starting daily mirror
This commit is contained in:
Quality System Admin
744
py_app/app/daily_mirror_db_setup.py
Normal file
744
py_app/app/daily_mirror_db_setup.py
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@@ -0,0 +1,744 @@
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"""
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Daily Mirror Database Setup and Management
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Quality Recticel Application
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This script creates the database schema and provides utilities for
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data import and Daily Mirror reporting functionality.
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"""
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import mariadb
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import pandas as pd
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import os
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from datetime import datetime, timedelta
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import logging
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# Setup logging
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logging.basicConfig(level=logging.INFO)
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logger = logging.getLogger(__name__)
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class DailyMirrorDatabase:
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def __init__(self, host='localhost', user='trasabilitate', password='Initial01!', database='trasabilitate'):
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self.host = host
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self.user = user
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self.password = password
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self.database = database
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self.connection = None
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def connect(self):
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"""Establish database connection"""
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try:
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self.connection = mariadb.connect(
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host=self.host,
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user=self.user,
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password=self.password,
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database=self.database
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)
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logger.info("Database connection established")
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return True
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except Exception as e:
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logger.error(f"Database connection failed: {e}")
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return False
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def disconnect(self):
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"""Close database connection"""
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if self.connection:
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self.connection.close()
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logger.info("Database connection closed")
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def create_database_schema(self):
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"""Create the Daily Mirror database schema"""
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try:
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cursor = self.connection.cursor()
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# Read and execute the schema file
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schema_file = os.path.join(os.path.dirname(__file__), 'daily_mirror_database_schema.sql')
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if not os.path.exists(schema_file):
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logger.error(f"Schema file not found: {schema_file}")
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return False
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with open(schema_file, 'r') as file:
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schema_sql = file.read()
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# Split by statements and execute each one
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statements = []
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current_statement = ""
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for line in schema_sql.split('\n'):
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line = line.strip()
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if line and not line.startswith('--'):
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current_statement += line + " "
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if line.endswith(';'):
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statements.append(current_statement.strip())
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current_statement = ""
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# Add any remaining statement
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if current_statement.strip():
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statements.append(current_statement.strip())
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for statement in statements:
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if statement and any(statement.upper().startswith(cmd) for cmd in ['CREATE', 'ALTER', 'DROP', 'INSERT']):
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try:
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cursor.execute(statement)
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logger.info(f"Executed: {statement[:80]}...")
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except Exception as e:
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if "already exists" not in str(e).lower():
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logger.warning(f"Error executing statement: {e}")
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self.connection.commit()
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logger.info("Database schema created successfully")
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return True
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except Exception as e:
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logger.error(f"Error creating database schema: {e}")
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return False
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def import_production_data(self, file_path):
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"""Import production data from Excel file (Comenzi Productie format)"""
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try:
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# The correct data is in the first sheet (DataSheet)
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df = None
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sheet_used = None
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# Get available sheets
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excel_file = pd.ExcelFile(file_path)
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logger.info(f"Available sheets: {excel_file.sheet_names}")
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# Try DataSheet first (where the actual production data is), then fallback options
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sheet_attempts = [
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('DataSheet', 'openpyxl'),
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('DataSheet', 'xlrd'),
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(0, 'openpyxl'),
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(0, 'xlrd'),
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('Sheet1', 'openpyxl'), # fallback to Sheet1 if DataSheet fails
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(1, 'openpyxl')
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]
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for sheet_name, engine in sheet_attempts:
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try:
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logger.info(f"Trying to read sheet '{sheet_name}' with engine '{engine}'")
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df = pd.read_excel(file_path, sheet_name=sheet_name, engine=engine, header=0)
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sheet_used = f"{sheet_name} (engine: {engine})"
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logger.info(f"Successfully read from sheet: {sheet_used}")
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break
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except Exception as e:
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logger.warning(f"Failed to read sheet {sheet_name} with {engine}: {e}")
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continue
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# If all engines fail on DataSheet, try a different approach
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if df is None:
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try:
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logger.info("Trying alternative method: reading without specifying engine")
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df = pd.read_excel(file_path, sheet_name='DataSheet')
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sheet_used = "DataSheet (default engine)"
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logger.info("Successfully read with default engine")
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except Exception as e:
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logger.error(f"Failed with default engine: {e}")
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raise Exception("Could not read the DataSheet from the Excel file. The file may be corrupted.")
