Fundamentos del Testing en Python
¿Qué son las Pruebas Unitarias y por qué es importante?
¿Qué es el Testing en Software?
Instalación y Configuración del Entorno de Pruebas
Conceptos Básicos de Unittest
Cómo Crear Pruebas Unitarias con UnitTest en Python
Cómo usar el método setup en tests de Python
Uso de tearDown para limpieza de Pruebas Unitarias en Python
Cómo validar excepciones y estructuras de datos con Unittest en Python
Control de pruebas unitarias con unittest.skip en Python
Organización y Gestión de Pruebas
Cómo organizar y ejecutar pruebas en Python con UnitTest
Mejores prácticas para organizar y nombrar pruebas en Python
Técnicas Avanzadas en Pruebas Unitarias
Mocking de APIs externas en Python con unittest
Uso de Side Effects en Mocking con Python
Uso de Patching para Modificar Comportamientos en Python
Exploración de Herramientas y Métodos Complementarios
Cómo parametrizar pruebas en Python con SubTest
Documentación de pruebas unitarias con Doctest en Python
Cómo generar datos de prueba dinámicos con Faker en Python
Mejora y Automatización de Pruebas
¿Cómo asegurar la cobertura de pruebas con Coverage en Python
Automatización de Pruebas Unitarias en Python con GitHub Actions
Pruebas Unitarias con PyTest en Python
Cómo crear pruebas unitarias con inteligencia artificial en Python
Testing software is not only a technical task, it is a critical process that can make the difference between the success or failure of a project. A small undetected error can cause big problems, as demonstrated in the case of the European Space Agency rocket in 1996. Fortunately, in software development we have tools like Python and its modules to ensure the quality of the code before it reaches the users.
What types of tests are necessary to ensure software quality?
- Unit tests: They are in charge of validating that each small component of the code works correctly in isolation.
- Integration tests: Verify that the different components work well together, avoiding problems in the interaction of parts.
- Functional testing: Validates that the system as a whole works as expected according to the requirements.
- Performance testing: Ensures that the software is fast and efficient, evaluating its behavior under different load conditions.
- Acceptance testing: Determines whether the software meets the end user's expectations.
What testing tools does Python offer?
- UnitTest: Allows you to create unit tests easily, ensuring that all parts of the code perform their function correctly.
- PyTest: Facilitates the creation of tests with advanced configuration to cover different scenarios.
- DocTest: Integrates tests directly into function comments, allowing you to validate code while maintaining documentation.
How to ensure that all lines of code are being tested?
It is crucial to identify the lines of code that are not covered by tests. For this, there is Coverage, a tool that generates an HTML report showing which parts of the code have not been validated, allowing additional tests to be added where necessary.
Why is testing important in software?
Testing ensures that software is functional, fast and reliable, but beyond that, it can prevent costly bugs, financial losses and in extreme cases, save lives. By testing software before it goes into production, developers have the advantage of correcting bugs before they impact users.
Contributions 16
Questions 0
Want to see more contributions, questions and answers from the community?