What you would learn in Hands-On Software Testing In Python (w/ unittest framework) course?
Are you looking for a beginner-friendly beginner's guide? Getting started guide? It is also as comprehensive as possible, with rich, real-world scenarios that fully cover every aspect, the ins and outs of Unit and Integration testing, and the bugs and grits that come with Unit or Integration test Python. Yes, dear, you're in the right place.
Welcoming to "Hands-On Software Testing in Python"!
Suppose you're a freelancer, a student at a college, or an engineer working in software at some point. In that case, it's a given not to have at least a few "exploratory testing" scripts that check and test different possible edge cases to be sure of how reliable your work is. But if things get a little more complicated when a particular component fails, you either enter a refactoring hell, or you begin the project all over again. In this course, I'll show you a variety of scenario scenarios in which there are existing code bases as mini-projects that we construct entirely from scratch in the code-along style. Most important is that we follow an orderly process to analyze and develop our test cases for each scenario and then implement the cases.
I'm Ahmed Alhallag; I'm a Software Engineer and Assistant Lecturer. I'll guide you through an extensive journey beginning with the theoretical foundations that underlie Software Testing, up to the most intimate parts that will teach you the most effective methods to approach any project that is developed and implemented in any way (Procedural and OOP are both taught within this class) regardless of how big or large it may appear on the surface.
Writing code isn't meant to be the primary area of attention on your part as a software developer, specifically code that is merely 'working for a specific period. There are a variety of other aspects needs to be considered, for example:
The quality of modeling:
It is possible to consider: "alright, I have this task to implement, so let's wing it! " You instantly launch your preferred IDE and begin to code. If you have a specific task, this would be the best method, but for bigger ones, this could eventually take up your time in the long run because you'll be back and forth.
You were encapsulating this code block and refactoring the section of code. You can save your sensitive data into a .env file after it was deleted in the middle of your script before you began working, and then record the output and store that output in JSON files instead of a simple TXT file, creating middleware or an API interface or controller you discovered out that you must execute a specific action, or implement a data handler as the code got complex and redundant, and altering the entire collection of data structures utilized that, in turn, alters the whole processing logic, written ahead of time too!
Look at all the above scenarios as everyday situations we experience on our journey to develop; even if you've never encountered one, this is a good thing! We'll go over how to apply our code through the analysis (OOA) or design (OOD with UML) with the aid of mini-projects we'll create with each other!
This is clearly not the primary focus of this course; therefore, we won't spend much time discussing that aspect; instead, we'll focus on the must-have an uncluttered code basis later when we begin to implement.
Following the short concepts on the conceptual design and model, we'll follow the instructions ( class diagrams) we designed to implement the system that we will try out later. We will use Object Oriented Programming (OOP) in most projects.
You may be asking yourself what the reason we would spend so much time on the execution of each use scenario. Why not just use the code in its current form and begin writing test cases?
It's a valid argument; however, listen to me. I think that you should consider this if you are looking to learn the inner workings of an application, no matter if you're performing a defensive or offensive security measure, creating the UI/UX for your system, setting up the database layer, or even executing a few tests, you need to be completely and fully informed about the technology that you are conducting work on.
For developers with experience who can pick up the pace at any time and start to implement their test cases. However, for those who haven't created many test cases before or at the beginning of the journey can be a challenge, not knowing what is required to be tested or not even knowing how or where to begin!
This is my approach for the majority of scenario scenarios, in which we'll build the system that we want to test thoroughly!
- Examine existing code bases (and then refactor them as necessary) and create the required test cases according.
- Manually run integration and unit tests on Procedural code, as well as Object Oriented code.
- Learn how to carry out Test Driven Development (TDD)
- Coverage of tests and run several tests at once.
- Learn to handle boilerplate code and pass-through functions.
- Use Pdb (Interactive Python Debugger) at run-time for a quick look at various test cases.
- Learn how to create mockups efficiently and how to create them using various situations,
- Know how to duplicate or sample real-world data.
- Learn about the most effective methods for OOA, OOD & OOP using UML design patterns starting from scratch. Write tests to test the code base you developed later.
- Learn to handle operations and processing on files (read-write, write, stdout functions, and more..)
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