"""
Schema Commands - SST schema management for the LightWave CLI.

SST Reference: packages/lightwave-core/lightwave/schema/definitions/cli.yaml
Domain: schema (runtime: python)
"""

from __future__ import annotations

from pathlib import Path
from typing import TYPE_CHECKING

if TYPE_CHECKING:
    from typing import Any

from lightwave.cli.runner import CommandError


def find_definitions_dir() -> Path:
    """Find the schema definitions directory."""
    # Look in common locations
    search_paths = [
        Path.cwd() / "packages" / "lightwave-core" / "lightwave" / "schema" / "definitions",
        Path.cwd() / "lightwave" / "schema" / "definitions",
        Path(__file__).parent.parent / "schema" / "definitions",
    ]

    for path in search_paths:
        if path.exists():
            return path

    raise CommandError("Could not find schema definitions directory")


def validate_schema(
    args: list[str],
    *,
    json_output: bool = False,
    dry_run: bool = False,
    verbose: bool = False,
) -> dict[str, Any] | None:
    """
    Validate all YAML definitions against Pydantic schemas.

    SST: domains.schema.commands[name=validate]
    flags: [--strict, --fix]
    """
    import yaml

    definitions_dir = find_definitions_dir()

    # Parse flags
    strict = "--strict" in args

    if verbose:
        print(f"Validating schemas in: {definitions_dir}")
        print(f"Strict mode: {strict}")

    if dry_run:
        if json_output:
            return {"success": True, "dry_run": True, "path": str(definitions_dir)}
        print(f"[dry-run] Would validate schemas in: {definitions_dir}")
        return None

    # Find all YAML files
    yaml_files = list(definitions_dir.glob("**/*.yaml"))
    yaml_files += list(definitions_dir.glob("**/*.yml"))

    results = []
    errors = []

    for yaml_file in yaml_files:
        try:
            with open(yaml_file) as f:
                data = yaml.safe_load(f)

            # Basic validation - check required fields
            if data is None:
                errors.append({"file": str(yaml_file), "error": "Empty file"})
                continue

            # Check for _meta section in definition files
            if yaml_file.name != "self-format.yaml" and not yaml_file.parent.name == "meta":
                if "_meta" not in data and "version" not in data:
                    if strict:
                        errors.append({"file": str(yaml_file), "error": "Missing _meta or version field"})

            results.append({"file": str(yaml_file), "valid": True})

        except yaml.YAMLError as e:
            errors.append({"file": str(yaml_file), "error": f"YAML parse error: {e}"})
        except Exception as e:
            errors.append({"file": str(yaml_file), "error": str(e)})

    if json_output:
        return {
            "success": len(errors) == 0,
            "total": len(yaml_files),
            "valid": len(results),
            "errors": len(errors),
            "error_details": errors,
        }

    # Print results
    print(f"\nSchema Validation: {len(results)}/{len(yaml_files)} valid")
    if errors:
        print("\nErrors:")
        for err in errors:
            print(f"  {err['file']}: {err['error']}")
        raise CommandError(f"{len(errors)} schema validation errors")

    print("All schemas valid!")
    return None


def drift_report(
    args: list[str],
    *,
    json_output: bool = False,
    verbose: bool = False,
) -> dict[str, Any] | None:
    """
    Generate drift report (YAML vs implementation).

    SST: domains.schema.commands[name=drift]
    flags: [--output]
    """
    # Parse flags
    output_file = None
    for i, arg in enumerate(args):
        if arg == "--output" and i + 1 < len(args):
            output_file = args[i + 1]

    if verbose:
        print("Generating drift report...")

    # TODO: Implement full drift detection
    # For now, return placeholder
    report = {
        "generated_at": str(__import__("datetime").datetime.now()),
        "drift_detected": False,
        "items": [],
        "summary": "Drift detection not yet fully implemented",
    }

    if output_file:
        import json

        with open(output_file, "w") as f:
            json.dump(report, f, indent=2)
        print(f"Report written to {output_file}")

    if json_output:
        return report

    print("\nDrift Report")
    print("=" * 50)
    print(f"Generated: {report['generated_at']}")
    print(f"Drift detected: {report['drift_detected']}")
    print(report["summary"])

    return None


def reconcile_schema(
    args: list[str],
    *,
    json_output: bool = False,
    dry_run: bool = False,
    verbose: bool = False,
) -> dict[str, Any] | None:
    """
    Reconcile differences between spec and implementation.

    SST: domains.schema.commands[name=reconcile]
    flags: [--dry-run]
    """
    if verbose:
        print("Reconciling schema differences...")

    if dry_run:
        if json_output:
            return {"success": True, "dry_run": True, "changes": []}
        print("[dry-run] Would reconcile schema differences")
        return None

    # TODO: Implement reconciliation
    result = {
        "success": True,
        "changes_made": 0,
        "message": "Schema reconciliation not yet implemented",
    }

    if json_output:
        return result

    print(result["message"])
    return None


def generate_types(
    args: list[str],
    *,
    json_output: bool = False,
    dry_run: bool = False,
    verbose: bool = False,
) -> dict[str, Any] | None:
    """
    Generate types for target language (go|typescript).

    SST: domains.schema.commands[name=generate]
    args: [target]
    flags: [--output]
    """
    if not args:
        raise CommandError("Target language required. Example: lw schema generate go")

    target = args[0]
    if target not in ("go", "typescript", "ts"):
        raise CommandError(f"Unknown target: {target}. Use 'go' or 'typescript'")

    # Parse flags
    output_path = None
    for i, arg in enumerate(args[1:]):
        if arg == "--output" and i + 1 < len(args[1:]):
            output_path = args[1:][i + 1]

    if verbose:
        print(f"Generating {target} types...")

    if dry_run:
        if json_output:
            return {"success": True, "dry_run": True, "target": target, "output": output_path}
        print(f"[dry-run] Would generate {target} types")
        return None

    # TODO: Implement type generation
    result = {
        "success": True,
        "target": target,
        "message": f"Type generation for {target} not yet implemented",
    }

    if json_output:
        return result

    print(result["message"])
    return None


def schema_coverage(
    args: list[str],
    *,
    json_output: bool = False,
    verbose: bool = False,
) -> dict[str, Any] | None:
    """
    Show SST coverage metrics.

    SST: domains.schema.commands[name=coverage]
    """
    definitions_dir = find_definitions_dir()

    if verbose:
        print(f"Calculating coverage for: {definitions_dir}")

    # Count YAML files
    yaml_files = list(definitions_dir.glob("**/*.yaml"))
    yaml_files += list(definitions_dir.glob("**/*.yml"))

    # TODO: Calculate actual coverage against Pydantic models
    coverage = {
        "total_definitions": len(yaml_files),
        "with_pydantic_schema": 0,  # TODO: count actual coverage
        "coverage_percent": 0.0,
        "uncovered": [],
    }

    if json_output:
        return coverage

    print("\nSST Coverage Report")
    print("=" * 50)
    print(f"Total definitions: {coverage['total_definitions']}")
    print(f"With Pydantic schema: {coverage['with_pydantic_schema']}")
    print(f"Coverage: {coverage['coverage_percent']:.1f}%")

    return None
