RIDE提供的库：
Create ListGet FileImport VariablesTemplateExcelLibrary自定义库：DataCenter.py
Read Data From ExcelRead Excel FileRead CSV FileRead Column From ExcelGet Sheet Values From Excel一、数据驱动测试 注重于测试软件的功能性需求，也即数据驱动测试执行程序所有功能需求的输入条件。
二、总结：根据数据源，灵活地实现KISS。
数据较少数据比较少的时候，可以使用 Create List， Get File & Import Variables。 创建 List 最快捷、最简单，但是处理多维列表就比较麻烦。如何创建多维列表，请查看齐道长的博客。
从 File 获取数据需要自己封装关键字，把原始数据处理并存储为列表。可以处理稍微复杂的数据，不过 File 存储的数据本身格式并不直观。
Import Variables 和 Create List 类似。相比 Create List，Import Variables 较灵活。因为 Import Variables 可以直接创建多维列表。
list1 = [[['grade1'], [5, 2, 3, 4], [6, 1, 7, 8]], [['grade2'], [1, 2, 3, 4], [5, 6, 7, 8]]]如果数据较少，比 Get Sheet Values From Excel 跟灵活。例如，在 Get Sheet Values From Excel 方法中的实例就需要把三维列表转换为二维列表。三维列表是从网页上获取并存储的数据。
def Reorgnize_List(self, alsit): newList = [] for element in alsit: if isinstance(element, list): for el in element: newList.append(natsort.natsorted(el)) OrderedData = natsort.natsorted(newList) return OrderedData if __name__ == '__main__': obj = main() list1 = [[['grade1'], [5, 2, 3, 4], [6, 1, 7, 8]], [['grade2'], [1, 2, 3, 4], [5, 6, 7, 8]]] list2 = obj.Reorgnize_List(list1) print list2测试新的二维列表与 Excel 中读取的数据保持一致。
list1 = [['grade1'], [5, 2, 3, 4], [6, 1, 7, 8]], ['grade2'], [1, 2, 3, 4], [5, 6, 7, 8]] 数据较多模板 Template，实现数据驱动简单。
但是，缺乏灵活度。比如，Read Column From Excel 方法中实现的选卡并测试每张卡所包含的课程，数据需要在关键字之间交互传递。如果写在一个关键字中，这个关键字将会过于复杂，不易管理维护。
RIDE 提供的 ExcelLibrary 功能较齐全。缺点较明显，即所有数据加上了行列值，处理起来比较麻烦。
如果不愿意修改源代码也可使用，不过在使用的时候需要小心谨慎。
最后，就是根据自身需求开发自定义关键字实现数据驱动。大家可以灵活运用，不用过于教条。
三、data_center.py 源代码
# -*- encoding = cp936 -*- # Author: Allan # Version: 2.0 # Data: 2017-3-20 import os, sys import csv import xdrlib import xlrd import json import natsort class data_center: def __init__(self): #Default File Path: self.data_dir = os.getenv('G_DATACENTER', 'F:\\Robotframework\\common\\resource') #print self.data_dir #Current Log Path: self.curr_dir = os.getenv('G_CURRENTLOG', 'f:\\robotframework\\logs') #print self.curr_dir def Read_Data_From_Excel(self, filename, path=None, includeEmptyCells=True): """ Returns the values from the file name specified. Returned values is separated and each sublist is one column. Arguments: | filename (string) | The selected Excel file that the cell values will be returned from. | | path | Default dirctory is G_DATACENTER | Example: | *Keywords* | *Parameters* | | ${data} | Read_Data_From_Excel | ExcelRobotTest.xls | %{G_DATACENTER} | includeEmptyCells=True | """ if path == None: file = os.path.join(self.data_dir, filename) # Default File Path else: file = os.path.join(path, filename) try: data = xlrd.open_workbook(file) table = data.sheets()[0] nrows = table.nrows nclos = table.ncols listAll=[] for row in range(2,nrows): alist=[] for col in range(1,nclos): val = table.cell(row,col).value # Solve issue that get integer data from Excel file would be auto-changed to float type. alist.append(self.keep_integer_type_from_excel(val)) listAll.append(alist) #print listAll listAll = self.unic(listAll) except Exception, e: print str(e) if includeEmptyCells is True: return listAll else: newList = [] for element in listAll: while "" in element: element.remove("") newList.append(natsort.natsorted(element)) OrderedData = natsort.natsorted(newList) return OrderedData def Read_Excel_File(self, filename, path=None, includeEmptyCells=True): """ Returns the values from the file name specified. Returned values is separated and each sublist is one column. Arguments: | filename (string) | The selected Excel file that the cell values will be returned from. | | path | Default dirctory is G_DATACENTER | Example: | *Keywords* | *Parameters* | | ${data} | Read_Excel_File | ExcelRobotTest.xls | %{G_DATACENTER} | includeEmptyCells=True | """ if path == None: file = os.path.join(self.data_dir, filename) # Default File Path else: file = os.path.join(path, filename) try: data = xlrd.open_workbook(file) table = data.sheets()[0] nrows = table.nrows nclos = table.ncols listAll=[] for row in range(2,nrows): for col in range(1,nclos): val = table.cell(row,col).value # Solve issue that get integer data from Excel file would be auto-changed to float type. value = self.keep_integer_type_from_excel(val) # print