59 lines
2.7 KiB
Python
59 lines
2.7 KiB
Python
"""
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===============================================================================
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FILE: services/scud_etl/pipeline.py
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ROLE: Выборка данных СКУД из SQLite (scud_logs) с жестким приоритетом Y-снапшотов.
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===============================================================================
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"""
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import os
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import logging
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import pandas as pd
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from core.connection import get_connection
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from services.data_loader import load_1c_data_smart
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logger = logging.getLogger("SCUD_PIPELINE")
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def load_best_snapshot_for_date(date_str: str, prefer_final_y: bool = True) -> pd.DataFrame:
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"""Извлекает срез СКУД. Для вчерашнего дня строго берет финальный вечерний срез Y."""
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with get_connection() as conn:
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df = pd.DataFrame()
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cursor = conn.cursor()
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if prefer_final_y:
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cursor.execute(
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"SELECT snapshot_id FROM scud_logs WHERE log_date = ? AND snapshot_id LIKE 'Y%' ORDER BY id DESC LIMIT 1",
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(date_str,)
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)
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row = cursor.fetchone()
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if row and row[0]:
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df = pd.read_sql_query("SELECT * FROM scud_logs WHERE snapshot_id = ?", conn, params=(row[0],))
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if df.empty:
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cursor.execute(
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"SELECT snapshot_id FROM scud_logs WHERE log_date = ? ORDER BY id DESC LIMIT 1",
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(date_str,)
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)
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row = cursor.fetchone()
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if row and row[0]:
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df = pd.read_sql_query("SELECT * FROM scud_logs WHERE snapshot_id = ?", conn, params=(row[0],))
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if not df.empty:
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rename_map = {
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'department': 'Подразделение', 'position': 'Должность', 'fio': 'Сотрудник',
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'time_in': 'Начало_дня', 'first_activity': 'Первая_активность', 'time_out': 'Конец_дня',
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'time_in_building': 'Находился_в_здании', 'is_present': 'Пришел'
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}
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df = df.rename(columns={k: v for k, v in rename_map.items() if k in df.columns})
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if 'fio_clean' not in df.columns and 'Сотрудник' in df.columns:
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df['fio_clean'] = df['Сотрудник'].astype(str).str.strip()
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if 'Пришел' in df.columns:
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df['Пришел'] = df['Пришел'].astype(bool)
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return df
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def load_1c_files_for_date(date_str: str) -> tuple[pd.DataFrame, pd.DataFrame]:
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df_staff, df_absences = load_1c_data_smart(date_str, use_db=False)
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return (df_staff if df_staff is not None else pd.DataFrame(),
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df_absences if df_absences is not None else pd.DataFrame()) |