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Let’s start with the main thing – Python is considered to be a universal programming language. It can be easily understood by both junior developers and senior developers and some analysts even regard it as the most popular language in IT.

According to Josh Howes (a Senior Principal Data Analyst in MaxPoint), Python is a magical tool that easily lets you solve the world’s toughest problems.
Python Logo

Python Logo

Why should we test on Python?

Python is simple, technically “elegant” and readable and this is exactly what is needed to transform test cases into efficient test scripts.

You can find below the examples of how we can efficiently use Python for automated testing:

  1. Developers can deploy tests into the docstrings function;
  2. Developers develops unit tests for a module or test packages;
  3. A tester creates a set of integrated tests for REST API;
  4. A QA Engineer creates end-to-end tests, by using all capabilities of Selenium;
  5. Data analysts test functions in a Jupyter notebook.

We should keep in mind that Python can easily be used to perform black-box testing, even if software has not been developed on Python.

Selecting a proper version of Python

It’s quite hard to select the correct version of Python.

We’d like to admit that choosing the right version of this programming language should go together with the following criteria:

  • Python version should be suitable for white-box testing;
  • Python version should be suitable for black-box testing.

Selecting a proper framework

Today there are numerous versions of Python frameworks, therefore, this choice is quite hard and is not as clear as it may seem.

We recommend using the following resources to do this:

Though there are numerous variants, we recommend using the following criteria of selection:

  • Choose a type of testing. You can use unittest and doctest for executing basic unit tests and pytest – for executing high-level tests;
  • Pay attention to the supported Python version. For example, Python 2 or 3 are completely different versions of the language. Different versions of the framework contain different supported versions and this is very bad for white-box testing. Moreover, the capabilities of the language also depend on the version you are using;
  • Consider future technical support. We recommend using mature and actively developed frameworks for future support.

Useful IDE

If you use very serious automation on your project, you can’t do without a qualitative IDE.

And the best variant here is jetBrains PyCharm. This IDE has a beautiful graphical interface, a user-friendly menu, and can also support several Python testing frameworks.

If needed, PyCharm can be easily downloaded as a separate version of IDE or in a form of a special extension – jetbrains IntelliJ IDEA.

The simplest and clearest text editors give you the possibility to instantly make changes. For sure, the best tools are Visual Studio Code, Notepad++, also, you can use such a new tool as Atom – a modern cross-platform editor by GitHub.

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