That’s why they’re also an efficient tool for documenting code. ![]() In Python, they can also include an optional message to unambiguously describe the error or problem at hand. Programmers also place assertions before functions’ return values to check if the output is valid (postconditions).Īssertions make it clear that you want to check if a given condition is and remains true. For example, programmers often place assertions at the beginning of functions to check if the input is valid (preconditions). In practice, you can use assertions to check preconditions and postconditions in your programs at development time. In this context, assertions mean Make sure that this condition remains true. ![]() The primary role of assertions is to trigger the alarms when a bug appears in a program. These use cases include documenting and testing your code. However, they can have other interesting use cases within your development process. They’ll help you ensure that you don’t introduce new bugs while adding features and fixing other bugs in your code. What Are Assertions Good For?Īssertions are mainly for debugging. These kinds of checks can help you catch errors as soon as possible when you’re developing a program. For example, you can test conditions along the lines of This argument is not None or This return value is a string. By doing so, you can check assumptions like preconditions and postconditions. With assertions, you can set checks to make sure that invariants within your code stay invariant. If the condition turns out to be false, then the assertion raises an exception and terminates the execution of your program. The assertion condition should always be true unless you have a bug in your program. Assertions allow you to test the correctness of your code by checking if some specific conditions remain true, which can come in handy while you’re debugging code. In Python, assertions are statements that you can use to set sanity checks during the development process. Having a basic understanding of documenting, debugging, and testing Python code is also a plus. To get the most out of this tutorial, you should have previous knowledge of expressions and operators, functions, conditional statements, and exceptions. What common pitfalls you might face when using assert statements.How assertions can be disabled to improve performance in production.How assert can help you document, debug, and test your code.What assertions are and when to use them. ![]() Assertions will help you make your code more efficient, robust, and reliable. Once you’ve debugged and tested your code with the help of assertions, then you can turn them off to optimize the code for production. If any of your assertions turn false, then you have a bug in your code.Īssertions are a convenient tool for documenting, debugging, and testing code during development. These checks are known as assertions, and you can use them to test if certain assumptions remain true while you’re developing your code. Python’s assert statement allows you to write sanity checks in your code.
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