"""Database query functions for XER data."""

from datetime import datetime, timedelta

from xer_mcp.db import db


def is_driving_relationship(
    pred_early_end: str | None,
    succ_early_start: str | None,
    lag_hours: float,
    pred_type: str,
) -> bool:
    """Determine if a relationship is driving the successor's early start.

    A relationship is "driving" when the predecessor's completion (plus lag)
    determines the successor's early start date. This is computed by comparing
    dates with a tolerance for overnight gaps and calendar differences.

    Args:
        pred_early_end: Predecessor's early end date (ISO format)
        succ_early_start: Successor's early start date (ISO format)
        lag_hours: Lag duration in hours (can be negative)
        pred_type: Relationship type (FS, SS, FF, SF)

    Returns:
        True if the relationship is driving, False otherwise
    """
    if pred_early_end is None or succ_early_start is None:
        return False

    try:
        pred_end = datetime.fromisoformat(pred_early_end)
        succ_start = datetime.fromisoformat(succ_early_start)
    except (ValueError, TypeError):
        return False

    # For FS (Finish-to-Start): pred_end + lag should equal succ_start
    if pred_type == "FS":
        expected_start = pred_end + timedelta(hours=lag_hours)
        # Allow tolerance of 24 hours for overnight gaps and calendar differences
        diff = abs((succ_start - expected_start).total_seconds())
        return diff <= 24 * 3600  # 24 hours tolerance

    # For SS (Start-to-Start): would need pred_early_start, not implemented
    # For FF (Finish-to-Finish): would need succ_early_end, not implemented
    # For SF (Start-to-Finish): complex case, not implemented
    # Default to False for non-FS relationships for now
    return False


def query_activities(
    limit: int = 100,
    offset: int = 0,
    start_date: str | None = None,
    end_date: str | None = None,
    wbs_id: str | None = None,
    activity_type: str | None = None,
) -> tuple[list[dict], int]:
    """Query activities with pagination and filtering.

    Args:
        limit: Maximum number of results to return
        offset: Number of results to skip
        start_date: Filter activities starting on or after this date (YYYY-MM-DD)
        end_date: Filter activities ending on or before this date (YYYY-MM-DD)
        wbs_id: Filter by WBS ID
        activity_type: Filter by task type (TT_Task, TT_Mile, etc.)

    Returns:
        Tuple of (list of activity dicts, total count matching filters)
    """
    # Build WHERE clause
    conditions = []
    params: list = []

    if start_date:
        conditions.append("target_start_date >= ?")
        params.append(f"{start_date}T00:00:00")

    if end_date:
        conditions.append("target_end_date <= ?")
        params.append(f"{end_date}T23:59:59")

    if wbs_id:
        conditions.append("wbs_id = ?")
        params.append(wbs_id)

    if activity_type:
        conditions.append("task_type = ?")
        params.append(activity_type)

    where_clause = " AND ".join(conditions) if conditions else "1=1"

    # Get total count
    with db.cursor() as cur:
        cur.execute(f"SELECT COUNT(*) FROM activities WHERE {where_clause}", params)  # noqa: S608
        total = cur.fetchone()[0]

    # Get paginated results
    query = f"""
        SELECT task_id, task_code, task_name, task_type,
               target_start_date, target_end_date, status_code,
               driving_path_flag, wbs_id, total_float_hr_cnt
        FROM activities
        WHERE {where_clause}
        ORDER BY target_start_date, task_code
        LIMIT ? OFFSET ?
    """  # noqa: S608

    with db.cursor() as cur:
        cur.execute(query, [*params, limit, offset])
        rows = cur.fetchall()

    activities = [
        {
            "task_id": row[0],
            "task_code": row[1],
            "task_name": row[2],
            "task_type": row[3],
            "target_start_date": row[4],
            "target_end_date": row[5],
            "status_code": row[6],
            "driving_path_flag": bool(row[7]),
        }
        for row in rows
    ]

    return activities, total


def get_activity_by_id(activity_id: str) -> dict | None:
    """Get a single activity by ID with full details.