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logger.info(f"Loaded production data from {sheet_used}: {len(df)} rows, {len(df.columns)} columns")
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logger.info(f"Available columns: {list(df.columns)}")
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cursor = self.connection.cursor()
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success_count = 0
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created_count = 0
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updated_count = 0
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error_count = 0
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# Prepare insert statement
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insert_sql = """
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INSERT INTO dm_production_orders (
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production_order, customer_code, client_order, article_code,
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article_description, quantity_requested, delivery_date, production_status,
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end_of_quilting, end_of_sewing, t1_status, t1_registration_date, t1_operator_name,
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t2_status, t2_registration_date, t2_operator_name, t3_status, t3_registration_date,
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t3_operator_name, machine_code, machine_type, classification, total_norm_time,
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data_deschiderii, model_lb2, data_planificare, machine_number, design_number, needle_position
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) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
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ON DUPLICATE KEY UPDATE
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customer_code = VALUES(customer_code),
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client_order = VALUES(client_order),
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article_code = VALUES(article_code),
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article_description = VALUES(article_description),
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quantity_requested = VALUES(quantity_requested),
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delivery_date = VALUES(delivery_date),
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production_status = VALUES(production_status),
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updated_at = CURRENT_TIMESTAMP
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"""
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for index, row in df.iterrows():
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try:
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# Prepare data tuple
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data = (
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row.get('Comanda Productie', ''),
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row.get('Customer', ''),
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row.get('Comanda client', ''),
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row.get('Cod Articol', ''),
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row.get('Descriere', ''),
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row.get('Cantitate ceruta', 0),
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self._parse_date(row.get('Delivery date')),
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row.get('Status', ''),
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self._parse_datetime(row.get('End of Quilting')),
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self._parse_datetime(row.get('End of sewing')),
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row.get('T1', 0),
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self._parse_datetime(row.get('Data inregistrare T1')),
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row.get('Numele Complet T1', ''),
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row.get('T2', 0),
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self._parse_datetime(row.get('Data inregistrare T2')),
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row.get('Numele Complet T2', ''),
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row.get('T3', 0),
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self._parse_datetime(row.get('Data inregistrare T3')),
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row.get('Numele Complet T3', ''),
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row.get('Masina Cusut ', ''),
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row.get('Tip Masina', ''),
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row.get('Clasificare', ''),
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row.get('Timp normat total', 0),
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self._parse_date(row.get('Data Deschiderii')),
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row.get('Model Lb2', ''),
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self._parse_date(row.get('Data Planific.')),
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row.get('Numar masina', ''),
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row.get('Design nr', 0),
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row.get('Needle position', 0)
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)
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cursor.execute(insert_sql, data)
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# Check if row was inserted (created) or updated
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# In MySQL with ON DUPLICATE KEY UPDATE:
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# - rowcount = 1 means INSERT (new row created)
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# - rowcount = 2 means UPDATE (existing row updated)
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# - rowcount = 0 means no change
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if cursor.rowcount == 1:
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created_count += 1
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elif cursor.rowcount == 2:
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updated_count += 1
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success_count += 1
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except Exception as row_error:
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logger.warning(f"Error processing row {index}: {row_error}")
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error_count += 1
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continue
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self.connection.commit()
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logger.info(f"Production data import completed: {success_count} successful, {error_count} failed")
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return {
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'success_count': success_count,
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'created_count': created_count,
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'updated_count': updated_count,
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'error_count': error_count,
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'total_rows': len(df)
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}
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except Exception as e:
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logger.error(f"Error importing production data: {e}")
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return None
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def import_orders_data(self, file_path):
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"""Import orders data from Excel file with enhanced error handling"""
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try:
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# Ensure we have a database connection
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if not self.connection:
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self.connect()
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if not self.connection:
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return {
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'success_count': 0,
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'error_count': 1,
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'total_rows': 0,
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'error_message': 'Could not establish database connection.'
