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Crafting Test-Driven Software with Python: Write test suites that scale with your applications' needs and complexity using Python and PyTest
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What Stands Out
Produkto Aprašymas
- Comprehensive guide for writing test-driven software with Python and PyTest
- Learn to create test suites that can scale with the complexity of your applications
- Detailed coverage of essential concepts and practical techniques
- Suitable for developers looking to improve software testing practices
- Written by experts with in-depth knowledge of Python testing
- Ideal for those seeking to strengthen their Python testing skills
| Publisher | Packt Publishing |
| Publication date | February 18, 2021 |
| Language | English |
| Print length | 338 pages |
| ISBN-10 | 183864265X |
| ISBN-13 | 978-1838642655 |
| Item Weight | 1.28 pounds (580 grams) |
| Dimensions | 7.5 x 0.77 x 9.25 inches (19.1 x 2 x 23.5 cm) |
Who Should Buy?
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Software Developers
Developers looking to improve code quality and maintainability will find this resource crucial for implementing testing strategies.
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Python Learners
Individuals learning Python can benefit from understanding test-driven development concepts integrated with practical examples using PyTest.
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DevOps Practitioners
DevOps teams seeking to integrate testing into their CI/CD pipelines will gain valuable insights for automated testing.
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Absolute Beginners
Beginners with no programming experience may struggle to comprehend advanced concepts related to test-driven development.
PRODUKTO APRAŠYMAS
Crafting Test-Driven Software with Python: Write test suites that scale with your applications' needs and complexity using Python and PyTest
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Testing Editorial Review
** "Crafting Test-Driven Software with Python"** Alessandro Molina's "Crafting Test-Driven Software with Python" emerges as a compelling guide tailored for developers aiming to solidify their understanding of software testing principles, specifically within the Python ecosystem. The book adeptly breaks down complex concepts of software testing into easily digestible sections, making it accessible to a variety of skill levels, from beginners to seasoned professionals. Molina starts by introducing fundamental testing concepts before progressively moving into more advanced topics like test-driven development (TDD), behavior-driven development (BDD), and the implementation of various testing frameworks such as unittest and pytest. This structured approach ensures that readers can build upon their knowledge incrementally, enhancing both comprehension and practical application. The inclusion of practical examples—ranging from small applications like a contact book to more intricate setups involving web applications—is particularly beneficial, demonstrating real-world applications of the discussed testing methods. Readers have noted the book's comprehensive nature, covering a vast array of testing strategies, from unit tests and integration tests to performance and acceptance tests. The explanations are thorough, bolstered by useful code examples available on GitHub, making it easy for readers to follow along and apply what they have learned. Furthermore, the book’s interviews with advanced topics, such as continuous integration using Travis CI, and the use of Tox for project management, highlight Molina’s intent to provide a holistic view of software testing. While the depth and scope of the material are commendable, some readers pointed out that certain examples, particularly those utilizing advanced programming concepts like threads or lambda functions, might pose challenges for novices. A more beginner-friendly approach might have enhanced the learning experience for those less familiar with these advanced topics. Overall, "Crafting Test-Driven Software with Python" is an invaluable resource for any programmer seeking to enhance their testing capabilities, ensuring they can achieve high-quality software with fewer bugs. Molina's thorough yet pragmatically structured exposition of the subject matter makes it a must-read for Python developers and QA teams alike. **
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Argumentai
- Comprehensive coverage of software testing concepts.
- Structured approach that gradually increases complexity.
- Practical examples that enhance real-world application.
- Accessible for a range of skill levels, from beginners to advanced users.
- Code examples available on GitHub for readers to follow.
- Relevant for both Python developers and those interested in general testing principles.
Minusai
- Some advanced examples may be challenging for novice programmers.
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