ControlNetwork/Back/GC/GCExport.py

import time

import openpyxl
import pandas as pd
import sqlite3
import os
from PySide6.QtWidgets import QMessageBox
from openpyxl.styles import Font, NamedStyle, Alignment
from openpyxl.utils.dataframe import dataframe_to_rows
from openpyxl import Workbook


def export_result_data(ui, utf_en, db_path, export_folder):
    try:
        # 解码 utf_en
        decoded_utf_en = utf_en.decode('utf-8') if isinstance(utf_en, bytes) else utf_en
        # 连接数据库
        conn = sqlite3.connect(db_path)

        # 查询数据库表为DataFrame，添加 TableName 条件
        query = "SELECT * FROM GC_Output_Point WHERE TableName=?"
        df = pd.read_sql_query(query, conn, params=(utf_en,))

        # 检查是否有匹配的数据
        if df.empty:
            QMessageBox.warning(ui, '警告', '没有找到匹配的数据进行导出')
            conn.close()
            return

        # 假设 TableName 字段是以字节序列存储的 UTF-8 编码字符串
        if 'TableName' in df.columns:
            try:
                df['TableName'] = df['TableName'].apply(lambda x: x.decode('utf-8') if isinstance(x, bytes) else x)
            except Exception as e:
                QMessageBox.critical(ui, '错误', f'TableName 字段解码失败: {str(e)}')
                conn.close()
                return

        # 删除 TableName 列
        if 'TableName' in df.columns:
            df.drop(columns=['TableName'], inplace=True)
        # new HDiff 保留小数点后6位
        if 'New_HDiff' in df.columns:
            df['New_HDiff'] = df['New_HDiff'].round(6)
        # New_RLen 保留小数点后6位
        if 'New_RLen' in df.columns:
            df['New_RLen'] = df['New_RLen'].round(6)
        # Correct_Factor 保留小数点后2位
        if 'Correct_Factor' in df.columns:
            df['Correct_Factor'] = df['Correct_Factor'].round(2)
        # Period_Diff 保留小数点后2位
        if 'Period_Diff' in df.columns:
            df['Period_Diff'] = df['Period_Diff'].round(2)

        # 重命名指定的列
        column_mapping = {
            'New_ID': '序号',
            'New_ResultName': '结果期数',
            'New_SPName': '起点',
            'New_EPName': '终点',
            'New_HDiff': '高差',
            'New_RLen': '路线长',
            'Correct_Factor': '修正数',
            'Period_Diff': '期间差异',
            'Dis_Ass': '变形判定'
        }
        df.rename(columns=column_mapping, inplace=True)
        # 查询 GC_Input_Param 表获取 Correct_Factor 字段
        query_param = "SELECT Correct_Factor FROM GC_Input_Param WHERE TableName=?"
        correct_factor_df = pd.read_sql_query(query_param, conn, params=(utf_en,))

        correct_factor = correct_factor_df.iloc[0]['Correct_Factor']

        # 创建一个新的 Excel 工作簿
        wb = Workbook()
        ws = wb.active
        # 在E1单元格添加内容“修正系数”
        ws.cell(row=1, column=1, value="序号")
        ws.cell(row=1, column=2, value="结果期数")
        ws.cell(row=1, column=3, value="起点")
        ws.cell(row=1, column=4, value="终点")
        ws.cell(row=1, column=5, value="修正系数")
        ws.cell(row=1, column=6, value=correct_factor)
        ws.cell(row=1, column=7, value="修正数")
        ws.cell(row=1, column=8, value="期间差异")
        ws.cell(row=1, column=9, value="变形判定")

        # 将 DataFrame 写入工作表
        for r in dataframe_to_rows(df, index=False, header=True):
            ws.append(r)

        # 定义自定义样式
        style_0_000000 = NamedStyle(name="style_0_000000", number_format='0.000000')
        style_0_00 = NamedStyle(name="style_0_00", number_format='0.00')

        # 添加样式到工作簿
        wb.add_named_style(style_0_000000)
        wb.add_named_style(style_0_00)

        # 应用样式到相应列
        hdiff_col_index = df.columns.get_loc('高差') + 1  # 获取“高差”列的索引（+1 因为 Excel 列索引从 1 开始）
        rlen_col_index = df.columns.get_loc('路线长') + 1  # 获取“路线长”列的索引
        correct_factor_col_index = df.columns.get_loc('修正数') + 1  # 获取“修正数”列的索引
        period_diff_col_index = df.columns.get_loc('期间差异') + 1  # 获取“期间差异”列的索引

        for row in range(2, ws.max_row + 1):  # 从第二行开始，因为第一行为标题行
            ws.cell(row=row, column=hdiff_col_index).style = style_0_000000
            ws.cell(row=row, column=rlen_col_index).style = style_0_000000
            ws.cell(row=row, column=correct_factor_col_index).style = style_0_00
            ws.cell(row=row, column=period_diff_col_index).style = style_0_00

