Reading test data from CSV in Selenium Python - Framework Patterns

Framework Mode - Reading test data from CSV

Folder Structure

selenium-python-project/
├── src/
│   ├── pages/
│   │   └── login_page.py
│   ├── tests/
│   │   └── test_login.py
│   ├── utils/
│   │   └── csv_reader.py
│   └── config/
│       └── config.yaml
├── test_data/
│   └── login_data.csv
├── requirements.txt
└── pytest.ini
  

Test Framework Layers

• Driver Layer: Handles browser setup and teardown using Selenium WebDriver.
• Page Objects: Classes representing web pages, encapsulating locators and actions.
• Tests: Test scripts that use page objects and test data to perform validations.
• Utilities: Helper modules like csv_reader.py to read CSV files and provide data.
• Config: Configuration files (e.g., YAML) for environment settings, URLs, and credentials.
• Test Data: CSV files storing test inputs, separated from code for easy updates.

Configuration Patterns

Use a config.yaml file to store environment URLs, browser choices, and credentials. Load this config in tests or fixtures.

Example config.yaml snippet:

environment:
  url: "https://example.com"
browser: "chrome"
credentials:
  username: "testuser"
  password: "password123"
  

Use Python's csv module in csv_reader.py to read test data from CSV files in test_data/. This keeps test data separate and easy to maintain.

Test Reporting and CI/CD Integration

• Use pytest with plugins like pytest-html or allure-pytest for clear HTML reports.
• Integrate tests in CI/CD pipelines (GitHub Actions, Jenkins) to run tests automatically on code changes.
• Reports help quickly see which tests passed or failed, including data-driven tests using CSV inputs.

Best Practices

• Separate Test Data: Keep CSV files outside code to update test inputs without changing code.
• Reusable CSV Reader: Create a utility function to read CSV and return data in a usable format (list of dicts).
• Data-Driven Tests: Use pytest parameterization to run tests with multiple data rows from CSV.
• Clear Naming: Name CSV columns clearly to match test parameters for easy mapping.
• Handle Exceptions: Add error handling when reading CSV to avoid test crashes on bad data.

Self Check

Where would you add a new CSV file for test data about user registration?

Answer: In the test_data/ folder, as this folder holds all CSV test data files.

Key Result

Organize test data in CSV files under a dedicated folder and use utility functions to read them for data-driven Selenium tests.

Practice

1. What is the main advantage of reading test data from a CSV file in Selenium Python tests?

easy

A. It allows running tests with multiple sets of data without changing the code.

B. It makes the test run faster by using CSV format.

C. It automatically fixes bugs in the test code.

D. It encrypts the test data for security.

Solution

1. Step 1: Understand the purpose of external test data

   Using CSV files lets you separate test data from test code, making tests flexible.

2. Step 2: Identify the benefit in test execution

   With CSV, you can run the same test multiple times with different inputs easily.

3. Final Answer:

   It allows running tests with multiple sets of data without changing the code. -> Option A

4. Quick Check:

   CSV externalizes data = flexible tests [OK]

Hint: CSV stores data separately for easy test reuse [OK]

Common Mistakes:

• Thinking CSV speeds up test execution
• Believing CSV fixes code bugs automatically
• Assuming CSV encrypts data

2. Which Python code snippet correctly opens a CSV file named data.csv for reading test data?

easy

A. file = open('data.csv', 'w')

B. file = open('data.csv', 'r')

C. file = open('data.csv', 'a')

D. file = open('data.csv')

Solution

1. Step 1: Identify the correct file mode for reading

   To read a file, use mode 'r' which stands for read-only.

2. Step 2: Check the options

   file = open('data.csv', 'r') uses 'r' mode correctly; others use write ('w'), append ('a'), or default mode which may not be explicit.

3. Final Answer:

   file = open('data.csv', 'r') -> Option B

4. Quick Check:

   Read mode = 'r' [OK]

Hint: Use 'r' mode to open files for reading [OK]

Common Mistakes:

• Using 'w' which overwrites the file
• Using 'a' which appends instead of reading
• Not specifying mode explicitly

3. Given the CSV file users.csv with content:

username,password
alice,pass123
bob,secure456

What will the output of this code be?

import csv
with open('users.csv', 'r') as file:
    reader = csv.reader(file)
    for row in reader:
        print(row)

medium

A. ('username', 'password')
('alice', 'pass123')
('bob', 'secure456')

B. username,password
alice,pass123
bob,secure456

C. Error: csv.reader cannot read files

D. ['username', 'password']
['alice', 'pass123']
['bob', 'secure456']

Solution

1. Step 1: Understand csv.reader output

   csv.reader reads each line as a list of strings split by commas.

2. Step 2: Analyze the print output

   Each row prints as a list, so header and data rows print as lists of strings.

3. Final Answer:

   ['username', 'password'] ['alice', 'pass123'] ['bob', 'secure456'] -> Option D

4. Quick Check:

   csv.reader returns lists per row [OK]

Hint: csv.reader returns list of strings per row [OK]

Common Mistakes:

• Expecting strings instead of lists
• Confusing tuples with lists
• Thinking csv.reader raises error on valid files

4. What is wrong with this code snippet that reads CSV data for Selenium tests?

import csv
file = open('testdata.csv')
reader = csv.reader(file)
for row in reader:
    print(row)
file.close()

medium

A. The file is not opened in read mode explicitly.

B. The file is not closed after reading.

C. Using open() without a context manager can cause resource leaks.

D. csv.reader cannot be used with open() function.

Solution

1. Step 1: Check file handling best practices

   Using open() without 'with' can cause the file to remain open if errors occur.

2. Step 2: Identify the issue in the code

   Though file.close() is called, if an error happens before, file may not close properly.

3. Final Answer:

   Using open() without a context manager can cause resource leaks. -> Option C

4. Quick Check:

   Use 'with' to auto-close files [OK]

Hint: Always use 'with' to open files safely [OK]

Common Mistakes:

• Thinking file.close() always prevents leaks
• Believing csv.reader can't work with open()
• Ignoring explicit read mode is optional

5. You want to run a Selenium test multiple times using usernames and passwords stored in credentials.csv. Which code snippet correctly reads the CSV and uses the data in a test function?

hard

A. import csv
with open('credentials.csv', 'r') as file:
reader = csv.DictReader(file)
for row in reader:
username = row['username']
password = row['password']
test_login(username, password)

B. import csv
file = open('credentials.csv', 'r')
reader = csv.reader(file)
for row in reader:
test_login(row[0], row[1])
file.close()

C. import csv
with open('credentials.csv') as file:
reader = csv.reader(file)
for row in reader:
test_login(row['username'], row['password'])

D. import csv
with open('credentials.csv', 'r') as file:
reader = csv.reader(file)
for row in reader:
test_login(row[0], row[1])

Solution

1. Step 1: Choose correct CSV reading method for named columns

   csv.DictReader reads CSV rows as dictionaries with column names as keys.

2. Step 2: Use dictionary keys to access username and password

   Accessing row['username'] and row['password'] matches CSV headers and passes correct data.

3. Final Answer:

   Using csv.DictReader and accessing row['username'] and row['password'] correctly. -> Option A

4. Quick Check:

   DictReader + keys = clean data access [OK]

Hint: Use csv.DictReader for named column access [OK]

Common Mistakes:

• Using csv.reader but accessing row by keys
• Not closing files without 'with' block
• Forgetting to specify read mode explicitly