    Args:
        activity_id: The task_id to look up

    Returns:
        Activity dict with all fields, or None if not found
    """
    query = """
        SELECT a.task_id, a.task_code, a.task_name, a.task_type,
               a.wbs_id, w.wbs_name,
               a.target_start_date, a.target_end_date,
               a.act_start_date, a.act_end_date,
               a.total_float_hr_cnt, a.status_code, a.driving_path_flag
        FROM activities a
        LEFT JOIN wbs w ON a.wbs_id = w.wbs_id
        WHERE a.task_id = ?
    """

    with db.cursor() as cur:
        cur.execute(query, (activity_id,))
        row = cur.fetchone()

    if row is None:
        return None

    # Count predecessors and successors
    with db.cursor() as cur:
        cur.execute(
            "SELECT COUNT(*) FROM relationships WHERE task_id = ?",
            (activity_id,),
        )
        predecessor_count = cur.fetchone()[0]

        cur.execute(
            "SELECT COUNT(*) FROM relationships WHERE pred_task_id = ?",
            (activity_id,),
        )
        successor_count = cur.fetchone()[0]

    return {
        "task_id": row[0],
        "task_code": row[1],
        "task_name": row[2],
        "task_type": row[3],
        "wbs_id": row[4],
        "wbs_name": row[5],
        "target_start_date": row[6],
        "target_end_date": row[7],
        "act_start_date": row[8],
        "act_end_date": row[9],
        "total_float_hr_cnt": row[10],
        "status_code": row[11],
        "driving_path_flag": bool(row[12]),
        "predecessor_count": predecessor_count,
        "successor_count": successor_count,
    }


def query_relationships(
    limit: int = 100,
    offset: int = 0,
) -> tuple[list[dict], int]:
    """Query relationships with pagination.

    Args:
        limit: Maximum number of results to return
        offset: Number of results to skip

    Returns:
        Tuple of (list of relationship dicts, total count)
    """
    # Get total count
    with db.cursor() as cur:
        cur.execute("SELECT COUNT(*) FROM relationships")
        total = cur.fetchone()[0]

    # Get paginated results with activity names and early dates for driving computation
    query = """
        SELECT r.task_pred_id, r.task_id, succ.task_name,
               r.pred_task_id, pred.task_name,
               r.pred_type, r.lag_hr_cnt,
               pred.early_end_date, succ.early_start_date
        FROM relationships r
        LEFT JOIN activities succ ON r.task_id = succ.task_id
        LEFT JOIN activities pred ON r.pred_task_id = pred.task_id
        ORDER BY r.task_pred_id
        LIMIT ? OFFSET ?
    """

    with db.cursor() as cur:
        cur.execute(query, (limit, offset))
        rows = cur.fetchall()

    # Convert pred_type from internal format (PR_FS) to API format (FS)
    def format_pred_type(pred_type: str) -> str:
        if pred_type.startswith("PR_"):
            return pred_type[3:]
        return pred_type

    relationships = []
    for row in rows:
        pred_type = format_pred_type(row[5])
        driving = is_driving_relationship(
            pred_early_end=row[7],
            succ_early_start=row[8],
            lag_hours=row[6] or 0.0,
            pred_type=pred_type,
        )
        relationships.append(
            {
                "task_pred_id": row[0],
                "task_id": row[1],
                "task_name": row[2],
                "pred_task_id": row[3],
                "pred_task_name": row[4],
                "pred_type": pred_type,
                "lag_hr_cnt": row[6],
                "driving": driving,
            }
        )

    return relationships, total


def get_predecessors(activity_id: str) -> list[dict]:
    """Get predecessor activities for a given activity.

    Args:
        activity_id: The task_id to find predecessors for

    Returns:
        List of predecessor activity dicts with relationship info and driving flag
    """
    # Get successor's early start for driving calculation
    with db.cursor() as cur:
        cur.execute(
            "SELECT early_start_date FROM activities WHERE task_id = ?",
            (activity_id,),
        )
        succ_row = cur.fetchone()
        succ_early_start = succ_row[0] if succ_row else None

    query = """
        SELECT pred.task_id, pred.task_code, pred.task_name,
               r.pred_type, r.lag_hr_cnt, pred.early_end_date
        FROM relationships r
        JOIN activities pred ON r.pred_task_id = pred.task_id
        WHERE r.task_id = ?
        ORDER BY pred.task_code
    """

    with db.cursor() as cur:
        cur.execute(query, (activity_id,))
        rows = cur.fetchall()

    def format_pred_type(pred_type: str) -> str:
        if pred_type.startswith("PR_"):
            return pred_type[3:]
        return pred_type

    result = []
    for row in rows:
        pred_type = format_pred_type(row[3])
        driving = is_driving_relationship(
            pred_early_end=row[5],
            succ_early_start=succ_early_start,
            lag_hours=row[4] or 0.0,
            pred_type=pred_type,
        )
        result.append(
            {
                "task_id": row[0],
                "task_code": row[1],
                "task_name": row[2],
                "relationship_type": pred_type,
                "lag_hr_cnt": row[4],
                "driving": driving,
            }
        )

    return result


def get_successors(activity_id: str) -> list[dict]:
    """Get successor activities for a given activity.

