Liste avec une longueur personnalisée

Vous avez déjà vu une préparation de list implémentée comme fixture. Mais que faire si vous souhaitez aussi personnaliser ce processus ? Par exemple, vous pourriez vouloir définir une longueur spécifique pour une list générée. Vous pouvez l’implémenter avec des demandes de fixtures chaînées en faisant de la "length" une fixture séparée ; appelons-la list_length(). Au final, vous aurez une fonction de test qui demande la list, laquelle est ensuite générée en demandant list_length().

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<cours>Introduction aux tests en Python</cours>

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Cet exercice fait partie du cours

<cours>Introduction aux tests en Python</cours>

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Learn what a test is and how to run the first one of your own with the pytest library! You will get used to the pytest testing framework and the command-line interface. You will also learn how to process specific contexts, like "failed tests" and "skipping the test" with pytest markers.

Exercise 1: Introduction to Testing in Python Exercise 2: The first test suite Exercise 3: pytest.raises Exercise 4: Invoking pytest from CLI Exercise 5: Run the test!Exercise 6: Run with the keyword Exercise 7: Applying test markers Exercise 8: Markers use cases Exercise 9: Failed tests with xfail Exercise 10: Conditional skipping

Learn what a fixture is and how to simplify your code by using it in tests. You will get familiar with the fixture @pytest.fixture decorator and the fixture tools. You will analyze your code to see the "fixture part" in it. Finally, learn how to use teardowns to prevent software failures.

Exercise 1: Introduction aux luminaires Exercise 2: Se familiariser avec les appareils Exercise 3: Préparation des données Exercise 4: Lancer avec une fixture Exercise 5: Demandes de fixation de chaînes Exercise 6: Enchaînez Exercise 7: Liste avec une longueur personnalisée

Exercice actuel

Exercise 8: Autouse de fixation Exercise 9: déclarations d'autouse Exercise 10: Ajout automatique de nombres Exercise 11: Démontage d'appareils Exercise 12: Données avec teardown Exercise 13: Lire des données avec un teardown

Learn what the basic testing types are and their features. Learn about test cases and how they help to implement tests. You will get more skilled with creating test functions and running pytest from CLI in IDE exercises. Finally, you will be able to differentiate the different testing types and create tests for each of them.

Exercise 1: Unit testing with pytest Exercise 2: Unit testing terms Exercise 3: Cover more test cases Exercise 4: Factorial of number Exercise 5: Run factorial Exercise 6: Feature testing with pytest Exercise 7: Feature or unit testing Exercise 8: Aggregate with sum Exercise 9: Integration testing with pytest Exercise 10: Integration test or not Exercise 11: Read the file Exercise 12: Performance testing with pytest Exercise 13: What is performance testing?Exercise 14: Finding an element Exercise 15: Speed of loops

In this final chapter, you will meet the unittest framework. First, you will learn basic assertion methods, then its CLI interface, and how to use fixtures. Finally, you will put everything together in the practical examples of data pipelines.

Exercise 1: Meeting the Unittest Exercise 2: Factorial with unittest Exercise 3: Is prime or not Exercise 4: CLI Interface Exercise 5: Run factorial with unittest Exercise 6: Erroneouos factorial Exercise 7: Unittest options Exercise 8: Fixtures in unittest Exercise 9: Test the string variable Exercise 10: Palindrome check Exercise 11: Practical examples Exercise 12: Integration and unit tests Exercise 13: Feature and performance tests Exercise 14: Energy pipeline Exercise 15: Congratulations!