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}
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logger.info(f"Attempting to import orders data from: {file_path}")
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# Check if file exists
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if not os.path.exists(file_path):
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logger.error(f"Orders file not found: {file_path}")
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return {
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'success_count': 0,
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'error_count': 1,
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'total_rows': 0,
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'error_message': f'Orders file not found: {file_path}'
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}
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# Try to get sheet names first
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try:
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excel_file = pd.ExcelFile(file_path)
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sheet_names = excel_file.sheet_names
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logger.info(f"Available sheets in orders file: {sheet_names}")
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except Exception as e:
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logger.warning(f"Could not get sheet names: {e}")
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sheet_names = ['DataSheet', 'Sheet1']
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# Try multiple approaches to read the Excel file
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df = None
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sheet_used = None
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approaches = [
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('openpyxl', 0, 'read_only'),
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('openpyxl', 0, 'normal'),
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('openpyxl', 1, 'normal'),
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('xlrd', 0, 'normal') if file_path.endswith('.xls') else None,
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('default', 0, 'normal')
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]
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for approach in approaches:
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if approach is None:
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continue
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engine, sheet_name, mode = approach
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try:
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logger.info(f"Trying to read orders with engine: {engine}, sheet: {sheet_name}, mode: {mode}")
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if engine == 'default':
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df = pd.read_excel(file_path, sheet_name=sheet_name, header=0)
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elif mode == 'read_only':
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df = pd.read_excel(file_path, sheet_name=sheet_name, engine=engine, header=0)
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else:
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df = pd.read_excel(file_path, sheet_name=sheet_name, engine=engine, header=0)
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sheet_used = f"{engine} (sheet: {sheet_name}, mode: {mode})"
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logger.info(f"Successfully read orders data with: {sheet_used}")
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break
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except Exception as e:
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logger.warning(f"Failed with {engine}, sheet {sheet_name}, mode {mode}: {e}")
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continue
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if df is None:
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logger.error("Could not read the orders file with any method")
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return {
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'success_count': 0,
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'error_count': 1,
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'total_rows': 0,
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'error_message': 'Could not read the orders Excel file. The file may have formatting issues or be corrupted.'
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}
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logger.info(f"Loaded orders data from {sheet_used}: {len(df)} rows, {len(df.columns)} columns")
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logger.info(f"Available columns: {list(df.columns)[:10]}...")
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cursor = self.connection.cursor()
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success_count = 0
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created_count = 0
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updated_count = 0
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error_count = 0
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# Prepare insert statement for orders
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insert_sql = """
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INSERT INTO dm_orders (
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order_id, customer_code, customer_name, client_order,
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article_code, article_description, quantity_requested, delivery_date,
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order_status, product_group, order_date
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) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
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ON DUPLICATE KEY UPDATE
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customer_code = VALUES(customer_code),
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customer_name = VALUES(customer_name),
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client_order = VALUES(client_order),
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article_code = VALUES(article_code),
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article_description = VALUES(article_description),
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quantity_requested = VALUES(quantity_requested),
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delivery_date = VALUES(delivery_date),
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order_status = VALUES(order_status),
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product_group = VALUES(product_group),
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order_date = VALUES(order_date),
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updated_at = CURRENT_TIMESTAMP
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"""
