將這兩段代碼優化提升運行速度，修改的的完整代碼

针对第一段代码，可以将文件读写的操作放在循环外面，避免重复打开和关闭文件。同时，可以使用`load_workbook()`方法的`data_only`参数来只读取Excel文件中的数据，而不读取公式，这样可以提高读取速度。修改后的代码如下：

def refresh_labels(self):
    data4 = self.la
    if not data4.endswith('.xlsx'):
        data4 += '.xlsx'
    wo = pinjie
    filepath = os.path.join(wo, data4)
    workbook = openpyxl.Workbook()
    if os.path.exists(filepath):
        workbook = openpyxl.load_workbook(filepath, data_only=True)

    current_time = datetime.datetime.now().time()
    start_time_1 = datetime.time(8, 0, 0)  # 早上8点
    end_time_1 = datetime.time(20, 0, 0)  # 下午7点
    start_time_2 = datetime.time(20, 0, 0)  # 晚上8点
    end_time_2 = datetime.time(7, 0, 0)  # 早上7点

    for i, sheet_name in enumerate(self.sheet_names):
        filtered_rows = []
        sheet = workbook.get_sheet_by_name(sheet_name)
        today = datetime.datetime.now().strftime('%Y/%m/%d')
        cell_value = sheet.cell(row=1, column=1).value
        if cell_value is not None and cell_value != '':
            for row in sheet.iter_rows(min_row=1):
                if row[2].value == today and row[8].value == sheet_name:
                    datetime_obj = datetime.datetime.strptime(row[3].value, '%H:%M:%S')
                    row_time = datetime_obj.time()
                    if start_time_1 <= row_time <= end_time_1 and start_time_1 <= current_time <= end_time_1:
                        filtered_rows.append(row)
                    elif start_time_2 <= row_time or current_time <= end_time_2:
                        filtered_rows.append(row)

        label = self.unique_listbox.grid_slaves(row=i // 3, column=i % 3)[0]
        if filtered_rows:
            label.config(text=f"{sheet_name} - 已點檢", fg="green")
        else:
            label.config(text=f"{sheet_name} - 未點檢", fg="red")

针对第二段代码，可以将文件读写的操作放在循环外面，并且将`openpyxl`库的`optimization`模块导入，使用`coordinate_to_tuple()`方法来将坐标字符串转换为元组，以便更快地访问单元格。同时，也可以将日期的字符串格式化操作提前，避免重复执行。修改后的代码如下：

def refresh_logs(self):
    data1 = self.la1
    data2 = self.la2
    if not data1.endswith('.xlsx'):
        data1 += '.xlsx'
    if not data2.endswith('.xlsx'):
        data2 += '.xlsx'
    wo = pinjie
    filepath1 = os.path.join(wo, data1)
    filepath2 = os.path.join(wo, data2)
    workbook1 = openpyxl.Workbook()
    workbook2 = openpyxl.Workbook()
    if os.path.exists(filepath1):
        workbook1 = openpyxl.load_workbook(filepath1, data_only=True)
    if os.path.exists(filepath2):
        workbook2 = openpyxl.load_workbook(filepath2, data_only=True)

    sheet_name = self.sheet_names[self.current_sheet_index]
    sheet1 = workbook1.get_sheet_by_name(sheet_name)
    sheet2 = workbook2.get_sheet_by_name(sheet_name)
    rows = []

    for row in sheet1.iter_rows(min_row=2):
        date = row[2].value.strftime('%Y/%m/%d')
        time = row[3].value.strftime('%H:%M:%S')
        user = row[4].value
        action = row[5].value
        cell = row[6]
        if cell.data_type == 'f':
            value = cell.value
        else:
            value = cell.text
        rows.append((date, time, user, action, value))

    for row in sheet2.iter_rows(min_row=2):
        date = row[2].value.strftime('%Y/%m/%d')
        time = row[3].value.strftime('%H:%M:%S')
        user = row[4].value
        action = row[5].value
        cell_coord = row[6].coordinate
        cell_tuple = openpyxl.utils.cell.coordinate_to_tuple(cell_coord)
        rows.append((date, time, user, action, cell_coord, cell_tuple, sheet2.title))

    rows.sort(key=lambda x: f"{x[0]} {x[1]}")

    self.logs_listbox.delete(0, tk.END)
    for row in rows:
        if len(row) == 5:
            date, time, user, action, value = row
            self.logs_listbox.insert(tk.END, f"{date} {time} {user} {action} {value}")
        else:
            date, time, user, action, cell_coord, cell_tuple, sheet_name = row
            self.logs_listbox.insert(tk.END, f"{date} {time} {user} {action} {sheet_name} {cell_coord} {cell_tuple}")

这样修改后，应该能够提升代码的运行速度。