Introduction to Web Test Automation in Python

The internet is an incredible market place hosting millions and millions of software products to make our lives indefinitely easier. To keep up with each other, software grew more and more elaborate in order to provide us customers with lots of different features and services to make us purchase a thing or two. Now due to the resulting increase of complexity we must take special care not to break existing features while developing the next big version. Testing that the next code increment does not break existing stuff is what we testers call „regression testing“, and there is one especially economical way of doing that: test automation.

That’s what we’re going to do today. We gonna test and we gonna automate and we do all that in Python, because with its well-designed concepts Python is suitable for beginners and experts alike. So let’s start!

Shopping list

To start our test automation journey, we will work with the following tools. The versions are the ones I used at the time of writing. I might update them in the future.

  • Docker, preferably in its latest version
  • Python 3 version 3.10.8
  • Firefox Browser 106.0.1
  • geckodriver for Firefox 0.32.0
  • a Spree Commerce docker image version 3.6.4 as our system under test
    (will be pulled automagically in the next step)
  • Selenium for Python 4.5.0
  • unittest as our first test runner (comes with Python 3)

After downloading and installing Docker and Python from their respective web sites, we’re ready to start our system under test.

Deploying the system under test

To achieve this, we simply run the following command:

docker run --name spree --rm -d -p 3000:3000 spreecommerce/spree:3.6.4

If it went well, a quick glance at http://localhost:3000/ should show a shopping catalog page full of cute Rails merch. Now we will prepare and install Selenium.

Installing Geckodriver and Selenium

First we need to download geckodriver that will be responsible for sending our actions to the browser. Please see our shopping list for a download page. Download and extract the appropriate archive and put the extracted executable on your PATH. Please do that in a way that fits your OS and your preferences. I’m a mac user, therefore I move it to /usr/local/bin:

$ mv ~/Downloads/geckodriver /usr/local/bin/ 

If everything went well,

$ geckodriver -h 

should print the version and an instruction page. If not, feel free to drop me a Q in the comments below. Otherwise we move on to installing Selenium.

We will leverage pip3 to quickly go through that step:

pip3 install selenium==4.5.0

Now we’re all set. Let’s go headlong into the real trouble.

Test runner boilerplate

First of all, we create the skeleton of our test class. We write a simple Python unittest class that we will fill in with Selenium web test automation goodness as we go further. Our goal is to see the basic structure of a unittest-based automated test case that we will leverage to execute our browser magic. In your favorite project directory, please create a file named and fill it with the following code. We will talk about the file name a bit later. Don’t worry, it was not a technical decision.

import unittest

# Start with a base class and derive it from 
# unittest.TestCase
class TestSpreeShop(unittest.TestCase):

    # setUp is executed at the start...
    def setUp(self):

    # ... and tearDown at the end of each test case.
    def tearDown(self):

    # This will be our first test:
    # We will open the shop's homepage
    # and verify that it worked.
    # For now, we will just let it pass.
    def test_isOpen(self):

# The main entry point of our unittest-based execution 
# script. Think of it as an actual main method similar 
# to Java's or C's.
if __name__ == '__main__':

Great, that almost looks like a real test already. Now finally we are going to open a browser window.

Starting and closing the browser

We write a small support function:

def open_browser(self):
    return webdriver.Firefox()

And we apply it in setUp:

def setUp(self):
    self.driver = self.open_browser()

This opens a Firefox window it its most pure form whenever we execute one of the class‘ test methods. We could configure it further in open_browser, but for our purpose at the moment, this is perfectly fine.

Now before we perform any actions on the page, we must make sure that the browser window is closed appropriately after each test run. In tearDown, we do:

def tearDown(self):

Caveat: confusion potential

Selenium’s webdriver has a close()-method, but please always use quit() instead. It takes care of clean browser termination with regards to Selenium’s execution, whereas close() will just terminate the browser causing warnings.

Alright! We have taken care of the browser handling. Time to do stuffs with it.

Opening the landing page

The most basic action ist to open a web page. Thankfully this task is handled by Selenium with a simple one-liner. Given our sample web shop is up and running, we do:


We introduce the line to the test case method test_isOpen, which we introduced in our boiler plate. But before we head into executing the test case, we have to be aware of the fact that we as the user can see the page being open, but the computer can’t. We have to programmatically verify that our expectation „landing page is open“ is met.

