#!/usr/bin/env python3
r"""
generate_time_bin_profile_chunkedV3.py

V3 patched time-bin profile generator.

Based on generate_time_bin_profile_chunkedV2.py, with the same safety style used in
generate_site_totals_chunkedV3_1.py.

Fixes / improvements over V2:
- Uses C:\DuckDBTemp by default, matching the recent stable V3/V3.1 scripts.
- Disables DuckDB Unicode progress bar to avoid PowerShell mojibake output.
- Uses defensive CSV parsing for existing time_bin_profile.csv.
- Writes explicit zero-row month marker rows so months such as 2018-12 do not loop forever.
- Excludes zero-row marker rows from final aggregation.
- Uses all_varchar=true when reading output CSV back through DuckDB.
- Adds detailed traceback printing if a month fails.
- Writes/refreshes final JSON after every successful month.
- Keeps one-month-per-run wrapper compatibility.

Outputs:
    A:\TrafficAnalytics\PROJECTS\reports\deduped\time_bin_profile.csv
    A:\TrafficAnalytics\PROJECTS\reports\deduped\time_bin_profile_final.json
"""

from __future__ import annotations

import csv
import json
import sys
import time
import traceback
from dataclasses import dataclass
from datetime import date
from pathlib import Path

import duckdb


MAIN_DB = r"A:\TrafficAnalytics\DATA\SCATS\scats.duckdb"
CONT_DB = r"A:\TrafficAnalytics\DATA\SCATS\scats_continuation.duckdb"
REC_DB = r"A:\TrafficAnalytics\DATA\SCATS\scats_recovery.duckdb"

TEMP_DIR = r"C:\DuckDBTemp"
MEMORY_LIMIT = "50GB"
MAX_TEMP_DIRECTORY_SIZE = "1000GiB"
THREADS = 10

REPORT_DIR = Path(r"A:\TrafficAnalytics\PROJECTS\reports\deduped")
TIME_BIN_CSV = REPORT_DIR / "time_bin_profile.csv"
FINAL_JSON = REPORT_DIR / "time_bin_profile_final.json"

DATE_RANGE_START = date(2014, 1, 1)
DATE_RANGE_END = date(2026, 4, 7)

ZERO_ROW_TIME_BIN_MARKER = "__ZERO_ROW_MONTH__"


@dataclass(frozen=True)
class MonthWindow:
    month_start: date
    next_month_start: date
    label: str


def fmt_int(value):
    if value is None:
        return "N/A"
    return f"{int(value):,}"


def fmt_seconds(seconds: float) -> str:
    seconds = max(0, int(seconds))
    hours, rem = divmod(seconds, 3600)
    minutes, secs = divmod(rem, 60)
    if hours > 0:
        return f"{hours}h {minutes}m {secs}s"
    if minutes > 0:
        return f"{minutes}m {secs}s"
    return f"{secs}s"


def fmt_gb(num_bytes: int) -> str:
    return f"{num_bytes / (1024 ** 3):,.1f} GB"


def month_iter(start: date, end: date) -> list[MonthWindow]:
    months: list[MonthWindow] = []
    y, m = start.year, start.month

    while True:
        month_start = date(y, m, 1)
        next_month_start = date(y + 1, 1, 1) if m == 12 else date(y, m + 1, 1)
        months.append(MonthWindow(month_start, next_month_start, f"{y:04d}-{m:02d}"))

        if y == end.year and m == end.month:
            break

        if m == 12:
            y += 1
            m = 1
        else:
            m += 1

    return months


def connect_db() -> duckdb.DuckDBPyConnection:
    Path(TEMP_DIR).mkdir(parents=True, exist_ok=True)
    REPORT_DIR.mkdir(parents=True, exist_ok=True)

    con = duckdb.connect(MAIN_DB, read_only=False)
    con.execute(f"SET memory_limit='{MEMORY_LIMIT}'")
    con.execute(f"SET temp_directory='{TEMP_DIR.replace(chr(92), '/')}'")
    con.execute(f"SET max_temp_directory_size='{MAX_TEMP_DIRECTORY_SIZE}'")
    con.execute(f"SET threads={THREADS}")
    con.execute("SET preserve_insertion_order=false")

