Reading test data from Excel in Selenium Python

Introduction

Reading test data from Excel helps you run tests with different inputs easily. It saves time and avoids mistakes from typing data again and again.

You want to test a login form with many usernames and passwords.

You need to check a calculator app with many number pairs.

You want to run the same test steps but with different data sets.

You want to keep test data separate from test code for easy updates.

Syntax

Selenium Python

import openpyxl

# Load Excel file
workbook = openpyxl.load_workbook('data.xlsx')

# Select sheet by name
sheet = workbook['Sheet1']

# Read cell value
value = sheet.cell(row=1, column=1).value

Use openpyxl library to read Excel files in Python.

Rows and columns start at 1, not 0.

Examples

This reads the value from row 2, column 3 of the active sheet.

Selenium Python

import openpyxl
workbook = openpyxl.load_workbook('testdata.xlsx')
sheet = workbook.active
print(sheet.cell(row=2, column=3).value)

This loops through all rows in the 'Users' sheet and prints usernames and passwords.

Selenium Python

import openpyxl
workbook = openpyxl.load_workbook('testdata.xlsx')
sheet = workbook['Users']
for row in range(2, sheet.max_row + 1):
    username = sheet.cell(row=row, column=1).value
    password = sheet.cell(row=row, column=2).value
    print(f"User: {username}, Pass: {password}")

Sample Program

This script reads login data from an Excel file and checks that the data is not empty. It simulates using this data in a test.

Selenium Python

import openpyxl

# Load Excel file
workbook = openpyxl.load_workbook('testdata.xlsx')
sheet = workbook['LoginData']

# Read username and password from second row
username = sheet.cell(row=2, column=1).value
password = sheet.cell(row=2, column=2).value

# Simple test simulation
print(f"Testing login with username: {username} and password: {password}")

# Assert username and password are not empty
assert username is not None and username != '', 'Username is empty'
assert password is not None and password != '', 'Password is empty'

print('Test data read successfully and assertions passed.')

Important Notes

Make sure the Excel file is in the same folder or provide the full path.

Use meaningful sheet names to avoid confusion.

Always check for empty or missing data to avoid test errors.

Summary

Reading test data from Excel helps run tests with many inputs easily.

Use openpyxl to load and read Excel files in Python.

Always validate the data read before using it in tests.

Practice

1. What is the main reason to read test data from an Excel file in Selenium Python tests?

easy

A. To create Excel files automatically

B. To make the test code run faster

C. To run tests with many different inputs easily

D. To avoid writing any test code

Solution

1. Step 1: Understand test data usage

   Test data from Excel allows running the same test with many inputs without changing code.

2. Step 2: Identify the benefit

   This makes tests flexible and easier to maintain.

3. Final Answer:

   To run tests with many different inputs easily -> Option C

4. Quick Check:

   Reading Excel data = flexible inputs [OK]

Hint: Excel stores many inputs for tests in one place [OK]

Common Mistakes:

• Thinking Excel makes tests faster
• Believing Excel replaces test code
• Confusing data reading with file creation

2. Which Python library is commonly used to read Excel files for Selenium tests?

easy

A. selenium

B. pandas

C. requests

D. openpyxl

Solution

1. Step 1: Recall Excel reading libraries

   openpyxl is a popular library to read/write Excel files in Python.

2. Step 2: Differentiate from other libraries

   pandas can read Excel but is heavier; requests is for web calls; selenium is for browser automation.

3. Final Answer:

   openpyxl -> Option D

4. Quick Check:

   Excel reading = openpyxl [OK]

Hint: openpyxl is made for Excel files in Python [OK]

Common Mistakes:

• Choosing selenium which automates browsers
• Picking requests which handles HTTP
• Confusing pandas with openpyxl

3. Given this code snippet, what will be printed?

from openpyxl import load_workbook
wb = load_workbook('data.xlsx')
sheet = wb.active
print(sheet['A2'].value)

Assuming cell A2 contains the text "TestUser".

medium

A. data.xlsx

B. TestUser

C. sheet['A2']

D. None

Solution

1. Step 1: Understand openpyxl cell access

   sheet['A2'].value reads the content of cell A2 in the active sheet.

2. Step 2: Check given cell content

   Cell A2 contains "TestUser", so print outputs this string.

3. Final Answer:

   TestUser -> Option B

4. Quick Check:

   sheet['A2'].value = "TestUser" [OK]

Hint: sheet['A2'].value reads cell A2 content [OK]

Common Mistakes:

• Printing the cell object instead of its value
• Confusing filename with cell content
• Expecting None if cell has text

4. What is wrong with this code snippet for reading Excel data?

from openpyxl import load_workbook
wb = load_workbook('testdata.xlsx')
sheet = wb['Sheet1']
for row in sheet.iter_rows(min_row=2, values_only=True):
    print(row[0])

medium

A. No error; code reads first column from second row correctly

B. Using sheet['Sheet1'] instead of wb['Sheet1']

C. Not specifying min_row=1 in iter_rows

D. Missing call to wb.save() before reading

Solution

1. Step 1: Check sheet access

   wb['Sheet1'] correctly accesses the sheet named 'Sheet1'.

2. Step 2: Analyze iter_rows usage

   iter_rows with min_row=2 and values_only=True returns tuples of cell values from second row onward.

3. Step 3: Confirm print statement

   Printing row[0] prints the first column value of each row starting from row 2.

4. Final Answer:

   No error; code reads first column from second row correctly -> Option A

5. Quick Check:

   Code reads data correctly [OK]

Hint: wb['Sheet1'] accesses sheet; iter_rows returns values [OK]

Common Mistakes:

• Using sheet['Sheet1'] instead of wb['Sheet1']
• Forgetting values_only=True to get cell values
• Thinking wb.save() is needed before reading

5. You want to read username and password pairs from Excel to run login tests. Which approach is best to handle empty cells safely?

hard

A. Use iter_rows with values_only=True and check if each cell is None before using

B. Skip checking cells and assume all data is present

C. Use sheet['A1'].value only and ignore other rows

D. Convert Excel file to CSV and read with open()

Solution

1. Step 1: Understand data safety

   Empty cells in Excel return None, which can cause errors if not checked.

2. Step 2: Use iter_rows with values_only=True and check for None

   This approach reads all rows and allows safe validation before using data in tests.

3. Step 3: Avoid unsafe assumptions

   Skipping checks or reading only one cell risks test failures or incomplete coverage.

4. Final Answer:

   Use iter_rows with values_only=True and check if each cell is None before using -> Option A

5. Quick Check:

   Check None in cells to avoid errors [OK]

Hint: Always check for None in Excel cell values [OK]

Common Mistakes:

• Ignoring empty cells causing test crashes
• Reading only one cell missing data
• Converting to CSV losing Excel features