How to Test Python Web Application Using PyTest

In today’s highly competitive business world, developers have the biggest challenge to ensure the accuracy, functionality, compatibility of an app across multiple devices and browsers. This is where testing plays a vital role to get desired outcomes from the web application.

Relying on the product goals and target market, the design & development team needs to craft a perfect testing strategy using reliable software tools. So here comes the role of PyTest.

What is PyTest?

PyTest is one of the open-source, simple, Python-based, and scalable test Automation Frameworks available to use. PyTest assists developers to test anything, including UI, API testing and databases as well. 

Developers can run it as an individual testing tool or attach it with Python web development frameworks such as Flask, Django and others, improving their unit testing capabilities and app’s reliability. 

Basically, tests in PyTest are Python functions, and developers can run these test functions based on names or tags or as a whole. PyTest also offers an inbuilt parallel test running feature, and it is easy to access by specifying an additional argument to your CLI pytest run. To better utilize this tool, you can hire Python developer online from 9series.

Know how to test Python web application using PyTest:

1. First Install PyTest

To start testing with PyTest, first, you need to install it. In numerous Python packages, developers can install PyTest in a virtual environment from PyPI utilizing pip:

$ python -m pip install PyTest


Now PyTest command will be in your installation environment.

2. Create Tests

In PyTest, creating tests is not a tough job because writing a Python Function is simpler than writing a separate test. The function name must start with ‘test_’. 

You can also write different test classes according to project needs. PyTest also enables developers to utilize assert like statements to verify the expert outcome and actual outcome.

Example:

In the below program we will test a simple Python function that returns an integral 10 as an output.

Program test_alpha.py
def my_alpha():
return 10
def test_my_alpha():
expected_out = 10
assert my_alpha() == expected_out


You can run this function using PyTest CLI and verify the expected outcome and functionality.

3. Auto Test Discovery

In the above, we created a test without specifying anything just by using the inbuilt test auto-discovery feature of PyTest. It automatically identifies file names starting with ‘test’ or ending with ‘_test’ from inbuilt directories. 

PyTest also identifies all Python functions name starting with ‘test_’ automatically. Developers can also introduce required name patterns by configuring pytest.ini in this test auto-discovery.

4. Command Line Execution

PyTest offers lots of unique features to developers which are available as command-line arguments. To see it, test ‘pytest-help’. Let’s see an example here.

pytest <file_name>
Execute test functions in the particular file
e.g., pytest test_beta.py
pytest filename::testName


 

Runs or executes the specified function in the described file; many files can be specified in the same format.

e.g:pytest test_beta::test_addition
pytest –m <marker tag>


Runs all the tests with listed users, markers for grouping

5. Parameterization of Test

Here we will have some scenarios where we require automating similar test cases in minute differences. For instance, we will need to verify whether some websites are reachable via https and http and take some other required steps. 

Therefore, if we have 20 steps, 17 or 18 will be similar; instead of writing two or three test cases, PyTest offers an amazing functional feature termed Parameterization, where you can group all as one and parameterize them using varied variables.

Example:

Program test_parameterization.py
from pytest import mark
@mark.parametrize(“http_method”,[‘http’, ‘https’])
def test_my_func(http_method):
# Some steps
print(http_method)
# some more steps
Output:


 

Here we can see that both of the parameters execute as different tests.

6. Fixtures

Fixtures are special functions that will run before the whole session, module, or test function relied on their configuration and returned any calculated outputs. They also assist you in running a piece of code. A fixture can be function scoped, module scoped or session scoped that defines their existence or lifetime.

Example:

Here we are returning a string to test functions. Fixtures allow doing a lot more.

Program test_db.py
import pytest
@pytest.fixture
def input_value():
database = ‘my_sql’
return database
def test_div_4(input_value):
print(input_value)
def test_div_6(input_value):
print(input_value)


7. Hooks

Hooks offer a unique approach to modify PyTest behaviour like logging and identification. We often write fixtures and hooks in a file in the specified directory where the tests are available.

8. Markers

Markers assists you categorize your tests easily. Markers allow you to mark the tests to run from start to end. Some of the markers contain unique behaviour.  

9. Use Plug-ins

The plug-in helps you enhance the functionality of pytest. Let’s check some of the widely used plug-ins listed below:

• Pytest-sugar
• Pytest-cov
• Pytest-picked
• Pytest-instafail
• Pytest-xdist

Wrap up

Testing Python web applications using PyTest is a widely used and favourable framework that offers unmatched features with which test engineers can easily implement multiple tests. 
Hire Python developer from an expert team who is experienced and well-versed with Python; unit testing would help you get desired outputs. Furthermore, since PyTest uses multiple concepts like ‘Dependency Injection, there will be less cost required to maintain the source code.