        # 设置 Dis_Ass 列为“变形”的行的字体颜色为红色
        red_font = Font(color="FF0000")
        dis_ass_col_index = df.columns.get_loc('变形判定') + 1  # 获取“变形判定”列的索引

        for row in range(2, ws.max_row + 1):  # 从第二行开始，因为第一行为标题行
            cell_value = ws.cell(row=row, column=dis_ass_col_index).value
            if cell_value == '变形':
                for col in range(1, ws.max_column + 1):
                    ws.cell(row=row, column=col).font = red_font
        # 设置列宽
        ws.column_dimensions['E'].width = 12
        ws.column_dimensions['F'].width = 12

        # 保存 Excel 文件之前添加单元格合并操作
        merge_cells = ['A1:A2', 'B1:B2', 'C1:C2', 'D1:D2', 'G1:G2', 'H1:H2', 'I1:I2']
        for cell_range in merge_cells:
            ws.merge_cells(cell_range)

        # 设置合并单元格后的居中对齐
        for cell_range in merge_cells:
            cell = ws[cell_range.split(':')[0]]
            cell.alignment = Alignment(horizontal='center', vertical='center')
            # 获取当前时间并格式化为字符串，例如：20231010_143000
        timestamp = time.strftime("%Y%m%d", time.localtime())
        # 保存 Excel 文件
        excel_filename = f"{os.path.splitext(decoded_utf_en)[0]}-成果数据-{timestamp}.xlsx"
        excel_filepath = os.path.join(export_folder, excel_filename)
        wb.save(excel_filepath)

        QMessageBox.information(ui, '成功', f'成果文件已成功导出到 {export_folder}')
    except Exception as e:
        QMessageBox.critical(ui, '错误', f'导出过程中发生错误: {str(e)}')
    finally:
        # 关闭数据库连接
        conn.close()


def export_initial_data(ui, utf_en, db_path, export_folder):
    try:
        # 解码 utf_en
        decoded_utf_en = utf_en.decode('utf-8') if isinstance(utf_en, bytes) else utf_en

        # 创建一个新的 Excel 工作簿
        wb = Workbook()
        ws = wb.active

        # 合并指定的单元格
        merge_cells = ['A1:B1', 'D1:E1', 'F1:G1', 'I1:J1']
        for cell_range in merge_cells:
            ws.merge_cells(cell_range)

        # 设置合并单元格后的居中对齐
        for cell_range in merge_cells:
            cell = ws[cell_range.split(':')[0]]
            cell.alignment = Alignment(horizontal='center', vertical='center')
        # 连接数据库
        conn = sqlite3.connect(db_path)
        cursor = conn.cursor()

        # 查询 GC_Input_Param 表获取 ObservationLevel, Last_ResultName, New_ResultName, Ms_Station 字段
        query_observation_level = "SELECT ObservationLevel, Last_ResultName, New_ResultName, Ms_Station FROM GC_Input_Param WHERE TableName=?"
        cursor.execute(query_observation_level, (utf_en,))
        result = cursor.fetchone()
        if result:
            observation_level, last_result_name, new_result_name, ms_station = result
        else:
            observation_level = "未找到"
            last_result_name = "未找到"
            new_result_name = "未找到"
            ms_station = "未找到"

        # 填写表头信息
        ws['A1'] = '观测等级'
        ws['C1'] = observation_level  # 将 ObservationLevel 写入 C1 单元格
        ws['A2'] = '序号'
        ws['B2'] = '起点'
        ws['C2'] = '终点'
        ws['D2'] = '高差（m）'
        ws['E2'] = '路线长（km）'
        ws['F1'] = '测站全中误差（mm）'
        ws['F2'] = '序号'
        ws['G2'] = '起点'
        ws['H2'] = '终点'
        ws['I2'] = '高差（m）'
        ws['J2'] = '路线长（km）'

        # 写入 Last_ResultName, New_ResultName, Ms_Station 到相应的单元格
        ws['D1'] = last_result_name
        ws['I1'] = new_result_name
        ws['H1'] = ms_station

        # 设置 H1 单元格的数值格式为保留两位小数
        ws['H1'].number_format = '0.00'

        # 连接数据库
        conn = sqlite3.connect(db_path)
        cursor = conn.cursor()

        # 查询数据库表为DataFrame，添加 TableName 条件
        query = "SELECT * FROM GC_Input_Point WHERE TableName=?"
        cursor.execute(query, (utf_en,))
        rows = cursor.fetchall()

