10 Reasons To Choose Python For Automation


Python for automation


Python is one of the best languages ​​for testing automation. That's what Dan Callahan stated in a report at PyCon 2018. And he gave 10 reasons why it’s better to choose Python when testing automation. Let's get acquainted with them.


So here are the 10 reasons to choose Python for automation.

1. Zen Python

Zen Python in PEP20 is an excellent guide for test automation. Tests describe the tested functionality, so they should be readable and visual. A few simple steps are better than one difficult step. Test code is the natural bridge between test steps and program calls, and Python's expressive elegance is the best fit for this. In general, you can always familiarize yourself with Zen Python yourself by typing in the interpreter import this.

2. Pytest

Pytest is a good test framework available now not only in Python. It helps to cope with any functional tests. Test cases with their help are written simply as functions and can accept parameterized input data. If you avoid global variables, there are no side effects. Assertions have automatic introspection; tests can be filtered at runtime.

There are a number of plugins that further enhance the capabilities of the Pytest. You can run tests in parallel, use Gherkin scripts, integrate with other frameworks: Django, Flask. We can confidently say that Pytest is the best we have today.

3. Software Packages

Python has a rich library of useful packages for testing: - Pytest, - Unittest, - Paramiko, - requests, - Doctest, - Selenium WebDriver, - tox, - logging, - Splinter, - Hypothesis, and others.

These are ready-made ingredients for your automation recipes. And no need to invent a bicycle.

4. Multiparadigm

Python is both functional and object-oriented. It makes it possible to decide what is best suited for your tasks - functions or classes. 

This is useful because the side effects of distributed functions are eliminated, and the simple syntax of the functions makes them extremely clear. In addition, Pytest uses functions for cases, rather than stuffing them into classes like JUnit.

5. Type as you like

Dynamic typing built into Python is well suited for test automation because the bulk of functional tests above the unit level does not require increased attention to types. But if you need static types - it doesn’t matter, there are Mypy, Pyre, MonkeyType.

6. IDE

Good IDE support makes it easy to use languages ​​and frameworks. If we talk about testing in Python, we have Jetbrains Pycharm


 The environment supports visual testing with Unittest, Pytest, and Doctest right out of the box, and the professional version has support for web development and BDD frameworks (for example, behave, Pytest-Bdd, lettuce).


 If you want something easier, there is a Visual Studio Code environment that is very popular today and supports a lot of useful things: snippets, debugs, environments, debugging, working with the command line terminal right in the window, etc. Atom, PyDev also works fine, Sublime, and Notepad ++.


7. Command Line

Python and the command line are a marriage made in heaven. The whole process of self-testing can be controlled via the command line, which is good news. 

Pipenv allows you to manage environments and packages. In any test framework, you can run the console to search and run tests. You do not need to create test code first, because Python is an interpreted language, which also simplifies the launch. The rich command line support makes it easy to manage to test both manually and through tools or build scripts.


The cherry on the cake - automation modules that can be called directly from the Python REPL interpreter and even (even better) right from the Jupyter notebook. 

8. Ease of entry

Python is friendly to beginners, and it’s not so important whether you are taking your first steps in programming or have rich experience. This is a plus of Python as an automation language because tests can and should be created simply and quickly. Spending time is an impermissible luxury, especially when you have new features on hand that urgently need to be checked.

9. Scalability

Despite its low entry threshold, Python is not a toy. It is able to solve industrial problems, and development can be scaled due to significant syntax, good structure, modularity, and a rich ecosystem of tools and packages. We cannot but mention the flexibility of the command line - it will allow you to integrate into any process or tool.

10. Popularity

Python is a very popular programming language. He regularly goes to the top on TIOBE, Stack Overflow, GitHub. It is chosen by web developers, infrastructure engineers, test automation, data analytics. 

The professional Python community also helps promote the language. There are a lot of developers, so there will be no problems with online support. And in the near foreseeable future, this language will not go anywhere.

Conclusion


When choosing automation languages, you can prefer Java, C #, and Ruby, which are also good options. But Python is Python, the one and only. 

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