Java vs Python для тестировщика. Что выбрать?

Азат Закуанов2 minutes read

Choosing a first programming language can be challenging for testers, but Python is highly recommended for its simplicity and versatility, providing a solid foundation for learning programming concepts that are applicable to other languages. While it offers ease of learning and is popular in fields like data science and automation with tools such as Selenium, Java remains more widely used in the industry, suggesting that mastering both languages can be beneficial for career opportunities.

Insights

  • Choosing Python as a first programming language is advantageous for testers due to its simplicity and versatility, making it easier to grasp fundamental programming concepts like object-oriented programming, which can later facilitate learning other languages. Despite Python's growing popularity, especially in fields like data science, Java still dominates the industry, offering more job opportunities and extensive documentation, which highlights the importance of understanding the landscape of programming languages when starting a career in testing.

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Recent questions

  • What is a programming language?

    A programming language is a formal set of instructions that can be used to produce various kinds of output, including software applications, scripts, or algorithms. It provides a means for humans to communicate with computers, allowing them to perform specific tasks. Programming languages have their own syntax and semantics, which dictate how commands are structured and interpreted. They can vary widely in complexity and purpose, ranging from high-level languages like Python, which are designed to be easy to read and write, to low-level languages that are closer to machine code. Understanding programming languages is essential for software development, automation, and data analysis, as they form the foundation of all computer programming.

  • How do I start learning programming?

    To start learning programming, it's essential to choose a language that suits your goals and interests. Many beginners find Python to be an excellent starting point due to its simplicity and versatility. Begin by familiarizing yourself with fundamental programming concepts such as variables, data types, control structures, and functions. Online resources, tutorials, and coding bootcamps can provide structured learning paths. Practice is crucial, so work on small projects or exercises to apply what you've learned. Additionally, joining programming communities can offer support and motivation. Remember, learning programming is a gradual process that requires patience and persistence, so don't be discouraged by initial challenges.

  • What is object-oriented programming?

    Object-oriented programming (OOP) is a programming paradigm that uses "objects" to represent data and methods to manipulate that data. It is based on several key concepts, including encapsulation, inheritance, and polymorphism. Encapsulation allows for bundling data and methods that operate on that data within a single unit or object, promoting modularity and code reuse. Inheritance enables new classes to inherit properties and behaviors from existing classes, facilitating code organization and reducing redundancy. Polymorphism allows for methods to be defined in multiple forms, enhancing flexibility in code execution. OOP is widely used in many programming languages, including Python and Java, and is particularly beneficial for managing complex software systems.

  • What is Selenium used for?

    Selenium is a widely-used open-source tool for automating web applications for testing purposes. It allows developers and testers to write scripts in various programming languages, including Python, to simulate user interactions with web browsers. Selenium can automate tasks such as clicking buttons, filling out forms, and navigating between pages, making it an invaluable resource for ensuring that web applications function correctly across different browsers and platforms. Its ability to perform regression testing helps identify bugs and issues before software deployment. Additionally, Selenium supports various testing frameworks, making it a flexible choice for integrating into existing testing workflows.

  • Why is Python popular for automation?

    Python's popularity for automation stems from its simplicity, readability, and extensive library support. The language is designed to be user-friendly, allowing both beginners and experienced programmers to write clear and concise code. Python's rich ecosystem includes libraries like Selenium for web automation and 'requests' for handling HTTP requests, which streamline the automation process. Its versatility enables it to be used in various domains, including web scraping, data analysis, and machine learning. Furthermore, Python's active community provides ample resources, documentation, and support, making it easier for users to find solutions to their automation challenges. This combination of features makes Python a preferred choice for many automation tasks.

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Summary

00:00

Choosing Python as a First Programming Language

  • Choosing a first programming language can be challenging for testers, with Python being a popular recommendation due to its simplicity and versatility in solving various tasks.
  • Testers often switch between programming languages throughout their careers, making it less critical to stick to one language; learning Python can provide a solid foundation for understanding programming concepts applicable to other languages.
  • The initial focus for beginners should be on grasping fundamental programming concepts such as object-oriented programming (OOP), classes, methods, and data types, which will ease the transition to learning new languages later.
  • Python is designed to be user-friendly, allowing for optional typing and a simplified program structure, which contrasts with more rigid languages like Java that require explicit class definitions and method structures.
  • The philosophy behind Python emphasizes simplicity, making it an ideal language for beginners, as it allows for quick program development with minimal code, such as printing "Hello, World!" in just one line.
  • Python's growing popularity in various fields, including data science and machine learning, enhances its appeal for testers, as many companies prefer hiring testers who are proficient in Python.
  • While Python's lack of strict typing can make it easier to learn, it may also lead to misunderstandings about data types and encapsulation, which are more clearly defined in languages like Java.
  • Despite Python's increasing popularity, Java remains more widely used in the industry, particularly in the U.S., which may result in more job opportunities for Java developers compared to Python developers.
  • Documentation and community support for Java are generally more extensive than for Python, which can pose challenges for Python learners seeking solutions to programming issues.
  • Learning Python or any programming language requires significant time and effort; it is unrealistic to expect to master Python in a month, as understanding programming fundamentals and building frameworks takes considerable practice and dedication.

11:30

Mastering Python for Automation and Testing

  • Programming can be challenging, and it's common to feel overwhelmed, especially when starting with languages like Python. It's important to remember that struggling with programming is normal, and no one knows everything; persistence and time are key to mastering the skills needed for programming and automation.
  • For automation in Python, the recommended tool is Selenium, which is widely used for web automation. After gaining a foundational understanding of Python, learners should focus on studying Selenium, as it provides a straightforward entry point into automation. For mobile automation, Appium is suggested, which shares similarities with Selenium but may require additional setup time.
  • To generate HTTP requests in Python, the 'requests' library is recommended for its simplicity and effectiveness in executing GET requests and other types of requests. This library simplifies the process of making requests compared to Python's native implementation, which can be complex.
  • For testing frameworks, 'pytest' is advised due to its powerful yet lightweight nature, making it practical for various testing needs. Additionally, for creating a framework that is understandable to both product managers and manual testers, 'Behave' is suggested, as it is user-friendly and easy to install, similar to Cucumber.
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