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In this guide, we explore two essential Pytest flags that can streamline your testing process: one flag to suppress excessive warnings and another to halt test execution upon the first failure. These techniques are invaluable for improving both output clarity and debugging efficiency.

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Suppressing Warning Messages

When running tests, you might encounter numerous warning messages from packages or deprecated code practices. For example, consider the following parameterized test: 
@pytest.mark.parametrize("num1, num2, expected", [
    (3, 2, 5),
    (7, 1, 8),
    (12, 4, 16)
])
def test_add(num1, num2, expected):
    print("testing add function")
    assert add(num1, num2) == expected
The typical output may include repeated warnings similar to the snippet below: 
venv\lib\site-packages\aiofiles\os.py:10
venv\lib\site-packages\aiofiles\os.py:10
venv\lib\site-packages\aiofiles\os.py:10
venv\lib\site-packages\aiofiles\os.py:10
c:\users\sanje\documents\courses\fastapi\venv\lib\site-packages\aiofiles\os.py:10: DeprecationWarning: "@coroutine" decorator is deprecated since Python 3.8, use "async def" instead
-- Docs: https://docs.pytest.org/en/stable/warnings.html
============================= short test summary info =============================
16 passed, 5 warnings in 0.63s
To eliminate these distractions, run Pytest with a flag such as --disable-warnings. This ensures that your test output remains focused on essential information.

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Stopping on the First Failure

By default, Pytest executes all tests even if some fail. While this is useful for a full test run, during active development you might prefer to halt at the first error. This allows you to quickly address failures without running the entire suite. Consider a scenario where the subtract function is deliberately modified to produce an incorrect result. A snippet of your test suite might look like this: 
import pytest
from app.calculations import add, subtract, multiply, divide, BankAccount, InsufficientFunds

@pytest.fixture
def zero_bank_account():
    print("creating empty bank account")
    return BankAccount()

@pytest.fixture
def bank_account():
    return BankAccount(50)

@pytest.mark.parametrize("num1, num2, expected", [
    # Add your test cases for add function here.
])
If you alter a test to intentionally fail, for instance: 
def test_subtract():
    assert subtract(9, 4) == 6
A complete test run might output: 
rootdir: C:\Users\sanje\Documents\Courses\fastapi
plugins: cov-2.12.1
collected 16 items

tests/test_calculations.py::test_add[3-2-5] PASSED
tests/test_calculations.py::test_add[7-1-8] PASSED
tests/test_calculations.py::test_add[12-4-16] PASSED
tests/test_calculations.py::test_subtract PASSED
tests/test_calculations.py::test_multiply PASSED
tests/test_calculations.py::test_divide PASSED
tests/test_calculations.py::test_bank_set_initial_amount PASSED
tests/test_calculations.py::test_bank_default_amount PASSED
tests/test_calculations.py::test_withdraw PASSED
tests/test_calculations.py::test_deposit PASSED
tests/test_calculations.py::test_collect_interest FAILED
tests/test_calculations.py::test_bank_transaction[200-100-100] PASSED
tests/test_calculations.py::test_bank_transaction[50-10-40] PASSED
Passing the -x flag to Pytest will modify this behavior. With -x, execution halts immediately on encountering the first failed test: 
platform win32 -- Python 3.9.5, pytest-6.2.5, py-1.10.0, pluggy-1.0.0 -- c:\users\sanje\documents\courses\fastapi\venv\scripts\python.exe
cachedir: .pytest_cache
rootdir: C:\Users\sanje\Documents\Courses\fastapi
plugins: cov-2.12.1
collected 16 items

tests/test_calculations.py::test_add[3-2-5] PASSED
tests/test_calculations.py::test_add[7-1-8] PASSED
tests/test_calculations.py::test_add[12-4-16] PASSED
tests/test_calculations.py::test_subtract FAILED
!!!!!!!!!!!!!!!!!!!!!!!! stopping after 1 failures !!!!!!!!!!!!!!!!!!!!!!!
This immediate halting is particularly beneficial when debugging issues in a large test suite or when tests involve time-consuming operations such as database queries or API calls.

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Resetting Changes and Final Verification

After experimenting with different testing flags, you might need to revert any modifications made for testing purposes. For example, reset the subtract function test to its intended state: 
def test_add(num1, num2, expected):
    print("testing add function")
    assert add(num1, num2) == expected

def test_subtract():
    assert subtract(9, 4) == 5

def test_multiply():
    assert multiply(4, 3) == 12
If adjustments were made to the collect_interest test, ensure the expected value is corrected: 
def test_collect_interest(bank_account):
    bank_account.collect_interest()
    assert round(bank_account.balance, 6) == 55
Similarly, update any parameterized tests, such as those for bank transactions: 
@pytest.mark.parametrize("deposited, withdrew, expected", [
    (200, 100, 100),
    (50, 40, 10),
    (1200, 200, 1000),
])
def test_bank_transaction(zero_bank_account, deposited, withdrew, expected):
    zero_bank_account.deposit(deposited)
    zero_bank_account.withdraw(withdrew)
After reverting changes, a full test run should confirm that all tests pass without errors: 
tests\test_calculations.py:27: AssertionError
FAILED tests/test_calculations.py::test_subtract - assert 5 == 6
=========================== short test summary info ============================
FAILED tests/test_calculations.py::test_subtract - assert 5 == 6
========================== 1 failed, 3 passed, 5 warnings in 0.85s ============================
Once all issues are resolved, the complete suite of tests will run successfully, ensuring your code meets all quality standards.
By leveraging these Pytest flags, you can create a more efficient and developer-friendly testing environment. Whether you’re suppressing unnecessary warnings or halting on the first failure for rapid debugging, these techniques help maintain a smooth and effective workflow.

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