279 lines
12 KiB
Python
279 lines
12 KiB
Python
"""
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Модуль автоматического экспорта данных СКУД (Orion) из MS SQL Server в SQLite и Excel.
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Исправлена логика определения направления проходов (Mode = 2 -> OUT).
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Адаптирован для Linux (Ubuntu 24.04).
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"""
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import argparse
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import logging
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import os
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import sys
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import warnings
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from datetime import datetime, timedelta
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import pandas as pd
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import pyodbc
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from openpyxl.utils import get_column_letter
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from config import SCUD_DIR, clean_scud_fio_light, load_exceptions
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from modules.database import save_scud_to_db
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warnings.filterwarnings("ignore", message="pandas only supports SQLAlchemy connectable")
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SCRIPT_DIR = os.path.dirname(os.path.abspath(__file__))
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LOG_DIR = os.path.join(SCRIPT_DIR, "..", "logs")
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os.makedirs(LOG_DIR, exist_ok=True)
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TODAY_DATE_STR = datetime.now().strftime("%d.%m.%Y")
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LOG_FILE = os.path.join(LOG_DIR, f"export_{TODAY_DATE_STR}.log")
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logger = logging.getLogger("scud_export")
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logger.setLevel(logging.INFO)
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if not logger.handlers:
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_file_handler = logging.FileHandler(LOG_FILE, encoding="utf-8")
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_console_handler = logging.StreamHandler(sys.stdout)
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_formatter = logging.Formatter("[%(asctime)s] [%(levelname)s] %(message)s", datefmt="%Y-%m-%d %H:%M:%S")
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_file_handler.setFormatter(_formatter)
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_console_handler.setFormatter(_formatter)
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logger.addHandler(_file_handler)
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logger.addHandler(_console_handler)
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def log(message: str, level: str = "INFO"):
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level_map = {
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"INFO": logging.INFO,
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"ERROR": logging.ERROR,
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"WARNING": logging.WARNING,
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"SUCCESS": logging.INFO,
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}
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if level == "SUCCESS":
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logger.info(f"[SUCCESS] {message}")
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else:
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logger.log(level_map.get(level, logging.INFO), message)
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SERVER_NAME = r"172.16.31.221\SQL"
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DATABASE_NAME = "Orion-14.01.21-1"
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SQL_USER = "sa"
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SQL_PASSWORD = "123456"
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ODBC_DRIVER = "ODBC Driver 18 for SQL Server"
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SQL_QUERY_TEMPLATE = r"""
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DECLARE @InputDate DATE = '{target_date}';
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DECLARE @TargetDate DATE = @InputDate;
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DECLARE @StartDate DATETIME = CAST(@TargetDate AS DATETIME);
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DECLARE @EndDate DATETIME = DATEADD(SECOND, -1, DATEADD(DAY, 1, @StartDate));
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WITH DailyLogs AS (
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SELECT
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log.HozOrgan AS EmployeeID,
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log.TimeVal,
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log.Event,
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log.Mode,
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CASE
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WHEN log.Mode = 2 OR log.Event IN (29, 27, 33) THEN 'OUT'
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WHEN log.Mode = 1 OR log.Event IN (28, 26, 32) THEN 'IN'
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ELSE 'OTHER'
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END AS Direction,
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ROW_NUMBER() OVER (PARTITION BY log.HozOrgan ORDER BY log.TimeVal DESC) AS RowNumDesc
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FROM pLogData log WITH (NOLOCK)
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WHERE log.TimeVal BETWEEN @StartDate AND @EndDate
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AND log.HozOrgan IS NOT NULL
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AND log.HozOrgan > 0
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AND (log.Event IN (28, 29, 26, 27, 32, 33) OR log.Mode IN (1, 2))
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),
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Passages AS (
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SELECT
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EmployeeID,
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MIN(CASE WHEN Direction = 'IN' THEN TimeVal END) AS FirstIn,
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MAX(CASE WHEN Direction = 'OUT' THEN TimeVal END) AS LastOut,
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MAX(CASE WHEN RowNumDesc = 1 THEN Direction END) AS LastEventType
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FROM DailyLogs
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GROUP BY EmployeeID
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)
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SELECT
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N'ЛЕНМОРНИИПРОЕКТ' AS [Фирма],