value, type(value) listAll.append(value) #print listAll listAll = self.unic(listAll) except Exception, e: print str(e) if includeEmptyCells is True: return listAll else: # Delete all empty data while '' in listAll: listAll.remove('') return listAll def Read_CSV_File(self, filename, path=None): """ Returns the values from the sheet name specified. Arguments: | filename (string) | The selected CSV file that the cell values will be returned from. | | path | Default dirctory is G_DATACENTER | Example: | *Keywords* | *Parameters* | | ${data} | Read_CSV_File | ExcelRobotTest.csv | %{G_DATACENTER} | """ if path == None: file = os.path.join(self.data_dir, filename) # Default File Path else: file = os.path.join(path, filename) data = [] with open(file, 'rb') as csvfile: data = [each for each in csv.DictReader(csvfile)] # reader =csv.reader(csvfile) # for col in reader: # data.append(col) return self.unic(data) def is_number(self, val): # Check if value is number not str. try: float(val) return True except ValueError: pass try: import unicodedata unicodedata.numeric(val) return True except (TypeError, ValueError): pass def keep_integer_type_from_excel(self, value): # Keep integer number as integer type. When reading from excel it has been changed to float type. if self.is_number(value) and type(value) != unicode and value%1 == 0: return str(int(value)) else: return value def unic(self, item): # Resolved Chinese mess code. try: item = json.dumps(item, ensure_ascii=False, encoding='cp936') except UnicodeDecodeError: try: item = json.dumps(item, ensure_ascii=False, encoding='cp936') except: pass except: pass item = json.loads(item, encoding='cp936') # Convert json data string back return item def Read_Column_From_Excel(self, filename, column, path=None, includeEmptyCells=True): reload(sys) sys.setdefaultencoding('cp936') alist = [] if path == None: file = os.path.join(self.data_dir, filename) #Default Data Directory else: file = os.path.join(path, filename) try: excel_data = xlrd.open_workbook(file) table = excel_data.sheets()[0] for row_index in range(2, table.nrows): value = table.cell(row_index, int(column)).value print value alist.append(self.keep_integer_type_from_excel(value)) #print alist listAll = self.unic(alist) except Exception, e: print str(e) if includeEmptyCells is True: return listAll else: # Delete all empty data while '' in listAll: listAll.remove('') return listAll def Get_Sheet_Values_From_Excel(self, filename, sheetname, path=None, includeEmptyCells=True): """ Returns the values from the sheet name specified. Arguments: | Sheet Name (string) | The selected sheet that the cell values will be returned from. | | Include Empty Cells (default=True) | The empty cells will be included by default. To deactivate and only return cells with values, pass 'False' in the variable. | Example: | *Keywords* | *Parameters* | | Get Sheet Values | ExcelRobotTest.csv | TestSheet1 | %{G_DATACENTER} | includeEmptyCells=True | """ if path == None: file = os.path.join(self.data_dir, filename) #Default Data Directory else: file = os.path.join(path, filename) try: excel_data = xlrd.open_workbook(file) sheetNames = self.get_sheet_names(excel_data) my_sheet_index = sheetNames.index(sheetname) #print my_sheet_index table = excel_data.sheet_by_index(my_sheet_index) nrows = table.nrows nclos = table.ncols listAll=[] for row in range(2,nrows): alist=[] for col in range(1,nclos): val = table.cell(row,col).value # Solve issue that get integer data from Excel file would be auto-changed to float type. alist.append(self.keep_integer_type_from_excel(val)) listAll.append(alist) #print listAll listAll = self.unic(listAll) except Exception, e: print str(e) if includeEmptyCells is True: return listAll else: newList = [] for element in listAll: while "" in element: element.remove("") newList.append(natsort.natsorted(element)) OrderedData = natsort.natsorted(newList) return OrderedData def get_sheet_names(self, wb): """ Returns the names of all the worksheets in the current workbook. Example: | *Keywords* | *Parameters* | | ${sheetNames} | Get Sheets Names | """ sheetNames = wb.sheet_names() return sheetNames