    # Important: disable progress bar because PowerShell commonly renders
    # DuckDB Unicode block characters as mojibake and can obscure errors.
    try:
        con.execute("SET enable_progress_bar=false")
    except Exception:
        pass

    con.execute(f"ATTACH '{CONT_DB.replace(chr(92), '/')}' AS cont")
    con.execute(f"ATTACH '{REC_DB.replace(chr(92), '/')}' AS rec")

    return con


def preflight_check(con: duckdb.DuckDBPyConnection) -> None:
    print("Running preflight checks...", flush=True)
    for obj in ["scats_clean", "cont.scats_clean", "rec.scats_clean"]:
        con.execute(f"SELECT COUNT(*) FROM {obj} LIMIT 1").fetchone()
        print(f"  OK: {obj}", flush=True)


def ensure_time_bin_csv() -> None:
    REPORT_DIR.mkdir(parents=True, exist_ok=True)

    if not TIME_BIN_CSV.exists():
        with TIME_BIN_CSV.open("w", newline="", encoding="utf-8") as f:
            writer = csv.writer(f)
            writer.writerow([
                "month_label",
                "month_start",
                "next_month_start",
                "time_bin",
                "month_time_bin_volume",
                "days_in_month_loaded",
                "month_elapsed_seconds",
                "completed_at_epoch",
                "row_type",
            ])
        return

    # If an older V2 CSV exists without row_type, leave it alone.
    # DictReader handles missing row_type as None; final SQL handles both.
    # We do not rewrite the file while a process may be running.


def load_completed_months() -> set[str]:
    ensure_time_bin_csv()
    done: set[str] = set()

    with TIME_BIN_CSV.open("r", newline="", encoding="utf-8-sig") as f:
        reader = csv.DictReader(f)

        if not reader.fieldnames or "month_label" not in reader.fieldnames:
            raise RuntimeError(f"Invalid CSV header in {TIME_BIN_CSV}: {reader.fieldnames}")

        for row in reader:
            label = (row.get("month_label") or "").strip()
            if not label:
                continue

            # A month is complete if at least one row exists for that month,
            # including the explicit zero-row marker.
            done.add(label)

    return done


def append_time_bin_rows(rows: list[tuple], month: MonthWindow, days_in_month_loaded: int, month_elapsed_seconds: float) -> None:
    ensure_time_bin_csv()
    now_epoch = round(time.time(), 3)

    with TIME_BIN_CSV.open("a", newline="", encoding="utf-8") as f:
        writer = csv.writer(f)

        if not rows:
            writer.writerow([
                month.label,
                month.month_start.isoformat(),
                month.next_month_start.isoformat(),
                ZERO_ROW_TIME_BIN_MARKER,
                "",
                0,
                round(month_elapsed_seconds, 3),
                now_epoch,
                "zero_row_month",
            ])
            return

        for time_bin, month_time_bin_volume in rows:
            writer.writerow([
                month.label,
                month.month_start.isoformat(),
                month.next_month_start.isoformat(),
                time_bin,
                int(month_time_bin_volume) if month_time_bin_volume is not None else "",
                days_in_month_loaded,
                round(month_elapsed_seconds, 3),
                now_epoch,
                "time_bin_total",
            ])


def current_temp_usage_bytes(temp_dir: str) -> int:
    total = 0
    root = Path(temp_dir)

    if not root.exists():
        return 0

    for p in root.rglob("*"):
        try:
            if p.is_file():
                total += p.stat().st_size
        except OSError:
            pass

    return total


def find_next_incomplete_month(months: list[MonthWindow], completed: set[str]) -> MonthWindow | None:
    for month in months:
        if month.label not in completed:
            return month
    return None


def query_month_time_bin_totals(con: duckdb.DuckDBPyConnection, month: MonthWindow) -> tuple[list[tuple], int]:
    start_s = month.month_start.isoformat()
    end_s = month.next_month_start.isoformat()

    sql = f"""
    WITH unified AS (
        SELECT scats_site, count_date, detector, source_file_id, interval_index, time_bin, volume_15m
        FROM scats_clean
        WHERE count_date >= DATE '{start_s}'
          AND count_date <  DATE '{end_s}'

        UNION ALL

        SELECT scats_site, count_date, detector, source_file_id, interval_index, time_bin, volume_15m
        FROM cont.scats_clean
        WHERE count_date >= DATE '{start_s}'
          AND count_date <  DATE '{end_s}'