Verifying the outcome

To do that we verify these 3 conditions:

  • the window title contains the landing page’s HTML title
  • the most prominent logo exists on the web page and
  • it’s actually visible (i.e. it does not have its display property set to none).

We add this code directly below the get – line from before:

self.assertTrue("Spree Demo" in self.driver.title, 
                "'Spree Demo' is not in the browser's title.")

logo_element = self.driver.find_element(By.ID, "logo")

The first line peeks into the page title, which is another staple of Selenium, and then checks, if it contains „Spree Demo“ with Python’s in-operator. Using unittest's assertTrue, we verify that this is the case, and if not, we print a custom error message. Condition 1 done.

The second line depicts the method you will probably use the most whilst moving forward in your test automation career: find_element goes through the page’s DOM and grabs the element that meets the given criteria. Here we search for an element with the HTML id „logo“. If it fails to find the element, it drops a NoSuchElementError. Therefore, we just implicitly verified condition 2.

The return value is a WebElement object that we can do clicks, inputs and various other actions on. We will use the object’s method is_displayed() to check, if the logo is visible therefore verifying our 3rd condition.

Straight-forward so far. At this point your code should look like that:

import unittest
from selenium import webdriver
from import By

# Start with a base class and derive it from unittest.TestCase
class TestSpreeShop(unittest.TestCase):

    # setUp is executed at the start...
    def setUp(self):
        self.driver = self.open_browser()

    # ... and tearDown at the end of each test case.
    def tearDown(self):

    def test_isOpen(self):
        self.assertTrue("Spree Demo" in self.driver.title, 
                        "'Spree Demo' is not in the browser's title.")

        logo_element = self.driver.find_element(By.ID, "logo")

    # Support method. We will use it to open a browser instance in setUp.
    def open_browser(self):
        return webdriver.Firefox()

# The main entry point of our unittest-based test execution script.
# Think of it as an actual main method similar to Java's or C's.
if __name__ == '__main__':

Let’s execute it by doing:

python3 # Linux or MacOS
python # Windows

If all went well, your console should display a big OK:

➜  pyta_tutorial git:(main) python3
Ran 1 test in 4.719s


Congratulations, you just executed your first Python-Selenium-test:
Our shop’s landing page can be opened and it is displayed correctly.

What is this driver thingy by the way?

Simply put, the driver is the glue between our code and Gecko (or Chromedriver respectively), thus it’s the interface to our browser window. It handles all the requests that we perform like find_element, click, „are you displayed?“, perform key strokes, „grab that text of an element“ etc. pp. Under the hood, Gecko is an http server, which receives requests sent by the driver everytime we perform one of the above actions. The driver then interacts with the browser in the way we tasked it to and sends a JSON-based response object that we can base our future work on. Everything is encapsulated by Selenium so that we can work with simple objects during test automation development without having to deal with HTTP or JSON.

Performing and validating browser actions

Now that we know the basics of how to write automated tests with Python and Selenium, let’s develop a more complex example.

The best candidates for automated tests are cross tests. These are tests that cover representative cross sections of the product. One example could be: Put items into the cart, view the cart page and perform the checkout. This is the reason we named our test file It is good practise to start test automation for a new project by coding these cross tests first.

For the sake of brevity here, we will write up the test until the checkout page. The rest is homework. Don’t worry, I got you covered with the full source code in my bitbucket.

Ok, without further ado, here’s the code. Please add the following method to the test class:

def test_findSpreeBagAndCheckout(self):

    # Landing and catalog page
    self.driver.find_element(By.CSS_SELECTOR, "[href='/t/spree']").click()
    self.driver.find_element(By.CSS_SELECTOR, "a[href*='spree-bag']").click()

    # Product page
    self.driver.find_element(By.CSS_SELECTOR, "input#quantity").clear()
    self.driver.find_element(By.CSS_SELECTOR, "input#quantity").send_keys("3")
    self.driver.find_element(By.ID, "add-to-cart-button").click()
    # Cart page
    self.assertTrue("Shopping Cart" in self.driver.title, 
                  "'Shopping Cart' is not in the browser's title.")
    self.driver.find_element(By.CSS_SELECTOR, "img[src$='/spree_bag.jpeg']").is_displayed()
    qty_value = self.driver.find_element(By.CSS_SELECTOR, ".line_item_quantity").get_attribute("value")
    self.assertEqual(qty_value, "3", "The item quantity is not the same we typed in!")
    cart_total = self.driver.find_element(By.CSS_SELECTOR, ".cart-total > .lead").text
    self.assertEqual(cart_total, "$68.97", "The total cart value does not match our expectations. That's a blocker!")