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# Process each row with the actual column mapping and better null handling
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for index, row in df.iterrows():
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try:
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# Helper function to safely get values and handle NaN
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def safe_get(row, column, default=''):
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value = row.get(column, default)
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if pd.isna(value) or value == 'nan':
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return default
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return str(value).strip() if isinstance(value, str) else value
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def safe_get_int(row, column, default=0):
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value = row.get(column, default)
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if pd.isna(value) or value == 'nan':
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return default
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try:
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return int(float(value)) if value != '' else default
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except (ValueError, TypeError):
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return default
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# Map columns based on the actual Vizual. Artic. Comenzi Deschise format
|
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data = (
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safe_get(row, 'Comanda', f'ORD_{index:06d}'), # Order ID
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safe_get(row, 'Cod. Client'), # Customer Code
|
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safe_get(row, 'Customer Name'), # Customer Name
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safe_get(row, 'Com. Achiz. Client'), # Client Order
|
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safe_get(row, 'Cod Articol'), # Article Code
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safe_get(row, 'Part Description', safe_get(row, 'Descr. Articol')), # Article Description
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safe_get_int(row, 'Cantitate'), # Quantity
|
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self._parse_date(row.get('Data livrare')), # Delivery Date
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safe_get(row, 'Statut Comanda', 'PENDING'), # Order Status
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safe_get(row, 'Model'), # Product Group
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self._parse_date(row.get('Data Comenzii')) # Order Date
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)
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cursor.execute(insert_sql, data)
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||||
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||||
# Track created vs updated
|
||||
if cursor.rowcount == 1:
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||||
created_count += 1
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||||
elif cursor.rowcount == 2:
|
||||
updated_count += 1
|
||||
|
||||
success_count += 1
|
||||
|
||||
except Exception as row_error:
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||||
logger.warning(f"Error processing row {index}: {row_error}")
|
||||
error_count += 1
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||||
continue
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||||
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||||
self.connection.commit()
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||||
logger.info(f"Orders import completed: {success_count} successful, {error_count} errors")
|
||||
|
||||
return {
|
||||
'success_count': success_count,
|
||||
'created_count': created_count,
|
||||
'updated_count': updated_count,
|
||||
'error_count': error_count,
|
||||
'total_rows': len(df),
|
||||
'error_message': None if error_count == 0 else f'{error_count} rows failed to import'
|
||||
}
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error importing orders data: {e}")
|
||||
return {
|
||||
'success_count': 0,
|
||||
'error_count': 1,
|
||||
'total_rows': 0,
|
||||
'error_message': str(e)
|
||||
}
|
||||
|
||||
def import_delivery_data(self, file_path):
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||||
"""Import delivery data from Excel file with enhanced error handling"""
|
||||
try:
|
||||
# Ensure we have a database connection
|
||||
if not self.connection:
|
||||
self.connect()
|
||||
if not self.connection:
|
||||
return {
|
||||
'success_count': 0,
|
||||
'error_count': 1,
|
||||
'total_rows': 0,
|
||||
'error_message': 'Could not establish database connection.'
|
||||
}
|
||||
|
||||
logger.info(f"Attempting to import delivery data from: {file_path}")
|
||||
|
||||
# Check if file exists
|
||||
if not os.path.exists(file_path):
|
||||
logger.error(f"Delivery file not found: {file_path}")
|
||||
return {
|
||||
'success_count': 0,
|
||||
'error_count': 1,
|
||||
'total_rows': 0,
|
||||
'error_message': f'Delivery file not found: {file_path}'
|
||||
}
|
||||
|
||||
# Try to get sheet names first
|
||||
try:
|
||||
excel_file = pd.ExcelFile(file_path)
|
||||
sheet_names = excel_file.sheet_names
|
||||
logger.info(f"Available sheets in delivery file: {sheet_names}")
|
||||
except Exception as e:
|
||||
logger.warning(f"Could not get sheet names: {e}")
|
||||
sheet_names = ['DataSheet', 'Sheet1']
|
||||
|
||||
# Try multiple approaches to read the Excel file
|
||||
df = None
|
||||
sheet_used = None
|
||||
approaches = [
|
||||
('openpyxl', 0, 'read_only'),
|
||||
('openpyxl', 0, 'normal'),
|
||||
('openpyxl', 1, 'normal'),
|
||||
('xlrd', 0, 'normal') if file_path.endswith('.xls') else None,
|
||||
('default', 0, 'normal')
|
||||
]
|
||||
|
||||
for approach in approaches:
|
||||
if approach is None:
|
||||
continue
|
||||
|
||||
engine, sheet_name, mode = approach
|
||||
try:
|
||||
logger.info(f"Trying to read delivery data with engine: {engine}, sheet: {sheet_name}, mode: {mode}")
|
||||
|
||||
if engine == 'default':
|
||||
df = pd.read_excel(file_path, sheet_name=sheet_name, header=0)
|
||||
elif mode == 'read_only':
|
||||
df = pd.read_excel(file_path, sheet_name=sheet_name, engine=engine, header=0)
|
||||
else:
|
||||
df = pd.read_excel(file_path, sheet_name=sheet_name, engine=engine, header=0)
|
||||
|
||||
sheet_used = f"{engine} (sheet: {sheet_name}, mode: {mode})"
|
||||
logger.info(f"Successfully read delivery data with: {sheet_used}")
|
||||
break
|
||||
|
||||
except Exception as e:
|
||||
logger.warning(f"Failed with {engine}, sheet {sheet_name}, mode {mode}: {e}")
|
||||
continue
|
||||
|
||||
if df is None:
|
||||
logger.error("Could not read the delivery file with any method")
|
||||
return {
|
||||
'success_count': 0,
|
||||
'error_count': 1,
|
||||
'total_rows': 0,
|
||||
'error_message': 'Could not read the delivery Excel file. The file may have formatting issues or be corrupted.'