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ISNULL(CAST(div.Name AS NVARCHAR(255)), N'Без подразделения') AS [Подразделение],
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LTRIM(RTRIM(
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ISNULL(CAST(p.Name AS NVARCHAR(255)), N'') +
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CASE WHEN p.FirstName IS NOT NULL AND CAST(p.FirstName AS NVARCHAR(255)) <> ''
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THEN N' ' + CAST(p.FirstName AS NVARCHAR(255)) ELSE N'' END +
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CASE WHEN p.MidName IS NOT NULL AND CAST(p.MidName AS NVARCHAR(255)) <> ''
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THEN N' ' + CAST(p.MidName AS NVARCHAR(255)) ELSE N'' END
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)) AS [Сотрудник],
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ISNULL(CAST(post.Name AS NVARCHAR(255)), N'—') AS [Должность],
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ISNULL(CAST(p.TabNumber AS NVARCHAR(50)), N'—') AS [Таб_№],
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CONVERT(VARCHAR(10), @TargetDate, 104) AS [Дата],
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ISNULL(CAST(CONVERT(VARCHAR(8), pass.FirstIn, 108) AS NVARCHAR(20)), N'Нет входа') AS [Начало_дня],
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CASE
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WHEN @TargetDate = CAST(GETDATE() AS DATE) AND (pass.LastEventType = 'IN' OR pass.LastOut IS NULL OR pass.LastOut <= pass.FirstIn)
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THEN N'Нет выхода'
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WHEN pass.LastOut IS NOT NULL AND pass.LastOut > pass.FirstIn
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THEN CAST(CONVERT(VARCHAR(8), pass.LastOut, 108) AS NVARCHAR(20))
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ELSE N'Нет выхода'
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END AS [Конец_дня],
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CASE
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WHEN pass.EmployeeID IS NOT NULL AND pass.FirstIn IS NOT NULL THEN
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RIGHT('0' + CAST(DATEDIFF(MINUTE,
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pass.FirstIn,
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CASE
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WHEN @TargetDate = CAST(GETDATE() AS DATE) AND (pass.LastEventType = 'IN' OR pass.LastOut IS NULL OR pass.LastOut <= pass.FirstIn) THEN GETDATE()
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ELSE ISNULL(pass.LastOut, pass.FirstIn)
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END) / 60 AS VARCHAR), 2) + ':' +
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RIGHT('0' + CAST(DATEDIFF(MINUTE,
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pass.FirstIn,
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CASE
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WHEN @TargetDate = CAST(GETDATE() AS DATE) AND (pass.LastEventType = 'IN' OR pass.LastOut IS NULL OR pass.LastOut <= pass.FirstIn) THEN GETDATE()
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ELSE ISNULL(pass.LastOut, pass.FirstIn)
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END) % 60 AS VARCHAR), 2)
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ELSE N'00:00'
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END AS [Находился_в_здании],
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CASE
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WHEN pass.EmployeeID IS NOT NULL THEN N'Присутствовал'
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ELSE N'Отсутствовал (Нет событий)'
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END AS [Статус]
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FROM pList p WITH (NOLOCK)
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LEFT JOIN PDivision div WITH (NOLOCK) ON p.Section = div.ID
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LEFT JOIN PPost post WITH (NOLOCK) ON p.Post = post.ID
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LEFT JOIN Passages pass ON p.ID = pass.EmployeeID
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WHERE
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ISNULL(p.StatusRecord, 0) = 0
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AND p.DateTimeInArchive IS NULL
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AND ISNULL(CAST(div.Name AS NVARCHAR(255)), N'') NOT LIKE N'Аренд%'
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AND ISNULL(CAST(div.Name AS NVARCHAR(255)), N'') NOT IN (N'Без подразделения', N'')
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AND p.Name NOT LIKE N'бр.%'
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AND p.Name NOT LIKE N'Гость%'
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AND ISNULL(CAST(div.Name AS NVARCHAR(255)), N'') NOT IN (N'БГИ', N'КНР')
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AND ISNULL(CAST(div.Name AS NVARCHAR(255)), N'') NOT LIKE N'Рабоч%'
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AND ISNULL(CAST(div.Name AS NVARCHAR(255)), N'') NOT LIKE N'Врем%'
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AND ISNULL(CAST(div.Name AS NVARCHAR(255)), N'') NOT LIKE N'Практика%'
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AND ISNULL(CAST(div.Name AS NVARCHAR(255)), N'') NOT LIKE N'тест%'
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AND ISNULL(CAST(post.Name AS NVARCHAR(255)), N'') NOT LIKE N'Практикант%'
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ORDER BY p.Name ASC;
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"""
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def auto_fit_columns(file_path: str, sheet_name: str, padding: float = 2.0, min_width: float = 8.0, max_width: float = 60.0):
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from openpyxl import load_workbook
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wb = load_workbook(file_path)
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ws = wb[sheet_name]
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for col_cells in ws.columns:
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max_len = 0
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col_letter = get_column_letter(col_cells[0].column)
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for cell in col_cells:
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if cell.value is not None:
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cell_len = len(str(cell.value))
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if cell_len > max_len:
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max_len = cell_len
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width = max(min_width, min(max_len + padding, max_width))
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ws.column_dimensions[col_letter].width = width
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wb.save(file_path)
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def get_targets(input_date: str | None):
