#python selenium course

The Seven Key Elements of Software Testing

Testing reveals that there are flaws.-python with selenium course

Testing enables us to show the presence of occurrences rather than their absence in a product. It is feasible to lessen the likelihood that incidents not yet identified will continue in the system after they have been reported and later fixed, but it is difficult to confirm and exceedingly improbable that there will be no occurrences at all.

Testing in its entirety is not feasible

Testing every conceivable set of data and activities across all of a software's features is typically not a practical option, barring exceptional circumstances, due to time, expense, or resource constraints. It is quite easy to take these elements into account while developing our strategy and creating test cases.

Initial testing - selenium and cucumber

This alliance is quite helpful when testing starts early in the software development process since it enables incidents to be found before the product fully develops. If these accidents weren't discovered until later stages, the cost of repair would be much higher.

Problem Clustering

When compared to the other components of a product, there are typically some modules and capabilities that are more prone to conceal issues (of higher priority). The 80/20 Rule, which claims that roughly 80% of results result from 20% of causes, is connected to this theory. This could be translated as follows in more exact terms: Not all software components are equally pertinent.

Paradox of pesticides

Repeatedly doing the same tests on a system's stable portion has a tendency to make it more difficult to find newly discovered incidents. Therefore, it is crucial that we continually examine and update our testing method as well as make sure that we thoroughly investigate all of the components that make up the product in order to maximize the likelihood of discovering events.

Testing depends on the situation

Depending on the system and the surroundings we want to verify, we will decide on the technique and the kinds of tests to run. For instance, testing for an e-commerce system will differ from testing for medical software. The techniques we employ

The fallacy of absence of errors

Assume that all the incidents that a certain system had noticed have now been resolved. After that, a fresh test cycle is run, after which additional instances are not found. However, the absence of any discovered mistakes does not necessarily suggest that the software is effective. This parameter does not represent its utility; rather, it measures how well a product can meet client expectations.

Understanding and putting these ideas into practice gives us a unique perspective that allows us to structure our testing strategy and work more accurately and efficiently.

What does Python-based automation testing entail?

python selenium tutorial Software can be tested using automated tools, frameworks, and scripts through the practice of automation testing. Reusable test scripts are created to test the app's functioning using this software testing technique, cutting down on overall regression time and facilitating quicker software releases. Utilizing test automation shortens the testing life cycle's regression time and improves quality releases.

Automated test scripts can be written in a number of different programming languages, such as Python, C#, Ruby, Java, etc. However, Python is more closely related to the English language and easy to learn programming language. Furthermore, compared to other programming languages, Python is an open-source language with an approachable syntax that is simple to read and grasp.

Which programming languages work the best for automated testing?

1. Python is an open-source programming language used for test automation, machine learning, network servers, media tools, and desktop and web application testing. It is a simple language with lots of library support.

2. One of the most well-liked programming languages for test automation is Java. Because it operates under the WORA (Write Once, Run Anywhere) paradigm, cross-platform testing is incredibly simple. It includes full test frameworks, packages, and data sources.

3. C#: This object-oriented programming language is used to create desktop and web software. One of the most popular programming languages for test automation is also this one. Windows, Android, and iOS applications and platforms are most suited for it.

4. Ruby: Ruby is an open-source programming language that is gradually gaining popularity among testers all around the world. This language is regarded as one of the simpler programming languages due to its ease of use, productivity, and simplicity.

5. Java Script is yet another popular programming language for front-end development and test automation. Testers use Java Script mostly because it allows shift-left techniques, which include developers in the creation of test code.

However, out of all the above-mentioned languages, Python is the most popular.

The value of Python for automated software testing

1. This language provides a variety of built-in testing frameworks, including Pytest, Robot, and others, which guarantees quicker debugging and the development of workflows.

2. It implements the code line by line and is an interpreted language, making debugging simple.

3. As a cross-platform language, it may be used with several operating systems, including Windows, Linux, and Mac.

4. Other programming languages, such as C, C++, JAVA, etc., can also be used to accomplish it quickly.

Python configuration: how to do it?

1. Quickly install Python on the operating system.

2. Install Python Selenium libraries

3. Get and set up the Pycharm editor.

4. Establish a fresh project and produce the Selenium test scripts.

5. Execute the test scripts, then confirm them.

Why do testers favor Python for automated software testing?

1. Simple to use and less verbose: 

Python is a relatively simple language to learn and use. Beginners who want to learn programming languages for software are advised to start with this.

2. Active community support: 

Python is the most popular language for test automation because of its active community support, which provides technical assistance at no cost.

3. Has a variety of included tools, frameworks, and libraries: 

Python has a sizable library of frameworks. Python's standard framework for test automation is PyUnit or Unittest. In addition, Python supports a number of alternative test automation frameworks, including PyTest, Behave, Robot, Lettuce, Nose2, Testify, etc.

4. allows parallel testing: 

Python allows parallel testing for test automation across operating systems and browsers, making it one of the languages that testers like to use for automation testing.

5. Easily integrates with CI/CD tools: 

One of the additional benefits of Python is the Python ecosystem's abundance of tools that can be quickly connected with CI/CD solutions like Jenkins.

Frameworks for automating testing in Python

1. Robotics Framework

It is an open-source test automation framework used for acceptance test-driven development (ATDD), user acceptability testing

2. Pytest:

It is a free framework for automating web tests that supports API testing, functional testing, and unit testing. Pytest is suitable for both straightforward and intricate functional test scenarios. The protest-exist plugin enables the Test Driven Development methodology and parallel test execution. Other Python testing frameworks like Unittest and Pyunit are compatible with Pytest.

3. PyUnit or Unittest:

It belongs to the Python standard library and provides a built-in testing framework for Python. A descendant of the xUnit framework unit test resembles it in certain ways. 

4. Testing Project:

It is a fully automated testing framework that is open-source. This test framework makes it simple for testers to create test cases for mobile, web, or general automation. It is a single-agent executable framework that includes the third-party libraries required to create and run general, web, and mobile test automation. It produces free automated reports in the formats of PDF and HTML.

5. Nose2:

It is a unit testing framework built on Python that can be used to execute DocTests and UnitTests. Nose2, a Domain-Specific Language (DSL) for creating functional tests, offers a built-in ecosystem of plugins that streamline and accelerate testing.

6. Behave:

It is one of the most popular Python frameworks for behavior-driven development testing. This framework offers good documentation support and enables testers to write test cases in a simple and intelligible manner.

7. Testify: 

Testify takes the place of Nose and Unittest. Compared to Unittest, it includes more sophisticated functionality. Unit, system, and integration testing can all be done using this framework.

8. Lettuce :

is a Python behavior-driven development framework built on the Cucumber programming language. The Gherkin language is supported. This language makes it simple for testers without a technical background to build automated tests.

Conclusion

In the past, software testers were required to be knowledgeable in advanced programming languages. Today's testers can easily run automated tests thanks to the availability of many programming languages.

One such simple-to-learn and use programming language for automated software testing is Python. Even for testers who are just beginning their software testing career, it makes automated software testing simpler. Speak to our specialists if you need assistance with Python automation testing.