        UNION ALL

        SELECT scats_site, count_date, detector, source_file_id, interval_index, time_bin, volume_15m
        FROM rec.scats_clean
        WHERE count_date >= DATE '{start_s}'
          AND count_date <  DATE '{end_s}'
    ),
    ranked AS (
        SELECT
            scats_site,
            count_date,
            detector,
            interval_index,
            source_file_id,
            time_bin,
            volume_15m,
            ROW_NUMBER() OVER (
                PARTITION BY scats_site, count_date, detector, interval_index
                ORDER BY source_file_id
            ) AS rn
        FROM unified
        WHERE scats_site IS NOT NULL
          AND count_date IS NOT NULL
          AND detector IS NOT NULL
          AND interval_index IS NOT NULL
          AND time_bin IS NOT NULL
    )
    SELECT
        time_bin,
        SUM(volume_15m) AS month_time_bin_volume
    FROM ranked
    WHERE rn = 1
      AND volume_15m IS NOT NULL
    GROUP BY time_bin
    ORDER BY time_bin
    """

    rows = con.execute(sql).fetchall()

    days_sql = f"""
    WITH unified AS (
        SELECT scats_site, count_date, detector, source_file_id, interval_index, time_bin, volume_15m
        FROM scats_clean
        WHERE count_date >= DATE '{start_s}'
          AND count_date <  DATE '{end_s}'

        UNION ALL

        SELECT scats_site, count_date, detector, source_file_id, interval_index, time_bin, volume_15m
        FROM cont.scats_clean
        WHERE count_date >= DATE '{start_s}'
          AND count_date <  DATE '{end_s}'

        UNION ALL

        SELECT scats_site, count_date, detector, source_file_id, interval_index, time_bin, volume_15m
        FROM rec.scats_clean
        WHERE count_date >= DATE '{start_s}'
          AND count_date <  DATE '{end_s}'
    ),
    ranked AS (
        SELECT
            scats_site,
            count_date,
            detector,
            interval_index,
            source_file_id,
            ROW_NUMBER() OVER (
                PARTITION BY scats_site, count_date, detector, interval_index
                ORDER BY source_file_id
            ) AS rn
        FROM unified
        WHERE scats_site IS NOT NULL
          AND count_date IS NOT NULL
          AND detector IS NOT NULL
          AND interval_index IS NOT NULL
    )
    SELECT COUNT(DISTINCT count_date)
    FROM ranked
    WHERE rn = 1
    """

    days_in_month_loaded = con.execute(days_sql).fetchone()[0]
    return rows, int(days_in_month_loaded or 0)


def build_final_result(con: duckdb.DuckDBPyConnection, months: list[MonthWindow]) -> dict:
    completed = load_completed_months()
    done_labels = [m.label for m in months if m.label in completed]
    all_labels = {m.label for m in months}

    zero_row_months: list[str] = []
    rows_in_csv = 0

    with TIME_BIN_CSV.open("r", newline="", encoding="utf-8-sig") as f:
        reader = csv.DictReader(f)
        for row in reader:
            rows_in_csv += 1
            label = (row.get("month_label") or "").strip()
            time_bin = (row.get("time_bin") or "").strip()
            row_type = (row.get("row_type") or "").strip()

            if label in all_labels and (row_type == "zero_row_month" or time_bin == ZERO_ROW_TIME_BIN_MARKER):
                zero_row_months.append(label)

    zero_row_months = sorted(set(zero_row_months))

    base_payload = {
        "metric_name": "time_bin_profile",
        "date_range_start": DATE_RANGE_START.isoformat(),
        "date_range_end": DATE_RANGE_END.isoformat(),
        "months_total": len(months),
        "months_completed": len(done_labels),
        "is_complete": len(done_labels) == len(months),
        "rows_in_time_bin_profile_csv": rows_in_csv,
        "busiest_time_bin": None,
        "busiest_time_bin_total_volume": None,
        "busiest_time_bin_average_daily_volume": None,
        "quietest_time_bin": None,
        "quietest_time_bin_total_volume": None,
        "total_days_loaded": 0,
        "zero_row_months": zero_row_months,
        "total_elapsed_seconds": 0.0,
        "generated_at_epoch": round(time.time(), 3),
        "time_bin_profile_csv": str(TIME_BIN_CSV),
    }

    if not done_labels:
        return base_payload

    time_bin_csv_path = str(TIME_BIN_CSV).replace(chr(92), "/")

