Parametrized fixtures in PyTest - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a parametrized fixture with pytest.

PyTest

import pytest

@pytest.fixture(params=[1, 2, 3])
def number(request):
    return request.[1]

Drag options to blanks, or click blank then click option'

Aitem

Bparam

Cvalue

Dparams

Attempts:

3 left

💡 Hint

Common Mistakes

Using request.params instead of request.param.

Trying to return request.value which does not exist.

The request.param attribute gives the current parameter value in a parametrized fixture.

2fill in blank

medium

Complete the test function to receive the parametrized fixture value.

PyTest

def test_is_positive([1]):
    assert [1] > 0

Drag options to blanks, or click blank then click option'

Anumber

Bparam

Crequest

Dvalue

Attempts:

3 left

💡 Hint

Common Mistakes

Using param or request as parameter names instead of the fixture name.

Not including any parameter in the test function.

The test function must accept the fixture name as a parameter to receive its value.

3fill in blank

hard

Fix the error in the fixture to correctly parametrize it with strings.

PyTest

import pytest

@pytest.fixture(params=[1])
def greeting(request):
    return request.param

Drag options to blanks, or click blank then click option'

A"hello, hi, hey"

B('hello', 'hi', 'hey')

C['hello', 'hi', 'hey']

Dhello, hi, hey

Attempts:

3 left

💡 Hint

Common Mistakes

Passing a single string instead of a list of strings.

Passing unquoted words without brackets.

The params argument must be a list or tuple of values. A list literal with quotes is correct.

4fill in blank

hard

Fill both blanks to parametrize a fixture with numbers and use it in a test.

PyTest

import pytest

@pytest.fixture(params=[1])
def num(request):
    return request.param

def test_even([2]):
    assert [2] % 2 == 0

Drag options to blanks, or click blank then click option'

A[2, 4, 6]

Bnum

Cnumber

D[1, 3, 5]

Attempts:

3 left

💡 Hint

Common Mistakes

Using odd numbers in the params list.

Using a different parameter name in the test function than the fixture name.

The fixture is parametrized with even numbers in a list. The test function must accept the fixture name num to get the values.

5fill in blank

hard

Fill all three blanks to create a parametrized fixture with mixed types and test their types.

PyTest

import pytest

@pytest.fixture(params=[1])
def data(request):
    return request.param

def test_type([2]):
    assert isinstance([3], (int, str))

Drag options to blanks, or click blank then click option'

A[42, 'answer', 7]

Bdata

D[42, 7, 13]

Attempts:

3 left

💡 Hint

Common Mistakes

Using only integers in the params list.

Using different names for the test function parameter and the variable in the assertion.

The fixture is parametrized with a list containing integers and a string. The test function receives the fixture data and checks if its type is int or str.

Practice

1. What is the main purpose of using @pytest.fixture(params=[...]) in pytest?

easy

A. To run the same test multiple times with different input data

B. To skip a test conditionally

C. To mark a test as expected to fail

D. To group multiple tests into a single test case

Solution

1. Step 1: Understand the role of parametrized fixtures

   Parametrized fixtures allow running a test function multiple times with different data inputs automatically.

2. Step 2: Match the purpose with the options

   To run the same test multiple times with different input data correctly describes this behavior, while others describe unrelated pytest features.

3. Final Answer:

   To run the same test multiple times with different input data -> Option A

4. Quick Check:

   Parametrized fixtures = run test multiple times [OK]

Hint: Parametrized fixtures repeat tests with different data [OK]

Common Mistakes:

• Confusing parametrized fixtures with test skipping
• Thinking it groups tests instead of repeating them
• Mixing up with expected failure markers

2. Which of the following is the correct syntax to define a parametrized fixture in pytest?

easy

A. @pytest.fixture(param=[1, 2, 3])\ndef data(request):\n return request.param

B. @pytest.param(params=[1, 2, 3])\ndef data(request):\n return request.param

C. @pytest.fixture(params=[1, 2, 3])\ndef data(request):\n return request.param

D. @pytest.fixture(params=(1, 2, 3))\ndef data():\n return param

Solution

1. Step 1: Identify correct decorator and parameter name

   The correct decorator is @pytest.fixture with the keyword params as a list.