What’s new here?

If we look back at our first landing page test, you will notice that we use a lot of new things. We will cover them one by one now.

CSS selectors

One thing that catches the eye is that we looked for elements by using CSS expressions. You may have heard about them from your frontend peers, or maybe you have even worked with them yourself already. If not, don’t worry. We will cover them in a followup post. For now, I will give you a few translations:


„Give me a page element, whose attribute href is equal to ‚/t/spree'“. Quick reminder: href is used in link elements for defining the target URL that is opened, when the user clicks the link.


„Give me any link element, whose attribute href contains ’spree-bag‘.“


„Give me an image element, whose attribute src ends with ‚/spree_bag.jpg‘.“


„Give me an input element, whose HTML id is equal to ‚quantity‘.“ Yes, we could have used By.ID with „quantity“ here, but I wanted to be explicit about the element type input.


„Give me an element that has line_item_quantity in its class attribute.“ The leading dot indicates that we are looking for elements that has the specified class. It is roughly equivalent to [class*='line_item_quantity'].

.cart-total > .lead

„Give me any element that has the lead class and that’s preceded by any element that has the cart-total class.“

By using CSS selectors you can be very specific about what element you want to use in your test case. This makes CSS selectors incredibly powerful and versatile while maintaining a solid degree of simplicity, especially compared to XPath (Ugh).

New properties and methods used in our test case

Aside from CSS selectors, we used several new methods and properties in our new automated test.

click() issues a click on the target element. Straight-forward.

.text contains the element’s written text. In <p>Some text</p> for example, we would get access to „Some text“.

get_attribute("someHtmlAttribute") gives us the content of an element’s HTML attribute. In our test we fetch an element’s value attribute that is often used to set the content of an input element. Another example might be the link element we talked about earlier. Given we want to have its href attribute for some further verifications. On our page:

<a id="mylink" href="">an example link</a>

Then in our test we could do:

target_href = self.driver.find_element(By.ID,"mylink")

send_keys("My desired input") imitates key strokes on an element. We use it to type any string we want into our target text input element. In our test, that would be the „quantity“ input box.

And finally, with clear() we have a little helper that clears an input element from any content. In our test we use that to remove the preset value. Otherwise we would accidentally order 31 bags: „3“ from us and „1“ from the value preset by the page.

Continuing from here

Alright, let’s sum up what we accomplished:

We have seen how to open and close a browser window, do various actions on the page, verify their outcomes and finally we used that to write a fairly large cross test. And all of that on a full fledged ecommerce web app. Great job! Now where should we go next? For the next post, as promised, I’d like to go back one step and give you a deeper introduction to CSS expressions, because they will accompany you for a long time during your test automation journey. Afterwards we have to tackle a big problem you probably already noticed:

Copious amounts of repetition.

To tackle that we will leverage Behave, a Behavior Driven Development framework that makes it possible to write test cases in human-readable text form on top of a DRY Python code base. Afterwards we will apply the Page Object Pattern, a test automation – specific design pattern to reduce repetition even more.

Okay. To keep you busy while I am busy, how about finishing the checkout? As a reminder, you can find the full source code in my bitbucket repo. Or you can spoil yourself a little about Cucumber in Rust.

See you in the next post!

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AccessDenied in psutil

psutil is an interesting Python package that provides us with valuable insights about running processes, their memory and CPU usage and many more key aspects for monitoring and profiling processes across all major platforms. Thus, it is an incredibly useful tool for system admins, developers and testers alike. Now one of my favourite methods is cmdline(). Defined in the package’s Process class, it yields the whole CLI command of a running process in array form. There is one important catch on Windows though that got me kinda by surprise: While iterating casually through all my processes I suddenly got an AccessDenied error.

