141 lines
6.9 KiB
Python
141 lines
6.9 KiB
Python
"""
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===============================================================================
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FILE: main_etl.py
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PROJECT: SCUD Orion AI (Unified Architecture)
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ROLE: Главная точка входа ETL-конвейера СКУД ⟷ 1С:ЗУП.
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===============================================================================
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"""
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import os
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import sys
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import argparse
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import logging
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import pandas as pd
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from datetime import datetime, timedelta
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from services.scud_etl.pipeline import load_best_snapshot_for_date, load_1c_files_for_date
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from services.scud_etl.merger import merge_scud_and_1c, calculate_summary_metrics
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from services.scud_etl.anomaly_detector import detect_registry_anomalies
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from services.scud_etl.svodka_generator import generate_svodka_service
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from services.scud_etl.otchet_generator import generate_otchet_service
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from services.text_reporter import generate_markdown_report
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from services.scud_export import run_export
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from services.share_copier import copy_1c_files_from_share
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from services.excel_exporter import export_raw_scud
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logging.basicConfig(level=logging.INFO, format="[%(asctime)s] [%(levelname)s] %(message)s")
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def main():
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parser = argparse.ArgumentParser(description="Модульный контроллинг СКУД ⟷ 1С")
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parser.add_argument("-d", "--debug", action="store_true", help="Режим отладки")
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parser.add_argument("--skip-export", action="store_true", help="Пропустить выгрузку СКУД из MS SQL")
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parser.add_argument("--date", type=str, default=None, help="Дата расчета в формате ДД.ММ.ГГГГ")
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parser.add_argument("--time", type=str, default=None, help="Время среза для сводки (например, 14:30)")
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parser.add_argument("--snapshot", type=str, default=None, help="Точный ID снапшота для расчета")
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args = parser.parse_args()
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print("=" * 60)
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print(f"ЗАПУСК СИСТЕМЫ МОДУЛЬНОГО КОНТРОЛЛИНГА СКУД ⟷ 1С {'[DEBUG]' if args.debug else ''}")
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print("=" * 60)
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now = datetime.now()
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if args.date:
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today_str = args.date.replace('_', '.')
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dt_target = datetime.strptime(today_str, "%d.%m.%Y")
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days_back = 3 if dt_target.weekday() == 0 else 1
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yesterday_str = (dt_target - timedelta(days=days_back)).strftime("%d.%m.%Y")
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else:
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today_str = now.strftime("%d.%m.%Y")
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if now.weekday() == 0:
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yesterday_str = (now - timedelta(days=3)).strftime("%d.%m.%Y")
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else:
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yesterday_str = (now - timedelta(days=1)).strftime("%d.%m.%Y")
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# [Этап 0] Выгрузка свежих данных СКУД
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if not args.skip_export and not args.snapshot:
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print(f"\n[0/5] Экспорт данных СКУД за {today_str} и {yesterday_str}...")
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run_export(input_date=args.date, debug=args.debug, save_xlsx=True)
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else:
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print("\n[0/5] Пропуск прямого экспорта СКУД из MS SQL (--skip-export)...")
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# [Этап 0.5] Синхронизация файлов с шары 1С
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if not args.snapshot and not args.skip_export:
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print(f"\n[0.5/5] Проверка и копирование файлов 1С с шары...")
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copy_1c_files_from_share()
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else:
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print("\n[0.5/5] Пропуск синхронизации с шары (чтение локальных данных)...")
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# [Этап 1-2] Загрузка данных
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print(f"\n[1-2/5] Загрузка срезов: Сегодня = {today_str}, Накануне = {yesterday_str}...")
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df_scud_yesterday = load_best_snapshot_for_date(yesterday_str, prefer_final_y=True)
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df_scud_today = load_best_snapshot_for_date(today_str, prefer_final_y=False)
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df_staff_yesterday, df_abs_yesterday = load_1c_files_for_date(yesterday_str)
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df_staff_today, df_abs_today = load_1c_files_for_date(today_str)
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if df_scud_today is not None and not df_scud_today.empty:
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export_raw_scud(df_scud_today, filename=f"СКУД_Сырые_данные_{today_str}.xlsx")
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# [Этап 3] Детальный отчет за вчера через otchet_generator
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print(f"\n[3/5] Обработка и построение детального отчета за ВЧЕРА ({yesterday_str})...")
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res_otchet = generate_otchet_service(target_date=yesterday_str)
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if res_otchet.get("status") == "success":
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print(f"[✓] {res_otchet.get('message')}: {res_otchet.get('filepath')}")
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# [Этап 4] Сводка за сегодня через svodka_generator
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print(f"\n[4/5] Обработка и построение Ежедневной сводки за {today_str} {args.time or ''}...")
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res_svodka = generate_svodka_service(
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target_date=today_str,
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target_time=args.time,
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snapshot_id=args.snapshot
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)
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if res_svodka.get("status") == "success":
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print(f"[✓] {res_svodka.get('message')}: {res_svodka.get('filepath')}")
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if res_svodka.get("note"):
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print(f" ℹ️ {res_svodka.get('note')}")
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# [Этап 5] Формирование Markdown-сводки через ИИ-аудитора (Ollama)
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print(f"\n[5/5] Формирование Markdown-сводки через ИИ-аудитора (Ollama)...")
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df_merged_today = merge_scud_and_1c(df_scud_today, df_staff_today, df_abs_today)
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anomalies_today = detect_registry_anomalies(df_merged_today, df_raw_scud=df_scud_today)
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absent_explained = df_merged_today[
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(df_merged_today['Пришел'] == False) &
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(df_merged_today['Вид_отсутствия'].notna()) &
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(~df_merged_today['Вид_отсутствия'].astype(str).str.startswith('Исключение'))
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]
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absent_unexplained = df_merged_today[
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(df_merged_today['Пришел'] == False) &
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(df_merged_today['Вид_отсутствия'].isna() | (df_merged_today['Вид_отсутствия'].astype(str).str.strip() == '')) &
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(df_merged_today.get('is_excluded', False) == False)
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]
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summary_md = generate_markdown_report(
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merged_df=df_merged_today[df_merged_today.get('is_excluded', False) == False],
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absent_explained=absent_explained,
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absent_unexplained=absent_unexplained,
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scud_present_but_absent_in_1c=pd.DataFrame(),
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anomalies_list=anomalies_today,
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raw_scud_df=df_scud_today,
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raw_staff_df=df_staff_today,
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raw_absent_df=df_abs_today,
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date_str=today_str
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)
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os.makedirs("output", exist_ok=True)
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md_file_path = f"output/Сводка_контроллинга_{today_str}.md"
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with open(md_file_path, "w", encoding="utf-8") as f:
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f.write(summary_md)
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print(f"[✓] Текстовый отчет сохранен в: {md_file_path}")
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print("\n" + "=" * 60)
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print("ГОТОВАЯ ТЕКСТОВАЯ СВОДКА ИИ-АУДИТОРА:")
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print("=" * 60)
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print(summary_md)
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if __name__ == "__main__":
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main() |