|
||||
}
|
||||
|
||||
logger.info(f"Loaded delivery data from {sheet_used}: {len(df)} rows, {len(df.columns)} columns")
|
||||
logger.info(f"Available columns: {list(df.columns)[:10]}...")
|
||||
|
||||
cursor = self.connection.cursor()
|
||||
success_count = 0
|
||||
created_count = 0
|
||||
updated_count = 0
|
||||
error_count = 0
|
||||
|
||||
# Prepare insert statement for deliveries
|
||||
insert_sql = """
|
||||
INSERT INTO dm_deliveries (
|
||||
shipment_id, order_id, customer_code, customer_name,
|
||||
article_code, article_description, quantity_delivered,
|
||||
shipment_date, delivery_date, delivery_status, total_value
|
||||
) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
|
||||
ON DUPLICATE KEY UPDATE
|
||||
customer_code = VALUES(customer_code),
|
||||
customer_name = VALUES(customer_name),
|
||||
article_code = VALUES(article_code),
|
||||
article_description = VALUES(article_description),
|
||||
quantity_delivered = VALUES(quantity_delivered),
|
||||
shipment_date = VALUES(shipment_date),
|
||||
delivery_date = VALUES(delivery_date),
|
||||
delivery_status = VALUES(delivery_status),
|
||||
total_value = VALUES(total_value),
|
||||
updated_at = CURRENT_TIMESTAMP
|
||||
"""
|
||||
|
||||
# Process each row with the actual column mapping and better null handling
|
||||
for index, row in df.iterrows():
|
||||
try:
|
||||
# Helper function to safely get values and handle NaN
|
||||
def safe_get(row, column, default=''):
|
||||
value = row.get(column, default)
|
||||
if pd.isna(value) or value == 'nan':
|
||||
return default
|
||||
return str(value).strip() if isinstance(value, str) else value
|
||||
|
||||
def safe_get_float(row, column, default=0.0):
|
||||
value = row.get(column, default)
|
||||
if pd.isna(value) or value == 'nan':
|
||||
return default
|
||||
try:
|
||||
return float(value) if value != '' else default
|
||||
except (ValueError, TypeError):
|
||||
return default
|
||||
|
||||
def safe_get_int(row, column, default=0):
|
||||
value = row.get(column, default)
|
||||
if pd.isna(value) or value == 'nan':
|
||||
return default
|
||||
try:
|
||||
return int(float(value)) if value != '' else default
|
||||
except (ValueError, TypeError):
|
||||
return default
|
||||
|
||||
# Map columns based on the actual Articole livrate_returnate format
|
||||
data = (
|
||||
safe_get(row, 'Document Number', f'SH_{index:06d}'), # Shipment ID
|
||||
safe_get(row, 'Comanda'), # Order ID
|
||||
safe_get(row, 'Cod. Client'), # Customer Code
|
||||
safe_get(row, 'Nume client'), # Customer Name
|
||||
safe_get(row, 'Cod Articol'), # Article Code
|
||||
safe_get(row, 'Part Description'), # Article Description
|
||||
safe_get_int(row, 'Cantitate'), # Quantity Delivered
|
||||
self._parse_date(row.get('Data')), # Shipment Date
|
||||
self._parse_date(row.get('Data')), # Delivery Date (same as shipment for now)
|
||||
safe_get(row, 'Stare', 'DELIVERED'), # Delivery Status
|
||||
safe_get_float(row, 'Total Price') # Total Value
|
||||
)
|
||||
|
||||
