自动化测试如何解析excel文件？

前言

　　自动化测试中我们存放数据无非是使用文件或者数据库，那么文件可以是csv，xlsx，xml，甚至是txt文件，通常excel文件往往是我们的首选，无论是编写测试用例还是存放测试数据，excel都是很方便的。那么今天我们就把不同模块处理excel文件的方法做个总结，直接做封装，方便我们以后直接使用，增加工作效率。

openpyxl

openpyxl是个第三方库，首先我们使用命令 pip install openpyxl 直接安装

注：openpyxl操作excel时，行号和列号都是从1开始计算的

封装代码

\"\"\"
------------------------------------
@Time : 2019/5/13 18:00
@Auth : linux超
@File : ParseExcel.py
@IDE  : PyCharm
@Motto: Real warriors,dare to face the bleak warning,dare to face the incisive error!
------------------------------------
\"\"\"
from openpyxl import load_workbook
from openpyxl.styles import Font
from openpyxl.styles.colors import BLACK
from collections import namedtuple


class ParseExcel(object):
    \"\"\"解析excel文件\"\"\"

    def __init__(self, filename, sheet_name=None):
        try:
            self.filename = filename
            self.sheet_name = sheet_name
            self.wb = load_workbook(self.filename)
            if self.sheet_name is None:
                self.work_sheet = self.wb.active
            else:
                self.work_sheet = self.wb[self.sheet_name]
        except FileNotFoundError as e:
            raise e

    def get_max_row_num(self):
        \"\"\"获取最大行号\"\"\"
        max_row_num = self.work_sheet.max_row
        return max_row_num

    def get_max_column_num(self):
        \"\"\"获取最大列号\"\"\"
        max_column = self.work_sheet.max_column
        return max_column

    def get_cell_value(self, coordinate=None, row=None, column=None):
        \"\"\"获取指定单元格的数据\"\"\"
        if coordinate is not None:
            try:
                return self.work_sheet[coordinate].value
            except Exception as e:
                raise e
        elif coordinate is None and row is not None and column is not None:
            if isinstance(row, int) and isinstance(column, int):
                return self.work_sheet.cell(row=row, column=column).value
            else:
                raise TypeError(\'row and column must be type int\')
        else:
            raise Exception(\"Insufficient Coordinate of cell!\")

    def get_row_value(self, row):
        \"\"\"获取某一行的数据\"\"\"
        column_num = self.get_max_column_num()
        row_value = []
        if isinstance(row, int):
            for column in range(1, column_num + 1):
                values_row = self.work_sheet.cell(row, column).value
                row_value.append(values_row)
            return row_value
        else:
            raise TypeError(\'row must be type int\')

    def get_column_value(self, column):
        \"\"\"获取某一列数据\"\"\"
        row_num = self.get_max_column_num()
        column_value = []
        if isinstance(column, int):
            for row in range(1, row_num + 1):
                values_column = self.work_sheet.cell(row, column).value
                column_value.append(values_column)
            return column_value
        else:
            raise TypeError(\'column must be type int\')

    def get_all_value_1(self):
        \"\"\"获取指定表单的所有数据(除去表头)\"\"\"
        max_row_num = self.get_max_row_num()
        max_column = self.get_max_column_num()
        values = []
        for row in range(2, max_row_num + 1):
            value_list = []
            for column in range(1, max_column + 1):
                value = self.work_sheet.cell(row, column).value
                value_list.append(value)
            values.append(value_list)
        return values

    def get_all_value_2(self):
        \"\"\"获取指定表单的所有数据(除去表头)\"\"\"
        rows_obj = self.work_sheet.iter_rows(min_row=2, max_row=self.work_sheet.max_row,
                                             values_only=True)  # 指定values_only 会直接提取数据不需要再使用cell().value
        values = []
        for row_tuple in rows_obj:
            value_list = []
            for value in row_tuple:
                value_list.append(value)
            values.append(value_list)
        return values

    def get_excel_title(self):
        \"\"\"获取sheet表头\"\"\"
        title_key = tuple(self.work_sheet.iter_rows(max_row=1, values_only=True))[0]
        return title_key

    def get_listdict_all_value(self):
        \"\"\"获取所有数据，返回嵌套字典的列表\"\"\"
        sheet_title = self.get_excel_title()
        all_values = self.get_all_value_2()
        value_list = []
        for value in all_values:
            value_list.append(dict(zip(sheet_title, value)))
        return value_list

    def get_list_nametuple_all_value(self):
        \"\"\"获取所有数据，返回嵌套命名元组的列表\"\"\"
        sheet_title = self.get_excel_title()
        values = self.get_all_value_2()

        excel = namedtuple(\'excel\', sheet_title)
        value_list = []
        for value in values:
            e = excel(*value)
            value_list.append(e)
        return value_list