    sql = f"""
    WITH raw_csv AS (
        SELECT *
        FROM read_csv_auto('{time_bin_csv_path}', header=true, all_varchar=true)
    ),
    tb AS (
        SELECT
            CAST(time_bin AS VARCHAR) AS time_bin,
            TRY_CAST(month_time_bin_volume AS BIGINT) AS month_time_bin_volume,
            TRY_CAST(days_in_month_loaded AS BIGINT) AS days_in_month_loaded
        FROM raw_csv
        WHERE time_bin IS NOT NULL
          AND time_bin <> ''
          AND time_bin <> '{ZERO_ROW_TIME_BIN_MARKER}'
          AND month_time_bin_volume IS NOT NULL
          AND month_time_bin_volume <> ''
    ),
    totals AS (
        SELECT
            time_bin,
            SUM(month_time_bin_volume) AS total_time_bin_volume
        FROM tb
        GROUP BY time_bin
    ),
    day_totals AS (
        SELECT
            SUM(days_in_month_loaded) AS total_days_loaded
        FROM (
            SELECT
                month_label,
                MAX(TRY_CAST(days_in_month_loaded AS BIGINT)) AS days_in_month_loaded
            FROM raw_csv
            WHERE month_label IS NOT NULL
              AND month_label <> ''
              AND time_bin IS NOT NULL
              AND time_bin <> ''
              AND time_bin <> '{ZERO_ROW_TIME_BIN_MARKER}'
            GROUP BY month_label
        )
    ),
    best AS (
        SELECT
            time_bin,
            total_time_bin_volume
        FROM totals
        ORDER BY total_time_bin_volume DESC, time_bin
        LIMIT 1
    ),
    quietest AS (
        SELECT
            time_bin,
            total_time_bin_volume
        FROM totals
        ORDER BY total_time_bin_volume ASC, time_bin
        LIMIT 1
    ),
    elapsed AS (
        SELECT SUM(month_elapsed_seconds) AS total_elapsed_seconds
        FROM (
            SELECT
                month_label,
                MAX(TRY_CAST(month_elapsed_seconds AS DOUBLE)) AS month_elapsed_seconds
            FROM raw_csv
            WHERE month_label IS NOT NULL
              AND month_label <> ''
            GROUP BY month_label
        )
    )
    SELECT
        (SELECT COUNT(*) FROM tb) AS rows_in_time_bin_profile_csv,
        best.time_bin AS busiest_time_bin,
        best.total_time_bin_volume AS busiest_time_bin_total_volume,
        quietest.time_bin AS quietest_time_bin,
        quietest.total_time_bin_volume AS quietest_time_bin_total_volume,
        day_totals.total_days_loaded,
        CASE
            WHEN day_totals.total_days_loaded IS NULL OR day_totals.total_days_loaded = 0 THEN NULL
            ELSE best.total_time_bin_volume * 1.0 / day_totals.total_days_loaded
        END AS busiest_time_bin_average_daily_volume,
        elapsed.total_elapsed_seconds
    FROM best
    CROSS JOIN quietest
    CROSS JOIN day_totals
    CROSS JOIN elapsed
    """

    row = con.execute(sql).fetchone()

    if row:
        base_payload.update({
            "rows_in_time_bin_profile_csv": row[0],
            "busiest_time_bin": row[1],
            "busiest_time_bin_total_volume": row[2],
            "quietest_time_bin": row[3],
            "quietest_time_bin_total_volume": row[4],
            "total_days_loaded": row[5],
            "busiest_time_bin_average_daily_volume": row[6],
            "total_elapsed_seconds": round(float(row[7]), 3) if row[7] is not None else 0.0,
        })

    return base_payload


def save_final_json(payload: dict) -> None:
    with FINAL_JSON.open("w", encoding="utf-8") as f:
        json.dump(payload, f, indent=2)


def print_final_payload(payload: dict) -> None:
    print("-" * 90, flush=True)
    print(f"Months completed     : {payload['months_completed']}/{payload['months_total']}", flush=True)
    print(f"Is complete          : {payload['is_complete']}", flush=True)
    print(f"Zero-row months      : {', '.join(payload['zero_row_months']) if payload['zero_row_months'] else 'None'}", flush=True)
    print(f"Rows in profile CSV  : {fmt_int(payload['rows_in_time_bin_profile_csv'])}", flush=True)
    print(f"Total days loaded    : {fmt_int(payload['total_days_loaded'])}", flush=True)
    print(f"Busiest time bin     : {payload['busiest_time_bin']}", flush=True)
    print(f"Busiest bin volume   : {fmt_int(payload['busiest_time_bin_total_volume'])}", flush=True)
    print(f"Avg daily busiest bin: {fmt_int(payload['busiest_time_bin_average_daily_volume'])}", flush=True)
    print(f"Quietest time bin    : {payload['quietest_time_bin']}", flush=True)
    print(f"Quietest bin volume  : {fmt_int(payload['quietest_time_bin_total_volume'])}", flush=True)
    print(f"Total elapsed        : {fmt_seconds(payload['total_elapsed_seconds'])}", flush=True)
    print("-" * 90, flush=True)


