If you are not currently testing your code, then it is something you will want to learn and start adding to your projects. Many people have probably heard of testing, but you might not know exactly why testing your code is the most exciting thing to do. Still, there is a reason that most companies and teams require their code to be thoroughly tested, and if you are going to get a job working on many large projects, you will need to know how to write tests correctly.
When you write good tests for your code, you save a lot of time and headaches down the road. Testing gives you more confidence that your updates and refactoring do not have any unintended consequences or are going to break your code in any way. For example, suppose you update a function in your project. Those changes may have broken several sections of your code even if that function itself is still working, and good unit tests will make sure that everything is still working as it should, and if it is not, then it will show you precisely what is broken. In this article, we will discuss some of the Python testing tools.
What Are Some Python Testing Tools?
How Does PyScripter Become Unmatched?
Why is PyScripter an unmatched Python IDE and testing tool?
PyScripter is an open-source and free-to-use Python integrated development environment (IDE) and all-in-one testing tool for Windows. It is built from Delphi's Object Pascal and Python. It initially began as a lightweight IDE intended to effectively provide a strong scripting solution for Delphi applications. Over the long run, it advanced into a full-fledge independent Python IDE and testing tool. Since it is built in a compiled language, thus, this feature makes it rather lightweight in contrast to the other IDEs.
The feature of automated test generation, integrated unit testing, and unit testing GUI make PyScripter an unmatched open-source and free-to-use python testing tool.
What Does Python Robot Framework Do?
Robot Framework is an open-source automation framework not only for web applications; it can be used for desktop applications, mobile applications, API testing, and many other things. Suppose we can do the robotic process automation as well. In that case, the main point about the robot framework is key driver keyword-driven and user acceptance testers which means that you can write the unit test cases by using the robot framework, and you will be using the keywords.
The keywords will be very brief, and it will be very short so that the end-user can create the automation test cases very easily rather than focusing on the code and rather than seeing the entire code. Let us say id and robot framework or robot files will have the extension called dot robot and supported by the python and java; however, implementation is done in the python.
Similarly, PyScripter has all these features available that any beginner python developer or tester can use.
Is Python Behave Also a Testing Tool?
Behave also follows the BDD (Behavior Driven Development) approach. It comes with Python style and is specially designed for Python. Usually, we can automate test cases using Python with its Python library. On top of it, if you add behave component, you can automate your test cases by using the BDD approach. It is just like cucumber for java.
Python operates on different directories that mainly contains feature files and step definition.
Feature files contain different scenarios which you have to automate for your application. Normally, these feature files are written by your business analyst, sponsor, or whoever is responsible for your behavior scenario. These feature files are very easy to understand. Everyone can easily read and understand these feature files simply in the English language. However, while writing feature files, you need to use specific keywords.
Likewise, PyScripter offers all of these features as well and you can use all-in-one PyScripter for your Python Code development and automation.
Why do Python Testers Use Python Lettuce?
Lettuce is a tool for Behavior-Driven Development (or BDD for short). It is an analog of cucumber but in Python. You can check it out on lettuce.it [1]. There are two ways of using this application; one for customers and the second one for developers.
In the case of customers, you can write tests completely readable in English and show them to the customer for approval. In the case of developers, you can use the BDD approach; testers or developers should write down the test for the application before the application is written. After that, the developer relies on this test to write the code. It would be easier to write code relying on these tests.
Similarly, you can use PyScripter to do customer-centric development, which can be validated by customers in a Behavior-Driven Development (BDD).
What Does Splinter Offer?
Splinter is a web application testing tool that is built around Python. It automates actions such as visiting specified URLs and interacting with their items. It also removes the drudgery from web application testing by replacing manual testing with automated testing. With the help of Splinter, it is easy to write automated tests. It has one of the simplest APIs among open-source tools used to automate different tests on web applications. That makes it easy to write an automated test for any web application.
Moreover, it supports different web drivers for various browsers. These drivers are the Firefox web driver from Mozilla Firefox, Chrome's web driver for Google Chrome, and PhantomjJS web driver for Phantom. With Splinter, it is easy to find web page elements. Splinter also allows us to find different elements in any web page by their span CSS tag element tag value, name, ID, text, or value. It also works with AJAX. Splinter has the ability to work with AJAX and asynchronous JavaScript using various built-in methods. Splinter also supports frames. It has extensive support frames and interacts with them by just passing the frame's name, ID, or index value.
There are two ways to install Splinter. First, there is a stable release via pip if you already have Python installed. If your interest is in the official and almost bug-free version, just run $pip install Splinter from the terminal. Second, you can download the under-development version from GitHub [2].
Just like automated testing in Splinter, PyScripter offers plenty of features like Integration with Python tools like PyLint, TabNanny, Profile, etc., along with Integrated Unit Testing.
What is Python Locust?
The term locust is derived from the Latin word 'locusta', which means grasshopper. Locust is an open-source load testing tool, and it is one of the popular python based testing tools in the market. The core features of locust are that you can define whatever you want to do by writing Python snippets, which is the power of locust. The terminologies of the locust have been derived from nature, so these are the terms you frequently come across when working in the locust tool.
The first one is a swarm which means a group of animals that aggregate and travel in the same direction. Here the term swam means attacking a particular system, or you are stress testing or load testing the web application, and it is called production when it comes to hatching. There is another term called hatching—the hatch rate before version 1.2, which got renamed to spawn. Spawn means releasing or depositing, so when it comes to spawning, you are spinning up the new user to attack the system, so these are the terms you should be aware of when it comes to the locust. With PyScripter, you can run tests based on unit tests using advanced GUI, the standard Python module.
Why Is Python Testing Important?
It is considered a good practice that you do not want these tests to pass. The whole idea of testing the code is that you are trying to break your code; you are trying to take this code that you so lovingly, carefully crafted, or copied from some other resource and push it to the absolute limit. Such that it can support, and then you discover those limits you find what is going wrong you improve the code, and then you do it all over again. You keep iterating on entering and iterating on this idea of breaking the code so much to the point that you will never get these tests to truly pass.
That is because you will never achieve infinite scale with the actual, real-world resources, budget, or whatever you are dealing with. You will never get to the point where you have just such an infinite scale that you can throw infinite resources at an application that can support unlimited resources. So, the idea here is that you are just trying to find where we are now and what we can do to iterate and find the next solution. Hopefully, by now you have studied a good understanding of basic Python testing tools.
What are you waiting for? Start using PyScripter for testing Python!
