350+ Exercises – Python Programming Mega Pack – Unit Tests
350+ Exercises – Python Programming Mega Pack – Unit Tests, available at $64.99, has an average rating of 4.45, with 321 lectures, 301 quizzes, based on 28 reviews, and has 19260 subscribers.
You will learn about solve over 350 exercises in Python and unit testing deal with real programming problems work with documentation guaranteed instructor support This course is ideal for individuals who are Python developers or programmers who want to deepen their understanding and proficiency in writing unit tests for their Python code or students or individuals studying computer science or software engineering who need practical exercises to reinforce their knowledge of unit testing principles and techniques in Python or professionals working on Python projects who want to adopt a test-driven development approach and improve the quality and reliability of their code through unit testing or programmers transitioning to Python from other programming languages who want to learn how to write effective unit tests in Python and ensure code correctness or software engineers or developers who want to enhance their skills in test automation and continuous integration using Python's unit testing frameworks or self-learners or enthusiasts interested in learning about unit testing and how to apply it to Python code for effective software development practices It is particularly useful for Python developers or programmers who want to deepen their understanding and proficiency in writing unit tests for their Python code or students or individuals studying computer science or software engineering who need practical exercises to reinforce their knowledge of unit testing principles and techniques in Python or professionals working on Python projects who want to adopt a test-driven development approach and improve the quality and reliability of their code through unit testing or programmers transitioning to Python from other programming languages who want to learn how to write effective unit tests in Python and ensure code correctness or software engineers or developers who want to enhance their skills in test automation and continuous integration using Python's unit testing frameworks or self-learners or enthusiasts interested in learning about unit testing and how to apply it to Python code for effective software development practices.
Enroll now: 350+ Exercises – Python Programming Mega Pack – Unit Tests
Summary
Title: 350+ Exercises – Python Programming Mega Pack – Unit Tests
Price: $64.99
Average Rating: 4.45
Number of Lectures: 321
Number of Quizzes: 301
Number of Published Lectures: 321
Number of Published Quizzes: 301
Number of Curriculum Items: 622
Number of Published Curriculum Objects: 622
Original Price: $19.99
Quality Status: approved
Status: Live
What You Will Learn
- solve over 350 exercises in Python and unit testing
- deal with real programming problems
- work with documentation
- guaranteed instructor support
Who Should Attend
- Python developers or programmers who want to deepen their understanding and proficiency in writing unit tests for their Python code
- students or individuals studying computer science or software engineering who need practical exercises to reinforce their knowledge of unit testing principles and techniques in Python
- professionals working on Python projects who want to adopt a test-driven development approach and improve the quality and reliability of their code through unit testing
- programmers transitioning to Python from other programming languages who want to learn how to write effective unit tests in Python and ensure code correctness
- software engineers or developers who want to enhance their skills in test automation and continuous integration using Python's unit testing frameworks
- self-learners or enthusiasts interested in learning about unit testing and how to apply it to Python code for effective software development practices
Target Audiences
- Python developers or programmers who want to deepen their understanding and proficiency in writing unit tests for their Python code
- students or individuals studying computer science or software engineering who need practical exercises to reinforce their knowledge of unit testing principles and techniques in Python
- professionals working on Python projects who want to adopt a test-driven development approach and improve the quality and reliability of their code through unit testing
- programmers transitioning to Python from other programming languages who want to learn how to write effective unit tests in Python and ensure code correctness
- software engineers or developers who want to enhance their skills in test automation and continuous integration using Python's unit testing frameworks
- self-learners or enthusiasts interested in learning about unit testing and how to apply it to Python code for effective software development practices
The “350+ Exercises – Python Programming Mega Pack – Unit Tests” course is an in-depth, hands-on guide to unit testing in Python. This course is aimed at both beginners who want to solidify their knowledge of Python and experienced developers who want to enhance their testing skills.
With over 350 exercises, this course thoroughly covers the unittest module, one of Python’s built-in libraries designed for testing. By working through these exercises, students will gain a practical understanding of unit testing in Python and the importance of test-driven development.
The course starts with the fundamentals of unit testing, including writing simple test cases and understanding the role of assertions. It then progressively moves into more complex areas such as setup and teardown methods, test suites, and mock objects. Throughout the course, students will learn to write robust and effective test cases, crucial for maintaining large codebases and ensuring software quality.
Each exercise is designed to reinforce the concepts learned in the course and provide practical experience. The course also includes solutions to all exercises, allowing students to compare their solutions and gain insights into different approaches.