def main() -> None:
    overall_start = time.time()
    months = month_iter(DATE_RANGE_START, DATE_RANGE_END)
    total_months = len(months)

    completed_before = load_completed_months()
    next_month = find_next_incomplete_month(months, completed_before)

    print("=" * 90, flush=True)
    print("TIME BIN PROFILE V3 - ONE MONTH PER EXECUTION", flush=True)
    print("=" * 90, flush=True)
    print(f"Date range           : {DATE_RANGE_START} to {DATE_RANGE_END}", flush=True)
    print(f"Months total         : {total_months}", flush=True)
    print(f"Already completed    : {sum(1 for m in months if m.label in completed_before)}/{total_months}", flush=True)
    print(f"Time-bin CSV output  : {TIME_BIN_CSV}", flush=True)
    print(f"Final JSON output    : {FINAL_JSON}", flush=True)
    print(f"Temp directory       : {TEMP_DIR}", flush=True)
    print(f"Memory limit         : {MEMORY_LIMIT}", flush=True)
    print(f"Threads              : {THREADS}", flush=True)
    print("=" * 90, flush=True)

    con = connect_db()

    try:
        preflight_check(con)

        if next_month is None:
            final_payload = build_final_result(con, months)
            save_final_json(final_payload)
            print("All months are already complete. Nothing to do.", flush=True)
            print_final_payload(final_payload)
            return

        next_idx = next(i for i, m in enumerate(months, start=1) if m.label == next_month.label)
        print(f"Next month to run    : {next_month.label} ({next_idx}/{total_months})", flush=True)
        print(f"Date window          : {next_month.month_start.isoformat()} to < {next_month.next_month_start.isoformat()}", flush=True)

        temp_before = current_temp_usage_bytes(TEMP_DIR)
        print(f"Temp usage before    : {fmt_gb(temp_before)}", flush=True)

        month_start_ts = time.time()
        rows, days_in_month_loaded = query_month_time_bin_totals(con, next_month)
        month_elapsed = time.time() - month_start_ts

        append_time_bin_rows(rows, next_month, days_in_month_loaded, month_elapsed)

        temp_after = current_temp_usage_bytes(TEMP_DIR)
        temp_delta = temp_after - temp_before

        month_best_time_bin = None
        month_best_volume = None
        if rows:
            month_best_time_bin, month_best_volume = max(rows, key=lambda x: (x[1] if x[1] is not None else -1, str(x[0])))

        final_payload = build_final_result(con, months)
        save_final_json(final_payload)

        print("-" * 90, flush=True)
        print(f"Finished month       : {next_month.label}", flush=True)
        print(f"Rows written         : {fmt_int(len(rows))}", flush=True)
        print(f"Days loaded          : {fmt_int(days_in_month_loaded)}", flush=True)
        print(f"Month best time bin  : {month_best_time_bin if month_best_time_bin is not None else 'N/A'}", flush=True)
        print(f"Month best volume    : {fmt_int(month_best_volume) if month_best_volume is not None else 'N/A'}", flush=True)
        print(f"Month elapsed        : {fmt_seconds(month_elapsed)}", flush=True)
        print(f"Temp usage after     : {fmt_gb(temp_after)}", flush=True)
        print(f"Temp delta           : {fmt_gb(temp_delta)}", flush=True)
        print(f"Overall elapsed      : {fmt_seconds(time.time() - overall_start)}", flush=True)

        print_final_payload(final_payload)

        upcoming = find_next_incomplete_month(months, load_completed_months())
        if upcoming is not None:
            print(f"Next launch will start at month: {upcoming.label}", flush=True)
        else:
            print("ARCHIVE COMPLETE.", flush=True)

    except Exception:
        print("\nERROR: generate_time_bin_profile_chunkedV3.py failed.", file=sys.stderr, flush=True)
        traceback.print_exc(file=sys.stderr)
        raise
    finally:
        try:
            con.close()
        except Exception:
            pass


if __name__ == "__main__":
    try:
        main()
    except KeyboardInterrupt:
        print("\nInterrupted by user.", flush=True)
        sys.exit(130)