    def write_cell(self, row, column, value=None, bold=True, color=BLACK):
        \"\"\"
        指定单元格写入数据
        :param work_sheet:
        :param row: 行号
        :param column: 列号
        :param value: 待写入数据
        :param bold: 加粗， 默认加粗
        :param color: 字体颜色，默认黑色
        :return:
        \"\"\"
        try:
            if isinstance(row, int) and isinstance(column, int):
                cell_obj = self.work_sheet.cell(row, column)
                cell_obj.font = Font(color=color, bold=bold)
                cell_obj.value = value
                self.wb.save(self.filename)
            else:
                raise TypeError(\'row and column must be type int\')
        except Exception as e:
            raise e

if __name__ == \'__main__\':
    pe = ParseExcel(\'testdata.xlsx\')
    # sheet = pe.get_sheet_object(\'testcase\')

    column_row = pe.get_max_column_num()
    print(\'最大列号:\', column_row)
    max_row = pe.get_max_row_num()
    print(\'最大行号:\', max_row)
    #
    cell_value_1 = pe.get_cell_value(row=2, column=3)
    print(\'第%d行, 第%d列的数据为: %s\' % (2, 3, cell_value_1))

    cell_value_2 = pe.get_cell_value(coordinate=\'A5\')
    print(\'A5单元格的数据为: {}\'.format(cell_value_2))

    value_row = pe.get_row_value(3)
    print(\'第{}行的数据为:{}\'.format(3, value_row))

    value_column = pe.get_column_value(2)
    print(\'第{}列的数据为:{}\'.format(2, value_column))
    #
    values_1 = pe.get_all_value_1()
    print(\'第一种方式获取所有数据\\n\', values_1)

    values_2 = pe.get_all_value_2()
    print(\'第二种方式获取所有数据\\n\', values_2)

    title = pe.get_excel_title()
    print(\'表头为\\n{}\'.format(title))

    dict_value = pe.get_listdict_all_value()
    print(\'所有数据组成的嵌套字典的列表:\\n\', dict_value)
    #
    namedtuple_value = pe.get_list_nametuple_all_value()
    print(\'所有数据组成的嵌套命名元组的列表:\\n\', namedtuple_value)

    pe.write_cell(1, 2, \'Tc_title\')

xlrd

安装xlrd，此模块只支持读操作， 如果要写需要使用xlwt或者使用xlutils配合xlrd， 但是使用xlwt只能对新的excel文件进行写操作，无法对原有文件进行写， 所以这里选择是用xlutils

但是还有一个问题就是，如果使用xlutils， 那么我们的excel文件需要以.xls 为后缀。因为以xlsx为后缀无法实现写，会报错(亲测，因为formatting_info参数还没有对新版本的xlsx的格式完成兼容)

注：xlrd操作excel时，行号和列号都是从0开始计算的

封装代码

\"\"\"
------------------------------------
@Time : 2019/5/13 21:22
@Auth : linux超
@File : ParseExcel_xlrd.py
@IDE  : PyCharm
@Motto: Real warriors,dare to face the bleak warning,dare to face the incisive error!
------------------------------------
\"\"\"
import xlrd
from xlutils import copy
from collections import namedtuple


class ParseExcel(object):
    # xlrd 解析excel， 行号和列号都是从0开始的
    def __init__(self, filename, sheet):
        try:
            self.filename = filename
            self.sheet = sheet
            self.wb = xlrd.open_workbook(self.filename, formatting_info=True)
            if isinstance(sheet, str):
                self.sheet = self.wb.sheet_by_name(sheet)
            elif isinstance(sheet, int):
                self.sheet = self.wb.sheet_by_index(sheet)
            else:
                raise TypeError(\'sheet must be int or str\')
        except Exception as e:
            raise e

    def get_max_row(self):
        \"\"\"获取表单的最大行号\"\"\"
        max_row_num = self.sheet.nrows
        return max_row_num

    def get_max_column(self):
        \"\"\"获取表单的最大列号\"\"\"
        min_row_num = self.sheet.ncols
        return min_row_num

    def get_cell_value(self, row, column):
        \"\"\"获取某个单元格的数据\"\"\"
        if isinstance(row, int) and isinstance(column, int):
            values = self.sheet.cell(row-1, column-1).value
            return values
        else:
            raise TypeError(\'row and column must be type int\')

    def get_row_values(self, row):
        \"\"\"获取某一行的数据\"\"\"
        if isinstance(row, int):
            values = self.sheet.row_values(row-1)
            return values
        else:
            raise TypeError(\'row must be type int\')

    def get_column_values(self, column):
        \"\"\"获取某一列的数据\"\"\"

        if isinstance(column, int):
            values = self.sheet.col_values(column-1)
            return values
        else:
            raise TypeError(\'column must be type int\')

    def get_table_title(self):
        \"\"\"获取表头\"\"\"
        table_title = self.get_row_values(1)
        return table_title

    def get_all_values_dict(self):
        \"\"\"获取所有的数据，不包括表头，返回一个嵌套字典的列表\"\"\"
        max_row = self.get_max_row()
        table_title = self.get_table_title()
        value_list = []
        for row in range(2, max_row):
            values = self.get_row_values(row)
            value_list.append(dict(zip(table_title, values)))
        return value_list

