    @workflow_step("ike_ingest_dedup", "Ingest dedup patterns into IKE KB")
    def _ike_ingest_dedup(self, params: Dict[str, Any], ctx: Optional[SDKContext] = None):
        # IKE P1: Ingest deduplication patterns (duplicate groups,
        # similarity scores, chosen survivors) into the institutional
        # knowledge base for future reference.
        #
        # ctx.ike.ingest_knowledge(
        #     content=f"Dedup on {params['source_path']}.{params['column']}: {summary}",
        #     source_type="run_result",
        #     tags=["deduplication", params["column"]],
        # )
        raise NotImplementedStubError(
            self.name,
            "ike_ingest_dedup",
            "ctx.ike.ingest_knowledge(content, source_type='run_result') — IKE P1 KB ingest",
        )

    # --- Graph integration ---

    @workflow_step("graph_record_lineage", "Record DERIVED_FROM edges in lineage")
    def _graph_record_lineage(self, params: Dict[str, Any], ctx: Optional[SDKContext] = None):
        # ctx.graphs.record_lineage_edge("sdk", original_record, survivor_record, "DERIVED")
        raise NotImplementedStubError(
            self.name,
            "graph_record_lineage",
            "ctx.graphs.record_lineage_edge — DERIVED_FROM edges for dedup survivors",
        )

    @workflow_step("graph_index_vectors", "Index dedup patterns in vector store")
    def _graph_index_vectors(self, params: Dict[str, Any], ctx: Optional[SDKContext] = None):
        # ctx.graphs.index_content(
        #     doc_id=f"dedup_{source}_{column}", content=dedup_summary,
        #     source_type="dedup_pattern", metadata={...},
        # )
        raise NotImplementedStubError(
            self.name,
            "graph_index_vectors",
            "ctx.graphs.index_content(doc_id, content, 'dedup_pattern', metadata)",
        )