cursor.execute(insert_sql, data)
|
||||
|
||||
# Track created vs updated
|
||||
if cursor.rowcount == 1:
|
||||
created_count += 1
|
||||
elif cursor.rowcount == 2:
|
||||
updated_count += 1
|
||||
|
||||
success_count += 1
|
||||
|
||||
except Exception as row_error:
|
||||
logger.warning(f"Error processing delivery row {index}: {row_error}")
|
||||
error_count += 1
|
||||
continue
|
||||
|
||||
self.connection.commit()
|
||||
logger.info(f"Delivery import completed: {success_count} successful, {error_count} errors")
|
||||
|
||||
return {
|
||||
'success_count': success_count,
|
||||
'created_count': created_count,
|
||||
'updated_count': updated_count,
|
||||
'error_count': error_count,
|
||||
'total_rows': len(df),
|
||||
'error_message': None if error_count == 0 else f'{error_count} rows failed to import'
|
||||
}
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error importing delivery data: {e}")
|
||||
return {
|
||||
'success_count': 0,
|
||||
'error_count': 1,
|
||||
'total_rows': 0,
|
||||
'error_message': str(e)
|
||||
}
|
||||
|
||||
def generate_daily_summary(self, report_date=None):
|
||||
"""Generate daily summary for Daily Mirror reporting"""
|
||||
if not report_date:
|
||||
report_date = datetime.now().date()
|
||||
|
||||
try:
|
||||
cursor = self.connection.cursor()
|
||||
|
||||
# Check if summary already exists for this date
|
||||
cursor.execute("SELECT id FROM dm_daily_summary WHERE report_date = ?", (report_date,))
|
||||
existing = cursor.fetchone()
|
||||
|
||||
# Get production metrics
|
||||
cursor.execute("""
|
||||
SELECT
|
||||
COUNT(*) as total_orders,
|
||||
SUM(quantity_requested) as total_quantity,
|
||||
SUM(CASE WHEN production_status = 'Inchis' THEN 1 ELSE 0 END) as completed_orders,
|
||||
SUM(CASE WHEN end_of_quilting IS NOT NULL THEN 1 ELSE 0 END) as quilting_done,
|
||||
SUM(CASE WHEN end_of_sewing IS NOT NULL THEN 1 ELSE 0 END) as sewing_done,
|
||||
COUNT(DISTINCT customer_code) as unique_customers
|
||||
FROM dm_production_orders
|
||||
WHERE DATE(data_planificare) = ?
|
||||
""", (report_date,))
|
||||
|
||||
production_metrics = cursor.fetchone()
|
||||
|
||||
# Get active operators count
|
||||
cursor.execute("""
|
||||
SELECT COUNT(DISTINCT CASE
|
||||
WHEN t1_operator_name IS NOT NULL THEN t1_operator_name
|
||||
WHEN t2_operator_name IS NOT NULL THEN t2_operator_name
|
||||
WHEN t3_operator_name IS NOT NULL THEN t3_operator_name
|
||||
END) as active_operators
|
||||
FROM dm_production_orders
|
||||
WHERE DATE(data_planificare) = ?
|
||||
""", (report_date,))
|
||||
|
||||
operator_metrics = cursor.fetchone()
|
||||
active_operators = operator_metrics[0] or 0
|
||||
|
||||
if existing:
|
||||
# Update existing summary
|
||||
update_sql = """
|
||||
UPDATE dm_daily_summary SET
|
||||
orders_quantity = ?, production_launched = ?, production_finished = ?,
|
||||
quilting_completed = ?, sewing_completed = ?, unique_customers = ?,
|
||||
active_operators = ?, updated_at = CURRENT_TIMESTAMP
|
||||
WHERE report_date = ?
