Data QA Developer with PyTest Salary in 2024

Where is PyTest used?

PyTest in the Wild: Wizards and Wands of Python Testing!

• Spellbinding CI/CD Rituals: PyTest conjures up a seamless pipeline to test your code spells before they go live. No more code curses in production!


• Plugin Potion Brewing: Brew your own enchanting PyTest potions! Plugins let developers expand their testing grimoire with magical extras.


• Parallel Potion Testing: Multiple cauldrons brewing at once? PyTest can handle lots of potions, I mean tests, in parallel. Get those results faster than a flying broomstick!


• Detective Work on Code: With its keen eye for detail, PyTest helps sleuth out those elusive bugs to keep the code realm safe and sound.

PyTest Alternatives

unittest

Built into Python's standard library, unittest is a unit testing framework inspired by JUnit. It supports test automation, sharing of setup and shutdown code, aggregation of tests into collections, and independence of the tests from the reporting framework.

Example:

import unittest

class SimpleTest(unittest.TestCase):
    def test(self):
        self.assertTrue(True)

if __name__ == '__main__':
    unittest.main()

Pros:

• Included with Python, no installation required.


• Familiar xUnit style testing for those transitioning from other languages.


• Well-integrated with Python's development tools.

Cons:

• Less Pythonic, more boilerplate code compared to PyTest.


• Lacks some advanced features and plugins available in PyTest.


• Verbose and less flexible in writing test cases.

nosetests

Nose extends unittest to make testing easier. It supports fixtures and test discovery which allows tests to be written with less boilerplate.


Example:

def test_numbers():
    assert 5 * 3 == 15

if __name__ == '__main__':
    import nose
    nose.run()

Pros:

• Simple to write tests due to less boilerplate compared to unittest.


• Automatic test discovery makes running tests easier.


• Highly extensible with a wide range of plugins.

Cons:

• Development of Nose has stalled; community has shifted towards Nose2 and PyTest.


• Not as feature-rich as PyTest for advanced testing needs.


• Some plugins may be outdated or lack maintenance.

doctest

The doctest module searches for pieces of text that look like interactive Python sessions, and then executes those sessions to verify that they work exactly as shown.

Example:

def multiply(a, b):
    """
    >>> multiply(2, 3)
    6
    """
    return a * b

if __name__ == "__main__":
    import doctest
    doctest.testmod()

Pros:

• Encourages writing documentation and tests concurrently.


• Tests are readable as they are part of the documentation.


• Simple to use for straightforward test cases.

Cons:

• Not suitable for complex testing scenarios.


• Tests can become cluttered in documentation if overused.


• Limited to testing only what can be expressed in docs as interactive sessions.

Quick Facts about PyTest

The Curious Birth of PyTest

Once upon a time in 2004, there was a dev named Holger Krekel who unleashed the testing champion PyTest into the wild. As the prodigy of Python testing frameworks, it came with a simple assert rewriting charm that captured the hearts of bug-squashers everywhere. Swifter than a speeding exception, it forged a place in the annals of testing lore.

PyTest's Plugin Pandemonium

Roll up, roll up to witness the magnificent plugin fiesta! PyTest, like a ringmaster, commands an exuberant crowd of over 315 plugins. With these magnificent critters, one can extend its capabilities to the moon and back, ensuring that tests are not just run but are performed like a Cirque du Soleil of code.

# Here's how you'd typically use a plugin
pytest --verbose --capture=no  # Look at me, using options!

Continuous Testimony with PyTest

Imagine a world where writing tests is as fun as slurping spaghetti. PyTest made that culinary code dream come true with its unique fixture model. Its continuous integration dazzle made it the darling of devs and the terror of bugs, effortlessly integrating with Jenkins, GitHub Actions, and more. With each commit, it whispers a gentle "Shall I test for thee?"

# Integrating PyTest with CI tools
# ...is as simple as adding a few lines to your config
# script: pytest -v

What is the difference between Junior, Middle, Senior and Expert PyTest developer?

Seniority Name	Years of Experience	Average Salary (USD/year)	Responsibilities & Activities
Junior PyTest Developer	0-2	50,000 - 70,000	Write basic tests under supervision Learn testing frameworks and company coding standards Debug simple code issues Assist in maintaining test documentation
Middle PyTest Developer	2-5	70,000 - 90,000	Independently write and manage tests Collaborate on test strategy development Integrate tests with CI/CD pipelines Contribute to test automation frameworks
Senior PyTest Developer	5-8	90,000 - 120,000	Design and lead testing strategy Mentor junior and middle developers Optimize test automation and frameworks Review and refactor code for quality assurance
Expert/Team Lead PyTest Developer	8+	120,000 - 150,000+	Oversee entire testing lifecycle Make key decisions on test and project direction Lead, coordinate, and support teams Interface with stakeholders on test and quality metrics

Top 10 PyTest Related Tech

1. Python Language

   
   

   The almighty language at the heart of it all—Python! It's as essential as coffee is to programmers and as widely loved as cats are on the internet. You'll be scripting your tests with this easy-to-read, 'I-can't-believe-it's-not-English' syntax. Being bilingual is cool, but being Python-lingual is cooler.

   
   




2. PyTest Framework

   
   

   If Python were the canvas, PyTest would be the paintbrush. It's the go-to framework for crafting your test masterpieces. Abundantly feature-packed, yet simpler than explaining why you need five minutes more sleep every time your alarm goes off.

   
   

   import pytest
   
   @pytest.mark.smoke
   def test_the_obvious():
       assert True is not False
   

   
   




3. pytest-xdist

   
   

   Why test one thing at a time when you can test ALL the things at once? pytest-xdist is like having extra arms to do more work. It's the octopus of plugins, letting you run tests in parallel, making your test suite go vroom!

   
   

   pytest -n 4  # Run tests in four parallel gulp...I mean groups!
   

   
   




4. pytest-cov

   
   

   Ever worried you're not covering enough test scenarios? Enter pytest-cov, a little like a nosy neighbor peering over your code's fence to ensure you've covered every nook & cranny. Code Coverage just got a bit less intimidating.

   
   

   pytest --cov=your_package_name  # Peeking time!
   

   
   




5. Selenium

   
   

   For the adventurer in every tester—Selenium takes you on a quest through web applications, battling bugs and automating browsers. It is your Excalibur when you're venturing into the realm of GUI testing.

   
   




6. Requests

   
   

   Need to nudge an API and see how it groans back? 'Requests' is your trusty messenger. It's as simple as requesting a pizza delivery—no toppings confusion included—and integral for API testing.

   
   

   import requests
   
   response = requests.get("https://api.ultimate-pizza.com/pizzas")
   

   
   




7. Tox

   
   

   Tox is like that overachiever who tests your package in different environments. It's a testament to the "works on my machine" philosophy, aiming to make this phrase as outdated as a beeper.

   
   




8. Mock and MonkeyPatch

   
   

   Mock is like a stunt double for your code, taking the hits so your app doesn’t have to. MonkeyPatch, on the other hand, is like that cheeky chap who switches out the banana while no one's looking. Both are key for isolating tests from uncertainties.





9. Docker

   
   

   Imagine you could pack your entire testing setup and move it anywhere without breaking anything—welcome to Docker, the virtual Tupperware for your apps. Perfect for making sure PyTest runs in a completely controlled chaos...erm, I mean, environment.





10. Git and GitHub

    
    

    Last but not least, Git along with GitHub are the dynamic duo for source control. Imagine a world where you magically never lose your code, can collaborate without overwriting each other's work like a bad game of Tetris—that's Git for you.