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targets = []
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if input_date:
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try:
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parsed = datetime.strptime(input_date, "%d.%m.%Y").date()
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targets.append({"name": "Указанная дата", "date": parsed})
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except ValueError:
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log(f"ОШИБКА: Неверный формат даты '{input_date}'. Используйте ДД.ММ.ГГГГ", "ERROR")
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sys.exit(1)
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else:
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now = datetime.now()
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yesterday = (now - timedelta(days=3 if now.weekday() == 0 else 1)).date()
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today = now.date()
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targets.append({"name": "Вчера", "date": yesterday})
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targets.append({"name": "Сегодня", "date": today})
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return targets
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def run_export(input_date: str | None = None, save_xlsx: bool = True, debug: bool = False):
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if debug:
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logger.setLevel(logging.DEBUG)
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log("=== ВКЛЮЧЕН РЕЖИМ ОТЛАДКИ (DEBUG MODE) ===", "WARNING")
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log("=== [ЭТАП 0] Выгрузка свежих данных СКУД напрямую из БД Орион ===")
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os.makedirs(SCUD_DIR, exist_ok=True)
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targets = get_targets(input_date)
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conn_str = (
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f"DRIVER={{{ODBC_DRIVER}}};"
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f"SERVER={SERVER_NAME};"
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f"DATABASE={DATABASE_NAME};"
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f"UID={SQL_USER};"
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f"PWD={SQL_PASSWORD};"
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f"TrustServerCertificate=yes;"
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f"Encrypt=no;"
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)
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success = True
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for target in targets:
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processing_date = target["date"]
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processing_date_str = processing_date.strftime("%d.%m.%Y")
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period_label = target["name"]
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log(f"--- Обработка периода: {period_label} ({processing_date_str}) ---")
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sql_query = SQL_QUERY_TEMPLATE.format(target_date=processing_date.strftime("%Y-%m-%d"))
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connection = None
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try:
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connection = pyodbc.connect(conn_str, timeout=120)
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df = pd.read_sql(sql_query, connection)
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log(f"База вернула {len(df)} строк за {processing_date_str}")
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if len(df) > 0:
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# 1. Готовим колонки для локальной БД
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df['fio_clean'] = df['Сотрудник'].apply(clean_scud_fio_light)
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df['Пришел'] = df['Статус'].str.contains('Присутствовал', case=False, na=False)
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# 2. ПРЯМОЕ СОХРАНЕНИЕ В SQLite (scud_orion_ai.db)
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save_scud_to_db(df, processing_date_str)
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log(f"[✓] Записи за {processing_date_str} успешно сохранены в SQLite!", "SUCCESS")
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# 3. Сохранение в Excel (если включен флаг save_xlsx)
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if save_xlsx:
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file_name = f"Сотрудники_{processing_date_str}.xlsx"
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file_path = os.path.join(SCUD_DIR, file_name)
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if os.path.exists(file_path):
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try:
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os.remove(file_path)
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except OSError as e:
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log(f"ОШИБКА при удалении старого файла {file_name}: {e}", "ERROR")
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df.to_excel(file_path, sheet_name="Отчет", index=False, engine="openpyxl")
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auto_fit_columns(file_path, sheet_name="Отчет")
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log(f"[✓] Успешно экспортирован файл: data/scud/{file_name}", "SUCCESS")
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else:
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log(f"Запрос за {processing_date_str} вернул 0 строк.", "WARNING")
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except Exception as e:
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log(f"🛑 ОШИБКА выгрузки СКУД за {processing_date_str}: {e}", "ERROR")
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success = False
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finally:
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if connection is not None:
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connection.close()
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log("=== Выгрузка СКУД завершена ===\n")
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return success
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(description="Экспорт данных СКУД в SQLite и Excel")
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parser.add_argument("--date", dest="input_date", default=None)
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parser.add_argument("-d", "--debug", action="store_true")
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parser.add_argument("--no-xlsx", dest="save_xlsx", action="store_false", default=True, help="Отключить сохранение в XLSX")
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args = parser.parse_args()
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run_export(args.input_date, save_xlsx=args.save_xlsx, debug=args.debug) |