By the end of the “350+ Exercises – Python Programming Mega Pack – Unit Tests” course, students will have a deep understanding of unit testing in Python, enabling them to write comprehensive test cases and enhance software quality in their future projects. This knowledge can lead to improved job prospects and performance in professional settings.
Unit Testing – Building Blocks of Reliable Code!
Unit testing is a software testing approach that focuses on testing individual units or components of a software system in isolation. In unit testing, developers write test cases for small, self-contained units of code, such as functions, methods, or classes, to ensure that they behave as expected. These tests are designed to validate the correctness of the individual units and detect any defects or errors early in the development process.
Unit testing is typically performed by writing test cases that cover various scenarios and expected outcomes for each unit. These test cases are executed automatically and can be run frequently, providing rapid feedback on the behavior of the code. By isolating and testing units independently, developers can identify and fix issues quickly, preventing them from propagating to other parts of the system.
The main benefits of unit testing include increased code reliability, easier debugging, faster development cycles, and improved maintainability. It helps ensure that individual units function correctly and interact properly with other units. Unit testing also promotes modular design, as it encourages the separation of concerns and the creation of testable and reusable code.
Overall, unit testing plays a vital role in software development by providing a foundation for building robust, high-quality applications. It forms an integral part of the broader testing strategy, complementing other testing techniques such as integration testing and system testing to achieve comprehensive software validation.
unittest – Harness the Power of Test-Driven Development!
unittest is a built-in testing framework in Python that allows developers to write and execute unit tests for their code. It provides a set of tools and assertions to define test cases, run tests, and check expected results. With unittest, developers can ensure the correctness and reliability of their code by systematically testing individual units or components.
unittest follows the principles of test-driven development (TDD) and provides a structured approach to writing tests. Test cases are organized into classes, with each test method focusing on a specific aspect of the code being tested. Developers can use assertions to verify that the actual output matches the expected output, ensuring that the code behaves as intended.
unittest supports test discovery, test fixtures, and test suites, making it scalable for testing large projects. It also integrates well with other testing tools and frameworks. By writing unit tests with unittest, developers can catch and fix bugs early in the development process, improve code quality, and facilitate future code changes without breaking existing functionality. unittest promotes robust and reliable software development through systematic and automated testing.
Course Curriculum
Chapter 1: Tips
Lecture 1: A few words from the author
Lecture 2: Configuration
Lecture 3: Requirements
Chapter 2: Starter
Lecture 1: Solution 0
Chapter 3: —–BASICS—–
Lecture 1: Intro
Chapter 4: print() function
Lecture 1: Solution 1
Lecture 2: Solution 2
Lecture 3: Solution 3
Lecture 4: Solution 4
Lecture 5: Solution 5
Lecture 6: Solution 6
Lecture 7: Solution 7
Lecture 8: Solution 8
Lecture 9: Solution 9
Lecture 10: Solution 10
Chapter 5: Calculations
Lecture 1: Solution 11
Lecture 2: Solution 12
Lecture 3: Solution 13
Lecture 4: Solution 14
Lecture 5: Solution 15
Lecture 6: Solution 16
Lecture 7: Solution 17
Lecture 8: Solution 18
Lecture 9: Solution 19
Lecture 10: Solution 20
Lecture 11: Solution 21
Lecture 12: Solution 22
Chapter 6: Slicing
Lecture 1: Solution 23
Lecture 2: Solution 24
Lecture 3: Solution 25
Lecture 4: Solution 26
Chapter 7: Data Types
Lecture 1: Solution 27
Lecture 2: Solution 28
Lecture 3: Solution 29
Chapter 8: Strings
Lecture 1: Solution 30
Lecture 2: Solution 31
Lecture 3: Solution 32
Lecture 4: Solution 33
Lecture 5: Solution 34
Lecture 6: Solution 35
Lecture 7: Solution 36
Lecture 8: Solution 37
Lecture 9: Solution 38
Lecture 10: Solution 39
Lecture 11: Solution 40
Lecture 12: Solution 41
Lecture 13: Solution 42
Lecture 14: Solution 43
Instructors
-
Paweł Krakowiak
Python Developer/Data Scientist/Stockbroker
Rating Distribution
- 1 stars: 0 votes
- 2 stars: 0 votes
- 3 stars: 3 votes
- 4 stars: 7 votes
- 5 stars: 18 votes
Frequently Asked Questions
How long do I have access to the course materials?
You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!
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