    def get_all_values_nametuple(self):
        \"\"\"获取所有的数据，不包括表头，返回一个嵌套命名元组的列表\"\"\"
        table_title = self.get_table_title()
        max_row = self.get_max_row()
        excel = namedtuple(\'excel\', table_title)
        value_list = []
        for row in range(2, max_row):
            values = self.get_row_values(row)
            e = excel(*values)
            value_list.append(e)
        return value_list

    def write_value(self, sheet_index, row, column, value):
        \"\"\"写入某个单元格数据\"\"\"
        if isinstance(row, int) and isinstance(column, int):
            if isinstance(sheet_index, int):
                wb = copy.copy(self.wb)
                worksheet = wb.get_sheet(sheet_index)
                worksheet.write(row-1, column-1, value)
                wb.save(self.filename)
            else:
                raise TypeError(\'{} must be int\'.format(sheet_index))
        else:
            raise TypeError(\'{} and {} must be int\'.format(row, column))

if __name__ == \'__main__\':
    pe = ParseExcel(\'testdata.xls\', \'testcase\')
    print(\'最大行号:\', pe.get_max_row())
    print(\'最大列号:\', pe.get_max_column())
    print(\'第2行第3列数据:\', pe.get_cell_value(2, 3))
    print(\'第2行数据\', pe.get_row_values(2))
    print(\'第3列数据\', pe.get_column_values(3))
    print(\'表头:\', pe.get_table_title())
    print(\'所有的数据返回嵌套字典的列表:\', pe.get_all_values_dict())
    print(\'所有的数据返回嵌套命名元组的列表:\', pe.get_all_values_nametuple())
　　 pe.write_value(0, 1, 3, \'test\')

pandas

pandas是一个做数据分析的库， 总是感觉在自动化测试中使用pandas解析excel文件读取数据有点大材小用，不论怎样吧，还是把pandas解析excel文件写一下把

我这里只封装了读，写的话我这有点小问题，后面改好再追加代码吧。

请先pip install pandas安装pandas

封装代码

\"\"\"
------------------------------------
@Time : 2019/5/13 14:00
@Auth : linux超
@File : ParseExcel_pandas.py
@IDE  : PyCharm
@Motto: Real warriors,dare to face the bleak warning,dare to face the incisive error!
------------------------------------
\"\"\"
import pandas as pd


class ParseExcel(object):
    def __init__(self, filename, sheet_name=None):
        try:
            self.filename = filename
            self.sheet_name = sheet_name
            self.df = pd.read_excel(self.filename, self.sheet_name)
        except Exception as e:
            raise e

    def get_row_num(self):
        \"\"\"获取行号组成的列表, 从0开始的\"\"\"
        row_num_list = self.df.index.values
        return row_num_list

    def get_cell_value(self, row, column):
        \"\"\"获取某一个单元格的数据\"\"\"
        try:
            if isinstance(row, int) and isinstance(column, int):
                cell_value = self.df.ix[row-2, column-1] # ix的行参数是按照有效数据行，且从0开始
                return cell_value
            else:
                raise TypeError(\'row and column must be type int\')
        except Exception as e:
            raise e

    def get_table_title(self):
        \"\"\"获取表头， 返回列表\"\"\"
        table_title = self.df.columns.values
        return table_title

    def get_row_value(self, row):
        \"\"\"获取某一行的数据， 行号从1开始\"\"\"
        try:
            if isinstance(row, int):
                row_data = self.df.ix[row-2].values
                return row_data
            else:
                raise TypeError(\'row must be type int\')
        except Exception as e:
            raise e

    def get_column_value(self, col_name):
        \"\"\"获取某一列数据\"\"\"
        try:
            if isinstance(col_name, str):
                col_data = self.df[col_name].values
                return col_data
            else:
                raise TypeError(\'col_name must be type str\')
        except Exception as e:
            raise e
        
    def get_all_value(self):
        \"\"\"获取所有的数据，不包括表头, 返回嵌套字典的列表\"\"\"
        rows_num = self.get_row_num()
        table_title = self.get_table_title()
        values_list = []
        for i in rows_num:
            row_data = self.df.ix[i, table_title].to_dict()
            values_list.append(row_data)
        return values_list


if __name__ == \'__main__\':
    pe = ParseExcel(\'testdata.xlsx\', \'testcase\')
    print(pe.get_row_num())
    print(pe.get_table_title())
    print(pe.get_all_value())
    print(pe.get_row_value(2))
    print(pe.get_cell_value(2, 3))
    print(pe.get_column_value(\'Tc_title\'))

总结

使用了3种方法，4个库 xlrd，openpyxl，xlwt，pandas 操作excel文件，个人感觉还是使用openpyxl比较适合在自动化中使用，当然不同人有不同选择，用哪个区别也不是很大。

以上3种方法，都可以拿来直接使用，不需要再做封装了 ！