|
||||
"""
|
||||
cursor.execute(update_sql, (
|
||||
production_metrics[1] or 0, production_metrics[0] or 0, production_metrics[2] or 0,
|
||||
production_metrics[3] or 0, production_metrics[4] or 0, production_metrics[5] or 0,
|
||||
active_operators, report_date
|
||||
))
|
||||
else:
|
||||
# Insert new summary
|
||||
insert_sql = """
|
||||
INSERT INTO dm_daily_summary (
|
||||
report_date, orders_quantity, production_launched, production_finished,
|
||||
quilting_completed, sewing_completed, unique_customers, active_operators
|
||||
) VALUES (?, ?, ?, ?, ?, ?, ?, ?)
|
||||
"""
|
||||
cursor.execute(insert_sql, (
|
||||
report_date, production_metrics[1] or 0, production_metrics[0] or 0, production_metrics[2] or 0,
|
||||
production_metrics[3] or 0, production_metrics[4] or 0, production_metrics[5] or 0,
|
||||
active_operators
|
||||
))
|
||||
|
||||
self.connection.commit()
|
||||
logger.info(f"Daily summary generated for {report_date}")
|
||||
return True
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error generating daily summary: {e}")
|
||||
return False
|
||||
|
||||
def clear_production_orders(self):
|
||||
"""Delete all rows from the Daily Mirror production orders table"""
|
||||
try:
|
||||
cursor = self.connection.cursor()
|
||||
cursor.execute("DELETE FROM dm_production_orders")
|
||||
self.connection.commit()
|
||||
logger.info("All production orders deleted from dm_production_orders table.")
|
||||
return True
|
||||
except Exception as e:
|
||||
logger.error(f"Error deleting production orders: {e}")
|
||||
return False
|
||||
|
||||
def _parse_date(self, date_value):
|
||||
"""Parse date with better null handling"""
|
||||
if pd.isna(date_value) or date_value == 'nan' or date_value is None or date_value == '':
|
||||
return None
|
||||
|
||||
try:
|
||||
if isinstance(date_value, str):
|
||||
# Handle various date formats
|
||||
for fmt in ['%Y-%m-%d', '%d/%m/%Y', '%m/%d/%Y', '%d.%m.%Y']:
|
||||
try:
|
||||
return datetime.strptime(date_value, fmt).date()
|
||||
except ValueError:
|
||||
continue
|
||||
|
||||
elif hasattr(date_value, 'date'):
|
||||
return date_value.date()
|
||||
elif isinstance(date_value, datetime):
|
||||
return date_value.date()
|
||||
|
||||
return None # If all parsing attempts fail
|
||||
|
||||
except Exception as e:
|
||||
logger.warning(f"Error parsing date {date_value}: {e}")
|
||||
return None
|
||||
|
||||
def _parse_datetime(self, datetime_value):
|
||||
"""Parse datetime value from Excel"""
|
||||
if pd.isna(datetime_value):
|
||||
return None
|
||||
if isinstance(datetime_value, str) and datetime_value == '00:00:00':
|
||||
return None
|
||||
return datetime_value
|
||||
|
||||
def setup_daily_mirror_database():
|
||||
"""Setup the Daily Mirror database schema"""
|
||||
db = DailyMirrorDatabase()
|
||||
|
||||
if not db.connect():
|
||||
return False
|
||||
|
||||
try:
|
||||
success = db.create_database_schema()
|
||||
if success:
|
||||
print("✅ Daily Mirror database schema created successfully!")
|
||||
|
||||
# Generate sample daily summary for today
|
||||
db.generate_daily_summary()
|
||||
|
||||
return success
|
||||
finally:
|
||||
db.disconnect()
|
||||
|
||||
if __name__ == "__main__":
|
||||
setup_daily_mirror_database()
|
||||
Reference in New Issue
Block a user