What did I try?

For an advanced verification in a process management – related test case I wanted to print the executed CLI command in a log file, so basically this:

import psutil

for pc in psutil.process_iter():

But that will just throw a painful AccessDenied error at us. Uff.

Why did that happen?

The reason is that psutil is quite consequent: It really lists every running process. That means even SYSTEM or root processes . That’s okay, it might even be interesting in one case or another, and you can still access selected attributes like the name() of a root process, if you want. But for me, it doesn’t suffice. I want to see the full-fledged cmdline(), but I understand that SYSTEM processes are none of my business. Once I came to term with that fact, the solution was easy: We just skip them.

The solution

What I did was applying a try-except around the loop’s inner statement:

import psutil

for pc in psutil.process_iter():
    except psutil.AccessDenied:

The continue statement will make sure that the processes that I’m not supposed to see are happily skipped without hurting the rest of the program flow.

But what if I need to monitor foreign processes?

In that case, we would need to execute the script within the process owner’s user context. That might be a bit fiddly in Windows depending on the use case, but of course that’s still possible. Just remember to keep the try-except block, because there still will be processes you wouldn’t be allowed to see.

Mine, for example.


So far for today. I hope this little Q3A (quick question quick answer) could shed some light upon that surprising AccessDenied error. If you want to learn more about psutil, I strongly recommend the readthedocs page. Otherwise, if you want to see more quick tips, I have one more for Python about environment variables. That one covers Python’s environment variable handling. As an alternative, if you are – like me – into containers, here is a handy docker ps trick useful for monitoring tasks as well.

Happy coding!

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Python Environment Variables: getenv() vs. environ[ ]

Last week, I was about to execute a test run using one of our functional test suites that requires a certain environment variable – and I forgot to set it, whoops.. The answer was harsh and generic: A good ol‘ Python KeyError. That put me up with two questions:

  1. What options do I have to get environment variables with Python and
  2. which one is the best?

Let’s start checking them out.

Introducing os.environ[key]

The first option is a simple dictionary that is prefilled with all environment variables when starting the Python process. This provides us with a simple-to-use interface that we already know and love.

Let’s try it out:

For python environment variables with os.environ[key], do the following: export MY_VAR="test", python3 -i, import os and os.environ["MY_VAR"]. This should yield 'test'.
Python environment variables with os.environ[key]

But what happens, when we query a variable that is not set? Then we hopefully prepared our try-except Block, because that call is going down the river faster than sound. This happens because dictionaries throw generic KeyErrors, when the queried key could not be found in the dict. That’s what happened in my test run.

os.getenv(key, default=None)

The second option follows a more higher-level approach by providing a function that takes our key in question and an optional default value. The usage is straight forward and it won’t crash as harshly as the first option does.

Let’s try it out:

For python environment variables with os.getenv(key, default), do the following: export MY_VAR="test", python3 -i, import os and os.getenv("MY_VAR"). This should yield 'test'. If you query MY_VAR2 instead, it should yield None. If you do os.getenv("MY_VAR2", "default"), it should yield default.
Python environment variables with os.getenv and default value handling

As we can see, we can now use any key we want; worst case is a result of None. But the increased flexibility comes with a price: We have to take care of whatever the function returns. Even harder, due to the fact that the default defaults to None (pun semi-intended), this solution is prone to hidden bugs. Therefore use it with care and set an appropriate default value if possible.

Conclusion: Which one works best for you?

We saw both options now, but which one works best (for you)? At the end of the day, it comes down to preference regarding two factors:

  1. Do you like your code to be more low-level or high-level?
  2. Do you want your fails fast or more controlled?

This is a decision you have to make, but once you have it, you find everything you need to get your environment variables with Python right here.

So long for the quick journey into my Python life. Usually I talk more about Rust as in my Cucumber Rust – tutorial and in this cheat sheet about Rust modules. But since Python is my main language on the job, there will definitely be more coming up soon. So if you are a friend of british comedy, feel free to stay tuned. Additionally, since container technologies are getting more and more important in my day job as well, I will write more about these techs, too, starting with this little docker ps – trick. Or, if you rather keep coding, check out my new Java threads tutorial.

Happy holidays and a merry Christmas Eeve!

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