        # 获取列名
        column_names = [description[0] for description in cursor.description]

        # 定义需要的列索引
        last_id_index = column_names.index('Last_ID')
        last_spname_index = column_names.index('Last_SPName')
        last_epname_index = column_names.index('Last_EPName')
        last_hdiff_index = column_names.index('Last_HDiff')
        last_rlen_index = column_names.index('Last_RLen')
        new_id_index = column_names.index('New_ID')
        new_spname_index = column_names.index('New_SPName')
        new_epname_index = column_names.index('New_EPName')
        new_hdiff_index = column_names.index('New_HDiff')
        new_rlen_index = column_names.index('New_RLen')

        # 填充数据到Excel
        for idx, row in enumerate(rows, start=3):
            ws.cell(row=idx, column=1, value=row[last_id_index])
            ws.cell(row=idx, column=2, value=row[last_spname_index])
            ws.cell(row=idx, column=3, value=row[last_epname_index])
            ws.cell(row=idx, column=4, value=row[last_hdiff_index])
            ws.cell(row=idx, column=5, value=row[last_rlen_index])
            ws.cell(row=idx, column=6, value=row[new_id_index])
            ws.cell(row=idx, column=7, value=row[new_spname_index])
            ws.cell(row=idx, column=8, value=row[new_epname_index])
            ws.cell(row=idx, column=9, value=row[new_hdiff_index])
            ws.cell(row=idx, column=10, value=row[new_rlen_index])

            # 设置 D, E, I, J 列为强制保留六位小数
            ws.cell(row=idx, column=4).number_format = '0.000000'
            ws.cell(row=idx, column=5).number_format = '0.000000'
            ws.cell(row=idx, column=9).number_format = '0.000000'
            ws.cell(row=idx, column=10).number_format = '0.000000'
        # 设置B,C,G,H的列宽为9.25
        ws.column_dimensions['B'].width = 9.25
        ws.column_dimensions['C'].width = 9.25
        ws.column_dimensions['G'].width = 9.25
        ws.column_dimensions['H'].width = 9.25

        # 设置 D, E, I, J 列的列宽为11.5
        ws.column_dimensions['D'].width = 11.5
        ws.column_dimensions['E'].width = 11.5
        ws.column_dimensions['I'].width = 11.5
        ws.column_dimensions['J'].width = 11.5
        # 获取当前时间并格式化为字符串，例如：20231010_143000
        timestamp = time.strftime("%Y%m%d", time.localtime())
        # 设置文件名
        excel_filename = f"{os.path.splitext(decoded_utf_en)[0]}-初始数据-{timestamp}.xlsx"
        excel_filepath = os.path.join(export_folder, excel_filename)

        # 保存 Excel 文件
        wb.save(excel_filepath)

        QMessageBox.information(ui, '成功', f'初始数据文件已成功导出到 {export_folder}')
    except Exception as e:
        if isinstance(e, PermissionError) or (isinstance(e, OSError) and e.errno == 13):
            QMessageBox.critical(ui, '错误', '请确认文件没有被其他程序（如Excel、文本编辑器等）打开。')
        else:
            QMessageBox.critical(ui, '错误', f'导出初始数据过程中发生错误: {str(e)}')

def process_utf_en(utf_en):
    # 确保 utf_en 是字节字符串
    if not isinstance(utf_en, bytes):
        utf_en = utf_en.encode('utf-8')

    # 将字节字符串解码为普通字符串
    file_name = utf_en.decode('utf-8')

    # 检查文件后缀名并进行相应处理
    if file_name.endswith('.xls'):
        # 去掉 .xls 后缀并添加 .xlsx 后缀
        file_name = file_name[:-4] + '.xlsx'

    # 将处理后的字符串重新编码为字节字符串
    utf_en = file_name.encode('utf-8')

    return utf_en

def main_function_initial(ui, utf_en, db_path):

    # 获取应用的安装目录
    app_install_dir = os.path.dirname(os.path.abspath(__file__))  # 假设脚本文件位于应用的安装目录下
    export_folder = os.path.join(app_install_dir, 'Export')

    # 如果 Export 文件夹不存在，则创建它
    if not os.path.exists(export_folder):
        os.makedirs(export_folder)

    # 调用导出初始数据函数
    export_initial_data(ui, utf_en, db_path, export_folder)


def main_function_result(ui, utf_en, db_path):
    # 处理 utf_en
    utf_en = process_utf_en(utf_en)
    # 获取应用的安装目录
    app_install_dir = os.path.dirname(os.path.abspath(__file__))  # 假设脚本文件位于应用的安装目录下
    export_folder = os.path.join(app_install_dir, 'Export')

    # 如果 Export 文件夹不存在，则创建它
    if not os.path.exists(export_folder):
        os.makedirs(export_folder)
    # 调用导出结果函数
    export_result_data(ui, utf_en, db_path, export_folder)