2. Step 2: Check function signature and usage

   The fixture function must accept request and return request.param to access each parameter value.

3. Final Answer:

   @pytest.fixture(params=[1, 2, 3])\ndef data(request):\n return request.param -> Option C

4. Quick Check:

   Use @pytest.fixture(params=[...]) and request.param [OK]

Hint: Use @pytest.fixture(params=[...]) and request.param inside function [OK]

Common Mistakes:

• Using @pytest.param instead of @pytest.fixture
• Misspelling 'params' as 'param'
• Not including 'request' parameter in fixture function
• Returning undefined variable instead of request.param

3. Given the following pytest code, what will be the output when running the test?

import pytest

@pytest.fixture(params=[10, 20])
def number(request):
    return request.param

def test_double(number):
    assert number * 2 in [20, 40]

medium

A. First test fails, second test passes

B. Both tests fail

C. First test passes, second test fails

D. Both tests pass

Solution

1. Step 1: Understand parametrized fixture values

   The fixture 'number' will run the test twice: once with 10, once with 20.

2. Step 2: Evaluate the assertion for each value

   For 10: 10*2=20, which is in [20,40]. For 20: 20*2=40, also in [20,40]. Both assertions pass.

3. Final Answer:

   Both tests pass -> Option D

4. Quick Check:

   10*2=20 and 20*2=40 both in list [OK]

Hint: Check each param value and test assertion separately [OK]

Common Mistakes:

• Assuming only one test runs
• Misreading the assertion condition
• Forgetting fixture runs test multiple times

4. Identify the error in this parametrized fixture code snippet:

@pytest.fixture(params=["a", "b"])
def letter():
    return param

def test_letter(letter):
    assert letter in ["a", "b"]

medium

A. Wrong assertion in test function

B. Missing 'request' parameter in fixture function

C. Incorrect decorator name

D. Fixture should not return any value

Solution

1. Step 1: Check fixture function parameters

   The fixture uses params, so it must accept request to access request.param.

2. Step 2: Identify incorrect return statement

   The function returns param, which is undefined. It should return request.param.

3. Final Answer:

   Missing 'request' parameter in fixture function -> Option B

4. Quick Check:

   Parametrized fixture needs 'request' param [OK]

Hint: Parametrized fixtures must accept 'request' to use request.param [OK]

Common Mistakes:

• Not including 'request' parameter in fixture
• Returning undefined variable instead of request.param
• Confusing fixture decorator names

5. You want to test a function with multiple sets of user data, but some data sets are invalid and should be skipped. How can you modify a parametrized fixture to skip tests for invalid data?

hard

A. Use pytest.skip() inside the fixture when data is invalid

B. Remove invalid data from the params list before parametrizing

C. Raise an exception inside the test function for invalid data

D. Use pytest.mark.skipif on the test function with a condition

Solution

1. Step 1: Understand skipping inside parametrized fixtures

   Inside the fixture, you can call pytest.skip() when the current parameter is invalid to skip that test run.

2. Step 2: Compare with other options

   Removing invalid data beforehand avoids testing them but doesn't show skipped tests. Raising exceptions fails tests, not skip. Using skipif on test function is less flexible for per-parameter skipping.

3. Final Answer:

   Use pytest.skip() inside the fixture when data is invalid -> Option A

4. Quick Check:

   Call pytest.skip() in fixture to skip invalid params [OK]

Hint: Call pytest.skip() inside fixture for invalid params [OK]

Common Mistakes:

• Removing invalid data silently instead of skipping
• Raising exceptions instead of skipping
• Using skipif without parameter-specific logic