Selenium Python Automation Testing from Scratch and Frameworks - Introduction to Excel Data-Driven Testing

The video tutorial covers using Excel for data-driven testing in Python, highlighting the openpyxl library. It explains the installation and setup of openpyxl, and demonstrates how to read and write Excel data in Python. The tutorial emphasizes the simplicity of using Python for these tasks compared to other languages like Java.

Why is Excel considered outdated for data-driven testing?

• It is considered outdated but still used in legacy projects.

• It is difficult to integrate with modern software.

• It is not supported by any programming language.

• It lacks the ability to handle large datasets.

What is the primary advantage of using Python for Excel data handling?

• Python simplifies the process compared to Java.

• Python does not support Excel data handling.

• Python requires more methods than Java.

• Python is more complex than Java.

What is the purpose of the openpyxl library in Python?

• To create Excel files from scratch.

• To read and write Excel files.

• To convert Excel files to PDF.

• To visualize Excel data in graphs.

What command is used to install the openpyxl library?

• pip install openpyxl

• pip download openpyxl

• python install openpyxl

• install openpyxl

How do you load an Excel workbook using openpyxl?

• openpyxl.open('file.xlsx')

• openpyxl.read('file.xlsx')

• openpyxl.load_workbook('file.xlsx')

• openpyxl.import('file.xlsx')

What method is used to get the active sheet in an Excel workbook?

• workbook.sheet_active()

• workbook.get_active()

• workbook.active_sheet()

• workbook.active

How do you access the value of a specific cell in openpyxl?

• sheet.cell(row=1, column=2).value

• sheet.cell(row=1, column=2).get_value()

• sheet.get_cell(1, 2).value

• sheet.value(row=1, column=2)