    Args:
        activity_id: The task_id to find successors for

    Returns:
        List of successor activity dicts with relationship info and driving flag
    """
    # Get predecessor's early end for driving calculation
    with db.cursor() as cur:
        cur.execute(
            "SELECT early_end_date FROM activities WHERE task_id = ?",
            (activity_id,),
        )
        pred_row = cur.fetchone()
        pred_early_end = pred_row[0] if pred_row else None

    query = """
        SELECT succ.task_id, succ.task_code, succ.task_name,
               r.pred_type, r.lag_hr_cnt, succ.early_start_date
        FROM relationships r
        JOIN activities succ ON r.task_id = succ.task_id
        WHERE r.pred_task_id = ?
        ORDER BY succ.task_code
    """

    with db.cursor() as cur:
        cur.execute(query, (activity_id,))
        rows = cur.fetchall()

    def format_pred_type(pred_type: str) -> str:
        if pred_type.startswith("PR_"):
            return pred_type[3:]
        return pred_type

    result = []
    for row in rows:
        pred_type = format_pred_type(row[3])
        driving = is_driving_relationship(
            pred_early_end=pred_early_end,
            succ_early_start=row[5],
            lag_hours=row[4] or 0.0,
            pred_type=pred_type,
        )
        result.append(
            {
                "task_id": row[0],
                "task_code": row[1],
                "task_name": row[2],
                "relationship_type": pred_type,
                "lag_hr_cnt": row[4],
                "driving": driving,
            }
        )

    return result


def get_project_summary(project_id: str) -> dict | None:
    """Get project summary information.

    Args:
        project_id: The project ID to get summary for

    Returns:
        Dictionary with project summary or None if not found
    """
    # Get project info
    with db.cursor() as cur:
        cur.execute(
            """
            SELECT proj_id, proj_short_name, plan_start_date, plan_end_date, last_recalc_date
            FROM projects
            WHERE proj_id = ?
            """,
            (project_id,),
        )
        project_row = cur.fetchone()

    if project_row is None:
        return None

    # Get activity count
    with db.cursor() as cur:
        cur.execute("SELECT COUNT(*) FROM activities")
        activity_count = cur.fetchone()[0]

    # Get milestone count (both start and finish milestones)
    with db.cursor() as cur:
        cur.execute("SELECT COUNT(*) FROM activities WHERE task_type IN ('TT_Mile', 'TT_FinMile')")
        milestone_count = cur.fetchone()[0]

    # Get critical activity count
    with db.cursor() as cur:
        cur.execute("SELECT COUNT(*) FROM activities WHERE driving_path_flag = 1")
        critical_count = cur.fetchone()[0]

    return {
        "project_id": project_row[0],
        "project_name": project_row[1],
        "data_date": project_row[4],
        "plan_start_date": project_row[2],
        "plan_end_date": project_row[3],
        "activity_count": activity_count,
        "milestone_count": milestone_count,
        "critical_activity_count": critical_count,
    }


def query_milestones() -> list[dict]:
    """Query all milestone activities (both start and finish milestones).

    Returns:
        List of milestone activity dicts with milestone_type (start/finish)
    """
    query = """
        SELECT task_id, task_code, task_name,
               target_start_date, target_end_date, status_code, milestone_type
        FROM activities
        WHERE task_type IN ('TT_Mile', 'TT_FinMile')
        ORDER BY target_start_date, task_code
    """

    with db.cursor() as cur:
        cur.execute(query)
        rows = cur.fetchall()

    return [
        {
            "task_id": row[0],
            "task_code": row[1],
            "task_name": row[2],
            "target_start_date": row[3],
            "target_end_date": row[4],
            "status_code": row[5],
            "milestone_type": row[6],
        }
        for row in rows
    ]


def query_critical_path() -> list[dict]:
    """Query all activities on the critical path.

    Returns:
        List of critical path activity dicts ordered by start date
    """
    query = """
        SELECT task_id, task_code, task_name, task_type,
               target_start_date, target_end_date,
               total_float_hr_cnt, status_code
        FROM activities
        WHERE driving_path_flag = 1
        ORDER BY target_start_date, task_code
    """

    with db.cursor() as cur:
        cur.execute(query)
        rows = cur.fetchall()

    return [
        {
            "task_id": row[0],
            "task_code": row[1],
            "task_name": row[2],
            "task_type": row[3],
            "target_start_date": row[4],
            "target_end_date": row[5],
            "total_float_hr_cnt": row[6],
            "status_code": row[7],
        }
        for row in rows
    ]