Database fixture patterns in PyTest - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is a database fixture in pytest?

A database fixture in pytest is a setup function that prepares a test database environment before tests run and cleans it up afterward. It helps tests run with consistent data and state.

beginner

Why use database fixtures instead of creating data inside each test?

Using database fixtures avoids repeating setup code in every test. It ensures tests start with a known database state, making tests faster, cleaner, and easier to maintain.

intermediate

What is the difference between function-scoped and session-scoped database fixtures?

Function-scoped fixtures run before and after each test function, giving a fresh database state every time. Session-scoped fixtures run once per test session, sharing the same database state across tests.

intermediate

How can you ensure database changes made during a test do not affect other tests?

You can use transactions that roll back after each test or recreate the database state using fixtures to isolate tests and keep the database clean.

beginner

What is a common pattern to load initial test data using pytest fixtures?

A common pattern is to create a fixture that inserts known test data into the database before tests run, so tests can rely on this data without setting it up themselves.

What does a pytest database fixture typically do?

A Generate user interface elements

B Compile the application code

C Set up and tear down database state for tests

D Send emails during tests

Database fixtures prepare the database before tests and clean it after, ensuring consistent test environments.

Which fixture scope gives a fresh database state for each test function?

A Function scope

B Session scope

C Module scope

D Class scope

Function-scoped fixtures run before each test function, providing a clean database state every time.

How can pytest fixtures help avoid test interference in database tests?

A By sharing the same database state for all tests

B By isolating tests with setup and teardown steps

C By disabling the database during tests

D By running tests in parallel without setup

Fixtures isolate tests by preparing and cleaning the database, preventing one test's changes from affecting others.

What is a benefit of using session-scoped database fixtures?

A They speed up tests by reusing setup

B They run before every test function

C They create a new database for each test

D They disable database access

Session-scoped fixtures run once per test session, reducing setup time by reusing the database state.

What is a common way to reset database changes after a test?

A Restart the computer

B Ignore database changes

C Delete the test code

D Use transactions with rollback

Using transactions that roll back after tests keeps the database clean and ready for the next test.

Explain how database fixtures help maintain test isolation in pytest.

Think about how tests share or reset data.

Describe the difference between function-scoped and session-scoped database fixtures and when to use each.

Consider test speed versus data freshness.

Practice

1. What is the main purpose of using database fixtures in pytest?

easy

A. To speed up the database server

B. To write SQL queries inside test functions

C. To prepare and clean test data automatically before and after tests

D. To replace the need for assertions in tests

Solution

1. Step 1: Understand what fixtures do

   Fixtures in pytest are used to set up and tear down resources needed for tests, such as database data.

2. Step 2: Identify the role of database fixtures

   Database fixtures specifically prepare test data before tests run and clean it up after tests finish, ensuring tests run reliably.

3. Final Answer:

   To prepare and clean test data automatically before and after tests -> Option C

4. Quick Check:

   Database fixtures = setup and cleanup [OK]

Hint: Fixtures handle setup and cleanup automatically [OK]

Common Mistakes:

• Thinking fixtures run SQL queries inside tests
• Believing fixtures speed up the database server
• Confusing fixtures with assertions

2. Which of the following is the correct way to write a pytest fixture that sets up a database connection and tears it down after the test using yield?

easy

A. def db():
conn = connect()
yield conn
conn.close()

B. def db():
conn = connect()
conn.close()
yield conn

C. def db():
yield connect()
conn.close()

D. def db():
conn = connect()
return conn
conn.close()

Solution

1. Step 1: Understand yield usage in fixtures

   Using yield in a fixture splits setup (before yield) and teardown (after yield).

2. Step 2: Check each option's order

   def db(): conn = connect() yield conn conn.close() sets up connection, yields it, then closes connection after test. Others close before yield or have unreachable code.

3. Final Answer:

   def db():\n conn = connect()\n yield conn\n conn.close() -> Option A

4. Quick Check:

   Setup before yield, teardown after yield [OK]

Hint: Yield separates setup and teardown in fixtures [OK]

Common Mistakes:

• Closing connection before yield
• Placing code after return (unreachable)
• Yielding before setup

3. Given the following pytest fixture and test, what will be printed when the test runs?

import pytest

@pytest.fixture
def sample_db():
    data = {'count': 0}
    yield data
    data['count'] += 1


def test_increment(sample_db):
    print(sample_db['count'])
    sample_db['count'] += 5
    print(sample_db['count'])

medium

A. 1\n6

B. 0\n5

C. 0\n0

D. 5\n10

Solution

1. Step 1: Analyze fixture setup and teardown

   The fixture yields data with 'count' 0. After test, it increments 'count' by 1 (not affecting test output).

2. Step 2: Trace test function prints

   First print shows initial 0. Then 'count' is increased by 5, so second print shows 5.

3. Final Answer:

   0\n5 -> Option B

4. Quick Check:

   Yielded data count = 0, incremented in test = 5 [OK]

Hint: Yield returns setup data; teardown runs after test [OK]

Common Mistakes:

• Thinking teardown runs before test prints
• Assuming fixture modifies data before yield
• Confusing fixture teardown with test code

4. Identify the error in this pytest fixture that is supposed to setup a test database and clean it after tests:

@pytest.fixture
def test_db():
    conn = connect_db()
    conn.execute('CREATE TABLE users')
    return conn
    conn.execute('DROP TABLE users')
    conn.close()

medium

A. The cleanup code after return is never executed

B. The fixture should use yield instead of return for cleanup

C. The table creation SQL is incorrect

D. The fixture is missing the @pytest.mark decorator

Solution

1. Step 1: Check the fixture structure

   Code after return statement is unreachable and will never run.

2. Step 2: Understand cleanup execution

   Cleanup code must run after test, so it should be placed after yield or before return, but not after return.

3. Final Answer:

   The cleanup code after return is never executed -> Option A

4. Quick Check:

   Code after return is unreachable [OK]

Hint: Code after return in fixture won't run [OK]

Common Mistakes:

• Thinking return allows cleanup after it
• Confusing yield and return usage
• Ignoring unreachable code warnings

5. You want to create a pytest fixture that sets up a test database with multiple tables and ensures all tables are dropped after tests, even if a test fails. Which pattern best achieves this?

hard

A. Create tables once globally without cleanup to speed up tests

B. Create tables inside each test and drop them at the end of each test

C. Use return in fixture to return connection, then drop tables in a separate teardown function

D. Use a fixture with yield: create tables before yield, drop tables after yield

Solution

1. Step 1: Understand reliable setup and teardown

   Using yield in fixtures allows setup before tests and guaranteed cleanup after, even if tests fail.

2. Step 2: Evaluate options for cleanup guarantee

   Use a fixture with yield: create tables before yield, drop tables after yield uses yield to create tables before tests and drop them after, ensuring cleanup always runs.

3. Final Answer:

   Use a fixture with yield: create tables before yield, drop tables after yield -> Option D

4. Quick Check:

   Yield fixture ensures setup and guaranteed teardown [OK]

Hint: Yield fixtures guarantee cleanup after tests [OK]

Common Mistakes:

• Skipping cleanup causing leftover tables
• Relying on test code for cleanup
• Avoiding yield and missing teardown